IEEE Open Journal of the Communications Society最新文献

{"title":"Generalized Implicit Transmission (GIT)","authors":"Dhanushki Hewawaduge;John P. Fonseka","doi":"10.1109/OJCOMS.2025.3572500","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3572500","url":null,"abstract":"Recently, two implicit transmission techniques, namely, implicit transmission with bit flipping (ITBF) and implicit transmission with collection decoding (ITCD) have been introduced to transmit an independent second coded sequence implicitly while transmitting a first coded sequence explicitly over the channel. In this study, a novel generalized implicit transmission (GIT) technique that can transmit any number of independent implicit sequences implicitly while transmitting a single explicit sequence over the channel is introduced. The GIT technique, its encoding and decoding are explained in detail. It is numerically demonstrated using the LDPC codes employed in the WiFi and 5G standards that GIT with multiple implicit sequences can increase the transmission rate significantly higher than those that can be achieved with a single implicit sequence reported in previous studies.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"4731-4741"},"PeriodicalIF":6.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11010111","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272818","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":"Integrated Communication and RIS-Aided Track-Before-Detect Radar Sensing","authors":"Georgios Mylonopoulos;Luca Venturino;Emanuele Grossi;Stefano Buzzi;Ciro D’Elia","doi":"10.1109/OJCOMS.2025.3572081","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3572081","url":null,"abstract":"This paper investigates an integrated sensing and communication system where the base station serves multiple downlink users, while employing a passive reconfigurable intelligent surface to detect small, noncooperative airborne targets. We propose a method to design the two-way beampattern of the RIS-assisted monostatic radar, which allows controlling the sidelobe levels in the presence of eavesdroppers, jammers, and other scattering objects and avoiding any radar interference to the users. To obtain more favorable system tradeoffs, we exploit the correlation of the target echoes over consecutive scans by resorting to a multi-frame radar detector, which includes a detector, a plot-extractor, and a track-before-detect processor. A numerical analysis is provided to verify the effectiveness of the proposed solutions and to assess the achievable tradeoffs. Our results show that, by increasing the number of scans processed by the radar detector (and therefore its implementation complexity), we can reduce the amount of power dedicated to the radar function while maintaining the same sensing performance (measured in terms of probability of target detection and root mean square error in the estimation of target position); this excess power can be reused to increase the user sum-rate.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"4519-4532"},"PeriodicalIF":6.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11008547","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205881","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":"A Game Theoretical Priority-Aware R2V Task Offloading Framework for Vehicular Fog Networks","authors":"Kinda Khawam;Maurice Khabbaz;Joe Saad","doi":"10.1109/OJCOMS.2025.3553787","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3553787","url":null,"abstract":"Modern vehicles, equipped with advanced digital infrastructure, are transforming from mere transportation units to powerful mobile servers. This trend, coupled with the rise of mobile edge computing (MEC), presents a unique opportunity to leverage vehicles as temporary computing resources. Roadside Units (RSUs) can then offload urgent tasks to passing vehicles, enabling ubiquitous connectivity and low-latency services. However, efficient task offloading remains a challenge. This paper proposes a two-level resource management framework for Priority-Aware RSU-to-Vehicle (PA-R2V) Task Offloading (PA-R2VTO) to address this issue. The first level utilizes a two-stage Stackelberg game to incentivize vehicles within RSU coverage to allocate a portion of their computing resources. The second level focuses on task assignment to participating vehicles. Two computation modes are considered: serial and parallel. Serial computation leverages a Multiple Knapsack Problem (MKP) formulation to prioritize tasks based on deadlines, while parallel computation employs a non-cooperative congestion game model. Both approaches are compared against the traditional Earliest Deadline First (EDF) scheduling algorithm. Extensive simulations validate the framework’s effectiveness, paving the way for a more tangible realization of the Vehicle-as-a-Resource (VaaR) concept.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"2206-2219"},"PeriodicalIF":6.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10937203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783357","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":"Empowering MIMO-FSO Systems: RIS Technology for Enhanced Performance in Challenging Conditions","authors":"Wafaa M. R. Shakir;Jinan Charafeddine","doi":"10.1109/OJCOMS.2025.3553813","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3553813","url":null,"abstract":"This paper presents a novel analytical framework to enhance the performance of reconfigurable intelligent surfaces (RIS)-integrated multiple-input-multiple-output (MIMO) free-space optical (FSO) communication systems. The study addresses critical challenges such as atmospheric turbulence, misalignment, and signal attenuation. It introduces a series-based approach to model the combined effects of Gamma-Gamma turbulence, generalized Rician pointing errors, and RIS size-related constraints. In contrast to previous studies, which often rely on oversimplified or idealized channel models, this framework provides closed-form expressions for the first time for the probability density function and cumulative distribution function of the end-to-end channel specifically designed for RIS-empowered (RIS-E) MIMO-FSO systems. These expressions capture the complex interactions between channel impairments and system parameters, enabling accurate performance evaluation in real-world deployments. The derived formulations provide key performance metrics, including outage probability, average bit error rate, ergodic capacity, data rate, and energy efficiency, for a variety of system configurations. Practical diversity combining techniques such as equal gain combining, maximal ratio combining, and selection combining are rigorously analyzed. In addition, asymptotic analyses at high signal-to-noise ratios offer simplified expressions that provide valuable insights into coding gain, diversity order, and system behavior under extreme conditions. A key contribution of this work is the investigation of the optimization of RIS placement, which improves signal alignment and reduces the outage probability, even under challenging atmospheric conditions. In addition, the study highlights the computational efficiency of the proposed framework through a detailed complexity analysis that confirms its feasibility for practical, large-scale applications. Monte Carlo simulations validate the theoretical findings, demonstrating strong agreement with the analytical results. These results confirm the transformative potential of RIS technology in mitigating turbulence-induced fading and misalignment. This research establishes RIS-E MIMO-FSO systems as a robust, energy-efficient solution for next-generation, high-bandwidth optical networks. Additionally, it provides practical deployment guidelines, ensuring the effective integration of RIS technology into real-world wireless communication infrastructures, thereby advancing the development of resilient and high-performance optical communication systems.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"2616-2641"},"PeriodicalIF":6.3,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10937202","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848849","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":"Meeting Stringent QoS Requirements in AAV-Assisted Networks: Resource Allocation and AAVs Positioning","authors":"Meriem Hammami;Cirine Chaieb;Wessam Ajib;Halima Elbiaze;Roch Glitho","doi":"10.1109/OJCOMS.2025.3553108","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3553108","url":null,"abstract":"Providing quick and reliable emergency communication in situations of natural disasters or unforeseen incidents may be crucial. In such situations, traditional communication infrastructure, such as ground-based wireless base stations, may become temporarily damaged or unavailable to support emergency teleoperations. Considered a promising solution, autonomous aerial vehicles (AAVs) can be deployed as flying base stations or relays to provide fast and reliable communication between physicians and remote robots in both uplink and downlink directions, while meeting strict transmission requirements. This paper addresses the joint optimization problem of AAV positioning and resource allocation in AAV-assisted wireless networks to minimize the number of deployed AAVs, all while satisfying stringent transmission quality demands. The formulated problem is a non-convex mixed-integer programming problem, which we prove to be <inline-formula> <tex-math>$mathcal {NP}$ </tex-math></inline-formula>-hard. We first develop efficient greedy and metaheuristic genetic algorithms. Then, we propose an efficient centralized deep reinforcement learning solution based on the deep deterministic policy gradient (DDPG), where the agent learns optimal AAV positions and resource allocation. Simulation results demonstrate that the greedy solution closely matches the performance of both the genetic and deep reinforcement learning approaches, with a significant reduction in computational complexity. Furthermore, the results highlight the effectiveness of the deep reinforcement learning solution in minimizing the number of AAVs required to fully satisfy the transmission requirements of all users in both uplink and downlink directions.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"2190-2205"},"PeriodicalIF":6.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10935685","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783253","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":"Transfer Probability-Based Job Reallocation Method for Heterogeneous Edge Clouds","authors":"Kohei Ogawa;Sumiko Miyata;Kenji Kanai","doi":"10.1109/OJCOMS.2025.3571924","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3571924","url":null,"abstract":"In mobile edge computing (MEC), efficient job allocation is essential to optimize system performance and reduce reliance on cloud computing. Edge servers, deployed at base stations, must handle user-submitted jobs without overloading, which would otherwise lead to excessive job transfers to the cloud. Current k-means-based server-placement and job-allocation methods primarily minimize communication costs but fail to handle heterogeneous server performance. This oversight results in load imbalances where low-performance servers become overloaded, increasing unnecessary cloud transfers and network congestion. Such methods also do not address k-means’ sensitivity to initialization, which impacts job-distribution efficiency. To overcome these limitations, we propose a joint optimization method for integrating edge-server placement and job allocation with the objective of minimizing transfer probability in heterogeneous MEC environments. The method integrates a k-means++-based initial placement algorithm to reduce initialization sensitivity and dynamic job-reallocation algorithm that adjusts assignments on the basis of transfer probability. Extensive simulations demonstrate that our method reduces job overflow and cloud transfers compared with conventional methods. Real-world millimeter-wave communication experiments also confirm the effectiveness of the proposed method in practical MEC environments.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"4549-4562"},"PeriodicalIF":6.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11007616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205877","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":"A Review of 6G and AI Convergence: Enhancing Communication Networks With Artificial Intelligence","authors":"Yousef Sanjalawe;Salam Fraihat;Salam Al-E’Mari;Mosleh Abualhaj;Sharif Makhadmeh;Emran Alzubi","doi":"10.1109/OJCOMS.2025.3553302","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3553302","url":null,"abstract":"This paper explores the integration of Artificial Intelligence into 6G networks, focusing on optimizing communication, resource allocation, and enhancing security. As communication systems transition from 5G to 6G, Artificial Intelligence’s role in addressing the increasing complexity of network management becomes pivotal. The paper reviews key AI technologies such as machine learning, deep learning, and reinforcement learning, demonstrating their applications in predictive maintenance, traffic management, and energy efficiency optimization. It also highlights how Artificial Intelligence enables intelligent network slicing, spectrum management, and resource allocation through dynamic algorithms. Furthermore, Artificial Intelligence-driven solutions are presented for addressing security concerns in 6G networks, focusing on intrusion detection, anomaly detection, and blockchain-based decentralized security. Challenges such as computational overhead, data privacy, and ethical concerns in implementing Artificial Intelligence in 6G systems are also discussed, along with future directions, including quantum AI and federated learning. This paper provides a comprehensive analysis of how Artificial Intelligence can enhance the capabilities of 6G networks, ensuring improved performance, security, and scalability for future communication technologies.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"2308-2355"},"PeriodicalIF":6.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10935636","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817887","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 and Performance Analysis of UAV-Assisted Maritime-LEO Satellite Communication Networks","authors":"Nilupuli Senadhira;Salman Durrani;Jing Guo;Nan Yang;Xiangyun Zhou","doi":"10.1109/OJCOMS.2025.3571757","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3571757","url":null,"abstract":"Monitoring oceanic conditions via maritime Internet of Things (IoT) is vital to the health of the planet. In this regard, providing wireless connectivity to low-end ships, maritime buoys and beacons at sea, which typically lack the technology needed for direct satellite connections, remains a fundamental challenge given the vast ocean expanse and absence of any coverage from on-shore base stations (BSs). To address this challenge, we consider a uncrewed aerial vehicle (UAV)-assisted maritime low Earth orbit (LEO) satellite communication network to provide coverage for low-end maritime users (MUs), such as buoys in remote ocean regions. In this network, we assume that the MUs are distributed across a finite ocean area outside the coverage of onshore BSs. These MUs transmit data to satellites through a swarm of relay UAVs hovering in a finite aerial region, resulting in two communication phases: (i) MU-to-UAV and (ii) UAV-to-satellite. Leveraging stochastic geometry and UAV-centric analysis (which is different from conventional user-centric analysis) in the uplink, we analyze the location-dependent performance and derive an approximate yet accurate expression for the success probability, a key metric characterizing the overall MU-to-UAV-to-satellite network performance. Our numerical results demonstrate that given a set of satellite constellation parameters (e.g., number of satellites, altitude, and beamwidth), the success probability is governed by the interplay between path loss and interference. These results provide theoretical insights for the deployment and planning of integrated maritime-aerial-satellite networks to extend coverage for low-end MUs in remote ocean regions.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"4667-4688"},"PeriodicalIF":6.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11007596","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255647","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":"A Slicing Model for Transport Networks With Traffic Burst Control and QoS Compliance for Traffic Flows","authors":"Aitor Encinas-Alonso;Carlos M. Lentisco;Ignacio Soto;Luis Bellido;David Fernandez","doi":"10.1109/OJCOMS.2025.3552839","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3552839","url":null,"abstract":"Network slicing has emerged as a key network technology, providing network operators with the means to offer virtual networks to vertical users over a single physical network infrastructure. Recent research has resulted mainly in techniques for managing and deploying network slices, but the implementation of network slices on a real physical transport network infrastructure has received much less attention. Standardization bodies, such as the Internet Engineering Task Force (IETF), have provided some implementation recommendations. Still, there is a lack of mechanisms to implement network slices capable of handling traffic bursts while simultaneously meeting the Quality of Service (QoS) requirements of the traffic flows associated with the slices. In this paper, we propose a novel fine-grained resource control mechanism to implement transport network slices that meet traffic QoS requirements while both accepting limited traffic bursts, and enabling efficient bandwidth sharing within and across slices. The mechanism is executed at the edge of the transport network. The proposed model aligns with current standards on network slicing and has been tested on an experimental platform. Using this platform, we have conducted an extensive experimental campaign that demonstrates that our proposal can effectively control traffic bursts generated within the network slices while maximizing bandwidth utilization across the network.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"2152-2176"},"PeriodicalIF":6.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10934051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769376","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":"Spectral Shaping Method for OFDM Combining Time-Shifted Active Interference Cancellation and Adaptive Symbol Transition","authors":"Javier Giménez;José A. Cortés;Eduardo Martos-Naya;Luis Díez","doi":"10.1109/OJCOMS.2025.3571196","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3571196","url":null,"abstract":"Out-of-band emission (OOBE) is a major concern in orthogonal frequency division multiplexing (OFDM) based systems, as it requires large guard bands to avoid interfering other channels or systems. Spectral shaping techniques combining active interference cancellation (AIC) and adaptive symbol transition (AST) strategies, herein shortened as C-AIC-AST, are effective to reduce it at the cost of a data rate penalty and a modest implementation complexity compared to precoding and filtering techniques. This paper presents a spectral shaping method that innovates previous C-AIC-AST proposals by expanding both the AIC and AST terms to preceding and subsequent OFDM symbols. The timeexpanded terms are orthogonal to the current symbol, which makes them transparent to the receiver. The additional degrees of freedom given by these supplementary OOBE reduction terms can be exploited in different ways. In pulse-shaped OFDM systems, it allows attaining the same OOBE level than existing C-AIC-AST techniques but avoiding the data rate loss of the latter. In systems with rectangular OFDM signals, it can notably reduce the OOBE with a much smaller reduction in the effective cyclic prefix length compared to currently employed methods. The efficiency of the proposed method in achieving both goals with reduced implementation cost is demonstrated through results obtained in actual wired and wireless systems.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"4476-4490"},"PeriodicalIF":6.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11006891","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205879","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}