@article{krishnamoorthy_optical_2025,

title = {Optical Wireless Communications: Enabling the Next-Generation Network of Networks},

author = {Aravindh Krishnamoorthy and Hossein Safi and Othman Younus and Hossein Kazemi and Isaac N. O. Osahon and Mingqing Liu and Yi Liu and Sina Babadi and Rizwana Ahmad and Asim Ihsan and Behnaz Majlesein and Yifan Huang and Johannes Herrnsdorf and Sujan Rajbhandari and Jonathan J. D. McKendry and Iman Tavakkolnia and Humeyra Caglayan and Henning Helmers and Graham Turnbull and Ifor D. W. Samuel and Martin D. Dawson and Robert Schober and Harald Haas},

url = {https://ieeexplore.ieee.org/document/10974735},

doi = {10.1109/MVT.2025.3555366},

issn = {1556-6080},

year  = {2025},

date = {2025-06-01},

urldate = {2025-10-08},

journal = {IEEE Vehicular Technology Magazine},

volume = {20},

number = {2},

pages = {20–39},

abstract = {Optical wireless communication (OWC) is a promising technology anticipated to play a key role in the next-generation network of networks (NoNs), especially as a complementary technology to traditional radio-frequency (RF) communications, for enhancing networking capabilities beyond conventional terrestrial networks. OWC is already a mature technology with diverse usage scenarios and can enable integrated applications via wireless access and backhaul networks, dynamic drone and satellite networks, underwater networks, inter- and intrasystem interconnecting networks, and vehicular communication networks. Furthermore, novel and emerging technological opportunities such as photovoltaic cells, orbital angular momentum-based modulation, optical reconfigurable intelligent surfaces, organic light-emitting and photo diodes, and recent advances in ultraviolet communications can help to enhance future OWC capabilities even further. Moreover, OWC networks can also support value-added services such as enhanced positioning and gesture recognition. Hence, OWC provides unique functionalities that can play a crucial role in building convergent and resilient future NoNs alongside RF and optical fiber technologies.},

keywords = {Bandwidth, Fiber optics, Laser beams, Optical fiber communication, Optical fibers, Optical transmitters, Terahertz communications, Vertical cavity surface emitting lasers, Wireless communication, Wireless networks},

pubstate = {published},

tppubtype = {article}

}

@article{mohammadi_ten_2025,

title = {Ten Years of Research Advances in Full-Duplex Massive MIMO},

author = {Mohammadali Mohammadi and Zahra Mobini and Hien Quoc Ngo and Michail Matthaiou},

url = {https://ieeexplore.ieee.org/document/10684260},

doi = {10.1109/TCOMM.2024.3464414},

issn = {1558-0857},

year  = {2025},

date = {2025-03-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

volume = {73},

number = {3},

pages = {1756–1786},

abstract = {We present an overview of ongoing research endeavors focused on in-band full-duplex (IBFD) massive multiple-input multiple-output (MIMO) systems and their applications. In response to the unprecedented demands for mobile traffic in concurrent and upcoming wireless networks, a paradigm shift from conventional cellular networks to distributed communication systems becomes imperative. Cell-free massive MIMO (CF-mMIMO) emerges as a practical and scalable implementation of distributed/network MIMO systems, serving as a crucial physical layer technology for the advancement of next-generation wireless networks. This architecture inherits benefits from co-located massive MIMO and distributed systems and provides the flexibility for integration with the IBFD technology. We delineate the evolutionary trajectory of cellular networks, transitioning from conventional half-duplex multi-user MIMO networks to IBFD CF-mMIMO. The discussion extends further to the emerging paradigm of network-assisted IBFD CF-mMIMO (NAFD CF-mMIMO), serving as an energy-efficient prototype for asymmetric uplink and downlink communication services. This novel approach finds applications in dual-functionality scenarios, including simultaneous wireless power and information transmission, wireless surveillance, and integrated sensing and communications. We highlight various current use case applications, discuss open challenges, and outline future research directions aimed at fully realizing the potential of NAFD CF-mMIMO systems to meet the evolving demands of future wireless networks.},

keywords = {Cell-free massive multiple-input multiple-output (CF-mMIMO), energy efficiency (EE), Full-duplex system, in-band full-duplex (IBFD), Interference cancellation, Massive MIMO, network-assisted IBFD CF-mMIMO (NAFD CF-mMIMO), self-interference (SI), spectral efficiency (SE), Surveys, Transceivers, Wireless networks, Wireless sensor networks},

pubstate = {published},

tppubtype = {article}

}

@article{wang_short-block_2025,

title = {Short-Block Polar-Coded Reverse and Direct Reconciliation in CV-QKD},

author = {Dingzhao Wang and Xin Liu and Chao Xu and Soon Xin Ng and Lajos Hanzo},

url = {https://ieeexplore.ieee.org/abstract/document/11087626},

doi = {10.1109/OJVT.2025.3591417},

issn = {2644-1330},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Open Journal of Vehicular Technology},

volume = {6},

pages = {2195–2209},

abstract = {Continuous-variable quantum key distribution (CV-QKD) is a promising technique of supporting quantum-safe wireless networks in the emerging 6 G era, mapping quantum information onto the amplitude or phase of electromagnetic waves. However, conventional CV-QKD reconciliation methods often assume ideal classical side-information channels, which is an unrealistic scenario in practical deployments. To address this critical challenge, we propose a novel protection scheme integrating Polar and low-density parity-check (LDPC) codes. Specifically, Polar codes safeguard quantum transmissions due to their superior performance for short block lengths, while LDPC codes robustly protect the classical side information exchanged over auxiliary classical channels. We further enhance the CV-QKD performance by harnessing a soft-decision Polar decoding method combined with protocols specifically tailored for reverse reconciliation (RR) and direct reconciliation (DR). In the RR scheme, conceived decoding complexity is strategically distributed: Polar decoding is performed by Alice, and LDPC decoding by Bob, hence significantly reducing the computational demands compared to traditional schemes where both decoding processes are invoked at a single node. Simulation results validate the effectiveness of our approach, demonstrating that Polar codes consistently outperform LDPC codes in quantum transmission scenarios having short block lengths under 512 bits. These findings emphasize the strong potential of Polar coding-assisted CV-QKD in achieving secure and efficient quantum-safe control information transmissions, paving the way for practical implementation in next-generation wireless networks.},

keywords = {Complexity theory, Continuous-variable quantum key distribution (CV-QKD), Fading channels, Maximum likelihood decoding, multidimensional reconciliation, Parity check codes, polar code, Polar codes, Protection, Protocols, Quantum key distribution, secret key rate, Simulation, Wireless networks},

pubstate = {published},

tppubtype = {article}

}

@article{zheng_over–air_2025,

title = {Over-the-Air Computation Enabled Semi-Asynchronous Wireless Federated Learning},

author = {Zijian Zheng and Yansha Deng and Wenqiang Yi and Hyundong Shin and Arumugam Nallanathan},

url = {https://ieeexplore.ieee.org/document/11048956},

doi = {10.1109/TCOMM.2025.3582727},

issn = {1558-0857},

year  = {2025},

date = {2025-01-01},

urldate = {2025-10-08},

journal = {IEEE Transactions on Communications},

pages = {1–1},

abstract = {The emerging field of federated learning (FL) holds significant promise for advancing edge intelligence while preserving data privacy. However, as FL systems scale or become more heterogeneous, challenges such as spectrum scarcity and the straggler problem arise. To address these issues, this paper proposes SA-AirFed, a semi-asynchronous FL architecture compatible with Over-the-Air Computation (AirComp). We develop an efficient scheduling scheme that meets AirComp’s requirements and analyze the factors affecting convergence under the Lipschitz-Smooth condition. Building on insights from the convergence analysis, we design an adaptive algorithm that mitigates staleness from semi-asynchronous aggregation and noise from AirComp by dynamically adjusting aggregation weights, formulated as a convex quadratic programming problem. Experimental results on MNIST and CIFAR-10 demonstrate that SA-AirFed significantly reduces wall-clock training time while achieving greater robustness compared to baseline models.},

keywords = {aggregation optimization, Atmospheric modeling, Computational modeling, Convergence, Federated learning, Noise, Optimization, over-the-air computation, Semi-asynchronous federated learning, Servers, Synchronization, Training, Wireless networks},

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}

}

@article{chen_federated_2024,

title = {Federated Learning Enabled Link Scheduling in D2D Wireless Networks},

author = {Tianrui Chen and Xinruo Zhang and Minglei You and Gan Zheng and Sangarapillai Lambotharan},

url = {https://ieeexplore.ieee.org/document/10268986},

doi = {10.1109/LWC.2023.3321500},

issn = {2162-2345},

year  = {2024},

date = {2024-01-01},

urldate = {2025-10-08},

journal = {IEEE Wireless Communications Letters},

volume = {13},

number = {1},

pages = {89–92},

abstract = {Centralized machine learning methods for device-to-device (D2D) link scheduling may lead to a computing burden for a central server, transmission latency for decisions, and privacy issues for D2D communications. To mitigate these challenges, a federated learning (FL) based method is proposed to solve the link scheduling problem, where a global model is distributedly trained at local devices, and a server is used for aggregating model parameters instead of training samples. Specially, a more realistic scenario with limited channel state information (CSI) is considered instead of full CSI. Despite a decentralized implementation, simulation results demonstrate that the proposed FL based approach with limited CSI performs close to the conventional optimization algorithm. In addition, the FL based solution achieves almost the same performance as that of the centralized training.},

keywords = {Computational modeling, device-to-device (D2D), Device-to-device communication, Federated learning, link scheduling, Scheduling, Servers, Training, Wireless networks},

pubstate = {published},

tppubtype = {article}

}