@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}

}

@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}

}

@article{rai_spectral_2025,

title = {The Spectral Versus Energy Efficiency Trade-Off in Dynamic User Clustering Aided mmWave NOMA Networks},

author = {Sudhakar Rai and Ekant Sharma and Aditya K. Jagannatham and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10769478},

doi = {10.1109/TCOMM.2024.3506920},

issn = {1558-0857},

year  = {2025},

date = {2025-06-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

volume = {73},

number = {6},

pages = {4503–4519},

abstract = {The spectral efficiency (SE) and global energy efficiency (GEE) trade-off encountered in the design of millimeter-wave (mmWave)-based massive multi-input multi-output (MIMO) non-orthogonal multiple access (NOMA) networks is investigated with a particular focus on user clustering. By exploiting the similarity among user channels a pair of spectral and energy-efficient user clustering algorithms are proposed for dynamically selecting both the number of clusters and the number of users in each cluster. Subsequently, a joint analog precoder/combiner and user clustering technique is developed, followed by a multi-objective optimization (MOO) framework for flexibly balancing the GEE and SE objectives in a mmWave NOMA network subject to specific constraints. The MOO objective is initially transformed to a weighted sum rate maximization problem, followed by a quadratic-transform (QT)-based approach conceived for maximizing the non-convex objective by approximating it as a concave-convex function. Our simulation results demonstrate that the user clustering techniques designed attain a 85% performance gain over random clustering technique and demonstrating the benefits of the algorithm designed for mmWave NOMA networks.},

keywords = {Array signal processing, Clustering algorithms, Energy Efficiency, fractional programming, Heuristic algorithms, Hybrid power systems, hybrid precoding, Interference cancellation, Millimeter wave communication, MIMO, mmWave, NOMA, Optimization, Resource management, Spectral efficiency, user clustering},

pubstate = {published},

tppubtype = {article}

}

@article{soleymani_rate_2025,

title = {Rate Splitting Multiple Access for RIS-aided URLLC MIMO Broadcast Channels},

author = {Mohammad Soleymani and Ignacio Santamaria and Eduard Jorswieck and Marco Di Renzo and Robert Schober and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/11123651},

doi = {10.1109/TWC.2025.3591365},

issn = {1558-2248},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Wireless Communications},

pages = {1–1},

abstract = {The performance of modern wireless communication systems is typically limited by interference. The impact of interference can be even more severe in ultra-reliable and low-latency communication (URLLC) use cases. A powerful tool for managing interference is rate splitting multiple access (RSMA), which encompasses many multiple-access technologies like non-orthogonal multiple access (NOMA), spatial division multiple access (SDMA), and broadcasting. Another effective technology to enhance the performance of URLLC systems and mitigate interference is constituted by reconfigurable intelligent surfaces (RISs). This paper develops RSMA schemes for multi-user multiple-input multiple-output (MIMO) RIS-aided broad-cast channels (BCs) based on finite block length (FBL) coding. We show that RSMA and RISs can substantially improve the spectral efficiency (SE) and energy efficiency (EE) of MIMO RIS-aided URLLC systems. Additionally, the gain of employing RSMA and RISs noticeably increases when the reliability and latency constraints are more stringent. Furthermore, RISs impact RSMA differently, depending on the user load. If the system is underloaded, RISs are able to manage the interference sufficiently well, making the gains of RSMA small. However, when the user load is high, RISs and RSMA become synergetic.},

keywords = {6G mobile communication, Channel coding, Europe, Finite block length coding, Interference, low latency, max-min energy efficiency, max-min rate, MIMO, MIMO systems, MISO, NOMA, reconfigurable intelligent surface, Reliability, Resource management, Ultra reliable low latency communication, ultra-reliable communications},

pubstate = {published},

tppubtype = {article}

}

@article{meng_network-level_2025,

title = {Network-level ISAC: An Analytical Study of Antenna Topologies Ranging from Massive to Cell-Free MIMO},

author = {Kaitao Meng and Kawon Han and Christos Masouros and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/11030947},

doi = {10.1109/TWC.2025.3576432},

issn = {1558-2248},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Wireless Communications},

pages = {1–1},

abstract = {A cooperative architecture is proposed for integrated sensing and communication (ISAC) networks, incorporating coordinated multi-point (CoMP) transmission along with multi-static sensing. We investigate how the allocation of antennas-to-base stations (BSs) affects cooperative sensing and cooperative communication performance. More explicitly, we balance the benefits of geographically concentrated antennas in the massive multiple input multiple output (MIMO) fashion, which enhance beamforming and coherent processing, against those of geographically distributed antennas towards cell-free transmission, which improve diversity and reduce service distances. Regarding sensing performance, we investigate three localization methods: angle-of-arrival (AOA)- based, time-of-flight (TOF)-based, and a hybrid approach combining both AOA and TOF measurements, for critically appraising their effects on ISAC network performance. Our analysis shows that in networks having N ISAC nodes following a Poisson point process, the localization accuracy of TOF-based methods follows a ln2 N scaling law (explicitly, the Cramér-Rao lower bound (CRLB) reduces with ln2 N). The AOA-based methods follow a ln N scaling law, while the hybrid methods scale as a ln2 N+b ln N, where a and b represent parameters related to TOF and AOA measurements, respectively. The difference between these scaling laws arises from the distinct ways in which measurement results are converted into the target location. Specifically, when converting AOA measurements to the target location, the localization error introduced during this conversion is inversely proportional to the distance between the BS and the target, leading to a more significant reduction in accuracy as the number of transceivers increases. In contrast, TOF-based localization avoids such distance dependent errors in the conversion process. In terms of communication performance, we derive a tractable expression for the communication data rate, considering various cooperative region sizes and antenna-to-BS allocation strategy. It is proved that higher path loss exponents favor distributed antenna allocation to reduce access distances, while lower exponents favor centralized antenna allocation to maximize beamforming gain. Simulations confirm that cooperative transmission and sensing in ISAC networks can effectively improve non-cooperative sensing and communication performance The proposed cooperative scheme shows superior performance improvement compared to centralized or distributed antenna allocation strategies.},

keywords = {antenna allocation, Antenna arrays, Antenna measurements, Antennas, Array signal processing, cooperative sensing and communication, Geometry, Integrated sensing and communication, Location awareness, MIMO, multi-cell networks, network performance analysis, Resource management, stochastic geometry, Transmitting antennas},

pubstate = {published},

tppubtype = {article}

}

@article{gupta_bayesian_2025,

title = {Bayesian Learning Aided Parameter Estimation and Joint Beamformer Design in mmWave MIMO-OFDM ISAC Systems},

author = {Awadhesh Gupta and Jitendra Singh and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/11030617},

doi = {10.1109/TCOMM.2025.3578813},

issn = {1558-0857},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

pages = {1–1},

abstract = {A three-dimensional (3D) sparse signal recovery problem formulation is conceived for delay, Doppler, and angular (DDA) domain target parameter estimation in millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems relying on a hybrid beamforming architecture. Subsequently, a 3D-sparse Bayesian learning (3D-BL) algorithm is proposed to jointly estimate the angular, range, velocity, and radar cross-section (RCS) parameters of the targets. Furthermore, an uplink beamformer is designed for the user equipment (UE) to alleviate the complexity of uplink parameter estimation at the dual-functional radar-communication (DFRC) base station (BS) by eliminating the need for angle of departure (AoD) estimation. Additionally, a Bayesian alternating minimization (BAT-MIN) algorithm is constructed for the designing of a DFRC waveform, enabling the simultaneous generation of beams toward both the radar targets and the UE. Furthermore, the sparse Bayesian learning lower bound (SBL-LB) and the Bayesian Cramér-Rao lower bound (BCRLB) are derived to serve as benchmarks for estimation performance. Finally, simulation results are presented to showcase the enhanced performance of the proposed methodologies in terms of multiple performance metrics when contrasted both to the existing sparse recovery techniques and to conventional non-sparse parameter estimation algorithms. The simulation outcomes unequivocally demonstrate the commendable performance of the proposed 3D-BL estimation methodology, approaching closely to the SBL-LB. Notably, this approach exhibits a substantial gain of at least 5 dB when compared to alternative techniques. Additionally, the introduced BAT-MIN beamformer emerges as a highly competitive solution, closely approximating the capabilities of a fully digital beamformer while maintaining a noteworthy minimum advantage over its contemporaries. These findings underscore the significance and efficacy of the proposed techniques in the context of advanced signal processing and beamforming.},

keywords = {Array signal processing, Bayes methods, dual-functional radar-communication (DFRC), Estimation, hybrid analog-digital (HAD) beamforming, Integrated sensing and communication (ISAC), millimeter wave (mmWave), Millimeter wave communication, MIMO, OFDM, Parameter estimation, Radar, Radar cross-sections, Radio frequency, sparse Bayesian learning (SBL)},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{maity_variational_2025,

title = {Variational Bayesian Learning for 3-D Localization of Extended Targets in mmWave MIMO OFDM ISAC Systems},

author = {Priyanka Maity and Deepika Harish and Suraj Srivastava and Aditya K. Jagannatham and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10990143},

doi = {10.1109/OJCOMS.2025.3567429},

issn = {2644-125X},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Open Journal of the Communications Society},

volume = {6},

pages = {4421–4436},

abstract = {Variational Bayesian learning (VBL)-aided extended target localization is conceived for orthogonal frequency division multiplexing (OFDM) based-mmWave MIMO systems using the OFDM integrated sensing and communication (ISAC) waveform. The proposed framework also considers the intercarrier interference (ICI) effects encountered in mobile scenarios and the clutter present in the environment. The proposed algorithm is based on a hybrid mmWave MIMO architecture, where the number of radio frequency (RF) chains is significantly lower than the number of antennas. A range, Doppler and angular (RDA)-domain representation of the target in three-dimensional (3D) space is conceived for accurate target parameter estimation. The proposed algorithm exploits the four-dimensional (4D) sparsity arising in the RDA domain of the scattering scene and employs the powerful VBL framework for the estimation of target parameters, such as elevation angle, azimuth angle, range and velocity. To handle a practical scenario where the actual target parameters typically deviate from their finite-resolution grid, a super-resolution-based improved off-grid VBL is developed for recursively updating the parameter grid, thereby progressively improving the estimates. We also determine the Cramér-Rao bound (CRB) and Bayesian CRB for the estimation of the target parameters in order to bound the estimation performance. Our simulation results validate the superior performance of the proposed approach in comparison to the existing algorithms.},

keywords = {azimuth angle, Bayes methods, Bayesian learning, Clutter, Direction-of-arrival estimation, Doppler effect, elevation angle, Estimation, extended targets, Integrated sensing and communication, Location awareness, Millimeter wave communication, MIMO, mmWave, OFDM, Radar, sparsity, Three-dimensional displays},

pubstate = {published},

tppubtype = {article}

}

@article{zhong_optimization_2024,

title = {Optimization of Surface Configuration in IRS-Aided MIMO-VLC: A BER Minimization Approach},

author = {Xin Zhong and Chen Chen and Wanli Wen and Min Liu and H. Y. Fu and Harald Haas},

url = {https://ieeexplore.ieee.org/document/10517366/},

doi = {10.1109/JPHOT.2024.3395894},

issn = {1943-0655, 1943-0647},

year  = {2024},

date = {2024-06-01},

urldate = {2024-10-30},

journal = {IEEE Photonics Journal},

volume = {16},

number = {3},

pages = {1–12},

keywords = {LRDC, MIMO},

pubstate = {published},

tppubtype = {article}

}

@article{winter_lattice-reduction_2024,

title = {A Lattice-Reduction Aided Vector Perturbation Precoder Relying on Quantum Annealing},

author = {Samuel Winter and Yangyishi Zhang and Gan Zheng and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10436537},

doi = {10.1109/LWC.2024.3365874},

issn = {2162-2345},

year  = {2024},

date = {2024-05-01},

urldate = {2025-10-08},

journal = {IEEE Wireless Communications Letters},

volume = {13},

number = {5},

pages = {1225–1229},

abstract = {Quantum annealing (QA) is proposed for vector perturbation precoding (VPP) in multiple input multiple output (MIMO) communications systems. The mathematical framework of VPP is presented, outlining the problem formulation and the benefits of lattice reduction algorithms. Lattice reduction aided quantum vector perturbation (LRAQVP) is designed by harnessing physical quantum hardware, and the optimization of hardware parameters is discussed. We observe a 5dB gain over lattice reduction zero forcing precoding (LRZFP), which behaves similarly to a quantum annealing algorithm operating without a lattice reduction stage. The proposed algorithm is also shown to approach the performance of a sphere encoder, which exhibits an exponentially escalating complexity.},

keywords = {Annealing, downlink precoding, Hardware, Lattices, MIMO, Perturbation methods, Quantum annealing, Qubit, Symbols, vector perturbation},

pubstate = {published},

tppubtype = {article}

}

@article{zhong_dual-mode_2024,

title = {Dual-mode spatial index modulation for MIMO-OWC},

author = {Xin Zhong and Chen Chen and Yinan Zhao and Min Liu and Cuiwei He and Harald Haas},

url = {https://opg.optica.org/abstract.cfm?URI=ol-49-2-334},

doi = {10.1364/OL.509658},

issn = {0146-9592, 1539-4794},

year  = {2024},

date = {2024-01-01},

urldate = {2024-10-30},

journal = {Optics Letters},

volume = {49},

number = {2},

pages = {334},

abstract = {In this Letter, we propose and demonstrate a dual-mode spatial index modulation (DM-SIM) scheme for spectral efficiency enhancement of band-limited multiple-input multiple-output optical wireless communication (MIMO-OWC) systems. By performing dual-mode index modulation in the spatial domain, DM-SIM can transmit both spatial and constellation symbols. Since constellation design plays a vital role in the proposed DM-SIM scheme, we further propose three dual-mode constellation design approaches including phase rotation, amplitude scaling and joint phase rotation and amplitude scaling. Moreover, we also designed a differential log-likelihood ratio (LLR) detector for the proposed DM-SIM scheme. Experimental results show that the joint phase rotation and amplitude scaling approach can achieve a remarkable 3.2 dB signal-to-noise ratio (SNR) gain compared with the phase rotation approach in a 2×2 MIMO-OWC system applying DM-SIM.},

keywords = {LRDC, MIMO, Optical wireless communication},

pubstate = {published},

tppubtype = {article}

}