1.
Li, Qingchao; El-Hajjar, Mohammed; Xu, Chao; An, Jiancheng; Yuen, Chau; Hanzo, Lajos
Stacked Intelligent Metasurface-Based Transceiver Design for Near-Field Wideband Systems Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 9, pp. 8125–8139, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, Channel models, Hardware, holographic beamforming architecture, Low earth orbit satellites, Metamaterials, Metasurfaces, near-field channel model, phase tuning error, Stacked intelligent metasurface, Transceivers, Tuning, Vectors, Wideband, wideband system
@article{li_stacked_2025,
title = {Stacked Intelligent Metasurface-Based Transceiver Design for Near-Field Wideband Systems},
author = {Qingchao Li and Mohammed El-Hajjar and Chao Xu and Jiancheng An and Chau Yuen and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10900449},
doi = {10.1109/TCOMM.2025.3544929},
issn = {1558-0857},
year = {2025},
date = {2025-09-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {9},
pages = {8125–8139},
abstract = {Intelligent metasurfaces may be harnessed for realizing efficient holographic multiple-input and multiple-output (MIMO) systems, at a low hardware-cost and high energy-efficiency. As part of this family, we propose a hybrid beamforming design for stacked intelligent metasurfaces (SIM) aided wideband wireless systems relying on the near-field channel model. Specifically, the holographic beamformer is designed based on configuring the phase shifts in each layer of the SIM for maximizing the sum of the baseband eigen-channel gains of all users. To optimize the SIM phase shifts, we propose a layer-by-layer iterative algorithm for optimizing the phase shifts in each layer alternately. Then, the minimum mean square error (MMSE) transmit precoding method is employed for the digital beamformer to support multi-user access. Furthermore, the mitigation of the SIM phase tuning error is also taken into account in the digital beamformer by exploiting its statistics. The power sharing ratio of each user is designed based on the iterative waterfilling power allocation algorithm. Additionally, our analytical results indicate that the spectral efficiency attained saturates in the high signal-to-noise ratio (SNR) region due to the phase tuning error resulting from the imperfect SIM hardware quality. The simulation results show that the SIM-aided holographic MIMO outperforms the state-of-the-art (SoA) single-layer holographic MIMO in terms of its achievable rate. We further demonstrate that the near-field channel model allows the SIM-based transceiver design to support multiple users, since the spatial resources represented both by the angle domain and the distance domain can be exploited.},
keywords = {Array signal processing, Channel models, Hardware, holographic beamforming architecture, Low earth orbit satellites, Metamaterials, Metasurfaces, near-field channel model, phase tuning error, Stacked intelligent metasurface, Transceivers, Tuning, Vectors, Wideband, wideband system},
pubstate = {published},
tppubtype = {article}
}
Intelligent metasurfaces may be harnessed for realizing efficient holographic multiple-input and multiple-output (MIMO) systems, at a low hardware-cost and high energy-efficiency. As part of this family, we propose a hybrid beamforming design for stacked intelligent metasurfaces (SIM) aided wideband wireless systems relying on the near-field channel model. Specifically, the holographic beamformer is designed based on configuring the phase shifts in each layer of the SIM for maximizing the sum of the baseband eigen-channel gains of all users. To optimize the SIM phase shifts, we propose a layer-by-layer iterative algorithm for optimizing the phase shifts in each layer alternately. Then, the minimum mean square error (MMSE) transmit precoding method is employed for the digital beamformer to support multi-user access. Furthermore, the mitigation of the SIM phase tuning error is also taken into account in the digital beamformer by exploiting its statistics. The power sharing ratio of each user is designed based on the iterative waterfilling power allocation algorithm. Additionally, our analytical results indicate that the spectral efficiency attained saturates in the high signal-to-noise ratio (SNR) region due to the phase tuning error resulting from the imperfect SIM hardware quality. The simulation results show that the SIM-aided holographic MIMO outperforms the state-of-the-art (SoA) single-layer holographic MIMO in terms of its achievable rate. We further demonstrate that the near-field channel model allows the SIM-based transceiver design to support multiple users, since the spatial resources represented both by the angle domain and the distance domain can be exploited.
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.
Liu, Xin; Xu, Chao; Ng, Soon Xin; Hanzo, Lajos
OTFS-Based CV-QKD Systems for Doubly Selective THz Channels Journal Article
In: IEEE Transactions on Communications, vol. 73, no. 8, pp. 6274–6289, 2025, ISSN: 1558-0857.
Abstract | Links | BibTeX | Tags: Array signal processing, continuous variable quantum key distribution (CV-QKD), Faces, Fading channels, low-density parity check (LDPC), multiple-input multiple-out (MIMO), OFDM, Orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), Parity check codes, Random variables, secret key rate (SKR), Symbols, Terahertz (THz), Terahertz communications, Time-frequency analysis, Vectors
@article{liu_otfs-based_2025,
title = {OTFS-Based CV-QKD Systems for Doubly Selective THz Channels},
author = {Xin Liu and Chao Xu and Soon Xin Ng and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10857395},
doi = {10.1109/TCOMM.2025.3535889},
issn = {1558-0857},
year = {2025},
date = {2025-08-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Communications},
volume = {73},
number = {8},
pages = {6274–6289},
abstract = {The feasibility of continuous variable quantum key distribution (CV-QKD) is considered in the Terahertz (THz) band, experiencing time-varying and frequency-selective fading. Advanced multi-carrier modulation is required for improving the secret key rate (SKR). However, the hostile quantum channel requires powerful classical channel coding schemes for maintaining an adequate reconciliation performance. Against this background, for the first time in the open literature, we propose a multi-carrier quantum transmission regime that incorporates both orthogonal frequency division multiplexing (OFDM) and orthogonal time frequency space (OTFS) transmission over doubly selective fading THz channels. Furthermore, we propose a modified multi-dimensional reconciliation algorithm for CV-QKD, facilitating the integration of OFDM/OTFS quantum transmission with low-density parity check (LDPC) coded key reconciliation. Moreover, we harness multiple-input multiple-output (MIMO) beamforming for mitigating the severe THz path loss. Our SKR analysis results demonstrate that the proposed OTFS-based and LDPC-assisted CV-QKD system is capable of outperforming its OFDM counterpart in mobile wireless scenarios. Moreover, we also demonstrate that increasing the MIMO dimension reduces the transmission power required for achieving the secure transmission distance target.},
keywords = {Array signal processing, continuous variable quantum key distribution (CV-QKD), Faces, Fading channels, low-density parity check (LDPC), multiple-input multiple-out (MIMO), OFDM, Orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), Parity check codes, Random variables, secret key rate (SKR), Symbols, Terahertz (THz), Terahertz communications, Time-frequency analysis, Vectors},
pubstate = {published},
tppubtype = {article}
}
The feasibility of continuous variable quantum key distribution (CV-QKD) is considered in the Terahertz (THz) band, experiencing time-varying and frequency-selective fading. Advanced multi-carrier modulation is required for improving the secret key rate (SKR). However, the hostile quantum channel requires powerful classical channel coding schemes for maintaining an adequate reconciliation performance. Against this background, for the first time in the open literature, we propose a multi-carrier quantum transmission regime that incorporates both orthogonal frequency division multiplexing (OFDM) and orthogonal time frequency space (OTFS) transmission over doubly selective fading THz channels. Furthermore, we propose a modified multi-dimensional reconciliation algorithm for CV-QKD, facilitating the integration of OFDM/OTFS quantum transmission with low-density parity check (LDPC) coded key reconciliation. Moreover, we harness multiple-input multiple-output (MIMO) beamforming for mitigating the severe THz path loss. Our SKR analysis results demonstrate that the proposed OTFS-based and LDPC-assisted CV-QKD system is capable of outperforming its OFDM counterpart in mobile wireless scenarios. Moreover, we also demonstrate that increasing the MIMO dimension reduces the transmission power required for achieving the secure transmission distance target.
4.
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.
5.
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.
6.
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.
7.
Lu, Zhou; El-Hajjar, Mohammed; Yang, Lie-Liang
Wavelet Transform Aided Single-Carrier FDMA With Index Modulation Journal Article
In: IEEE Open Journal of Vehicular Technology, vol. 6, pp. 1524–1538, 2025, ISSN: 2644-1330.
Abstract | Links | BibTeX | Tags: detection, Frequency division multiaccess, Frequency-domain analysis, index modulation, Indexes, Maximum likelihood detection, Modulation, OFDM, Peak to average power ratio, peak-to-average power ratio, single carrier-frequency division multiple access (SC-FDMA), spatial modulation, Symbols, Time-domain analysis, Vectors, Wavelet, Wireless communication
@article{lu_wavelet_2025,
title = {Wavelet Transform Aided Single-Carrier FDMA With Index Modulation},
author = {Zhou Lu and Mohammed El-Hajjar and Lie-Liang Yang},
url = {https://ieeexplore.ieee.org/document/11021437},
doi = {10.1109/OJVT.2025.3576062},
issn = {2644-1330},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of Vehicular Technology},
volume = {6},
pages = {1524–1538},
abstract = {Single-carrier frequency-division multiple access (SC-FDMA) is a well-known multiuser transmission method for uplink communications owing to its low peak-to-average power ratio (PAPR) characteristics. Simultaneously, index modulation (IM) has been widely studied owing to its flexibility for spectral-efficiency versus energy-efficiency trade-off. However, applying conventional IM schemes with SC-FDMA may affect the desirable characteristics of SC-FDMA signals, resulting in the increase of PAPR, for example. On the other side, Wavelet Transform (WT) has been shown to provide an improved performance over the fast Fourier transform (FFT)-based SC-FDMA, owing to WT's local focusing capability in both time and frequency domains. In this paper, we propose three IM schemes, namely Symbol Position Index Modulation (SPIM), Spreading Matrix Index Modulation (SMIM) and Joint Matrix-Symbol Index Modulation (JMSIM) schemes, which perform IM at the symbol vector level, spreading matrix level, or a combination of both. These IM schemes are implemented with the WT-based SC-FDMA for data transmission. We consider two spreading matrix design schemes, namely random dispersion matrix design and Gram-Schmidt (GS) orthogonalization matrix design. Correspondingly, we propose different detection schemes, including Maximum Likelihood Detection (MLD), Simplified Maximum Likelihood Detection (SMLD), and the Two Stage Index-QAM Detection (TSD). The performance of the proposed schemes is evaluated by simulations. Our studies and results show that all the three schemes can effectively reduce the PAPR encountered by the conventional IM-assisted SC-FDMA signals. Moreover, the method of GS matrices can provide a gain upto 20 dB compared with the method of random dispersion matrices. Furthermore, the GS-based system can employ the proposed low-complexity TSD, allowing to achieve a similar bit error rate (BER) performance as MLD, while requiring significantly low complexity.},
keywords = {detection, Frequency division multiaccess, Frequency-domain analysis, index modulation, Indexes, Maximum likelihood detection, Modulation, OFDM, Peak to average power ratio, peak-to-average power ratio, single carrier-frequency division multiple access (SC-FDMA), spatial modulation, Symbols, Time-domain analysis, Vectors, Wavelet, Wireless communication},
pubstate = {published},
tppubtype = {article}
}
Single-carrier frequency-division multiple access (SC-FDMA) is a well-known multiuser transmission method for uplink communications owing to its low peak-to-average power ratio (PAPR) characteristics. Simultaneously, index modulation (IM) has been widely studied owing to its flexibility for spectral-efficiency versus energy-efficiency trade-off. However, applying conventional IM schemes with SC-FDMA may affect the desirable characteristics of SC-FDMA signals, resulting in the increase of PAPR, for example. On the other side, Wavelet Transform (WT) has been shown to provide an improved performance over the fast Fourier transform (FFT)-based SC-FDMA, owing to WT's local focusing capability in both time and frequency domains. In this paper, we propose three IM schemes, namely Symbol Position Index Modulation (SPIM), Spreading Matrix Index Modulation (SMIM) and Joint Matrix-Symbol Index Modulation (JMSIM) schemes, which perform IM at the symbol vector level, spreading matrix level, or a combination of both. These IM schemes are implemented with the WT-based SC-FDMA for data transmission. We consider two spreading matrix design schemes, namely random dispersion matrix design and Gram-Schmidt (GS) orthogonalization matrix design. Correspondingly, we propose different detection schemes, including Maximum Likelihood Detection (MLD), Simplified Maximum Likelihood Detection (SMLD), and the Two Stage Index-QAM Detection (TSD). The performance of the proposed schemes is evaluated by simulations. Our studies and results show that all the three schemes can effectively reduce the PAPR encountered by the conventional IM-assisted SC-FDMA signals. Moreover, the method of GS matrices can provide a gain upto 20 dB compared with the method of random dispersion matrices. Furthermore, the GS-based system can employ the proposed low-complexity TSD, allowing to achieve a similar bit error rate (BER) performance as MLD, while requiring significantly low complexity.
8.
Li, Qingchao; El-Hajjar, Mohammed; Xu, Chao; Zhang, Chao; Hanzo, Lajos
XL-MIMO Based Hierarchical Receive Beamforming Subject to Hardware Impairments in the Uplink of Cell-Free Networks Journal Article
In: IEEE Transactions on Vehicular Technology, pp. 1–11, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Antenna arrays, Antennas, Array signal processing, cell-free network, Central Processing Unit, Computer architecture, Estimation, Extremely large-scale multiple-input and multiple-output (XL-MIMO), Hardware, hardware impairment (HWI), hierarchical detection, near-field, Signal processing algorithms, Signal to noise ratio, Vectors
@article{li_xl-mimo_2025,
title = {XL-MIMO Based Hierarchical Receive Beamforming Subject to Hardware Impairments in the Uplink of Cell-Free Networks},
author = {Qingchao Li and Mohammed El-Hajjar and Chao Xu and Chao Zhang and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11091536},
doi = {10.1109/TVT.2025.3592149},
issn = {1939-9359},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
pages = {1–11},
abstract = {Extremely large-scale multiple-input and multiple-output (XL-MIMO) exhibit substantial spatial multiplexing capabilities owing to their high degree of freedom. As the number of antenna elements increases, it becomes more practically suitable to utilize cost-effective antennas equipped with low-resolution RF chains. However, hardware impairments (HWIs) associated with these cost-effective antennas lead to performance saturation in the high signal-to-noise ratio (SNR) region, which cannot be mitigated by merely increasing the transmit power. To address these challenges, we propose a hierarchical receive beamforming method for XL-MIMO based near-field cell-free networks with HWIs. Specifically, the antenna array of each access point (AP) is partitioned into multiple sub-arrays, with each sub-array independently harnessing the minimum mean-square error (MMSE) receive beamforming algorithm. The local data estimates at each AP are then optimized using the results from all sub-arrays, and the central processing unit (CPU) performs its final information recovery by integrating these local estimates. Our theoretical analysis shows that the proposed hierarchical receive beamforming method achieves a higher ergodic sum-rate than the state-of-the-art (SoA) scheme in XL-MIMO systems in the face of HWIs.},
keywords = {Antenna arrays, Antennas, Array signal processing, cell-free network, Central Processing Unit, Computer architecture, Estimation, Extremely large-scale multiple-input and multiple-output (XL-MIMO), Hardware, hardware impairment (HWI), hierarchical detection, near-field, Signal processing algorithms, Signal to noise ratio, Vectors},
pubstate = {published},
tppubtype = {article}
}
Extremely large-scale multiple-input and multiple-output (XL-MIMO) exhibit substantial spatial multiplexing capabilities owing to their high degree of freedom. As the number of antenna elements increases, it becomes more practically suitable to utilize cost-effective antennas equipped with low-resolution RF chains. However, hardware impairments (HWIs) associated with these cost-effective antennas lead to performance saturation in the high signal-to-noise ratio (SNR) region, which cannot be mitigated by merely increasing the transmit power. To address these challenges, we propose a hierarchical receive beamforming method for XL-MIMO based near-field cell-free networks with HWIs. Specifically, the antenna array of each access point (AP) is partitioned into multiple sub-arrays, with each sub-array independently harnessing the minimum mean-square error (MMSE) receive beamforming algorithm. The local data estimates at each AP are then optimized using the results from all sub-arrays, and the central processing unit (CPU) performs its final information recovery by integrating these local estimates. Our theoretical analysis shows that the proposed hierarchical receive beamforming method achieves a higher ergodic sum-rate than the state-of-the-art (SoA) scheme in XL-MIMO systems in the face of HWIs.
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.
Nguyen, Doan Hieu; Nguyen, Xuan Tung; Jeong, Seon-Geun; Chien, Trinh Van; Hanzo, Lajos; Hwang, Won-Joo
Hybrid Quantum Convolutional Neural Network-Aided Pilot Assignment in Cell-Free Massive MIMO Systems Journal Article
In: IEEE Transactions on Vehicular Technology, pp. 1–6, 2025, ISSN: 1939-9359.
Abstract | Links | BibTeX | Tags: Cell-free massive MIMO, Convergence, Convolutional neural networks, Integrated circuit modeling, Massive MIMO, Pilot Allocation, Quantum circuit, Quantum Machine Learning, Quantum state, Qubit, Throughput, Training, Vectors
@article{nguyen_hybrid_2025,
title = {Hybrid Quantum Convolutional Neural Network-Aided Pilot Assignment in Cell-Free Massive MIMO Systems},
author = {Doan Hieu Nguyen and Xuan Tung Nguyen and Seon-Geun Jeong and Trinh Van Chien and Lajos Hanzo and Won-Joo Hwang},
url = {https://ieeexplore.ieee.org/document/11091511},
doi = {10.1109/TVT.2025.3588212},
issn = {1939-9359},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Vehicular Technology},
pages = {1–6},
abstract = {A sophisticated hybrid quantum convolutional neural network (HQCNN) is conceived for handling the pilot assignment task in cell-free massive MIMO systems, while maximizing the total ergodic sum throughput. The existing model-based solutions found in the literature are inefficient and/or computationally demanding. Similarly, conventional deep neural networks may struggle in the face of high-dimensional inputs, require complex architectures, and their convergence is slow due to training numerous hyperparameters. The proposed HQCNN leverages parameterized quantum circuits (PQCs) relying on superposition for enhanced feature extraction. Specifically, we exploit the same PQC across all the convolutional layers for customizing the neural network and for accelerating the convergence. Our numerical results demonstrate that the proposed HQCNN offers a total network throughput close to that of the excessive-complexity exhaustive search and outperforms the state-of-the-art benchmarks.},
keywords = {Cell-free massive MIMO, Convergence, Convolutional neural networks, Integrated circuit modeling, Massive MIMO, Pilot Allocation, Quantum circuit, Quantum Machine Learning, Quantum state, Qubit, Throughput, Training, Vectors},
pubstate = {published},
tppubtype = {article}
}
A sophisticated hybrid quantum convolutional neural network (HQCNN) is conceived for handling the pilot assignment task in cell-free massive MIMO systems, while maximizing the total ergodic sum throughput. The existing model-based solutions found in the literature are inefficient and/or computationally demanding. Similarly, conventional deep neural networks may struggle in the face of high-dimensional inputs, require complex architectures, and their convergence is slow due to training numerous hyperparameters. The proposed HQCNN leverages parameterized quantum circuits (PQCs) relying on superposition for enhanced feature extraction. Specifically, we exploit the same PQC across all the convolutional layers for customizing the neural network and for accelerating the convergence. Our numerical results demonstrate that the proposed HQCNN offers a total network throughput close to that of the excessive-complexity exhaustive search and outperforms the state-of-the-art benchmarks.
11.
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.
12.
Soleymani, Mohammad; Jorswieck, Eduard; Schober, Robert; Hanzo, Lajos
A Framework for Fractional Matrix Programming Problems with Applications in FBL MU-MIMO Journal Article
In: IEEE Transactions on Wireless Communications, pp. 1–1, 2025, ISSN: 1558-2248.
Abstract | Links | BibTeX | Tags: Delays, Finite block length coding, fractional matrix programming, latency minimization, mean square error, Measurement, MIMO, Minimization, multi-user MIMO systems, Optimization, Performance metrics, Programming, reconfigurable intelligent surface, Resource management, spectral-energy efficiency tradeoff, Transforms, Vectors
@article{soleymani_framework_2025,
title = {A Framework for Fractional Matrix Programming Problems with Applications in FBL MU-MIMO},
author = {Mohammad Soleymani and Eduard Jorswieck and Robert Schober and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11096011},
doi = {10.1109/TWC.2025.3590162},
issn = {1558-2248},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Transactions on Wireless Communications},
pages = {1–1},
abstract = {An efficient framework is conceived for fractional matrix programming (FMP) optimization problems (OPs) namely for minimization and maximization. In each generic OP, either the objective or the constraints are functions of multiple arbitrary continuous-domain fractional functions (FFs). This ensures the framework’s versatility, enabling it to solve a broader range of OPs than classical FMP solvers, like Dinkelbach-based algorithms. Specifically, the generalized Dinkelbach algorithm can only solve multiple-ratio FMP problems. By contrast, our framework solves OPs associated with a sum or product of multiple FFs as the objective or constraint functions. Additionally, our framework provides a single-loop solution, while most FMP solvers require twin-loop algorithms. Many popular performance metrics of wireless communications are FFs. For instance, latency has a fractional structure, and minimizing the sum delay leads to an FMP problem. Moreover, the mean square error (MSE) and energy efficiency (EE) metrics have fractional structures. Thus, optimizing EE-related metrics such as the sum or geometric mean of EEs and enhancing the metrics related to spectral-versus-energy-efficiency tradeoff yield FMP problems. Furthermore, both the signal-to-interference-plus-noise ratio and the channel dispersion are FFs. In this paper, we also develop resource allocation schemes for multi-user multiple-input multiple-output (MU-MIMO) systems, using finite block length (FBL) coding, demonstrating attractive practical applications of FMP by optimizing the aforementioned metrics.},
keywords = {Delays, Finite block length coding, fractional matrix programming, latency minimization, mean square error, Measurement, MIMO, Minimization, multi-user MIMO systems, Optimization, Performance metrics, Programming, reconfigurable intelligent surface, Resource management, spectral-energy efficiency tradeoff, Transforms, Vectors},
pubstate = {published},
tppubtype = {article}
}
An efficient framework is conceived for fractional matrix programming (FMP) optimization problems (OPs) namely for minimization and maximization. In each generic OP, either the objective or the constraints are functions of multiple arbitrary continuous-domain fractional functions (FFs). This ensures the framework’s versatility, enabling it to solve a broader range of OPs than classical FMP solvers, like Dinkelbach-based algorithms. Specifically, the generalized Dinkelbach algorithm can only solve multiple-ratio FMP problems. By contrast, our framework solves OPs associated with a sum or product of multiple FFs as the objective or constraint functions. Additionally, our framework provides a single-loop solution, while most FMP solvers require twin-loop algorithms. Many popular performance metrics of wireless communications are FFs. For instance, latency has a fractional structure, and minimizing the sum delay leads to an FMP problem. Moreover, the mean square error (MSE) and energy efficiency (EE) metrics have fractional structures. Thus, optimizing EE-related metrics such as the sum or geometric mean of EEs and enhancing the metrics related to spectral-versus-energy-efficiency tradeoff yield FMP problems. Furthermore, both the signal-to-interference-plus-noise ratio and the channel dispersion are FFs. In this paper, we also develop resource allocation schemes for multi-user multiple-input multiple-output (MU-MIMO) systems, using finite block length (FBL) coding, demonstrating attractive practical applications of FMP by optimizing the aforementioned metrics.
13.
Feng, Xinyu; El-Hajjar, Mohammed; Xu, Chao; Hanzo, Lajos
Graph Neural Network Aided Detection for the Multi-User Multi-Dimensional Index Modulated Uplink Journal Article
In: IEEE Open Journal of Vehicular Technology, vol. 6, pp. 1593–1612, 2025, ISSN: 2644-1330.
Abstract | Links | BibTeX | Tags: Artificial neural networks, Detectors, graph factor, graph neural network (GNN), Graph neural networks, Index modulation (IM), Indexes, machine learning, Message passing, message passing (MP), multi-user, Next generation networking, Peak to average power ratio, Symbols, Uplink, Vectors
@article{feng_graph_2025,
title = {Graph Neural Network Aided Detection for the Multi-User Multi-Dimensional Index Modulated Uplink},
author = {Xinyu Feng and Mohammed El-Hajjar and Chao Xu and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/11017516},
doi = {10.1109/OJVT.2025.3574934},
issn = {2644-1330},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of Vehicular Technology},
volume = {6},
pages = {1593–1612},
abstract = {The concept of Compressed Sensing-aided Space-Frequency Index Modulation (CS-SFIM) is conceived for the Large-Scale Multi-User Multiple-Input Multiple-Output Uplink (LS-MU-MIMO-UL) of Next-Generation (NG) networks. Explicitly, in CS-SFIM, the information bits are mapped to both spatial- and frequency-domain indices, where we treat the activation patterns of the transmit antennas and of the subcarriers separately. Serving a large number of users in an MU-MIMO-UL system leads to substantial Multi-User Interference (MUI). Hence, we design the Space-Frequency (SF) domain matrix as a joint factor graph, where the Approximate Message Passing (AMP) and Expectation Propagation (EP) based MU detectors can be utilized. In the LS-MU-MIMO-UL scenario considered, the proposed system uses optimal Maximum Likelihood (ML) and Minimum Mean Square Error (MMSE) detectors as benchmarks for comparison with the proposed MP-based detectors. These MP-based detectors significantly reduce the detection complexity compared to ML detection, making the design eminently suitable for LS-MU scenarios. To further reduce the detection complexity and improve the detection performance, we propose a pair of Graph Neural Network (GNN) based detectors, which rely on the orthogonal AMP (OAMP) and on the EP algorithm, which we refer to as the GNN-AMP and GEPNet detectors, respectively. The GEPNet detector maximizes the detection performance, while the GNN-AMP detector strikes a performance versus complexity trade-off. The GNN is trained for a single system configuration and yet it can be used for any number of users in the system. The simulation results show that the GNN-based detector approaches the ML performance in various configurations.},
keywords = {Artificial neural networks, Detectors, graph factor, graph neural network (GNN), Graph neural networks, Index modulation (IM), Indexes, machine learning, Message passing, message passing (MP), multi-user, Next generation networking, Peak to average power ratio, Symbols, Uplink, Vectors},
pubstate = {published},
tppubtype = {article}
}
The concept of Compressed Sensing-aided Space-Frequency Index Modulation (CS-SFIM) is conceived for the Large-Scale Multi-User Multiple-Input Multiple-Output Uplink (LS-MU-MIMO-UL) of Next-Generation (NG) networks. Explicitly, in CS-SFIM, the information bits are mapped to both spatial- and frequency-domain indices, where we treat the activation patterns of the transmit antennas and of the subcarriers separately. Serving a large number of users in an MU-MIMO-UL system leads to substantial Multi-User Interference (MUI). Hence, we design the Space-Frequency (SF) domain matrix as a joint factor graph, where the Approximate Message Passing (AMP) and Expectation Propagation (EP) based MU detectors can be utilized. In the LS-MU-MIMO-UL scenario considered, the proposed system uses optimal Maximum Likelihood (ML) and Minimum Mean Square Error (MMSE) detectors as benchmarks for comparison with the proposed MP-based detectors. These MP-based detectors significantly reduce the detection complexity compared to ML detection, making the design eminently suitable for LS-MU scenarios. To further reduce the detection complexity and improve the detection performance, we propose a pair of Graph Neural Network (GNN) based detectors, which rely on the orthogonal AMP (OAMP) and on the EP algorithm, which we refer to as the GNN-AMP and GEPNet detectors, respectively. The GEPNet detector maximizes the detection performance, while the GNN-AMP detector strikes a performance versus complexity trade-off. The GNN is trained for a single system configuration and yet it can be used for any number of users in the system. The simulation results show that the GNN-based detector approaches the ML performance in various configurations.