IEEE Open Journal of the Communications Society最新文献

{"title":"Long-Term Secrecy Throughput and Fairness Tradeoff for Wireless Powered Secure IoT Networks","authors":"Lei Zheng;Xiaolong Lan;Juanjuan Ren;Yong Liu;Qingchun Chen","doi":"10.1109/OJCOMS.2025.3526286","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3526286","url":null,"abstract":"This paper focuses on the interplay between secrecy throughput and fairness for a wireless powered secure Internet of Things (IoT) network, where IoT devices harvest energy from an access point (AP), and securely upload their data to the AP by exploiting physical layer security (PLS) technology. To achieve it, a multi-objective stochastic optimization problem is formulated to simultaneously maximize long-term averaged secrecy sum-rate and minimum rate (min-rate) of devices, subject to devices’ energy sustainability and AP’s energy budget constraints, where energy beamforming, power allocation, and time scheduling policies are jointly optimized. In order to ensure network fairness, we construct a virtual fairness queue for each device to characterize the gap between its averaged secrecy rate and the expected secrecy min-rate, and incorporate its status into the transmission design. Due to the non-convexity of original problem and massive number of optimization variables, Lyapunov optimization framework is leveraged to decompose it into multiple online resource allocation problems, each of which is dependent on the system status of current slot. Accordingly, a fairness-energy-aware secure transmission (FEaST) scheme is proposed, where the closed-form energy beamforming, power allocation and time scheduling are derived according to the instantaneous status of fairness queue, energy consumption and wireless channels. Finally, simulation results validate that the gain of secrecy min-rate is over 84% and 123% under linear and nonlinear energy harvesting models respectively, and that of the weighted sum of secrecy sum-rate and min-rate is over 30% and 50% respectively, when compared with fixed scheduling scheme. Moreover, the inherent tradeoff between long-term secrecy sum-rate and min-rate is unveiled.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"986-1003"},"PeriodicalIF":6.3,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Free Space Optical Mesh Networks: A Survey","authors":"Ferdaous Tarhouni;Ruibo Wang;Mohamed-Slim Alouini","doi":"10.1109/OJCOMS.2025.3525468","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525468","url":null,"abstract":"Free space optical (FSO) communication, known for its high data rates and immunity to electromagnetic interference, encounters challenges such as weather dependency, misalignment issues, and line-of-sight (LoS) requirements. Mesh networks, with their inherent scalability and redundancy, can mitigate these limitations by providing multiple pathways for data transmission and robust network configurations. This paper investigates the key motivations for integrating FSO transmission within mesh structures. We review existing literature on both FSO and hybrid RF/FSO mesh networks, discussing technical studies aimed at maximizing network performance and minimizing delay and cost deployments. We equally explore some relaying approaches in FSO mesh networks and shed light on the advantages of some relaying solutions, mainly, flying platforms and reconfigurable intelligent surfaces (RIS). We discuss the use of FSO in satellite communication to establish two types of mesh networks: inter-satellite and satellite-aerial/ground mesh networks. Finally, some open issues and future research directions are explored.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"642-655"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10821003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Efficiency and Fairness in Large Scale Systems Using RSMA","authors":"Usman Ali;Luca De Nardis;Maria-Gabriella Di Benedetto","doi":"10.1109/OJCOMS.2025.3525954","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525954","url":null,"abstract":"The performance of Space Division Multiple Access (SDMA) in Multiuser Multiple Input Single Output (MU-MISO) systems degrades significantly under imperfect Channel State Information at the Transmitter (CSIT). To address this, Rate-Splitting Multiple Access (RSMA) has been shown to outperform SDMA in scenarios where CSIT is imperfect, particularly in underloaded scenarios, where the number of potential users is lower than the number of antennas. This paper investigates the use of RSMA in a large-scale, overloaded system, where the number of users exceeds the number of antennas at the base station. We propose a novel approximation of the RSMA sum rate under limited feedback conditions and develop an optimal power allocation strategy that dynamically switches between RSMA and SDMA to maximize energy efficiency and system performance. Additionally, a robust Minimum Mean Square Error (MMSE) based precoding method is introduced to mitigate the effects of imperfect CSIT in private streams of RSMA. Numerical simulations validate our analytical derivations and show that RSMA offers superior performance over SDMA in large user regimes with low feedback loads, providing significant performance gains in realistic network conditions. These findings offer new insights into the design of energy-efficient and scalable downlink communication systems for future wireless networks.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"611-628"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10824841","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resource Scheduling in MU-MIMO and NOMA Enabled Integrated Access and Backhaul Networks","authors":"Chuan-Wei Cho;Meng-Shiuan Pan","doi":"10.1109/OJCOMS.2025.3525506","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525506","url":null,"abstract":"The integrated access and backhaul (IAB) architecture utilizes wireless backhaul to facilitate the expansion of fifth-generation (5G) New Radio (NR) networks. In an IAB network, intermediate base stations (or say IAB nodes) can be connected in a multi-hop fashion. However, optimizing resource scheduling in such a network remains a critical challenge. In this work, we present a novel method that integrates multi-user multiple-input and multiple-output (MU-MIMO) and non-orthogonal multiple access (NOMA) technologies into IAB networks. The designed two-phase algorithm has the following features: 1) support for multi-path routing and efficient resource utilization through the combined use of MU-MIMO and NOMA, 2) a novel route decision phase that selects optimal paths by considering load balancing among IAB nodes, and 3) a dynamic link scheduling phase that allocates transmission power and schedules links to maximize network capacity. Simulation results demonstrate that the proposed solution achieves significant improvements in throughput, fairness, and latency compared to existing methods.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"551-559"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820963","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of Stacked Intelligent Metasurfaces With Reconfigurable Amplitude and Phase for Multiuser Downlink Beamforming","authors":"Donatella Darsena;Francesco Verde;Ivan Iudice;Vincenzo Galdi","doi":"10.1109/OJCOMS.2025.3526126","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3526126","url":null,"abstract":"A novel technology based on stacked intelligent metasurfaces (SIM) has recently emerged. This platform involves cascading multiple metasurfaces, each acting as a digitally programmable physical layer within a diffractive neural network. SIM enable the implementation of signal-processing transformations directly in the electromagnetic wave domain, eliminating the need for expensive, high-precision, and power-intensive digital platforms. However, existing studies employing SIM in wireless communication applications rely solely on nearly passive structures that control only the phase of the meta-atoms in each layer. In this study, we propose a SIM-aided downlink multiuser transmission scheme, where the SIM at the base station (BS) end is designed by combining nearly passive layers with phase-only reconfiguration capabilities and active layers integrated with amplifier chips to enable amplitude control. Our optimal design aims at maximizing the sum rate for the best group of users by jointly optimizing the transmit power allocation at the BS and the wave-based beamforming at the SIM. In addition to the standard sum-power constraint at the BS, our optimization framework includes two additional constraints: (i) a per-stream power preserving constraint to prevent propagation losses across the SIM, and (ii) an amplitude constraint to account for power limitations for each active layer. To further reduce the complexity of the optimal beamforming solution, we explore a simple yet suboptimal zero-forcing (ZF) beamforming design, where the wave-based transformation implemented by the SIM is selected to eliminate interference among user streams. Finally, extensive Monte Carlo simulations demonstrate that incorporating both nearly passive and active layers within the SIM significantly enhances capacity compared to previously reported phase-only coding SIM. Additionally, the numerical results reveal that low-complexity ZF beamforming approaches optimality in terms of maximum sum rate even for a relatively small number of users.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"531-550"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10824842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Mobile Crowd Sensing Model for Remote Detection of Flying UAVs","authors":"Ashfaq Ahmed;Ruba Alkadi;Kais Belwafi;Mohammad Atrouz;Abdulhadi Shoufan","doi":"10.1109/OJCOMS.2025.3525483","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3525483","url":null,"abstract":"Conformance monitoring is crucial for ensuring the safe operation of uncrewed aerial vehicles (UAVs). It aims to alert relevant parties to any deviations from authorized flight plans. The European Union Aviation Safety Agency (EASA) mandates conformance monitoring and suggests integrating it into UAV traffic management (UTM) systems. Although traditional monitoring systems, such as wireless sensor networks, can serve this purpose, the associated expenses for installation and maintenance make them impractical for large-scale implementations. To tackle this challenge, we propose a monitoring system that capitalizes on UAV remote identification (RID) technology and mobile crowd sensing. RID is becoming a global regulatory requirement. It enables ground observers to identify drones using standard mobile devices. Our solution collects RID data by gathering reports from these observers to assess UAV operations in real-time. A significant component of this approach is determining the optimal number of reports that should be considered to allow reliable and quick evaluation. While processing more reports can enhance the evaluation accuracy, it increases the computational demands and may compromise the system’s real-time performance. Moreover, in a reward-based system, processing more reports incurs higher costs. Therefore, our system uses a mechanism that adjusts the number of received and processed reports based on airspace conditions and the crowd density in the area of interest. In addition, our approach incorporates signal quality metrics - path loss, shadowing, and received signal strength (RSS) - along with distance considerations in the activation process of ground observers for RID message forwarding. This comprehensive consideration of both signal integrity and spatial proximity significantly improves detection and monitoring precision of the UAVs. We validated the proposed model through Monte Carlo simulations. Results indicate that, compared to a naive model, our approach outperforms in terms of received RIDs, paid rewards, and real-time performance.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"1103-1128"},"PeriodicalIF":6.3,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10820970","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PRIDA-ME: A Privacy-Preserving, Interoperable and Decentralized Authentication Scheme for Metaverse Environment","authors":"Mehmood Ul Hassan;Yawar Abbas Bangash;Waseem Iqbal;Abdellah Chehri;Javed Iqbal","doi":"10.1109/OJCOMS.2024.3523518","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3523518","url":null,"abstract":"The metaverse is a new virtual world that has the potential to significantly impact our interactions with digital content and with each other. It is a shared virtual environment where users can seamlessly and with immersive experiences create, interact, and enjoy digital assets. Nevertheless, the metaverse also poses fundamental challenges, particularly about security and privacy concerns, that require careful consideration. One of the most daunting aspects of securing the metaverse is authentication. Several solutions have been proposed, including deployment of blockchain technology and smart contracts, to address these authentication challenges. While these methods provide a secure and tamper-proof authentication mechanism, they fail to meet certain critical security and privacy requirements like interoperability and decentralization. This research proposes an enhanced privacy-preserving authentication scheme based on blockchain, elliptic curve cryptography, biohashing, and a physical unclonable function that guards against various attacks. The proposed scheme does not rely on a single central authority and consists of various phases, including user and avatar authentication, password change, and avatar generation phases. The proposed scheme underwent security assessment using the Burrows Abadi Needham (BAN) logic, ProVerif tool, and Scyther tool. The results demonstrate that it provides a better level of security against a wide range of attack vectors. The proposed scheme offers a swift and efficient authentication mechanism that adheres to the requirements of the metaverse environment, such as interoperability, decentralization, and privacy protection, and requires less computation cost as compared to state-of-the-art schemes.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"493-515"},"PeriodicalIF":6.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10819498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Concept Drift Aware Wireless Key Generation in Dynamic LiFi Networks","authors":"Elmahedi Mahalal;Eslam Hasan;Muhammad Ismail;Zi-Yang Wu;Mostafa M. Fouda;Zubair Md Fadlullah;Nei Kato","doi":"10.1109/OJCOMS.2024.3524497","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3524497","url":null,"abstract":"This paper studies the generation of cryptographic keys from wireless channels in light-fidelity (LiFi) networks. Unlike existing studies, we account for several practical considerations (a) realistic indoor multi-user mobility scenarios, (b) non-ideal channel reciprocity given the unique characteristics of the downlink visible light (VL) and uplink infrared (IR) channels, (c) different room occupancy levels, (d) different room layouts, and (e) different receivers’ field-of-view (FoV). Since general channel models in dynamic LiFi networks are inaccurate, we propose a novel deep learning-based framework to generate secret keys with minimal key disagreement rate (KDR) and maximal key generation rate (KGR). However, we find that wireless channels in LiFi networks exhibit different statistical behaviors under various conditions, leading to concept drift in the deep learning model. As a result, key generation suffers from (a) a deterioration in KDR and KGR up to 29% and 38%, respectively, and (b) failing the NIST randomness test. To enable a concept drift aware framework, we propose an adaptive learning strategy using the similarity of channel probability density functions and the mix-of-experts ensemble method. Results show our adaptive learning strategy can achieve stable performance that passes the NIST randomness test and achieves 8% KDR and 89 bits/s KGR for a case of study with 60° FoV.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"742-758"},"PeriodicalIF":6.3,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818749","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Iterative Syndrome-Based Deep Neural Network Decoding","authors":"Dmitry Artemasov;Kirill Andreev;Pavel Rybin;Alexey Frolov","doi":"10.1109/OJCOMS.2024.3524429","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3524429","url":null,"abstract":"While the application of deep neural networks (DNNs) for channel decoding is a well-researched topic, most studies focus on hard output decoding, potentially restricting the practical application of such decoders in real communication systems. Modern receivers require iterative decoders, a pivotal criterion for which is the ability to produce soft output. In this paper, we focus on this property. We begin by modifying the syndrome-based DNN-decoding approach proposed by Bennatan et al. (2018). The DNN model is trained to provide soft output and replicate the maximum a posteriori probability decoder. To assess the quality of the proposed decoder’s soft output, we examine the iterative decoding method, specifically the turbo product code (TPC) with extended BCH (eBCH) codes as its component codes. A sequential training procedure for optimizing the behavior of component decoders is utilized. We illustrate that the described approach achieves exceptional performance results and is applicable for iterative codes with larger code lengths <inline-formula> <tex-math>$[n=4096, k=2025]$ </tex-math></inline-formula>, compared to state-of-the-art DNN-based methods. Finally, we address the issues of computational complexity and memory requirements of DNN-based decoding by analyzing the model’s compression limits through pruning and matrix decomposition methods.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"629-641"},"PeriodicalIF":6.3,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10818780","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Throughput Adaptive Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning","authors":"Mostafa Naseri;Eli De Poorter;Ingrid Moerman;H. Vincent Poor;Adnan Shahid","doi":"10.1109/OJCOMS.2024.3523797","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3523797","url":null,"abstract":"Co-channel interference cancellation (CCI) is the process used to reduce interference from other signals using the same frequency channel, thereby enhancing the performance of wireless communication systems. An improvement to this approach is adaptive CCI, which reduces interference without relying on prior knowledge of the interfering signal characteristics. Recent work suggested using machine learning (ML) models for this purpose, but high-throughput ML solutions are still lacking, especially for edge devices with limited resources. This work explores the adaptation of U-Net Convolutional Neural Network models for high-throughput adaptive source separation. Our approach is established on architectural modifications, notably through quantization and the incorporation of depthwise separable convolution, to achieve a balance between computational efficiency and performance. Our results demonstrate that the proposed models achieve superior MSE scores when removing unknown interference sources from the signals while maintaining significantly lower computational complexity compared to baseline models. One of our proposed models is deeper and fully convolutional, while the other is shallower with a convolutional structure incorporating an LSTM. Depthwise separable convolution and quantization further reduce the memory footprint and computational demands, albeit with some performance tradeoffs. Specifically, applying depthwise separable convolutions to the model with the LSTM results in only a 0.72% degradation in MSE score while reducing MACs by 58.66%. For the fully convolutional model, we observe a 0.63% improvement in MSE score with even 61.10% fewer MACs. Additionally, the models exhibit excellent scalability on GPUs, with the fully convolutional model achieving the highest symbol rates (up to 800<inline-formula> <tex-math>$times$ </tex-math></inline-formula>103 symbol per second) at larger batch sizes. Overall, our findings underscore the feasibility of using optimized machine-learning models for interference cancellation in devices with limited resources.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"656-670"},"PeriodicalIF":6.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}