@article{smith_dimensional_2025,

title = {Dimensional Scaling Laws for Continuous Fluid Antenna Systems},

author = {Peter J. Smith and Amy S. Inwood and Michail Matthaiou and Rajitha Senanayake},

url = {https://ieeexplore.ieee.org/document/10965723},

doi = {10.1109/LWC.2025.3560861},

issn = {2162-2345},

year  = {2025},

date = {2025-07-01},

urldate = {2025-10-08},

journal = {IEEE Wireless Communications Letters},

volume = {14},

number = {7},

pages = {2004–2008},

abstract = {Consider the signal-to-noise ratio (SNR) of a continuous fluid antenna system (CFAS) operating over a Rayleigh fading channel. In this letter, we extend traditional system assumptions and consider spatially coherent isotropic correlation, continuous positioning of the antenna rather than discrete, and the use of multi-dimensional space (1D, 2D and 3D). By focusing on the upper tail of the received SNR distribution (the high SNR probability (HSP)), we are able to derive asymptotically exact closed-form formulas for the HSP. Finally, these results lead to scaling laws which describe the increase in the HSP as we employ more dimensions and the optimal CFAS dimensions.},

keywords = {3D antenna geometries, Antennas, Correlation, Fluid antenna systems, Fluids, high SNR probability, random fields, Rayleigh channels, Rayleigh fading, Shape, Signal to noise ratio, Tail, Three-dimensional displays, Training, Wireless communication},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{singh_pareto_2025,

title = {Pareto Optimal Hybrid Beamforming for Short-Packet Millimeter-Wave Integrated Sensing and Communication},

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

url = {https://ieeexplore.ieee.org/document/10778580},

doi = {10.1109/TCOMM.2024.3511704},

issn = {1558-0857},

year  = {2025},

date = {2025-06-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

volume = {73},

number = {6},

pages = {4570–4585},

abstract = {Pareto optimal solutions are conceived for radar beamforming error (RBE) and sum rate maximization in short-packet (SP) millimeter-wave (mmWave) integrated sensing and communication (ISAC). Our ultimate goal is to realize ultra-reliable low-latency communication (uRLLC) and real-time sensing capabilities for 6G applications. The ISAC base station (BS) transmits short packets in the downlink (DL) to serve multiple communication users (CUs) and detect multiple radar targets (RTs). We investigate the performance trade-off between the sensing and communication capabilities by optimizing both the radio frequency (RF) and the baseband (BB) transmit precoder (TPC), together with the block lengths. The optimization problem considers the minimum rate requirements of the CUs, the maximum tolerable radar beamforming error (RBE) for the RTs, the unit modulus (UM) elements of the RF TPC, and the finite transmit power as the constraints for SP transmission. The resultant problem is highly non-convex due to the intractable rate expression of the SP regime coupled with the non-convex rate and UM constraints. To solve this problem, we propose an innovative two-layer bisection search (TLBS) algorithm, wherein the RF and BB TPCs are optimized in the inner layer, followed by the block length in the outer layer. Furthermore, a pair of novel methods, namely a bisection search-based majorizer and minimizer (BMM) as well as exact penalty-based manifold optimization (EPMO) are harnessed for optimizing the RF TPC in the inner layer. Subsequently, the BB TPC and the block length are derived via second-order cone programming (SOCP) and mixed integer programming methods, respectively. Finally, our exhaustive simulation results reveal the effect of system parameters for various settings on the RBE-rate region of the SP mmWave ISAC system and demonstrate a significantly enhanced performance compared to the benchmarks.},

keywords = {Array signal processing, Copper, hybrid beamforming, Integrated sensing and communication, Millimeter wave communication, Millimeter wave radar, Optimization, Pareto boundary, Programming, Radio frequency, Short packet communication, Signal to noise ratio, Ultra reliable low latency communication, Ultra-reliable low latency communication},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@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}

}

@article{singh_spectral_2025,

title = {Spectral Efficiency Maximization for Mmwave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints},

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

url = {https://ieeexplore.ieee.org/document/11027785},

doi = {10.1109/TVT.2025.3577955},

issn = {1939-9359},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Vehicular Technology},

pages = {1–16},

abstract = {A hybrid transmit precoder (TPC) and receive combiner (RC) pair is conceived for millimeter wave (mmWave) multiple input multiple output (MIMO) integrated sensing and communication (ISAC) systems. The proposed design considers a practical mean squared error (MSE) constraint between the desired and the achieved beampatterns constructed for identifying radar targets (RTs). To achieve optimal performance, we formulate an optimization problem relying on sum spectral efficiency (SE) maximization of the communication users (CUs), while satisfying certain radar beampattern similarity (RBPS), total transmit power, and constant modulus constraints, where the latter are attributed to the hybrid mmWave MIMO architecture. Since the aforementioned problem is non-convex and intractable, a sequential approach is proposed wherein the TPCs are designed first, followed by the RCs. To deal with the non-convex MSE and constant modulus constraints in the TPC design problem, we propose a majorization and minimization (MM) based Riemannian conjugate gradient (RCG) method, which restricts the tolerable MSE of the beampattern to within a predefined limit. Moreover, the least squares and the zero-forcing methods are adopted for maximizing the sum-SE and for mitigating the multiuser interference (MUI), respectively. Furthermore, to design the RC at each CU, we propose a linear MM-based blind combiner (LMBC) scheme that does not rely on the knowledge of the TPC at the CUs and has a low complexity. To achieve user fairness, we further extend the proposed sequential approach for maximizing the geometric mean (GM) of the CU's rate. Simulation results are presented, which show the superior performance of the proposed hybrid TPC and RC in comparison to the state-of-the-art designs in the mmWave MIMO ISAC systems under consideration.},

keywords = {Copper, Hybrid power systems, Integrated sensing and communication, Interference, millimeter wave, Millimeter wave communication, Optimization, Radar, radar beampattern similarity, Radio frequency, Signal to noise ratio, Spectral efficiency},

pubstate = {published},

tppubtype = {article}

}

@article{singh_multi-beam_2025,

title = {Multi-Beam Object-Localization for Millimeter-Wave ISAC-Aided Connected Autonomous Vehicles},

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

url = {https://ieeexplore.ieee.org/document/10677488},

doi = {10.1109/TVT.2024.3451480},

issn = {1939-9359},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Vehicular Technology},

volume = {74},

number = {1},

pages = {1725–1729},

abstract = {Millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems capable of integrated sensing and communication (ISAC) constitute a key technology for connected autonomous vehicles (CAVs). In this context, we propose a multi-beam object-localization (MBOL) model for enhancing the sensing beampattern (SBP) gain of adjacent objects in CAV scenarios. Given the ultra-narrow beams of mmWave MIMO systems, a single pencil beam is unsuitable for closely located objects, which tend to require multiple beams. Hence, we formulate the SBP gain maximization problem, considering also the constraints on the signal-to-interference and noise ratio (SINR) of the communication users (CUs), on the transmit power, and the constant modulus of the phase-shifters in the mmWave hybrid transceiver. To solve this non-convex problem, we propose a penalty-based triple alternating optimization algorithm to design the hybrid beamformer. Finally, simulation results are provided for demonstrating the efficacy of the proposed model.},

keywords = {connected autonomous vehicles (CAVs), Copper, Integrated sensing and communication, Integrated sensing and communication (ISAC), Interference, millimeter wave, Millimeter wave communication, Optimization, Radio frequency, sensing beampattern (SBP) gain, Signal to noise ratio},

pubstate = {published},

tppubtype = {article}

}

@article{chen_effect_2024,

title = {Effect of Source Signal Traffic on Signal Detection for Ambient Backscatter Communication},

author = {Yunfei Chen and Aziz Altaf Khuwaja and Cheng-Xiang Wang},

url = {https://ieeexplore.ieee.org/document/10572306},

doi = {10.1109/TVT.2024.3419423},

issn = {1939-9359},

year  = {2024},

date = {2024-11-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Vehicular Technology},

volume = {73},

number = {11},

pages = {16790–16804},

abstract = {Ambient backscatter communication (ABC) is a promising method of reducing energy consumption in wireless communications. Previous works on signal detection for ABC often assume that the ambient source signal is always present during backscattering. However, this may not be the case due to the random traffic of the ambient source and the asynchronous operation between source and tag. In this work, the effect of source signal traffic on the detection performance is studied for ABC systems. Firstly, the performances of the existing detectors are analyzed in the presence of source traffic. Both random arrival and random departure are considered. The exponential and uniform traffic models are used. Their bit error rate expressions are obtained by taking advantage of different approximation methods. Then, new detectors taking into account the random traffic models are derived by weighting the samples exponentially or linearly with their arrival times. Numerical results show that the random source traffic could cause large performance degradation to the existing detectors, leading to error floors at small signal-to-noise ratios (SNRs). In particular, the exponential departure causes the largest performance degradation, followed by the uniform arrival and departure. Numerical results also show that the new detectors could have significant performance gains over the conventional detectors in the presence of source traffic. In some case, the gain could be over 3 dB in SNR, and it increases with the sample size and traffic parameters. However, this gain could become negative for large SNRs and small sample sizes due to the use of heuristic detection thresholds.},

keywords = {Ambient backscatter communications, Backscatter, Indexes, Numerical models, Phase shift keying, Signal detection, Signal to noise ratio, signal traffic},

pubstate = {published},

tppubtype = {article}

}

@article{huang_sidelobe_2024,

title = {Sidelobe Suppression Method with Improved CLEAN Algorithm for Pulse Compression OTDR},

author = {Yi Huang and Xiaofeng Chen and Wei Shen and Ziyi Wei and Chengyong Hu and Chuanlu Deng and Lisen Wang and Qi Zhang and Wei Chen and Xiaobei Zhang and Lin Chen and Wei Jin and Jianming Tang and Tingyun Wang},

url = {https://ieeexplore.ieee.org/document/10685474},

doi = {10.1109/LPT.2024.3465501},

issn = {1941-0174},

year  = {2024},

date = {2024-11-01},

urldate = {2025-10-08},

journal = {IEEE Photonics Technology Letters},

volume = {36},

number = {22},

pages = {1321–1324},

abstract = {Although pulse compression optical time domain reflectometry (PC-OTDR) exhibits high performance in spatial resolution and dynamic range, it inevitably introduces auto-correlation sidelobes, potentially impacting measurement accuracy. In this letter, an improved CLEAN algorithm is proposed to efficiently suppress sidelobes and enhance the peak-to-sidelobe ratio (PSLR) of signals in PC-OTDR. The proposed method introduces an adaptive step factor instead of the traditional fixed factor to reduce the number of iterations. Compared to the traditional method, the proposed method achieves a 2.87 dB improvement of PSLR from a 10 km sensing fiber. In addition, the computation time cost is significantly reduced, which is 1.92 s less than that of the traditional CLEAN algorithm.},

keywords = {CLEAN algorithm, Encoding, Filtering, Optical fibers, Optical filters, Perturbation methods, phase coding, Pulse compression optical time domain reflectometry (PC-OTDR), sidelobe suppression, Signal to noise ratio, Spatial resolution},

pubstate = {published},

tppubtype = {article}

}

@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}

}