1.
Mehrotra, Anand; Singh, Jitendra; Srivastava, Suraj; Singh, Rahul Kumar; Jagannatham, Aditya K.; Hanzo, Lajos
Multi-Dimensional Sparse CSI Acquisition for Hybrid mmWave MIMO OTFS Systems Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 9, pp. 8330–8344, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Bayes methods, Channel estimation, Complexity theory, delay-Doppler-angular domain, Estimation, high-mobility, hybrid precoding, Millimeter wave communication, MIMO, mmWave, Modulation, OFDM, OTFS, sparsity, Symbols, Training
@article{mehrotra_multi-dimensional_2025,
title = {Multi-Dimensional Sparse CSI Acquisition for Hybrid mmWave MIMO OTFS Systems},
author = {Anand Mehrotra and Jitendra Singh and Suraj Srivastava and Rahul Kumar Singh and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10918701},
doi = {10.1109/TCOMM.2025.3549501},
issn = {1558-0857},
year = {2025},
date = {2025-09-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {9},
pages = {8330–8344},
abstract = {Multi-dimensional sparse channel state information (CSI) acquisition is conceived for Orthogonal time frequency space (OTFS) modulation-based millimetre wave (mmWave) multiple input and multiple output (MIMO) systems. A comprehensive end-to-end relationship is derived in the delay-Doppler (DDA) domain by additionally considering the angular parameters and a hybrid beamforming (HB) architecture. A time-domain pilot model tailored for CSI estimation (CE) in the DDA-domain is proposed, which exploits the inherent multi-dimensional (4D) sparsity that emerges in the DDA-domain during the CE process. An efficient low-complexity Bayesian learning (LC-BL) technique is conceived to fulfil the objective of CSI estimation in such systems. Subsequently, a comprehensive examination of the complexity of the algorithm under consideration is also provided. It is worth noting that the complexity of the BL scheme designed is similar to that of popular orthogonal matching pursuit (OMP), but significantly lower than that of the traditional expectation-maximization (EM) based BL technique. Moreover, a single-stage transmit precoder (TPC) and receiver combiner (RC) design is proposed. This procedure aims for maximizing the directional gain of the RF TPC/RC pair by optimizing their weights. Additionally, a series of comprehensive simulations are conducted which incorporate the use of a practical channel model and fractional Doppler shifts. In light of the inherent trade-offs between complexity and estimation algorithm performance, our proposed scheme, LC-BL, appears suitable, especially considering the substantial enhancement in the performance of CE compared to the existing benchmarks.},
keywords = {Bayes methods, Channel estimation, Complexity theory, delay-Doppler-angular domain, Estimation, high-mobility, hybrid precoding, Millimeter wave communication, MIMO, mmWave, Modulation, OFDM, OTFS, sparsity, Symbols, Training},
pubstate = {published},
tppubtype = {article}
}
Multi-dimensional sparse channel state information (CSI) acquisition is conceived for Orthogonal time frequency space (OTFS) modulation-based millimetre wave (mmWave) multiple input and multiple output (MIMO) systems. A comprehensive end-to-end relationship is derived in the delay-Doppler (DDA) domain by additionally considering the angular parameters and a hybrid beamforming (HB) architecture. A time-domain pilot model tailored for CSI estimation (CE) in the DDA-domain is proposed, which exploits the inherent multi-dimensional (4D) sparsity that emerges in the DDA-domain during the CE process. An efficient low-complexity Bayesian learning (LC-BL) technique is conceived to fulfil the objective of CSI estimation in such systems. Subsequently, a comprehensive examination of the complexity of the algorithm under consideration is also provided. It is worth noting that the complexity of the BL scheme designed is similar to that of popular orthogonal matching pursuit (OMP), but significantly lower than that of the traditional expectation-maximization (EM) based BL technique. Moreover, a single-stage transmit precoder (TPC) and receiver combiner (RC) design is proposed. This procedure aims for maximizing the directional gain of the RF TPC/RC pair by optimizing their weights. Additionally, a series of comprehensive simulations are conducted which incorporate the use of a practical channel model and fractional Doppler shifts. In light of the inherent trade-offs between complexity and estimation algorithm performance, our proposed scheme, LC-BL, appears suitable, especially considering the substantial enhancement in the performance of CE compared to the existing benchmarks.
2.
Jafri, Meesam; Kumar, Pankaj; Srivastava, Suraj; Jagannatham, Aditya K.; Hanzo, Lajos
Robust Hybrid Beamforming in Cooperative Cell-Free mmWave MIMO Networks Relying on Imperfect CSI Journal Article
In: IEEE Transactions on Vehicular Technology, vol. 74, no. 8, pp. 12590–12602, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Antenna arrays, Array signal processing, cell-free networks, Channel estimation, cooperative beamforming, CSI uncertainty, Downlink, Millimeter wave communication, MIMO, mmWave, Radio frequency, robust beamforming, Uncertainty, Uplink, Vectors
@article{jafri_robust_2025,
title = {Robust Hybrid Beamforming in Cooperative Cell-Free mmWave MIMO Networks Relying on Imperfect CSI},
author = {Meesam Jafri and Pankaj Kumar and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10945645},
doi = {10.1109/TVT.2025.3555484},
issn = {1939-9359},
year = {2025},
date = {2025-08-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
volume = {74},
number = {8},
pages = {12590–12602},
abstract = {A low-complexity robust cooperative hybrid beamformer is designed for both the downlink and uplink of cell-free millimeter wave (mmWave) multiple-input-multiple-output (MIMO) networks, while considering realistic imperfect channel state information (CSI). To begin with, a second-order cone program (SOCP)-based robust fully-digital beamformer (FDBF) is designed for minimizing the worst-case interference for the downlink of multiple-input-single-output (MISO) systems. Subsequently, we develop a Bayesian learning (BL) framework for determining both the analog and digital components of the hybrid transmit precoder (TPC) from the FDBF. The above designs are subsequently extended to employing eigenvector perturbation theory for constructing the robust TPC for the cell-free mmWave MIMO downlink, where the users have multiple receive antennas (RAs). Furthermore, the multi-dimensional covariance fitting (MCF) framework is harnessed for designing the robust TPC of the corresponding uplink. Finally, the efficiency of the proposed TPC designs is evaluated by simulation results both in terms of their ability to mitigate the multi-user interference (MUI), and improving the spectral efficiency achieved. Additionally, the proposed designs are shown to be computationally efficient and equivalent to a minimum variance hybrid beamformer.},
keywords = {Antenna arrays, Array signal processing, cell-free networks, Channel estimation, cooperative beamforming, CSI uncertainty, Downlink, Millimeter wave communication, MIMO, mmWave, Radio frequency, robust beamforming, Uncertainty, Uplink, Vectors},
pubstate = {published},
tppubtype = {article}
}
A low-complexity robust cooperative hybrid beamformer is designed for both the downlink and uplink of cell-free millimeter wave (mmWave) multiple-input-multiple-output (MIMO) networks, while considering realistic imperfect channel state information (CSI). To begin with, a second-order cone program (SOCP)-based robust fully-digital beamformer (FDBF) is designed for minimizing the worst-case interference for the downlink of multiple-input-single-output (MISO) systems. Subsequently, we develop a Bayesian learning (BL) framework for determining both the analog and digital components of the hybrid transmit precoder (TPC) from the FDBF. The above designs are subsequently extended to employing eigenvector perturbation theory for constructing the robust TPC for the cell-free mmWave MIMO downlink, where the users have multiple receive antennas (RAs). Furthermore, the multi-dimensional covariance fitting (MCF) framework is harnessed for designing the robust TPC of the corresponding uplink. Finally, the efficiency of the proposed TPC designs is evaluated by simulation results both in terms of their ability to mitigate the multi-user interference (MUI), and improving the spectral efficiency achieved. Additionally, the proposed designs are shown to be computationally efficient and equivalent to a minimum variance hybrid beamformer.
3.
Linfu, Zou; Zhiwen, Pan; El-Hajjar, Mohammed
Graph Neural Network Aided Beamforming for Holographic Millimeter Wave MIMO Systems Journal Article
In: IEEE Transactions on Vehicular Technology, vol. 74, no. 7, pp. 10582–10595, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Accuracy, Array signal processing, Beamforming, Channel estimation, Downlink, Estimation, graph neural network, Graph neural networks, holographic MIMO, millimeter wave, Millimeter wave communication, OFDM, Optimization, Training
@article{linfu_graph_2025,
title = {Graph Neural Network Aided Beamforming for Holographic Millimeter Wave MIMO Systems},
author = {Zou Linfu and Pan Zhiwen and Mohammed El-Hajjar},
url = {https://ieeexplore.ieee.org/document/10896848},
doi = {10.1109/TVT.2025.3544063},
issn = {1939-9359},
year = {2025},
date = {2025-07-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
volume = {74},
number = {7},
pages = {10582–10595},
abstract = {Holographic multiple-input multiple-output (HMIMO) systems are considered as one of the potential techniques to meet the demands of next-generation communications by replacing costly and power-hungry devices with sub-half-wavelength antenna elements. However, optimizing the beamforming matrix in the base station (BS) for HMIMO systems is challenging, given the prohibitive overhead of directly estimating the channels between the BS and the user equipment. Instead of following the traditional method of channel estimation and beamforming optimization, in this paper we employ a deep-learning technique to optimize the beamformers at the BS based on a loss function. Specifically, in this paper we introduce a graph neural network (GNN) designed to map the received pilot signals to optimized beamforming matrices and to model interactions among user equipment within the network. The simulation results show that our deep-learning method effectively maximizes the sum-rate objective while using reduced number of pilots than traditional channel estimation and beamforming optimization techniques.},
keywords = {Accuracy, Array signal processing, Beamforming, Channel estimation, Downlink, Estimation, graph neural network, Graph neural networks, holographic MIMO, millimeter wave, Millimeter wave communication, OFDM, Optimization, Training},
pubstate = {published},
tppubtype = {article}
}
Holographic multiple-input multiple-output (HMIMO) systems are considered as one of the potential techniques to meet the demands of next-generation communications by replacing costly and power-hungry devices with sub-half-wavelength antenna elements. However, optimizing the beamforming matrix in the base station (BS) for HMIMO systems is challenging, given the prohibitive overhead of directly estimating the channels between the BS and the user equipment. Instead of following the traditional method of channel estimation and beamforming optimization, in this paper we employ a deep-learning technique to optimize the beamformers at the BS based on a loss function. Specifically, in this paper we introduce a graph neural network (GNN) designed to map the received pilot signals to optimized beamforming matrices and to model interactions among user equipment within the network. The simulation results show that our deep-learning method effectively maximizes the sum-rate objective while using reduced number of pilots than traditional channel estimation and beamforming optimization techniques.
4.
Rai, Sudhakar; Sharma, Ekant; Jagannatham, Aditya K.; Hanzo, Lajos
The Spectral Versus Energy Efficiency Trade-Off in Dynamic User Clustering Aided mmWave NOMA Networks Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 6, pp. 4503–4519, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, Clustering algorithms, Energy Efficiency, fractional programming, Heuristic algorithms, Hybrid power systems, hybrid precoding, Interference cancellation, Millimeter wave communication, MIMO, mmWave, NOMA, Optimization, Resource management, Spectral efficiency, user clustering
@article{rai_spectral_2025,
title = {The Spectral Versus Energy Efficiency Trade-Off in Dynamic User Clustering Aided mmWave NOMA Networks},
author = {Sudhakar Rai and Ekant Sharma and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10769478},
doi = {10.1109/TCOMM.2024.3506920},
issn = {1558-0857},
year = {2025},
date = {2025-06-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {6},
pages = {4503–4519},
abstract = {The spectral efficiency (SE) and global energy efficiency (GEE) trade-off encountered in the design of millimeter-wave (mmWave)-based massive multi-input multi-output (MIMO) non-orthogonal multiple access (NOMA) networks is investigated with a particular focus on user clustering. By exploiting the similarity among user channels a pair of spectral and energy-efficient user clustering algorithms are proposed for dynamically selecting both the number of clusters and the number of users in each cluster. Subsequently, a joint analog precoder/combiner and user clustering technique is developed, followed by a multi-objective optimization (MOO) framework for flexibly balancing the GEE and SE objectives in a mmWave NOMA network subject to specific constraints. The MOO objective is initially transformed to a weighted sum rate maximization problem, followed by a quadratic-transform (QT)-based approach conceived for maximizing the non-convex objective by approximating it as a concave-convex function. Our simulation results demonstrate that the user clustering techniques designed attain a 85% performance gain over random clustering technique and demonstrating the benefits of the algorithm designed for mmWave NOMA networks.},
keywords = {Array signal processing, Clustering algorithms, Energy Efficiency, fractional programming, Heuristic algorithms, Hybrid power systems, hybrid precoding, Interference cancellation, Millimeter wave communication, MIMO, mmWave, NOMA, Optimization, Resource management, Spectral efficiency, user clustering},
pubstate = {published},
tppubtype = {article}
}
The spectral efficiency (SE) and global energy efficiency (GEE) trade-off encountered in the design of millimeter-wave (mmWave)-based massive multi-input multi-output (MIMO) non-orthogonal multiple access (NOMA) networks is investigated with a particular focus on user clustering. By exploiting the similarity among user channels a pair of spectral and energy-efficient user clustering algorithms are proposed for dynamically selecting both the number of clusters and the number of users in each cluster. Subsequently, a joint analog precoder/combiner and user clustering technique is developed, followed by a multi-objective optimization (MOO) framework for flexibly balancing the GEE and SE objectives in a mmWave NOMA network subject to specific constraints. The MOO objective is initially transformed to a weighted sum rate maximization problem, followed by a quadratic-transform (QT)-based approach conceived for maximizing the non-convex objective by approximating it as a concave-convex function. Our simulation results demonstrate that the user clustering techniques designed attain a 85% performance gain over random clustering technique and demonstrating the benefits of the algorithm designed for mmWave NOMA networks.
5.
Singh, Jitendra; Naveen, Banda; Srivastava, Suraj; Jagannatham, Aditya K.; Hanzo, Lajos
Pareto-Optimal Hybrid Beamforming for Finite-Blocklength Millimeter Wave Systems Journal Article
In: IEEE Transactions on Vehicular Technology, vol. 74, no. 6, pp. 9910–9915, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Array signal processing, Error probability, hybrid beamforming, millimeter wave, Millimeter wave communication, Millimeter wave technology, Optimization, Pareto boundary, Radio frequency, Short packet communication, Signal to noise ratio, Symbols, Ultra reliable low latency communication, Vectors
@article{singh_pareto-optimal_2025,
title = {Pareto-Optimal Hybrid Beamforming for Finite-Blocklength Millimeter Wave Systems},
author = {Jitendra Singh and Banda Naveen and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10854905},
doi = {10.1109/TVT.2025.3534021},
issn = {1939-9359},
year = {2025},
date = {2025-06-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
volume = {74},
number = {6},
pages = {9910–9915},
abstract = {Short-packet communication (SPC) is essentially synonymous with ultra-reliable low-latency communication (uRLLC), which must meet stringent latency and reliability requirements. However, achieving efficient hybrid beamforming (HBF) in SPC-based millimeter wave (mmWave) systems is challenging due to the constraints of finite block lengths, limited number of radio frequency chains (RFCs), and owing to the complex optimization of transmit precoders (TPCs). In this work, we investigate the achievable rate region of an SPC-based mmWave downlink system. We harness the HBF for finite block lengths low-latency communication, relying on a low number of RFCs. We formulate a Pareto optimization problem for characterizing the achievable rate region, while considering the transmit power, mmWave hardware, and block length constraints. To solve this highly non-convex problem, we propose a bisection search-based block coordinate descent (Bi-BCD) algorithm, in which we optimize the RF TPC, the baseband (BB) TPC, and the block length. Specifically, we jointly optimize the RF and BB TPCs for a fixed block length, which involves both Remanian conjugate gradient (RCG) and second-order cone programming (SOCP) techniques, and then we optimize the block length by the mixed integer programming method. Subsequently, we update the achievable rate via the bisection search method. Finally, we present simulation results and quantify the efficiency of the proposed scheme.},
keywords = {Array signal processing, Error probability, hybrid beamforming, millimeter wave, Millimeter wave communication, Millimeter wave technology, Optimization, Pareto boundary, Radio frequency, Short packet communication, Signal to noise ratio, Symbols, Ultra reliable low latency communication, Vectors},
pubstate = {published},
tppubtype = {article}
}
Short-packet communication (SPC) is essentially synonymous with ultra-reliable low-latency communication (uRLLC), which must meet stringent latency and reliability requirements. However, achieving efficient hybrid beamforming (HBF) in SPC-based millimeter wave (mmWave) systems is challenging due to the constraints of finite block lengths, limited number of radio frequency chains (RFCs), and owing to the complex optimization of transmit precoders (TPCs). In this work, we investigate the achievable rate region of an SPC-based mmWave downlink system. We harness the HBF for finite block lengths low-latency communication, relying on a low number of RFCs. We formulate a Pareto optimization problem for characterizing the achievable rate region, while considering the transmit power, mmWave hardware, and block length constraints. To solve this highly non-convex problem, we propose a bisection search-based block coordinate descent (Bi-BCD) algorithm, in which we optimize the RF TPC, the baseband (BB) TPC, and the block length. Specifically, we jointly optimize the RF and BB TPCs for a fixed block length, which involves both Remanian conjugate gradient (RCG) and second-order cone programming (SOCP) techniques, and then we optimize the block length by the mixed integer programming method. Subsequently, we update the achievable rate via the bisection search method. Finally, we present simulation results and quantify the efficiency of the proposed scheme.
6.
Singh, Jitendra; Naveen, Banda; Srivastava, Suraj; Jagannatham, Aditya K.; Hanzo, Lajos
Pareto Optimal Hybrid Beamforming for Short-Packet Millimeter-Wave Integrated Sensing and Communication Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 6, pp. 4570–4585, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, Copper, hybrid beamforming, Integrated sensing and communication, Millimeter wave communication, Millimeter wave radar, Optimization, Pareto boundary, Programming, Radio frequency, Short packet communication, Signal to noise ratio, Ultra reliable low latency communication, Ultra-reliable low latency communication
@article{singh_pareto_2025,
title = {Pareto Optimal Hybrid Beamforming for Short-Packet Millimeter-Wave Integrated Sensing and Communication},
author = {Jitendra Singh and Banda Naveen and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10778580},
doi = {10.1109/TCOMM.2024.3511704},
issn = {1558-0857},
year = {2025},
date = {2025-06-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {6},
pages = {4570–4585},
abstract = {Pareto optimal solutions are conceived for radar beamforming error (RBE) and sum rate maximization in short-packet (SP) millimeter-wave (mmWave) integrated sensing and communication (ISAC). Our ultimate goal is to realize ultra-reliable low-latency communication (uRLLC) and real-time sensing capabilities for 6G applications. The ISAC base station (BS) transmits short packets in the downlink (DL) to serve multiple communication users (CUs) and detect multiple radar targets (RTs). We investigate the performance trade-off between the sensing and communication capabilities by optimizing both the radio frequency (RF) and the baseband (BB) transmit precoder (TPC), together with the block lengths. The optimization problem considers the minimum rate requirements of the CUs, the maximum tolerable radar beamforming error (RBE) for the RTs, the unit modulus (UM) elements of the RF TPC, and the finite transmit power as the constraints for SP transmission. The resultant problem is highly non-convex due to the intractable rate expression of the SP regime coupled with the non-convex rate and UM constraints. To solve this problem, we propose an innovative two-layer bisection search (TLBS) algorithm, wherein the RF and BB TPCs are optimized in the inner layer, followed by the block length in the outer layer. Furthermore, a pair of novel methods, namely a bisection search-based majorizer and minimizer (BMM) as well as exact penalty-based manifold optimization (EPMO) are harnessed for optimizing the RF TPC in the inner layer. Subsequently, the BB TPC and the block length are derived via second-order cone programming (SOCP) and mixed integer programming methods, respectively. Finally, our exhaustive simulation results reveal the effect of system parameters for various settings on the RBE-rate region of the SP mmWave ISAC system and demonstrate a significantly enhanced performance compared to the benchmarks.},
keywords = {Array signal processing, Copper, hybrid beamforming, Integrated sensing and communication, Millimeter wave communication, Millimeter wave radar, Optimization, Pareto boundary, Programming, Radio frequency, Short packet communication, Signal to noise ratio, Ultra reliable low latency communication, Ultra-reliable low latency communication},
pubstate = {published},
tppubtype = {article}
}
Pareto optimal solutions are conceived for radar beamforming error (RBE) and sum rate maximization in short-packet (SP) millimeter-wave (mmWave) integrated sensing and communication (ISAC). Our ultimate goal is to realize ultra-reliable low-latency communication (uRLLC) and real-time sensing capabilities for 6G applications. The ISAC base station (BS) transmits short packets in the downlink (DL) to serve multiple communication users (CUs) and detect multiple radar targets (RTs). We investigate the performance trade-off between the sensing and communication capabilities by optimizing both the radio frequency (RF) and the baseband (BB) transmit precoder (TPC), together with the block lengths. The optimization problem considers the minimum rate requirements of the CUs, the maximum tolerable radar beamforming error (RBE) for the RTs, the unit modulus (UM) elements of the RF TPC, and the finite transmit power as the constraints for SP transmission. The resultant problem is highly non-convex due to the intractable rate expression of the SP regime coupled with the non-convex rate and UM constraints. To solve this problem, we propose an innovative two-layer bisection search (TLBS) algorithm, wherein the RF and BB TPCs are optimized in the inner layer, followed by the block length in the outer layer. Furthermore, a pair of novel methods, namely a bisection search-based majorizer and minimizer (BMM) as well as exact penalty-based manifold optimization (EPMO) are harnessed for optimizing the RF TPC in the inner layer. Subsequently, the BB TPC and the block length are derived via second-order cone programming (SOCP) and mixed integer programming methods, respectively. Finally, our exhaustive simulation results reveal the effect of system parameters for various settings on the RBE-rate region of the SP mmWave ISAC system and demonstrate a significantly enhanced performance compared to the benchmarks.
7.
Vallejo, Luis; Mora, Jose; Ortega, Beatriz; Jin, Wei; Romero, Jaime; Tang, Jianming
Full-Duplex Transmissions in Heterogeneous Fiber-FSO-Wireless Converged Access Networks at Ka-Band Proceedings Article
In: 2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), pp. 840–845, 2025, ISSN: 2575-4912, (ISSN: 2575-4912).
Abstract | Links | BibTeX | Tags: 5G mobile communication, B5G, bidirectional heterogeneous networks, converged networks, free-running lasers, Full-duplex system, fullduplex, Heterogeneous networks, Millimeter wave communication, mmWave, Phase shift keying, Radio links, Resource management, RF envelope detection, Throughput, Uplink, Wireless communication
@inproceedings{vallejo_full-duplex_2025,
title = {Full-Duplex Transmissions in Heterogeneous Fiber-FSO-Wireless Converged Access Networks at Ka-Band},
author = {Luis Vallejo and Jose Mora and Beatriz Ortega and Wei Jin and Jaime Romero and Jianming Tang},
url = {https://ieeexplore.ieee.org/document/11037218},
doi = {10.1109/EuCNC/6GSummit63408.2025.11037218},
issn = {2575-4912},
year = {2025},
date = {2025-06-01},
urldate = {2025-10-08},
booktitle = {2025 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)},
pages = {840–845},
abstract = {To overcome the challenges associated with increased demands for mobile capacity and network densification in the 5 G and beyond era, this paper experimentally demonstrates full-duplex heterogeneous fiber-FSO-wireless converged links between the central office-baseband unit (CO-BBU) and the remote radio head (RRH). The centralization of active optical sources for the downlink (DL) and uplink (UL) enables dynamic resource sharing and allocation, optimizing wavelength utilization and improving overall network efficiency. The DL uses a directly modulated laser (DML) with free-running laser-assisted mmWave signal generation and envelope detection for the downstream, transmitting a 100 textbackslashtextMHz 16-textbackslashtextQAM signal at 39 GHz. The UL reuses the DL wavelength for upstream transmission, employing intensity modulation and direct detection (IM-DD) of a 100 MHz QPSK signal at 36.5 GHz. The bidirectional heterogeneous network comprises a 10 km SSMF, a 1.8 m FSO link, and a 3 m wireless radio link, providing flexibility for future networks. The results show successful transmissions of 16-QAM and QPSK signals up to 200 textbackslashtextMbit / textbackslashmathrms and 400 textbackslashtextMbit / textbackslashmathrms for DL and UL, respectively, under the full-duplex transmissions. Additionally, using 5G NR OFDM signals, a maximum bit rate of 2.15 textbackslashtextGbit / textbackslashmathrms and 1.07 Gbit/s is achieved for the DL and UL, respectively, demonstrating the cost-effectiveness of the proposed solution.},
note = {ISSN: 2575-4912},
keywords = {5G mobile communication, B5G, bidirectional heterogeneous networks, converged networks, free-running lasers, Full-duplex system, fullduplex, Heterogeneous networks, Millimeter wave communication, mmWave, Phase shift keying, Radio links, Resource management, RF envelope detection, Throughput, Uplink, Wireless communication},
pubstate = {published},
tppubtype = {inproceedings}
}
To overcome the challenges associated with increased demands for mobile capacity and network densification in the 5 G and beyond era, this paper experimentally demonstrates full-duplex heterogeneous fiber-FSO-wireless converged links between the central office-baseband unit (CO-BBU) and the remote radio head (RRH). The centralization of active optical sources for the downlink (DL) and uplink (UL) enables dynamic resource sharing and allocation, optimizing wavelength utilization and improving overall network efficiency. The DL uses a directly modulated laser (DML) with free-running laser-assisted mmWave signal generation and envelope detection for the downstream, transmitting a 100 textbackslashtextMHz 16-textbackslashtextQAM signal at 39 GHz. The UL reuses the DL wavelength for upstream transmission, employing intensity modulation and direct detection (IM-DD) of a 100 MHz QPSK signal at 36.5 GHz. The bidirectional heterogeneous network comprises a 10 km SSMF, a 1.8 m FSO link, and a 3 m wireless radio link, providing flexibility for future networks. The results show successful transmissions of 16-QAM and QPSK signals up to 200 textbackslashtextMbit / textbackslashmathrms and 400 textbackslashtextMbit / textbackslashmathrms for DL and UL, respectively, under the full-duplex transmissions. Additionally, using 5G NR OFDM signals, a maximum bit rate of 2.15 textbackslashtextGbit / textbackslashmathrms and 1.07 Gbit/s is achieved for the DL and UL, respectively, demonstrating the cost-effectiveness of the proposed solution.
8.
Gadamsetty, Pavan Kumar; Hari, K. V. S.; Hanzo, Lajos
Sum-Rate Maximization of RIS-Aided Digital and Holographic Beamformers in MU-MISO Systems Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 5, pp. 3106–3118, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: alternating maximization (AM), Array signal processing, Arrays, Beamforming, Millimeter wave communication, MISO communication, Programming, Radio frequency, Reconfigurable holographic surfaces (RHS), reconfigurable intelligent surfaces (RIS), Signal to noise ratio, sum-rate, Transceivers, Vectors, Wireless communication
@article{kumar_gadamsetty_sum-rate_2025,
title = {Sum-Rate Maximization of RIS-Aided Digital and Holographic Beamformers in MU-MISO Systems},
author = {Pavan Kumar Gadamsetty and K. V. S. Hari and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10737121},
doi = {10.1109/TCOMM.2024.3487305},
issn = {1558-0857},
year = {2025},
date = {2025-05-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {5},
pages = {3106–3118},
abstract = {Reconfigurable holographic surfaces (RHS) are intrinsically amalgamated with reconfigurable intelligent surfaces (RIS), for beneficially ameliorating the signal propagation environment. This potent architecture significantly improves the system performance in non-line-of-sight scenarios at a low power consumption. Briefly, the RHS technology integrates ultra-thin, lightweight antennas onto the transceiver, for creating sharp, high-gain directional beams. We formulate a user sum-rate maximization problem for our RHS-RIS-based hybrid beamformer. Explicitly, we jointly design the digital, holographic, and passive beamformers for maximizing the sum-rate of all user equipment (UE). To tackle the resultant nonconvex optimization problem, we propose an alternating maximization (AM) framework for decoupling and iteratively solving the subproblems involved. Specifically, we employ the zero-forcing criterion for the digital beamformer, leverage fractional programming to determine the radiation amplitudes of the RHS and utilize the Riemannian conjugate gradient algorithm for optimizing the RIS phase shift matrix of the passive beamformer. Our simulation results demonstrate that the proposed RHS-RIS-based hybrid beamformer outperforms its conventional counterpart operating without an RIS in multi-UE scenarios. The sum-rate improvement attained ranges from 8 bps/Hz to 13 bps/Hz for various transmit powers at the base station (BS) and at the UEs, which is significant.},
keywords = {alternating maximization (AM), Array signal processing, Arrays, Beamforming, Millimeter wave communication, MISO communication, Programming, Radio frequency, Reconfigurable holographic surfaces (RHS), reconfigurable intelligent surfaces (RIS), Signal to noise ratio, sum-rate, Transceivers, Vectors, Wireless communication},
pubstate = {published},
tppubtype = {article}
}
Reconfigurable holographic surfaces (RHS) are intrinsically amalgamated with reconfigurable intelligent surfaces (RIS), for beneficially ameliorating the signal propagation environment. This potent architecture significantly improves the system performance in non-line-of-sight scenarios at a low power consumption. Briefly, the RHS technology integrates ultra-thin, lightweight antennas onto the transceiver, for creating sharp, high-gain directional beams. We formulate a user sum-rate maximization problem for our RHS-RIS-based hybrid beamformer. Explicitly, we jointly design the digital, holographic, and passive beamformers for maximizing the sum-rate of all user equipment (UE). To tackle the resultant nonconvex optimization problem, we propose an alternating maximization (AM) framework for decoupling and iteratively solving the subproblems involved. Specifically, we employ the zero-forcing criterion for the digital beamformer, leverage fractional programming to determine the radiation amplitudes of the RHS and utilize the Riemannian conjugate gradient algorithm for optimizing the RIS phase shift matrix of the passive beamformer. Our simulation results demonstrate that the proposed RHS-RIS-based hybrid beamformer outperforms its conventional counterpart operating without an RIS in multi-UE scenarios. The sum-rate improvement attained ranges from 8 bps/Hz to 13 bps/Hz for various transmit powers at the base station (BS) and at the UEs, which is significant.
9.
Nafees, Muhammad; Baniasadi, Mohammadamin; Hopgood, James R.; Safari, Majid; Thompson, John S.
Integrated Sensing and Communication for UAV Trajectory Optimization in Mixed FSO-RF Networks in Dynamic Weather Conditions Proceedings Article
In: 2025 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6, 2025, ISSN: 1558-2612, (ISSN: 1558-2612).
Abstract | Links | BibTeX | Tags: 6G mobile communication, Autonomous aerial vehicles, Backhaul networks, free-space optical (FSO), Integrated sensing and communication, Meteorology, millimeter wave (mmWave), Millimeter wave communication, Optical attenuators, Optical feedback, Optical integrated sensing and communication (O-ISAC), Optical sensors, Sixth-generation (6G), Throughput, unmanned aerial vehicles (UAVs)
@inproceedings{nafees_integrated_2025,
title = {Integrated Sensing and Communication for UAV Trajectory Optimization in Mixed FSO-RF Networks in Dynamic Weather Conditions},
author = {Muhammad Nafees and Mohammadamin Baniasadi and James R. Hopgood and Majid Safari and John S. Thompson},
url = {https://ieeexplore.ieee.org/document/10978163},
doi = {10.1109/WCNC61545.2025.10978163},
issn = {1558-2612},
year = {2025},
date = {2025-03-01},
urldate = {2025-10-08},
booktitle = {2025 IEEE Wireless Communications and Networking Conference (WCNC)},
pages = {1–6},
abstract = {Integrated sensing and communication (ISAC) is expected to transform data transmission and real-time sensing, enhancing sixth-generation (6G) networks. Free-space optical (FSO) communication is a key 6G backhaul solution, complementing radio frequency (RF) technologies like millimeter wave (mmWave) for improved network reliability. However, adverse weather can significantly reduce FSO link reliability due to atmospheric attenuation. Such adverse weather conditions also increase the level of back-scattered light, potentially enabling the real-time sensing of the atmospheric channel gain at the transmitter side. Therefore, this paper proposes a novel optical ISAC (O-ISAC) framework, where the back-scattered light from the FSO communication signal is used as the sensing feedback signal. This O-ISAC framework is analyzed considering a single-cell network aided by an unmanned aerial vehicle (UAV) to support edge users. The UAV is connected to the gateway via a FSO backhaul link while estimating the FSO channel gain based on the back-scattered light and dynamically optimizing its trajectory. The aim of this adaptive O-ISAC system is to maximize the end-to-end network throughput of the edge users while considering FSO backhaul capacity and the UAV's directional antenna beamwidth and bandwidth allocation. Numerical results demonstrate that UAV can effectively optimize its trajectory by adjusting the antenna beamwidth and downlink bandwidth allocation at different weather conditions. The proposed framework is tested using hourly visibility data from Edinburgh, demonstrating that optical channel sensing is crucial for the system's overall performance.},
note = {ISSN: 1558-2612},
keywords = {6G mobile communication, Autonomous aerial vehicles, Backhaul networks, free-space optical (FSO), Integrated sensing and communication, Meteorology, millimeter wave (mmWave), Millimeter wave communication, Optical attenuators, Optical feedback, Optical integrated sensing and communication (O-ISAC), Optical sensors, Sixth-generation (6G), Throughput, unmanned aerial vehicles (UAVs)},
pubstate = {published},
tppubtype = {inproceedings}
}
Integrated sensing and communication (ISAC) is expected to transform data transmission and real-time sensing, enhancing sixth-generation (6G) networks. Free-space optical (FSO) communication is a key 6G backhaul solution, complementing radio frequency (RF) technologies like millimeter wave (mmWave) for improved network reliability. However, adverse weather can significantly reduce FSO link reliability due to atmospheric attenuation. Such adverse weather conditions also increase the level of back-scattered light, potentially enabling the real-time sensing of the atmospheric channel gain at the transmitter side. Therefore, this paper proposes a novel optical ISAC (O-ISAC) framework, where the back-scattered light from the FSO communication signal is used as the sensing feedback signal. This O-ISAC framework is analyzed considering a single-cell network aided by an unmanned aerial vehicle (UAV) to support edge users. The UAV is connected to the gateway via a FSO backhaul link while estimating the FSO channel gain based on the back-scattered light and dynamically optimizing its trajectory. The aim of this adaptive O-ISAC system is to maximize the end-to-end network throughput of the edge users while considering FSO backhaul capacity and the UAV's directional antenna beamwidth and bandwidth allocation. Numerical results demonstrate that UAV can effectively optimize its trajectory by adjusting the antenna beamwidth and downlink bandwidth allocation at different weather conditions. The proposed framework is tested using hourly visibility data from Edinburgh, demonstrating that optical channel sensing is crucial for the system's overall performance.
10.
Singh, Jitendra; Srivastava, Suraj; Yadav, Surya P.; Jagannatham, Aditya K.; Hanzo, Lajos
Joint Hybrid Transceiver and Reflection Matrix Design for RIS-Aided mmWave MIMO Cognitive Radio Systems Journal Article
In: IEEE Transactions on Cognitive Communications and Networking, vol. 11, no. 1, pp. 391–407, 2025, ISSN: 2332-7731.
Abstract | Links | BibTeX | Tags: Array signal processing, cognitive radio, Downlink, hybrid beamforming, Interference, Millimeter wave communication, MIMO communication, mmWave, Quality of service, Radio frequency, Riemannian conjugate gradient, RIS
@article{singh_joint_2025,
title = {Joint Hybrid Transceiver and Reflection Matrix Design for RIS-Aided mmWave MIMO Cognitive Radio Systems},
author = {Jitendra Singh and Suraj Srivastava and Surya P. Yadav and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10561503},
doi = {10.1109/TCCN.2024.3415620},
issn = {2332-7731},
year = {2025},
date = {2025-02-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Cognitive Communications and Networking},
volume = {11},
number = {1},
pages = {391–407},
abstract = {In this work, a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) cognitive radio (CR) downlink operating in the underlay mode is investigated. The cognitive base station (CBS) communicates with multiple secondary users (SUs), each having multiple RF chains in the presence of a primary user (PU). We conceive a joint hybrid transmit precoder (TPC), receiver combiner (RC), and RIS reflection matrix (RM) design, which maximizes the sum spectral efficiency (SE) of the secondary system while maintaining the interference induced at the PU below a specified threshold. To this end, we formulate the sum-SE maximization problem considering the total transmit power (TP), the interference power (IP), and the non-convex unity modulus constraints of the RF TPC, RF RC, and RM. To solve this highly non-convex problem, we propose a two-stage hybrid transceiver design in conjunction with a novel block coordinate descent (BCD)-successive Riemannian conjugate gradient (SRCG) algorithm. We initially decompose the RF TPC, RC, and RM optimization problem into a series of sub-problems and subsequently design pairs of RF TPC and RC vectors, followed by successively optimizing the elements of the RM using the iterative BCD-SRCG algorithm. Furthermore, based on the effective baseband (BB) channel, the BB TPC and BB RC are designed using the proposed direct singular value decomposition (D-SVD) and projection based SVD (P-SVD) methods. Subsequently, the proportional water-filling solution is proposed for optimizing the power, which maximizes the weighted sum-SE of the system. Finally, simulation results are provided to compare our proposed schemes to several benchmarks and quantify the impact of other parameters on the sum-SE of the system.},
keywords = {Array signal processing, cognitive radio, Downlink, hybrid beamforming, Interference, Millimeter wave communication, MIMO communication, mmWave, Quality of service, Radio frequency, Riemannian conjugate gradient, RIS},
pubstate = {published},
tppubtype = {article}
}
In this work, a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) cognitive radio (CR) downlink operating in the underlay mode is investigated. The cognitive base station (CBS) communicates with multiple secondary users (SUs), each having multiple RF chains in the presence of a primary user (PU). We conceive a joint hybrid transmit precoder (TPC), receiver combiner (RC), and RIS reflection matrix (RM) design, which maximizes the sum spectral efficiency (SE) of the secondary system while maintaining the interference induced at the PU below a specified threshold. To this end, we formulate the sum-SE maximization problem considering the total transmit power (TP), the interference power (IP), and the non-convex unity modulus constraints of the RF TPC, RF RC, and RM. To solve this highly non-convex problem, we propose a two-stage hybrid transceiver design in conjunction with a novel block coordinate descent (BCD)-successive Riemannian conjugate gradient (SRCG) algorithm. We initially decompose the RF TPC, RC, and RM optimization problem into a series of sub-problems and subsequently design pairs of RF TPC and RC vectors, followed by successively optimizing the elements of the RM using the iterative BCD-SRCG algorithm. Furthermore, based on the effective baseband (BB) channel, the BB TPC and BB RC are designed using the proposed direct singular value decomposition (D-SVD) and projection based SVD (P-SVD) methods. Subsequently, the proportional water-filling solution is proposed for optimizing the power, which maximizes the weighted sum-SE of the system. Finally, simulation results are provided to compare our proposed schemes to several benchmarks and quantify the impact of other parameters on the sum-SE of the system.
11.
Singh, Jitendra; Mehrotra, Anand; Srivastava, Suraj; Jagannatham, Aditya K.; Hanzo, Lajos
Spectral Efficiency Maximization for Mmwave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints Journal Article
In: IEEE Transactions on Vehicular Technology, pp. 1–16, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Copper, Hybrid power systems, Integrated sensing and communication, Interference, millimeter wave, Millimeter wave communication, Optimization, Radar, radar beampattern similarity, Radio frequency, Signal to noise ratio, Spectral efficiency
@article{singh_spectral_2025,
title = {Spectral Efficiency Maximization for Mmwave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints},
author = {Jitendra Singh and Anand Mehrotra and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11027785},
doi = {10.1109/TVT.2025.3577955},
issn = {1939-9359},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
pages = {1–16},
abstract = {A hybrid transmit precoder (TPC) and receive combiner (RC) pair is conceived for millimeter wave (mmWave) multiple input multiple output (MIMO) integrated sensing and communication (ISAC) systems. The proposed design considers a practical mean squared error (MSE) constraint between the desired and the achieved beampatterns constructed for identifying radar targets (RTs). To achieve optimal performance, we formulate an optimization problem relying on sum spectral efficiency (SE) maximization of the communication users (CUs), while satisfying certain radar beampattern similarity (RBPS), total transmit power, and constant modulus constraints, where the latter are attributed to the hybrid mmWave MIMO architecture. Since the aforementioned problem is non-convex and intractable, a sequential approach is proposed wherein the TPCs are designed first, followed by the RCs. To deal with the non-convex MSE and constant modulus constraints in the TPC design problem, we propose a majorization and minimization (MM) based Riemannian conjugate gradient (RCG) method, which restricts the tolerable MSE of the beampattern to within a predefined limit. Moreover, the least squares and the zero-forcing methods are adopted for maximizing the sum-SE and for mitigating the multiuser interference (MUI), respectively. Furthermore, to design the RC at each CU, we propose a linear MM-based blind combiner (LMBC) scheme that does not rely on the knowledge of the TPC at the CUs and has a low complexity. To achieve user fairness, we further extend the proposed sequential approach for maximizing the geometric mean (GM) of the CU's rate. Simulation results are presented, which show the superior performance of the proposed hybrid TPC and RC in comparison to the state-of-the-art designs in the mmWave MIMO ISAC systems under consideration.},
keywords = {Copper, Hybrid power systems, Integrated sensing and communication, Interference, millimeter wave, Millimeter wave communication, Optimization, Radar, radar beampattern similarity, Radio frequency, Signal to noise ratio, Spectral efficiency},
pubstate = {published},
tppubtype = {article}
}
A hybrid transmit precoder (TPC) and receive combiner (RC) pair is conceived for millimeter wave (mmWave) multiple input multiple output (MIMO) integrated sensing and communication (ISAC) systems. The proposed design considers a practical mean squared error (MSE) constraint between the desired and the achieved beampatterns constructed for identifying radar targets (RTs). To achieve optimal performance, we formulate an optimization problem relying on sum spectral efficiency (SE) maximization of the communication users (CUs), while satisfying certain radar beampattern similarity (RBPS), total transmit power, and constant modulus constraints, where the latter are attributed to the hybrid mmWave MIMO architecture. Since the aforementioned problem is non-convex and intractable, a sequential approach is proposed wherein the TPCs are designed first, followed by the RCs. To deal with the non-convex MSE and constant modulus constraints in the TPC design problem, we propose a majorization and minimization (MM) based Riemannian conjugate gradient (RCG) method, which restricts the tolerable MSE of the beampattern to within a predefined limit. Moreover, the least squares and the zero-forcing methods are adopted for maximizing the sum-SE and for mitigating the multiuser interference (MUI), respectively. Furthermore, to design the RC at each CU, we propose a linear MM-based blind combiner (LMBC) scheme that does not rely on the knowledge of the TPC at the CUs and has a low complexity. To achieve user fairness, we further extend the proposed sequential approach for maximizing the geometric mean (GM) of the CU's rate. Simulation results are presented, which show the superior performance of the proposed hybrid TPC and RC in comparison to the state-of-the-art designs in the mmWave MIMO ISAC systems under consideration.
12.
Gupta, Awadhesh; Singh, Jitendra; Srivastava, Suraj; Jagannatham, Aditya K.; Hanzo, Lajos
Bayesian Learning Aided Parameter Estimation and Joint Beamformer Design in mmWave MIMO-OFDM ISAC Systems Journal Article
In: IEEE Transactions on Communications, pp. 1–1, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, Bayes methods, dual-functional radar-communication (DFRC), Estimation, hybrid analog-digital (HAD) beamforming, Integrated sensing and communication (ISAC), millimeter wave (mmWave), Millimeter wave communication, MIMO, OFDM, Parameter estimation, Radar, Radar cross-sections, Radio frequency, sparse Bayesian learning (SBL)
@article{gupta_bayesian_2025,
title = {Bayesian Learning Aided Parameter Estimation and Joint Beamformer Design in mmWave MIMO-OFDM ISAC Systems},
author = {Awadhesh Gupta and Jitendra Singh and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11030617},
doi = {10.1109/TCOMM.2025.3578813},
issn = {1558-0857},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
pages = {1–1},
abstract = {A three-dimensional (3D) sparse signal recovery problem formulation is conceived for delay, Doppler, and angular (DDA) domain target parameter estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems relying on a hybrid beamforming architecture. Subsequently, a 3D-sparse Bayesian learning (3D-BL) algorithm is proposed to jointly estimate the angular, range, velocity, and radar cross-section (RCS) parameters of the targets. Furthermore, an uplink beamformer is designed for the user equipment (UE) to alleviate the complexity of uplink parameter estimation at the dual-functional radar-communication (DFRC) base station (BS) by eliminating the need for angle of departure (AoD) estimation. Additionally, a Bayesian alternating minimization (BAT-MIN) algorithm is constructed for the designing of a DFRC waveform, enabling the simultaneous generation of beams toward both the radar targets and the UE. Furthermore, the sparse Bayesian learning lower bound (SBL-LB) and the Bayesian Cramér-Rao lower bound (BCRLB) are derived to serve as benchmarks for estimation performance. Finally, simulation results are presented to showcase the enhanced performance of the proposed methodologies in terms of multiple performance metrics when contrasted both to the existing sparse recovery techniques and to conventional non-sparse parameter estimation algorithms. The simulation outcomes unequivocally demonstrate the commendable performance of the proposed 3D-BL estimation methodology, approaching closely to the SBL-LB. Notably, this approach exhibits a substantial gain of at least 5 dB when compared to alternative techniques. Additionally, the introduced BAT-MIN beamformer emerges as a highly competitive solution, closely approximating the capabilities of a fully digital beamformer while maintaining a noteworthy minimum advantage over its contemporaries. These findings underscore the significance and efficacy of the proposed techniques in the context of advanced signal processing and beamforming.},
keywords = {Array signal processing, Bayes methods, dual-functional radar-communication (DFRC), Estimation, hybrid analog-digital (HAD) beamforming, Integrated sensing and communication (ISAC), millimeter wave (mmWave), Millimeter wave communication, MIMO, OFDM, Parameter estimation, Radar, Radar cross-sections, Radio frequency, sparse Bayesian learning (SBL)},
pubstate = {published},
tppubtype = {article}
}
A three-dimensional (3D) sparse signal recovery problem formulation is conceived for delay, Doppler, and angular (DDA) domain target parameter estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems relying on a hybrid beamforming architecture. Subsequently, a 3D-sparse Bayesian learning (3D-BL) algorithm is proposed to jointly estimate the angular, range, velocity, and radar cross-section (RCS) parameters of the targets. Furthermore, an uplink beamformer is designed for the user equipment (UE) to alleviate the complexity of uplink parameter estimation at the dual-functional radar-communication (DFRC) base station (BS) by eliminating the need for angle of departure (AoD) estimation. Additionally, a Bayesian alternating minimization (BAT-MIN) algorithm is constructed for the designing of a DFRC waveform, enabling the simultaneous generation of beams toward both the radar targets and the UE. Furthermore, the sparse Bayesian learning lower bound (SBL-LB) and the Bayesian Cramér-Rao lower bound (BCRLB) are derived to serve as benchmarks for estimation performance. Finally, simulation results are presented to showcase the enhanced performance of the proposed methodologies in terms of multiple performance metrics when contrasted both to the existing sparse recovery techniques and to conventional non-sparse parameter estimation algorithms. The simulation outcomes unequivocally demonstrate the commendable performance of the proposed 3D-BL estimation methodology, approaching closely to the SBL-LB. Notably, this approach exhibits a substantial gain of at least 5 dB when compared to alternative techniques. Additionally, the introduced BAT-MIN beamformer emerges as a highly competitive solution, closely approximating the capabilities of a fully digital beamformer while maintaining a noteworthy minimum advantage over its contemporaries. These findings underscore the significance and efficacy of the proposed techniques in the context of advanced signal processing and beamforming.
13.
Maity, Priyanka; Harish, Deepika; Srivastava, Suraj; Jagannatham, Aditya K.; Hanzo, Lajos
Variational Bayesian Learning for 3-D Localization of Extended Targets in mmWave MIMO OFDM ISAC Systems Journal Article
In: IEEE Open Journal of the Communications Society, vol. 6, pp. 4421–4436, 2025, ISSN: 2644-125X.
Abstract | Links | BibTeX | Tags: azimuth angle, Bayes methods, Bayesian learning, Clutter, Direction-of-arrival estimation, Doppler effect, elevation angle, Estimation, extended targets, Integrated sensing and communication, Location awareness, Millimeter wave communication, MIMO, mmWave, OFDM, Radar, sparsity, Three-dimensional displays
@article{maity_variational_2025,
title = {Variational Bayesian Learning for 3-D Localization of Extended Targets in mmWave MIMO OFDM ISAC Systems},
author = {Priyanka Maity and Deepika Harish and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10990143},
doi = {10.1109/OJCOMS.2025.3567429},
issn = {2644-125X},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of the Communications Society},
volume = {6},
pages = {4421–4436},
abstract = {Variational Bayesian learning (VBL)-aided extended target localization is conceived for orthogonal frequency division multiplexing (OFDM) based-mmWave MIMO systems using the OFDM integrated sensing and communication (ISAC) waveform. The proposed framework also considers the intercarrier interference (ICI) effects encountered in mobile scenarios and the clutter present in the environment. The proposed algorithm is based on a hybrid mmWave MIMO architecture, where the number of radio frequency (RF) chains is significantly lower than the number of antennas. A range, Doppler and angular (RDA)-domain representation of the target in three-dimensional (3D) space is conceived for accurate target parameter estimation. The proposed algorithm exploits the four-dimensional (4D) sparsity arising in the RDA domain of the scattering scene and employs the powerful VBL framework for the estimation of target parameters, such as elevation angle, azimuth angle, range and velocity. To handle a practical scenario where the actual target parameters typically deviate from their finite-resolution grid, a super-resolution-based improved off-grid VBL is developed for recursively updating the parameter grid, thereby progressively improving the estimates. We also determine the Cramér-Rao bound (CRB) and Bayesian CRB for the estimation of the target parameters in order to bound the estimation performance. Our simulation results validate the superior performance of the proposed approach in comparison to the existing algorithms.},
keywords = {azimuth angle, Bayes methods, Bayesian learning, Clutter, Direction-of-arrival estimation, Doppler effect, elevation angle, Estimation, extended targets, Integrated sensing and communication, Location awareness, Millimeter wave communication, MIMO, mmWave, OFDM, Radar, sparsity, Three-dimensional displays},
pubstate = {published},
tppubtype = {article}
}
Variational Bayesian learning (VBL)-aided extended target localization is conceived for orthogonal frequency division multiplexing (OFDM) based-mmWave MIMO systems using the OFDM integrated sensing and communication (ISAC) waveform. The proposed framework also considers the intercarrier interference (ICI) effects encountered in mobile scenarios and the clutter present in the environment. The proposed algorithm is based on a hybrid mmWave MIMO architecture, where the number of radio frequency (RF) chains is significantly lower than the number of antennas. A range, Doppler and angular (RDA)-domain representation of the target in three-dimensional (3D) space is conceived for accurate target parameter estimation. The proposed algorithm exploits the four-dimensional (4D) sparsity arising in the RDA domain of the scattering scene and employs the powerful VBL framework for the estimation of target parameters, such as elevation angle, azimuth angle, range and velocity. To handle a practical scenario where the actual target parameters typically deviate from their finite-resolution grid, a super-resolution-based improved off-grid VBL is developed for recursively updating the parameter grid, thereby progressively improving the estimates. We also determine the Cramér-Rao bound (CRB) and Bayesian CRB for the estimation of the target parameters in order to bound the estimation performance. Our simulation results validate the superior performance of the proposed approach in comparison to the existing algorithms.
14.
Li, Kunlun; El-Hajjar, Mohammed; Xu, Chao; Hanzo, Lajos
Indoor Localization and Tracking in Reconfigurable Intelligent Surface Aided mmWave Systems Journal Article
In: IEEE Open Journal of Vehicular Technology, vol. 6, pp. 1815–1831, 2025, ISSN: 2644-1330.
Abstract | Links | BibTeX | Tags: Array signal processing, Channel estimation, Covariance matrices, Estimation, Kalman filters, localization/positioning, Location awareness, Millimeter wave communication, mmWave, OFDM, Radar tracking, Reconfigurable Intelligent Surfaces, sparse Bayesian learning, tracking
@article{li_indoor_2025,
title = {Indoor Localization and Tracking in Reconfigurable Intelligent Surface Aided mmWave Systems},
author = {Kunlun Li and Mohammed El-Hajjar and Chao Xu and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11050944},
doi = {10.1109/OJVT.2025.3582885},
issn = {2644-1330},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of Vehicular Technology},
volume = {6},
pages = {1815–1831},
abstract = {Millimeter wave (mmWave) carriers have a high available bandwidth, which can be beneficial for high-resolution localization in both the angular and temporal domains. However, the limited coverage due to severe path loss and line-of-sight (LoS) blockage are considered to be major challenges in mmWave. A promising solution is to employ reconfigurable intelligent surfaces (RIS) to circumvent the lack of line-of-sight paths, which can assist in localization. Furthermore, radio localization and tracking are capable of accurate real-time monitoring of the UE's locations and trajectories. In this paper, we propose a three-stage indoor tracking scheme. In the first stage, channel sounding is harnessed in support of the transmitter beamforming and receiver combining design. Based on the estimation in the first stage, a simplified received signal model is obtained, while using a discrete Fourier transform (DFT) matrix for the configuration of the RIS phase shifter for each time block. Based on the simplified received signal model, tracking initialization is carried out. Finally, in the third stage, Kalman filtering is employed for tracking. Our results demonstrate that the proposed scheme is capable of improving both the accuracy and robustness of tracking compared to single-shot successive localization. Additionally, we derive the position error bounds (PEB) of single-shot localization.},
keywords = {Array signal processing, Channel estimation, Covariance matrices, Estimation, Kalman filters, localization/positioning, Location awareness, Millimeter wave communication, mmWave, OFDM, Radar tracking, Reconfigurable Intelligent Surfaces, sparse Bayesian learning, tracking},
pubstate = {published},
tppubtype = {article}
}
Millimeter wave (mmWave) carriers have a high available bandwidth, which can be beneficial for high-resolution localization in both the angular and temporal domains. However, the limited coverage due to severe path loss and line-of-sight (LoS) blockage are considered to be major challenges in mmWave. A promising solution is to employ reconfigurable intelligent surfaces (RIS) to circumvent the lack of line-of-sight paths, which can assist in localization. Furthermore, radio localization and tracking are capable of accurate real-time monitoring of the UE's locations and trajectories. In this paper, we propose a three-stage indoor tracking scheme. In the first stage, channel sounding is harnessed in support of the transmitter beamforming and receiver combining design. Based on the estimation in the first stage, a simplified received signal model is obtained, while using a discrete Fourier transform (DFT) matrix for the configuration of the RIS phase shifter for each time block. Based on the simplified received signal model, tracking initialization is carried out. Finally, in the third stage, Kalman filtering is employed for tracking. Our results demonstrate that the proposed scheme is capable of improving both the accuracy and robustness of tracking compared to single-shot successive localization. Additionally, we derive the position error bounds (PEB) of single-shot localization.
15.
Singh, Jitendra; Jagannatham, Aditya K.; Hanzo, Lajos
Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix Journal Article
In: IEEE Open Journal of the Communications Society, vol. 6, pp. 4756–4771, 2025, ISSN: 2644-125X.
Abstract | Links | BibTeX | Tags: and geometric mean rate, Array signal processing, Base stations, Copper, Costs, Hardware, Integrated sensing and communication, millimeter wave, Millimeter wave communication, Optimization, Radio frequency, reconfigurable intelligent surface, Reconfigurable Intelligent Surfaces
@article{singh_geometric_2025,
title = {Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix},
author = {Jitendra Singh and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11012749/similar},
doi = {10.1109/OJCOMS.2025.3573196},
issn = {2644-125X},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of the Communications Society},
volume = {6},
pages = {4756–4771},
abstract = {The joint optimization of the hybrid transmit precoders (HTPCs) and reflective elements of a millimeter wave (mmWave) integrated sensing and communication (ISAC) system is considered. The system also incorporates a reconfigurable intelligent surface (RIS) relying on a non-diagonal RIS (NDRIS) phase shift matrix. Specifically, we consider a hybrid architecture at the ISAC base station (BS) that serves multiple downlink communication users (CUs) via the reflected links from the RIS, while concurrently detecting multiple radar targets (RTs). We formulate an optimization problem that aims for maximizing the geometric mean (GM) rate of the CUs, subject to the sensing requirement for each RT. Additional specifications related to the limited transmit power and unit modulus (UM) constraints for both the HTPCs and the reflective elements of the NDRIS phase shift matrix make the problem challenging. To solve this problem, we first transform the intractable GM rate expression to a tractable weighted sum rate objective and next split the transformed problem into sub-problems. Consequently, we propose an iterative alternating optimization approach that leverages the majorization-minimization (MM) framework and block coordinate descent (BCD) method to solve each sub-problem. Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. Similarly, the phases of the reflective elements of the NDRIS are optimized by employing the Riemannian manifold, and the locations of the non-zero entries of the NDRIS phase shift matrix are obtained by the maximal ratio combining (MRC) criterion. Finally, we present our simulation results, which show that deploying an NDRIS achieves additional gains for the CUs over a conventional RIS, further enhancing both the communication efficiency and sensing reliability. Furthermore, we compare the results to the pertinent benchmarks, which validate the effectiveness of our proposed algorithms.},
keywords = {and geometric mean rate, Array signal processing, Base stations, Copper, Costs, Hardware, Integrated sensing and communication, millimeter wave, Millimeter wave communication, Optimization, Radio frequency, reconfigurable intelligent surface, Reconfigurable Intelligent Surfaces},
pubstate = {published},
tppubtype = {article}
}
The joint optimization of the hybrid transmit precoders (HTPCs) and reflective elements of a millimeter wave (mmWave) integrated sensing and communication (ISAC) system is considered. The system also incorporates a reconfigurable intelligent surface (RIS) relying on a non-diagonal RIS (NDRIS) phase shift matrix. Specifically, we consider a hybrid architecture at the ISAC base station (BS) that serves multiple downlink communication users (CUs) via the reflected links from the RIS, while concurrently detecting multiple radar targets (RTs). We formulate an optimization problem that aims for maximizing the geometric mean (GM) rate of the CUs, subject to the sensing requirement for each RT. Additional specifications related to the limited transmit power and unit modulus (UM) constraints for both the HTPCs and the reflective elements of the NDRIS phase shift matrix make the problem challenging. To solve this problem, we first transform the intractable GM rate expression to a tractable weighted sum rate objective and next split the transformed problem into sub-problems. Consequently, we propose an iterative alternating optimization approach that leverages the majorization-minimization (MM) framework and block coordinate descent (BCD) method to solve each sub-problem. Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. Similarly, the phases of the reflective elements of the NDRIS are optimized by employing the Riemannian manifold, and the locations of the non-zero entries of the NDRIS phase shift matrix are obtained by the maximal ratio combining (MRC) criterion. Finally, we present our simulation results, which show that deploying an NDRIS achieves additional gains for the CUs over a conventional RIS, further enhancing both the communication efficiency and sensing reliability. Furthermore, we compare the results to the pertinent benchmarks, which validate the effectiveness of our proposed algorithms.
16.
Singh, Jitendra; Gupta, Awadhesh; Jagannatham, Aditya K.; Hanzo, Lajos
Multi-Beam Object-Localization for Millimeter-Wave ISAC-Aided Connected Autonomous Vehicles Journal Article
In: IEEE Transactions on Vehicular Technology, vol. 74, no. 1, pp. 1725–1729, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: connected autonomous vehicles (CAVs), Copper, Integrated sensing and communication, Integrated sensing and communication (ISAC), Interference, millimeter wave, Millimeter wave communication, Optimization, Radio frequency, sensing beampattern (SBP) gain, Signal to noise ratio
@article{singh_multi-beam_2025,
title = {Multi-Beam Object-Localization for Millimeter-Wave ISAC-Aided Connected Autonomous Vehicles},
author = {Jitendra Singh and Awadhesh Gupta and Aditya K. Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10677488},
doi = {10.1109/TVT.2024.3451480},
issn = {1939-9359},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
volume = {74},
number = {1},
pages = {1725–1729},
abstract = {Millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems capable of integrated sensing and communication (ISAC) constitute a key technology for connected autonomous vehicles (CAVs). In this context, we propose a multi-beam object-localization (MBOL) model for enhancing the sensing beampattern (SBP) gain of adjacent objects in CAV scenarios. Given the ultra-narrow beams of mmWave MIMO systems, a single pencil beam is unsuitable for closely located objects, which tend to require multiple beams. Hence, we formulate the SBP gain maximization problem, considering also the constraints on the signal-to-interference and noise ratio (SINR) of the communication users (CUs), on the transmit power, and the constant modulus of the phase-shifters in the mmWave hybrid transceiver. To solve this non-convex problem, we propose a penalty-based triple alternating optimization algorithm to design the hybrid beamformer. Finally, simulation results are provided for demonstrating the efficacy of the proposed model.},
keywords = {connected autonomous vehicles (CAVs), Copper, Integrated sensing and communication, Integrated sensing and communication (ISAC), Interference, millimeter wave, Millimeter wave communication, Optimization, Radio frequency, sensing beampattern (SBP) gain, Signal to noise ratio},
pubstate = {published},
tppubtype = {article}
}
Millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems capable of integrated sensing and communication (ISAC) constitute a key technology for connected autonomous vehicles (CAVs). In this context, we propose a multi-beam object-localization (MBOL) model for enhancing the sensing beampattern (SBP) gain of adjacent objects in CAV scenarios. Given the ultra-narrow beams of mmWave MIMO systems, a single pencil beam is unsuitable for closely located objects, which tend to require multiple beams. Hence, we formulate the SBP gain maximization problem, considering also the constraints on the signal-to-interference and noise ratio (SINR) of the communication users (CUs), on the transmit power, and the constant modulus of the phase-shifters in the mmWave hybrid transceiver. To solve this non-convex problem, we propose a penalty-based triple alternating optimization algorithm to design the hybrid beamformer. Finally, simulation results are provided for demonstrating the efficacy of the proposed model.
17.
Gonem, Omaro Fawzi Abdelhamid; Vallejo, Luis; He, Jiaxiang; Giddings, Roger Philip; Jin, Wei; Yi, Xingwen; Faruk, Md Saifuddin; Tang, Jianming
Seamless Fiber-Wireless Access Network Convergence with Dynamic O-E-O Conversion-less Sub-Wavelength Switching and Tunable Photonic mmWave Generation Proceedings Article
In: 2024 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC), pp. 1–4, 2024, ISSN: 2162-1098, (ISSN: 2162-1098).
Abstract | Links | BibTeX | Tags: Adaptive systems, B5G, Digital signal processing, fiber-wireless converged access networks, free-running lasers, Millimeter wave communication, millimeter waves, Optical fiber networks, Optical fibers, Optical signal processing, Optical switches, optical switching, Photonics, reconfigurable optical add/drop multiplexer (ROADM), Standards, Wireless networks
@inproceedings{abdelhamid_gonem_seamless_2024,
title = {Seamless Fiber-Wireless Access Network Convergence with Dynamic O-E-O Conversion-less Sub-Wavelength Switching and Tunable Photonic mmWave Generation},
author = {Omaro Fawzi Abdelhamid Gonem and Luis Vallejo and Jiaxiang He and Roger Philip Giddings and Wei Jin and Xingwen Yi and Md Saifuddin Faruk and Jianming Tang},
url = {https://ieeexplore.ieee.org/document/10809809},
doi = {10.1109/ACP/IPOC63121.2024.10809809},
issn = {2162-1098},
year = {2024},
date = {2024-11-01},
urldate = {2025-10-08},
booktitle = {2024 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC)},
pages = {1–4},
abstract = {In order to meet the diverse needs of different services and applications in the B5G era, seamless integration of fiber and wireless network segments of next-generation radio access networks (NG-RANs), with flexible/fine channel switching granularity and ultra-low latency, is vital for enabling dynamic and continuous flow of heterogenous signals of various characteristics across different network segments without optical-electrical-optical (O-E-O) conversions or digital signal processing (DSP) at intermediate nodes. To address these requirements cost-effectively, we experimentally demonstrate 3xl.333 Gbps flexible BBU-UE connections over 10 km standard single-mode fiber (SSMF) and adaptable millimeter-wave (mmWave) wireless reach up to 50 m, using free-running laser/envelope detection-based tunable mm Wave generation/detection, and soft-ROADM-enabled dynamic sub-wavelength-level channel switching. The proposed technique requires no O-E-O conversions or DSP at intermediate nodes and offers dynamic RRH-controllable mmWave transmission with large frequency tunability and adaptive wireless network coverage.},
note = {ISSN: 2162-1098},
keywords = {Adaptive systems, B5G, Digital signal processing, fiber-wireless converged access networks, free-running lasers, Millimeter wave communication, millimeter waves, Optical fiber networks, Optical fibers, Optical signal processing, Optical switches, optical switching, Photonics, reconfigurable optical add/drop multiplexer (ROADM), Standards, Wireless networks},
pubstate = {published},
tppubtype = {inproceedings}
}
In order to meet the diverse needs of different services and applications in the B5G era, seamless integration of fiber and wireless network segments of next-generation radio access networks (NG-RANs), with flexible/fine channel switching granularity and ultra-low latency, is vital for enabling dynamic and continuous flow of heterogenous signals of various characteristics across different network segments without optical-electrical-optical (O-E-O) conversions or digital signal processing (DSP) at intermediate nodes. To address these requirements cost-effectively, we experimentally demonstrate 3xl.333 Gbps flexible BBU-UE connections over 10 km standard single-mode fiber (SSMF) and adaptable millimeter-wave (mmWave) wireless reach up to 50 m, using free-running laser/envelope detection-based tunable mm Wave generation/detection, and soft-ROADM-enabled dynamic sub-wavelength-level channel switching. The proposed technique requires no O-E-O conversions or DSP at intermediate nodes and offers dynamic RRH-controllable mmWave transmission with large frequency tunability and adaptive wireless network coverage.
18.
Mohammadi, Mohammadali; Mobini, Zahra; Ngo, Hien Quoc; Matthaiou, Michail
Next-Generation Multiple Access With Cell-Free Massive MIMO Journal Article
In: Proceedings of the IEEE, vol. 112, no. 9, pp. 1372–1420, 2024, ISSN: 1558-2256.
Abstract | Links | BibTeX | Tags: 5G mobile communication, 6G mobile communication, Cell-free massive multiple-input multiple-output (CF-mMIMO), Channel estimation, Energy Efficiency, energy efficiency (EE), Massive MIMO, Millimeter wave communication, Next generation networking, Signal to noise ratio, sixth-generation (6G) wireless, Spectral efficiency, spectral efficiency (SE), Surveys, Telecommunication traffic, Wireless networks
@article{mohammadi_next-generation_2024,
title = {Next-Generation Multiple Access With Cell-Free Massive MIMO},
author = {Mohammadali Mohammadi and Zahra Mobini and Hien Quoc Ngo and Michail Matthaiou},
url = {https://ieeexplore.ieee.org/document/10684238},
doi = {10.1109/JPROC.2024.3451372},
issn = {1558-2256},
year = {2024},
date = {2024-09-01},
urldate = {2025-10-08},
journal = {Proceedings of the IEEE},
volume = {112},
number = {9},
pages = {1372–1420},
abstract = {To meet the unprecedented mobile traffic demands of future wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems is imperative. Cell-free massive multiple-input multiple-output (CF-mMIMO) represents a practical and scalable embodiment of distributed/network MIMO systems. It inherits not only the key benefits of co-located massive MIMO systems but also the macro-diversity gains from distributed systems. This innovative architecture has demonstrated significant potential in enhancing network performance from various perspectives, outperforming co-located mMIMO and conventional small-cell systems. Moreover, CF-mMIMO offers flexibility in integration with emerging wireless technologies such as full-duplex (FD), nonorthogonal transmission schemes, millimeter-wave (mmWave) communications, ultrareliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this article, we provide an overview of current research efforts on CF-mMIMO systems and their promising future application scenarios. We then elaborate on new requirements for CF-mMIMO networks in the context of these technological breakthroughs. We also present several current open challenges and outline future research directions aimed at fully realizing the potential of CF-mMIMO systems in meeting the evolving demands of future wireless networks.},
keywords = {5G mobile communication, 6G mobile communication, Cell-free massive multiple-input multiple-output (CF-mMIMO), Channel estimation, Energy Efficiency, energy efficiency (EE), Massive MIMO, Millimeter wave communication, Next generation networking, Signal to noise ratio, sixth-generation (6G) wireless, Spectral efficiency, spectral efficiency (SE), Surveys, Telecommunication traffic, Wireless networks},
pubstate = {published},
tppubtype = {article}
}
To meet the unprecedented mobile traffic demands of future wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems is imperative. Cell-free massive multiple-input multiple-output (CF-mMIMO) represents a practical and scalable embodiment of distributed/network MIMO systems. It inherits not only the key benefits of co-located massive MIMO systems but also the macro-diversity gains from distributed systems. This innovative architecture has demonstrated significant potential in enhancing network performance from various perspectives, outperforming co-located mMIMO and conventional small-cell systems. Moreover, CF-mMIMO offers flexibility in integration with emerging wireless technologies such as full-duplex (FD), nonorthogonal transmission schemes, millimeter-wave (mmWave) communications, ultrareliable low-latency communication (URLLC), unmanned aerial vehicle (UAV)-aided communication, and reconfigurable intelligent surfaces (RISs). In this article, we provide an overview of current research efforts on CF-mMIMO systems and their promising future application scenarios. We then elaborate on new requirements for CF-mMIMO networks in the context of these technological breakthroughs. We also present several current open challenges and outline future research directions aimed at fully realizing the potential of CF-mMIMO systems in meeting the evolving demands of future wireless networks.
19.
Vallejo, Luis; Gonem, Omaro Fawzi Abdelhamid; Jin, Wei; Giddings, Roger Philip; Tang, Jianming
Soft-ROADM-enabled Seamlessly Converged Optical-Wireless Access Networks with Free-Running Laser-based Tunable mmWave Generation and RF Envelope Detection Proceedings Article
In: 2024 IEEE Opto-Electronics and Communications Conference (OECC), pp. 1–3, 2024, ISSN: 2166-8892, (ISSN: 2166-8892).
Abstract | Links | BibTeX | Tags: B5G, Bit rate, fronthaul, Millimeter wave communication, mmWave, Optical fiber networks, Optical fibers, Optical switches, optical switching, Photonics, radio access network (RAN), Radio access networks, Radio frequency, RF envelope detection, Wireless communication
@inproceedings{vallejo_soft-roadm-enabled_2024,
title = {Soft-ROADM-enabled Seamlessly Converged Optical-Wireless Access Networks with Free-Running Laser-based Tunable mmWave Generation and RF Envelope Detection},
author = {Luis Vallejo and Omaro Fawzi Abdelhamid Gonem and Wei Jin and Roger Philip Giddings and Jianming Tang},
url = {https://ieeexplore.ieee.org/document/10975552},
doi = {10.1109/OECC54135.2024.10975552},
issn = {2166-8892},
year = {2024},
date = {2024-06-01},
urldate = {2025-10-08},
booktitle = {2024 IEEE Opto-Electronics and Communications Conference (OECC)},
pages = {1–3},
abstract = {Incorporating O-E-O conversion-free Soft-ROADMs and free-running laser-based tunable mmWave generations with RF envelope detection, a cost-effective optical-wireless-converged RAN supporting flexible ultra-dense BBU-UE connectivity without O-E-O conversion and DSPs at any intermediate nodes is proposed and experimentally demonstrated, achieving 2×2.4-Gbit/s dynamic connections over 10-km fiber and 2-m @38GHz mmWave transmissions.},
note = {ISSN: 2166-8892},
keywords = {B5G, Bit rate, fronthaul, Millimeter wave communication, mmWave, Optical fiber networks, Optical fibers, Optical switches, optical switching, Photonics, radio access network (RAN), Radio access networks, Radio frequency, RF envelope detection, Wireless communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Incorporating O-E-O conversion-free Soft-ROADMs and free-running laser-based tunable mmWave generations with RF envelope detection, a cost-effective optical-wireless-converged RAN supporting flexible ultra-dense BBU-UE connectivity without O-E-O conversion and DSPs at any intermediate nodes is proposed and experimentally demonstrated, achieving 2×2.4-Gbit/s dynamic connections over 10-km fiber and 2-m @38GHz mmWave transmissions.