@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{chen_otfs-mdma_2025,

title = {OTFS-MDMA: An Elastic Multi-Domain Resource Utilization Mechanism for High Mobility Scenarios},

author = {Jie Chen and Xianbin Wang and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10845880/footnotes},

doi = {10.1109/JSAC.2025.3531568},

issn = {1558-0008},

year  = {2025},

date = {2025-04-01},

urldate = {2025-10-08},

journal = {IEEE Journal on Selected Areas in Communications},

volume = {43},

number = {4},

pages = {1405–1420},

abstract = {By harnessing the delay-Doppler (DD) resource domain, orthogonal time-frequency space (OTFS) substantially improves the communication performance under high-mobility scenarios by maintaining quasi-time-invariant channel characteristics. However, conventional multiple access (MA) techniques fail to efficiently support OTFS in the face of diverse communication requirements. Recently, multi-dimensional MA (MDMA) has emerged as a flexible channel access technique by elastically exploiting multi-domain resources for tailored service provision. Therefore, we conceive an elastic multi-domain resource utilization mechanism for a novel multi-user OTFS-MDMA system by leveraging user-specific channel characteristics across the DD, power, and spatial resource domains. Specifically, we divide all DD resource bins into separate subregions called DD resource slots (RSs), each of which supports a fraction of users, thus reducing the multi-user interference. Then, the most suitable MA, including orthogonal, non-orthogonal, or spatial division MA (OMA/ NOMA/ SDMA), will be selected with each RS based on the interference levels in the power and spatial domains, thus enhancing the spectrum efficiency. Then, we jointly optimize the user assignment, MA scheme selection, and power allocation in all DD RSs to maximize the weighted sum-rate subject to their minimum rate and various practical constraints. Since this results in a non-convex problem, we develop a dynamic programming and monotonic optimization (DPMO) method to find the globally optimal solution in the special case of disregarding rate constraints. Subsequently, we apply a low-complexity algorithm to find sub-optimal solutions in general cases.},

keywords = {delay-Doppler, Delays, Doppler effect, dynamic programming, Modulation, monotonic optimization, multi-dimensional multiple access (MDMA), Multiaccess communication, NOMA, OFDM, Optimization, orthogonal time frequency space (OTFS), Resource management, Symbols, Time-frequency analysis},

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{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{hong_precoded_2025,

title = {Precoded Faster-Than-Nyquist Signaling Using Optimal Power Allocation for OTFS},

author = {Zekun Hong and Shinya Sugiura and Chao Xu and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/document/10742918},

doi = {10.1109/LWC.2024.3491777},

issn = {2162-2345},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Wireless Communications Letters},

volume = {14},

number = {1},

pages = {173–177},

abstract = {A precoded orthogonal time frequency space (OTFS) modulation scheme relying on faster-than-Nyquist (FTN) transmission over doubly selective fading channels is proposed, which enhances the spectral efficiency and improves the Doppler resilience. We derive the input-output relationship of the FTN signaling in the delay-Doppler domain. Eigenvalue decomposition (EVD) is used for eliminating both the effects of inter-symbol interference and correlated additive noise encountered in the delay-Doppler domain to enable efficient symbol-by-symbol demodulation. Furthermore, the power allocation coefficients of individual frames are optimized for maximizing the mutual information under the constraint of the derived total transmit power. Our performance results demonstrate that the proposed FTN-based OTFS scheme can enhance the information rate while achieving a comparable BER performance to that of its conventional Nyquist-based OTFS counterpart that employs the same root-raised-cosine shaping filter.},

keywords = {Bandwidth, Delays, Doppler shift, doubly selective fading, Faster-than-Nyquist signaling, information rate, Information rates, Interference, mutual information, OTFS, Precoding, Pulse shaping methods, Receivers, Resource management, Symbols, Time-frequency analysis},

pubstate = {published},

tppubtype = {article}

}

@article{goay_range_2025,

title = {Range Maximization by Optimizing Tag-to-Tag Cooperative Backscatter Communication},

author = {Amus Chee Yuen Goay and Deepak Mishra and Michail Matthaiou and Aruna Seneviratne},

url = {https://ieeexplore.ieee.org/document/11008574},

doi = {10.1109/TGCN.2025.3570568},

issn = {2473-2400},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Green Communications and Networking},

pages = {1–1},

abstract = {Backscatter communication (BackCom) is a wireless technology that transmits information wirelessly by modulating the reflection of an incident signal, offering the advantages of low power consumption and low cost. This paper introduces a novel cooperative timing protocol in a two-tag BackCom network, where a single reader communicates with two passive backscatter tags using a cooperative scheme. These tags encode their information by modulating the backscattered signal and then transmitting it back to the reader. In the considered tag-to-tag cooperative scheme, the tag closer to the reader assists the farther tag in relaying its information, effectively mitigating the doubly near-far problem commonly experienced in BackCom systems. The primary objective is to maximize the transmission range of the farther tag by jointly optimizing the proposed time allocation scheme and reflection coefficients while meeting the spectral efficiency and energy threshold constraints for the quality of service and sustainability requirements. This article formulates a non-convex optimization problem and proposes a solution methodology that efficiently approximates the optimized solution with low complexity. Numerical simulations are presented to analyze the effects of varying energy and spectral efficiency requirements on the maximized transmission range. The results demonstrate that the proposed tag-to-tag cooperative BackCom framework provides a significant performance improvement, with an average range gain of over 30% compared to the non-cooperative scheme.},

keywords = {Backscatter, Backscatter communication, cooperation, green communication, Internet of Things, Protocols, Quality of service, range maximization, Reflection coefficient, Relays, Resource management, tag-to-tag network, Throughput, time allocation, Wireless communication, Wireless sensor networks},

pubstate = {published},

tppubtype = {article}

}