1.
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.
2.
Hawkins, Hugo; Xu, Chao; Yang, Lie-Liang; Hanzo, Lajos
CDMA/OTFS Sensing Outperforms Pure OTFS at the Same Communication Throughput Journal Article
In: IEEE Open Journal of Vehicular Technology, vol. 6, pp. 502–519, 2025, ISSN: 2644-1330.
Abstract | Links | BibTeX | Tags: Channel estimation, Code Division Multiple Access (CDMA), Codes, Complexity theory, Delays, Detectors, Integrated sensing and communication, Integrated sensing and communication (ISAC), Multiaccess communication, orthogonal time frequency space (OTFS), sequence spreading, Symbols, Transforms, Uplink
@article{hawkins_cdmaotfs_2025,
title = {CDMA/OTFS Sensing Outperforms Pure OTFS at the Same Communication Throughput},
author = {Hugo Hawkins and Chao Xu and Lie-Liang Yang and Lajos Hanzo},
url = {https://ieeexplore.ieee.org/document/10849597},
doi = {10.1109/OJVT.2025.3532848},
issn = {2644-1330},
year = {2025},
date = {2025-01-01},
urldate = {2025-10-08},
journal = {IEEE Open Journal of Vehicular Technology},
volume = {6},
pages = {502–519},
abstract = {There is a dearth of publications on the subject of spreading-aided Orthogonal Time Frequency Space (OTFS) solutions, especially for Integrated Sensing and Communication (ISAC), even though Code Division Multiple Access (CDMA) assisted multi-user OTFS (CDMA/OTFS) exhibits tangible benefits. Hence, this work characterises both the communication Bit Error Rate (BER) and sensing Root Mean Square Error (RMSE) performance of Code Division Multiple Access OTFS (CDMA/OTFS), and contrasts them to pure OTFS. Three CDMA/OTFS configurations are considered: Delay Code Division Multiple Access OTFS (Dl-CDMA/OTFS), Doppler Code Division Multiple Access OTFS (Dp-CDMA/OTFS), and Delay Doppler Code Division Multiple Access OTFS (DD-CDMA/OTFS), which harness direct sequence spreading along the delay axis, Doppler axis, and DD domains respectively. For each configuration, the performance of Gold, Hadamard, and Zadoff-Chu sequences is investigated. The results demonstrate that Zadoff-Chu Dl-CDMA/OTFS and DD-CDMA/OTFS consistently outperform pure OTFS sensing, whilst maintaining a similar communication performance at the same throughput. The extra modulation complexity of CDMA/OTFS is similar to that of other OTFS multi-user methodologies, but the demodulation complexity of CDMA/OTFS is lower than that of some other OTFS multi-user methodologies. CDMA/OTFS sensing can also consistently outperform OTFS sensing whilst not requiring any additional complexity for target parameter estimation. Therefore, CDMA/OTFS is an appealing candidate for implementing multi-user OTFS ISAC.},
keywords = {Channel estimation, Code Division Multiple Access (CDMA), Codes, Complexity theory, Delays, Detectors, Integrated sensing and communication, Integrated sensing and communication (ISAC), Multiaccess communication, orthogonal time frequency space (OTFS), sequence spreading, Symbols, Transforms, Uplink},
pubstate = {published},
tppubtype = {article}
}
There is a dearth of publications on the subject of spreading-aided Orthogonal Time Frequency Space (OTFS) solutions, especially for Integrated Sensing and Communication (ISAC), even though Code Division Multiple Access (CDMA) assisted multi-user OTFS (CDMA/OTFS) exhibits tangible benefits. Hence, this work characterises both the communication Bit Error Rate (BER) and sensing Root Mean Square Error (RMSE) performance of Code Division Multiple Access OTFS (CDMA/OTFS), and contrasts them to pure OTFS. Three CDMA/OTFS configurations are considered: Delay Code Division Multiple Access OTFS (Dl-CDMA/OTFS), Doppler Code Division Multiple Access OTFS (Dp-CDMA/OTFS), and Delay Doppler Code Division Multiple Access OTFS (DD-CDMA/OTFS), which harness direct sequence spreading along the delay axis, Doppler axis, and DD domains respectively. For each configuration, the performance of Gold, Hadamard, and Zadoff-Chu sequences is investigated. The results demonstrate that Zadoff-Chu Dl-CDMA/OTFS and DD-CDMA/OTFS consistently outperform pure OTFS sensing, whilst maintaining a similar communication performance at the same throughput. The extra modulation complexity of CDMA/OTFS is similar to that of other OTFS multi-user methodologies, but the demodulation complexity of CDMA/OTFS is lower than that of some other OTFS multi-user methodologies. CDMA/OTFS sensing can also consistently outperform OTFS sensing whilst not requiring any additional complexity for target parameter estimation. Therefore, CDMA/OTFS is an appealing candidate for implementing multi-user OTFS ISAC.