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.
Mehrotra, Anand; Srivastava, Suraj; Reddy, N. Shanmughanadha; Jagannatham, Aditya; Hanzo, Lajos
Sparse Channel Estimation for MIMO OTFS/OTSM Systems Using Finite-Resolution ADCs Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 6, pp. 3971–3987, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Bayes methods, Channel estimation, delay-Doppler, delay-sequency, Estimation, finite-resolution ADCs, Modulation, OFDM, OTFS, OTSM, Quantization (signal), Receivers, Signal processing algorithms, Signal resolution, sparsity, Time-domain analysis
@article{mehrotra_sparse_2025,
title = {Sparse Channel Estimation for MIMO OTFS/OTSM Systems Using Finite-Resolution ADCs},
author = {Anand Mehrotra and Suraj Srivastava and N. Shanmughanadha Reddy and Aditya Jagannatham and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10758799},
doi = {10.1109/TCOMM.2024.3502682},
issn = {1558-0857},
year = {2025},
date = {2025-06-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {6},
pages = {3971–3987},
abstract = {Variational Bayesian learning (VBL)-based sparse channel state information (CSI) estimation is conceived for multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) and for orthogonal time sequence multiplexing (OTSM)-based systems relying on low-resolution analog-to-digital convertors (ADCs). First, the CSI estimation model is developed for MIMO-OTFS systems considering quantized outputs. Then a novel VBL technique is developed for exploiting the inherent DD domain sparsity. Subsequently, an end-to-end system model is derived for MIMO-OTSM systems, once again, using only finite-resolution ADCs. Similar to OTFS systems, it is demonstrated that the channel is sparse in the delay-sequency (DS)-domain. Thus the sparse CSI estimation problem of the MIMO-OTSM system can also be solved using the VBL technique developed for its OTFS counterpart. A bespoke minimum mean square error (MMSE) receiver is developed for data detection, which unlike the conventional MMSE receiver also accounts for the quantization error. Finally, finite-resolution ADCs emerge as a solution, offering reduced costs and energy consumption amid the growing challenge posed by energy-intensive high-resolution ADCs in Next-Generation (NG) systems. The efficacy of the proposed techniques is validated by simulation results, surpassing the state-of-the-art and signalling a transition towards more sustainable communication technologies.},
keywords = {Bayes methods, Channel estimation, delay-Doppler, delay-sequency, Estimation, finite-resolution ADCs, Modulation, OFDM, OTFS, OTSM, Quantization (signal), Receivers, Signal processing algorithms, Signal resolution, sparsity, Time-domain analysis},
pubstate = {published},
tppubtype = {article}
}
Variational Bayesian learning (VBL)-based sparse channel state information (CSI) estimation is conceived for multiple input multiple output (MIMO) orthogonal time frequency space (OTFS) and for orthogonal time sequence multiplexing (OTSM)-based systems relying on low-resolution analog-to-digital convertors (ADCs). First, the CSI estimation model is developed for MIMO-OTFS systems considering quantized outputs. Then a novel VBL technique is developed for exploiting the inherent DD domain sparsity. Subsequently, an end-to-end system model is derived for MIMO-OTSM systems, once again, using only finite-resolution ADCs. Similar to OTFS systems, it is demonstrated that the channel is sparse in the delay-sequency (DS)-domain. Thus the sparse CSI estimation problem of the MIMO-OTSM system can also be solved using the VBL technique developed for its OTFS counterpart. A bespoke minimum mean square error (MMSE) receiver is developed for data detection, which unlike the conventional MMSE receiver also accounts for the quantization error. Finally, finite-resolution ADCs emerge as a solution, offering reduced costs and energy consumption amid the growing challenge posed by energy-intensive high-resolution ADCs in Next-Generation (NG) systems. The efficacy of the proposed techniques is validated by simulation results, surpassing the state-of-the-art and signalling a transition towards more sustainable communication technologies.
5.
Xu, Chao; Masouros, Christos; Sugiura, Shinya; Petropoulos, Periklis; Maunder, Robert G.; Yang, Lie-Liang; Haas, Harald; Hanzo, Lajos
Integrated Positioning and Communication Relying on Wireless Optical OFDM Journal Article
In: IEEE Journal on Selected Areas in Communications, vol. 43, no. 5, pp. 1721–1737, 2025, ISSN: 1558-0008.
Abstract | Links | BibTeX | Tags: Accuracy, Bandwidth, bi-static, Channel estimation, Estimation, Integrated sensing and communication, ISAC, Light emitting diodes, multipath, NLoS, non-line-of-sight, Nonlinear optics, OFDM, Optical sensors, orthogonal frequency-division multiplexing, Radar, Visible Light Communication, visible light positioning, VLC, VLP
@article{xu_integrated_2025,
title = {Integrated Positioning and Communication Relying on Wireless Optical OFDM},
author = {Chao Xu and Christos Masouros and Shinya Sugiura and Periklis Petropoulos and Robert G. Maunder and Lie-Liang Yang and Harald Haas and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/abstract/document/10900727},
doi = {10.1109/JSAC.2025.3543532},
issn = {1558-0008},
year = {2025},
date = {2025-05-01},
urldate = {2025-10-08},
journal = {IEEE Journal on Selected Areas in Communications},
volume = {43},
number = {5},
pages = {1721–1737},
abstract = {Visible Light Positioning and Communication (VLPC) is a promising candidate for implementing Integrated Sensing And Communication (ISAC) in the unlicensed 400 THz to 800 THz band. The current Visible Light Positioning (VLP) systems mainly operate based on the Received Signal Strength (RSS) of the Line-of-Sight (LoS) path. However, its accuracy is degraded by interferences from Non-LoS (NLoS) paths. Furthermore, in Visible Light Communication (VLC) systems, the estimation of Channel State Information (CSI) also becomes challenging, when the optical channel becomes dispersive. Against this background, we propose a new VLPC scheme using Direct Current (DC) biased Optical Orthogonal Frequency-Division Multiplexing (VLPC-DCO-OFDM), where OFDM-based sensing is applied for the sake of improving the resolution of the estimated Channel Impulse Response (CIRs) exploited for positioning functionality. The CIRs estimated by sensing are further exploited to provide enhanced CSI for communication data detection. Moreover, we propose a hybrid Radar-RSS based solution, where the conventional RSS-aided VLP method is invoked for the sake of refining OFDM radar. Our simulation results demonstrate that the proposed VLPC-DCO-OFDM scheme – which simultaneously supports the triple functionalities of illumination, bi-static sensing and communication – is capable of achieving centimeter-level positioning accuracy and Giga-bits-per-second data rate.},
keywords = {Accuracy, Bandwidth, bi-static, Channel estimation, Estimation, Integrated sensing and communication, ISAC, Light emitting diodes, multipath, NLoS, non-line-of-sight, Nonlinear optics, OFDM, Optical sensors, orthogonal frequency-division multiplexing, Radar, Visible Light Communication, visible light positioning, VLC, VLP},
pubstate = {published},
tppubtype = {article}
}
Visible Light Positioning and Communication (VLPC) is a promising candidate for implementing Integrated Sensing And Communication (ISAC) in the unlicensed 400 THz to 800 THz band. The current Visible Light Positioning (VLP) systems mainly operate based on the Received Signal Strength (RSS) of the Line-of-Sight (LoS) path. However, its accuracy is degraded by interferences from Non-LoS (NLoS) paths. Furthermore, in Visible Light Communication (VLC) systems, the estimation of Channel State Information (CSI) also becomes challenging, when the optical channel becomes dispersive. Against this background, we propose a new VLPC scheme using Direct Current (DC) biased Optical Orthogonal Frequency-Division Multiplexing (VLPC-DCO-OFDM), where OFDM-based sensing is applied for the sake of improving the resolution of the estimated Channel Impulse Response (CIRs) exploited for positioning functionality. The CIRs estimated by sensing are further exploited to provide enhanced CSI for communication data detection. Moreover, we propose a hybrid Radar-RSS based solution, where the conventional RSS-aided VLP method is invoked for the sake of refining OFDM radar. Our simulation results demonstrate that the proposed VLPC-DCO-OFDM scheme – which simultaneously supports the triple functionalities of illumination, bi-static sensing and communication – is capable of achieving centimeter-level positioning accuracy and Giga-bits-per-second data rate.
6.
Meng, Kaitao; Masouros, Christos; Wong, Kai-Kit; Petropulu, Athina P.; Hanzo, Lajos
Integrated Sensing and Communication Meets Smart Propagation Engineering: Opportunities and Challenges Journal Article
In: IEEE Network, vol. 39, no. 2, pp. 278–285, 2025, ISSN: 1558-156X.
Abstract | Links | BibTeX | Tags: Antennas, Channel estimation, fluid antennas, Fluids, Integrated sensing and communication, intelligent surfaces, Interference, Mobile antennas, Radio transmitters, smart propagation engineering, Trajectory, Transmitting antennas, Wireless communication
@article{meng_integrated_2025,
title = {Integrated Sensing and Communication Meets Smart Propagation Engineering: Opportunities and Challenges},
author = {Kaitao Meng and Christos Masouros and Kai-Kit Wong and Athina P. Petropulu and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10833779},
doi = {10.1109/MNET.2025.3527130},
issn = {1558-156X},
year = {2025},
date = {2025-03-01},
urldate = {2025-10-08},
journal = {IEEE Network},
volume = {39},
number = {2},
pages = {278–285},
abstract = {Both smart propagation engineering as well as integrated sensing and communication (ISAC) constitute promising candidates for next-generation (NG) mobile networks. We provide a synergistic view of these technologies, and explore their mutual benefits. First, moving beyond just intelligent surfaces, we provide a holistic view of the engineering aspects of smart propagation environments. By delving into the fundamental characteristics of intelligent surfaces, fluid antennas, and unmanned aerial vehicles, we reveal that more efficient control of the pathloss and fading can be achieved, thus facilitating intrinsic integration and mutual assistance between sensing and communication functionalities. In turn, with the exploitation of the sensing capabilities of ISAC to orchestrate the efficient configuration of radio environments, both the computational effort and signaling overheads can be reduced. We present indicative simulation results, which verify that cooperative smart propagation environment design significantly enhances the ISAC performance. Finally, some promising directions are outlined for combining ISAC with smart propagation engineering.},
keywords = {Antennas, Channel estimation, fluid antennas, Fluids, Integrated sensing and communication, intelligent surfaces, Interference, Mobile antennas, Radio transmitters, smart propagation engineering, Trajectory, Transmitting antennas, Wireless communication},
pubstate = {published},
tppubtype = {article}
}
Both smart propagation engineering as well as integrated sensing and communication (ISAC) constitute promising candidates for next-generation (NG) mobile networks. We provide a synergistic view of these technologies, and explore their mutual benefits. First, moving beyond just intelligent surfaces, we provide a holistic view of the engineering aspects of smart propagation environments. By delving into the fundamental characteristics of intelligent surfaces, fluid antennas, and unmanned aerial vehicles, we reveal that more efficient control of the pathloss and fading can be achieved, thus facilitating intrinsic integration and mutual assistance between sensing and communication functionalities. In turn, with the exploitation of the sensing capabilities of ISAC to orchestrate the efficient configuration of radio environments, both the computational effort and signaling overheads can be reduced. We present indicative simulation results, which verify that cooperative smart propagation environment design significantly enhances the ISAC performance. Finally, some promising directions are outlined for combining ISAC with smart propagation engineering.
7.
Fu, Jiafei; Mobini, Zahra; Ngo, Hien Quoc; Zhu, Pengcheng; Matthaiou, Michail
WMMSE-Based Processing in Cell-Free Massive MIMO Systems Journal Article
In: IEEE Wireless Communications Letters, vol. 14, no. 2, pp. 330–334, 2025, ISSN: 2162-2345.
Abstract | Links | BibTeX | Tags: Approximation algorithms, Cell-free massive MIMO, Channel estimation, Data communication, Downlink, Optimization, Power control, Precoding, Quality of service, Uplink, Vectors, weighted minimum mean square error, weighted sum-rate maximization
@article{fu_wmmse-based_2025,
title = {WMMSE-Based Processing in Cell-Free Massive MIMO Systems},
author = {Jiafei Fu and Zahra Mobini and Hien Quoc Ngo and Pengcheng Zhu and Michail Matthaiou},
url = {https://ieeexplore.ieee.org/document/10755172},
doi = {10.1109/LWC.2024.3501156},
issn = {2162-2345},
year = {2025},
date = {2025-02-01},
urldate = {2025-10-08},
journal = {IEEE Wireless Communications Letters},
volume = {14},
number = {2},
pages = {330–334},
abstract = {In this letter, we address the weighted sum-rate maximization problem in a cell-free massive multi-input multi-output (CF-mMIMO) system, subject to constraints on the minimum individual quality of service (QoS), maximum power consumption at each access point (AP), and maximum fronthaul capacity. By harnessing the low computational complexity weighted minimum mean square error (WMMSE) framework, two algorithms are proposed to solve the formulated mixed integer nonlinear programming (MINLP) problems with instantaneous/statistical channel state information (CSI). Our instantaneous CSI-based approach can be applied to jointly optimize the power control, precoding, and user association, while the statistical CSI-based approach can be utilized to jointly optimize the power control and user association. Simulation results demonstrate that the proposed instantaneous CSI-based algorithm can provide approximately 66.72% sum-rate gain compared to the scheme with random user association, equal power allocation, and fixed local MMSE-based precoding design. Additionally, the statistical CSI-based algorithm offers competitive performance compared with the instantaneous CSI-based algorithm.},
keywords = {Approximation algorithms, Cell-free massive MIMO, Channel estimation, Data communication, Downlink, Optimization, Power control, Precoding, Quality of service, Uplink, Vectors, weighted minimum mean square error, weighted sum-rate maximization},
pubstate = {published},
tppubtype = {article}
}
In this letter, we address the weighted sum-rate maximization problem in a cell-free massive multi-input multi-output (CF-mMIMO) system, subject to constraints on the minimum individual quality of service (QoS), maximum power consumption at each access point (AP), and maximum fronthaul capacity. By harnessing the low computational complexity weighted minimum mean square error (WMMSE) framework, two algorithms are proposed to solve the formulated mixed integer nonlinear programming (MINLP) problems with instantaneous/statistical channel state information (CSI). Our instantaneous CSI-based approach can be applied to jointly optimize the power control, precoding, and user association, while the statistical CSI-based approach can be utilized to jointly optimize the power control and user association. Simulation results demonstrate that the proposed instantaneous CSI-based algorithm can provide approximately 66.72% sum-rate gain compared to the scheme with random user association, equal power allocation, and fixed local MMSE-based precoding design. Additionally, the statistical CSI-based algorithm offers competitive performance compared with the instantaneous CSI-based algorithm.
8.
Sui, Zeping; Ngo, Hien Quoc; Chien, Trinh Van; Matthaiou, Michail; Hanzo, Lajos
RIS-Assisted Cell-Free Massive MIMO Relying on Reflection Pattern Modulation Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 2, pp. 968–982, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, Cell-free massive MIMO, Channel estimation, Chaotic communication, Energy Efficiency, iterative optimization, Optimization, Reconfigurable Intelligent Surfaces, reflection pattern modulation, Spectral efficiency, Symbols, Technological innovation, Uplink
@article{sui_ris-assisted_2025,
title = {RIS-Assisted Cell-Free Massive MIMO Relying on Reflection Pattern Modulation},
author = {Zeping Sui and Hien Quoc Ngo and Trinh Van Chien and Michail Matthaiou and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10640072},
doi = {10.1109/TCOMM.2024.3446589},
issn = {1558-0857},
year = {2025},
date = {2025-02-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {2},
pages = {968–982},
abstract = {We propose reflection pattern modulation-aided reconfigurable intelligent surface (RPM-RIS)-assisted cell-free massive multiple-input-multiple-output (CF-mMIMO) schemes for green uplink transmission. In our RPM-RIS-assisted CF-mMIMO system, extra information is conveyed by the indices of the active RIS blocks, exploiting the joint benefits of both RIS-assisted CF-mMIMO transmission and RPM. Since only part of the RIS blocks are active, our proposed architecture strikes a flexible energy vs. spectral efficiency (SE) trade-off. We commence with introducing the system model by considering spatially correlated channels. Moreover, we conceive a channel estimation scheme subject to the linear minimum mean-square error (MMSE) constraint, yielding sufficient information for the subsequent signal processing steps. Then, upon exploiting a so-called large-scale fading decoding (LSFD) scheme, the uplink signal-to-interference-and-noise ratio (SINR) is derived based on the RIS ON/OFF statistics, where both maximum ratio (MR) and local minimum mean-square error (L-MMSE) combiners are considered. By invoking the MR combiner, the closed-form expression of the uplink SE is formulated based only on the channel statistics. Furthermore, we derive the total energy efficiency (EE) of our proposed RPM-RIS-assisted CF-mMIMO system. Additionally, we propose a chaotic sequence-based adaptive particle swarm optimization (CSA-PSO) algorithm to maximize the total EE by designing the RIS phase shifts. Specifically, the initial particle diversity is promoted by invoking chaotic sequences, and an adaptive time-varying inertia weight is developed to improve its particle search performance. Furthermore, the particle mutation and reset steps are appropriately selected to enable the algorithm to escape from local optima. Finally, our simulation results demonstrate that the proposed RPM-RIS-assisted CF-mMIMO architecture strikes an attractive SE vs. EE trade-off, while the CSA-PSO algorithm is capable of attaining a significant EE performance gain compared to conventional solutions.},
keywords = {Array signal processing, Cell-free massive MIMO, Channel estimation, Chaotic communication, Energy Efficiency, iterative optimization, Optimization, Reconfigurable Intelligent Surfaces, reflection pattern modulation, Spectral efficiency, Symbols, Technological innovation, Uplink},
pubstate = {published},
tppubtype = {article}
}
We propose reflection pattern modulation-aided reconfigurable intelligent surface (RPM-RIS)-assisted cell-free massive multiple-input-multiple-output (CF-mMIMO) schemes for green uplink transmission. In our RPM-RIS-assisted CF-mMIMO system, extra information is conveyed by the indices of the active RIS blocks, exploiting the joint benefits of both RIS-assisted CF-mMIMO transmission and RPM. Since only part of the RIS blocks are active, our proposed architecture strikes a flexible energy vs. spectral efficiency (SE) trade-off. We commence with introducing the system model by considering spatially correlated channels. Moreover, we conceive a channel estimation scheme subject to the linear minimum mean-square error (MMSE) constraint, yielding sufficient information for the subsequent signal processing steps. Then, upon exploiting a so-called large-scale fading decoding (LSFD) scheme, the uplink signal-to-interference-and-noise ratio (SINR) is derived based on the RIS ON/OFF statistics, where both maximum ratio (MR) and local minimum mean-square error (L-MMSE) combiners are considered. By invoking the MR combiner, the closed-form expression of the uplink SE is formulated based only on the channel statistics. Furthermore, we derive the total energy efficiency (EE) of our proposed RPM-RIS-assisted CF-mMIMO system. Additionally, we propose a chaotic sequence-based adaptive particle swarm optimization (CSA-PSO) algorithm to maximize the total EE by designing the RIS phase shifts. Specifically, the initial particle diversity is promoted by invoking chaotic sequences, and an adaptive time-varying inertia weight is developed to improve its particle search performance. Furthermore, the particle mutation and reset steps are appropriately selected to enable the algorithm to escape from local optima. Finally, our simulation results demonstrate that the proposed RPM-RIS-assisted CF-mMIMO architecture strikes an attractive SE vs. EE trade-off, while the CSA-PSO algorithm is capable of attaining a significant EE performance gain compared to conventional solutions.
9.
Chien, Trinh Van; Viet, Nguyen Hoang; Chatzinotas, Symeon; Hanzo, Lajos
Improved Differential Evolution for Enhancing the Aggregated Channel Estimation of RIS-Aided Cell-Free Massive MIMO Journal Article
In: IEEE Transactions on Vehicular Technology, pp. 1–6, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Cell-free massive MIMO, Channel estimation, Closed-form solutions, Contamination, Correlation, differential evolution, Massive MIMO, Optimization, Rayleigh channels, reconfigurable intelligent surface, Reconfigurable Intelligent Surfaces, Training, Vectors
@article{chien_improved_2025,
title = {Improved Differential Evolution for Enhancing the Aggregated Channel Estimation of RIS-Aided Cell-Free Massive MIMO},
author = {Trinh Van Chien and Nguyen Hoang Viet and Symeon Chatzinotas and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11080325},
doi = {10.1109/TVT.2025.3589240},
issn = {1939-9359},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
pages = {1–6},
abstract = {Cell-Free Massive multiple-input multiple-output (MIMO) systems are investigated with the support of a reconfigurable intelligent surface (RIS). The RIS phase shifts are designed for improved channel estimation in the presence of spatial correlation. Specifically, we formulate the channel estimate and estimation error expressions using linear minimum mean square error (LMMSE) estimation for the aggregated channels. An optimization problem is then formulated to minimize the average normalized mean square error (NMSE) subject to practical phase shift constraints. To circumvent the problem of inherent nonconvexity, we then conceive an enhanced version of the differential evolution algorithm that is capable of avoiding local minima by introducing an augmentation operator applied to some high-performing Diffential Evolution (DE) individuals. Numerical results indicate that our proposed algorithm can significantly improve the channel estimation quality of the state-of-the-art benchmarks.},
keywords = {Cell-free massive MIMO, Channel estimation, Closed-form solutions, Contamination, Correlation, differential evolution, Massive MIMO, Optimization, Rayleigh channels, reconfigurable intelligent surface, Reconfigurable Intelligent Surfaces, Training, Vectors},
pubstate = {published},
tppubtype = {article}
}
Cell-Free Massive multiple-input multiple-output (MIMO) systems are investigated with the support of a reconfigurable intelligent surface (RIS). The RIS phase shifts are designed for improved channel estimation in the presence of spatial correlation. Specifically, we formulate the channel estimate and estimation error expressions using linear minimum mean square error (LMMSE) estimation for the aggregated channels. An optimization problem is then formulated to minimize the average normalized mean square error (NMSE) subject to practical phase shift constraints. To circumvent the problem of inherent nonconvexity, we then conceive an enhanced version of the differential evolution algorithm that is capable of avoiding local minima by introducing an augmentation operator applied to some high-performing Diffential Evolution (DE) individuals. Numerical results indicate that our proposed algorithm can significantly improve the channel estimation quality of the state-of-the-art benchmarks.
10.
Liu, Xin; Xu, Chao; Wang, Stephen; Ng, Soon Xin; Hanzo, Lajos
Hybrid Beamforming Assisted OTFS-Based CV-QKD Systems for Doubly Selective THz Channels Journal Article
In: IEEE Transactions on Communications, pp. 1–1, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, Channel estimation, continuous variable quantum key distribution (CV-QKD), Decoding, Fading channels, hybrid beamforming (HBF), low-density parity check (LDPC), multiple-input multiple-out (MIMO), OFDM, Orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), Parity check codes, secret key rate (SKR), Terahertz (THz), Terahertz communications, Time-frequency analysis, Vectors, Wireless communication
@article{liu_hybrid_2025,
title = {Hybrid Beamforming Assisted OTFS-Based CV-QKD Systems for Doubly Selective THz Channels},
author = {Xin Liu and Chao Xu and Stephen Wang and Soon Xin Ng and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11069272},
doi = {10.1109/TCOMM.2025.3585501},
issn = {1558-0857},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
pages = {1–1},
abstract = {Continuous-variable quantum key distribution (CV-QKD) maps information onto the quadrature components of electromagnetic waves, so that off-the-shelf wireless transceivers can be utilized. This motivates the move from optical to Terahertz (THz) bands. However, wireless THz channels suffer from severe path loss, while the mobility of wireless users imposes doubly selective fading. Against this background, we propose a new CV-QKD regime that relies on hybrid beamforming (HBF) assisted multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) and orthogonal time frequency space (OTFS) system, where the channel’s transmissivity and robustness against double selectivity are overcome by HBF and OTFS, respectively. Secondly, in order to provide channel state information (CSI) for both the transmitter (CSI-T) and receiver (CSI-R), practical channel estimation methods are conceived. They operate in the time-frequency domain for OFDM and in the delay-Doppler domain for OTFS. Thirdly, soft-decision detection is devised for our MIMO OFDM/OTFS aided multi-dimensional reconciliation (MDR) scheme. Low-density parity-check (LDPC) coding is invoked for further improving secure CV-QKD transmission distance in the THz band. Our simulation results demonstrate that the proposed HBF MIMO OTFS-based CV-QKD system relying on realistic estimated CSI is capable of achieving an adequate secret key rate (SKR) and secure transmission distance in hostile doubly selective THz channels.},
keywords = {Array signal processing, Channel estimation, continuous variable quantum key distribution (CV-QKD), Decoding, Fading channels, hybrid beamforming (HBF), low-density parity check (LDPC), multiple-input multiple-out (MIMO), OFDM, Orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), Parity check codes, secret key rate (SKR), Terahertz (THz), Terahertz communications, Time-frequency analysis, Vectors, Wireless communication},
pubstate = {published},
tppubtype = {article}
}
Continuous-variable quantum key distribution (CV-QKD) maps information onto the quadrature components of electromagnetic waves, so that off-the-shelf wireless transceivers can be utilized. This motivates the move from optical to Terahertz (THz) bands. However, wireless THz channels suffer from severe path loss, while the mobility of wireless users imposes doubly selective fading. Against this background, we propose a new CV-QKD regime that relies on hybrid beamforming (HBF) assisted multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) and orthogonal time frequency space (OTFS) system, where the channel’s transmissivity and robustness against double selectivity are overcome by HBF and OTFS, respectively. Secondly, in order to provide channel state information (CSI) for both the transmitter (CSI-T) and receiver (CSI-R), practical channel estimation methods are conceived. They operate in the time-frequency domain for OFDM and in the delay-Doppler domain for OTFS. Thirdly, soft-decision detection is devised for our MIMO OFDM/OTFS aided multi-dimensional reconciliation (MDR) scheme. Low-density parity-check (LDPC) coding is invoked for further improving secure CV-QKD transmission distance in the THz band. Our simulation results demonstrate that the proposed HBF MIMO OTFS-based CV-QKD system relying on realistic estimated CSI is capable of achieving an adequate secret key rate (SKR) and secure transmission distance in hostile doubly selective THz channels.
11.
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.
12.
Hawkins, Hugo; Xu, Chao; Yang, Lie-Liang; Hanzo, Lajos
CDMA/OTFS Sensing Outperforms Pure OTFS at the Same Communication Throughput Journal Article
In: IEEE Open Journal of Vehicular Technology, vol. 6, pp. 502–519, 2025, ISSN: 2644-1330.
Abstract | Links | BibTeX | Tags: Channel estimation, Code Division Multiple Access (CDMA), Codes, Complexity theory, Delays, Detectors, Integrated sensing and communication, Integrated sensing and communication (ISAC), Multiaccess communication, orthogonal time frequency space (OTFS), sequence spreading, Symbols, Transforms, Uplink
@article{hawkins_cdmaotfs_2025,
title = {CDMA/OTFS Sensing Outperforms Pure OTFS at the Same Communication Throughput},
author = {Hugo Hawkins and Chao Xu and Lie-Liang Yang and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10849597},
doi = {10.1109/OJVT.2025.3532848},
issn = {2644-1330},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of Vehicular Technology},
volume = {6},
pages = {502–519},
abstract = {There is a dearth of publications on the subject of spreading-aided Orthogonal Time Frequency Space (OTFS) solutions, especially for Integrated Sensing and Communication (ISAC), even though Code Division Multiple Access (CDMA) assisted multi-user OTFS (CDMA/OTFS) exhibits tangible benefits. Hence, this work characterises both the communication Bit Error Rate (BER) and sensing Root Mean Square Error (RMSE) performance of Code Division Multiple Access OTFS (CDMA/OTFS), and contrasts them to pure OTFS. Three CDMA/OTFS configurations are considered: Delay Code Division Multiple Access OTFS (Dl-CDMA/OTFS), Doppler Code Division Multiple Access OTFS (Dp-CDMA/OTFS), and Delay Doppler Code Division Multiple Access OTFS (DD-CDMA/OTFS), which harness direct sequence spreading along the delay axis, Doppler axis, and DD domains respectively. For each configuration, the performance of Gold, Hadamard, and Zadoff-Chu sequences is investigated. The results demonstrate that Zadoff-Chu Dl-CDMA/OTFS and DD-CDMA/OTFS consistently outperform pure OTFS sensing, whilst maintaining a similar communication performance at the same throughput. The extra modulation complexity of CDMA/OTFS is similar to that of other OTFS multi-user methodologies, but the demodulation complexity of CDMA/OTFS is lower than that of some other OTFS multi-user methodologies. CDMA/OTFS sensing can also consistently outperform OTFS sensing whilst not requiring any additional complexity for target parameter estimation. Therefore, CDMA/OTFS is an appealing candidate for implementing multi-user OTFS ISAC.},
keywords = {Channel estimation, Code Division Multiple Access (CDMA), Codes, Complexity theory, Delays, Detectors, Integrated sensing and communication, Integrated sensing and communication (ISAC), Multiaccess communication, orthogonal time frequency space (OTFS), sequence spreading, Symbols, Transforms, Uplink},
pubstate = {published},
tppubtype = {article}
}
There is a dearth of publications on the subject of spreading-aided Orthogonal Time Frequency Space (OTFS) solutions, especially for Integrated Sensing and Communication (ISAC), even though Code Division Multiple Access (CDMA) assisted multi-user OTFS (CDMA/OTFS) exhibits tangible benefits. Hence, this work characterises both the communication Bit Error Rate (BER) and sensing Root Mean Square Error (RMSE) performance of Code Division Multiple Access OTFS (CDMA/OTFS), and contrasts them to pure OTFS. Three CDMA/OTFS configurations are considered: Delay Code Division Multiple Access OTFS (Dl-CDMA/OTFS), Doppler Code Division Multiple Access OTFS (Dp-CDMA/OTFS), and Delay Doppler Code Division Multiple Access OTFS (DD-CDMA/OTFS), which harness direct sequence spreading along the delay axis, Doppler axis, and DD domains respectively. For each configuration, the performance of Gold, Hadamard, and Zadoff-Chu sequences is investigated. The results demonstrate that Zadoff-Chu Dl-CDMA/OTFS and DD-CDMA/OTFS consistently outperform pure OTFS sensing, whilst maintaining a similar communication performance at the same throughput. The extra modulation complexity of CDMA/OTFS is similar to that of other OTFS multi-user methodologies, but the demodulation complexity of CDMA/OTFS is lower than that of some other OTFS multi-user methodologies. CDMA/OTFS sensing can also consistently outperform OTFS sensing whilst not requiring any additional complexity for target parameter estimation. Therefore, CDMA/OTFS is an appealing candidate for implementing multi-user OTFS ISAC.
13.
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.
14.
Lu, Zhizheng; Han, Yu; Jin, Shi; Matthaiou, Michail
Near-Field Localization and Channel Reconstruction for ELAA Systems Journal Article
In: IEEE Transactions on Wireless Communications, vol. 23, no. 7, pp. 6938–6953, 2024, ISSN: 1558-2248.
Abstract | Links | BibTeX | Tags: Antenna arrays, Channel estimation, Channel reconstruction, localization, Location awareness, Mobile antennas, near-field, PEB, Precoding, Radio frequency, Receiving antennas, subarray hybrid ELAA systems
@article{lu_near-field_2024,
title = {Near-Field Localization and Channel Reconstruction for ELAA Systems},
author = {Zhizheng Lu and Yu Han and Shi Jin and Michail Matthaiou},
url = {https://ieeexplore.ieee.org/document/10345492},
doi = {10.1109/TWC.2023.3336328},
issn = {1558-2248},
year = {2024},
date = {2024-07-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Wireless Communications},
volume = {23},
number = {7},
pages = {6938–6953},
abstract = {In this paper, an efficient near-field channel reconstruction and user equipment (UE) localization scheme is proposed for extremely large antenna array (ELAA) systems using a subarray hybrid precoding architecture. Considering the non-negligible signal amplitude and phase variations across the different receive antennas, a more realistic channel model is adopted. The channel environment, with an approximate smooth ground surface, is modeled. In fact, the channel can be divided into a line-of-sight (LoS) path, a reflection path and some non-LoS (NLoS) paths. Based on the sparsity of the channel in the spatial domain, the damped Newtonized orthogonal matching pursuit (DNOMP) algorithm is also proposed to accurately estimate the multipaths, and reconstruct the channel. Then, a UE localization algorithm is proposed, which can detect the existence of the LoS path and locate the UE. A joint localization algorithm is also devised to further increase the positioning reliability. Simulation results verify that the DNOMP algorithm can reconstruct the channel with better NMSE performance than other schemes. The localization algorithm can locate the UE with low error whenever the LoS path exists or not, with an accuracy close enough to the position error bound (PEB), while the joint localization algorithm can further enhance the positioning reliability.},
keywords = {Antenna arrays, Channel estimation, Channel reconstruction, localization, Location awareness, Mobile antennas, near-field, PEB, Precoding, Radio frequency, Receiving antennas, subarray hybrid ELAA systems},
pubstate = {published},
tppubtype = {article}
}
In this paper, an efficient near-field channel reconstruction and user equipment (UE) localization scheme is proposed for extremely large antenna array (ELAA) systems using a subarray hybrid precoding architecture. Considering the non-negligible signal amplitude and phase variations across the different receive antennas, a more realistic channel model is adopted. The channel environment, with an approximate smooth ground surface, is modeled. In fact, the channel can be divided into a line-of-sight (LoS) path, a reflection path and some non-LoS (NLoS) paths. Based on the sparsity of the channel in the spatial domain, the damped Newtonized orthogonal matching pursuit (DNOMP) algorithm is also proposed to accurately estimate the multipaths, and reconstruct the channel. Then, a UE localization algorithm is proposed, which can detect the existence of the LoS path and locate the UE. A joint localization algorithm is also devised to further increase the positioning reliability. Simulation results verify that the DNOMP algorithm can reconstruct the channel with better NMSE performance than other schemes. The localization algorithm can locate the UE with low error whenever the LoS path exists or not, with an accuracy close enough to the position error bound (PEB), while the joint localization algorithm can further enhance the positioning reliability.