IEEE Open Journal of the Communications Society最新文献

{"title":"Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting","authors":"David E. Ruíz-Guirola;Onel L. A. López;Samuel Montejo-Sánchez","doi":"10.1109/OJCOMS.2025.3583867","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3583867","url":null,"abstract":"Industrial Internet of Things (IIoT) applications involve real-time monitoring, detection, and data analysis. However, the intermittent activity of IIoT devices and limited battery capacity pose critical challenges. This paper addresses these interconnected issues, focusing on extending the battery life of IIoT devices sensing events/alarms by minimizing the number of unnecessary transmissions. We propose a threshold-based transmission-decision policy based on the sensing quality and the network spatial deployment. We optimize the transmission thresholds using several approaches such as successive convex approximation, block coordinate descent methods, Voronoi diagrams, explainable machine learning, algorithms based on natural selection and social behavior, and Q-learning. Through numerical evaluation, we demonstrate significant performance enhancements in low-power IIoT environments, with Q-learning performing the best, while the block coordinate descending method performs the worst. We compare the proposed methods to a benchmark that assigns the same transmission threshold to all devices. In low-density scenarios, all proposed methods outperform the benchmark, while in high-density scenarios, only Voronoi-(i), K-nearest neighbors, and Q-learning show better performance. Power consumption is reduced by up to 95% in low-density scenarios compared to the benchmark and by 63% in high-density scenarios.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5490-5508"},"PeriodicalIF":6.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11054051","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597955","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":"Multi-Task Learning for mmWave Transceiver Beam Prediction","authors":"Muhammad Qurratulain Khan;Abdo Gaber;Mohammad Parvini;Philipp Schulz;Gerhard Fettweis","doi":"10.1109/OJCOMS.2025.3583074","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3583074","url":null,"abstract":"Rigorous and reliable alignment of narrow transceiver beams is a requisite for ensuring the highly directional transmission in millimeter-wave (mmWave) communications. Exhaustively testing these narrow beam pairs results in increased reference signal (RS) overhead, latency, and power consumption. In this paper, we propose a centralized multi-task learning (MTL) based beam prediction strategy that ensures a high success rate using measurements from a few site-specific probing beams identified via the proposed uniformly distributed beam relevance and beam significance (UDBRBS) criterion, thereby obviating the need for an exhaustive scan. Performance evaluation over 3rd Generation Partnership Project (3GPP) defined performance indicators demonstrates that the proposed method outperforms existing independent task learning (ITL) and single task learning (STL) beam prediction designs. We further argue that the proposed strategy is highly practical for implementation in fifth generation (5G)-Advanced and sixth generation (6G) communication systems.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5535-5551"},"PeriodicalIF":6.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11050966","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144598033","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":"Accelerating Ray Tracing-Based Wireless Channels Generation for Real-Time Network Digital Twins","authors":"Cláudio Modesto;Lucas Mozart;Pedro Batista;André Cavalcante;Aldebaro Klautau","doi":"10.1109/OJCOMS.2025.3583202","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3583202","url":null,"abstract":"Ray tracing (RT) simulation is a widely used approach to enable modeling wireless channels in applications such as network digital twins. However, the computational cost to execute ray tracing (RT) is proportional to factors such as the level of detail used in the adopted 3D scenario. This work proposes RT pre-processing algorithms that aim at simplifying the 3D scene without distorting the channel, by reducing the scenario area and/or simplifying object shapes in the scenario. It also proposes a post-processing method that augments a set of RT results to achieve an improved time resolution. These methods enable using RT in applications that use a detailed and photorealistic 3D scenario while generating consistent wireless channels over time. Our simulation results with different urban scenarios scales, in terms of area and object details, demonstrate that it is possible to reduce the simulation time by more than 50% without compromising the accuracy of the multipath RT parameters, such as angles of arrival and departure, delay, phase, and path gain.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5464-5478"},"PeriodicalIF":6.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11050957","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597860","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 Tutorial on Wideband XL-MIMO: Challenges, Opportunities, and Future Trends","authors":"Mohammad Parvini;Bitan Banerjee;Muhammad Qurratulain Khan;Torge Mewes;Ahmad Nimr;Gerhard Fettweis","doi":"10.1109/OJCOMS.2025.3583091","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3583091","url":null,"abstract":"As identified by international telecommunication union (ITU), extremely large-scale multiple-input multiple-output (XL-MIMO) is one of the pivotal enablers for sixth generation (6G) mobile communication networks across mmWave, sub-THz, and emerging mid-band (FR3) frequencies. These systems employ very large antenna arrays to achieve high spatial resolution and throughput. However, the conventional phase-shift-based beamforming which is designed under the narrowband assumption faces limitations due to large bandwidth and array sizes, which subsequently lead to beam squint. This phenomenon exists in both near-field and far-field regions of the antenna. This frequency-dependent misalignment of the beam degrades array gain, increases bit error rate, and limits data rates, especially in wideband scenarios. This paper presents both a comprehensive survey and a unifying framework for beam squint mitigation in XL-MIMO systems. Motivated by the challenges of maintaining consistent beamforming across frequency, we categorize existing solutions into two main classes: subband division-based methods, which are based on filtering the wideband signal to narrowband signals and applying a subband-dependent set of phase shifts to each subband to reduce the beam squint, and subarray division-based techniques, which involve partitioning the entire array into smaller subarrays or utilizing a subarray of true-time-delays (TTDs). We compare these solutions and outline their advantages and disadvantages. Our approach includes theoretical derivation of the beam squint channel for both the far-field and near-field channels, comparative analysis of the beam squint mitigation approaches, and numerical simulations. Finally, we outline open research challenges and suggest potential directions for future work in beam squint mitigation within XL-MIMO systems.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5509-5534"},"PeriodicalIF":6.3,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11050910","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597772","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":"Guest Editorial Special section on Emerging Modulation Techniques Toward 6G Networks","authors":"Miaowen Wen;Tianqi Mao;Ertugrul Basar;Gunes Karabulut Kurt;Zhaocheng Wang;Naofal Al-Dhahir","doi":"10.1109/OJCOMS.2025.3571304","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3571304","url":null,"abstract":"","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"iv-viii"},"PeriodicalIF":6.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045348","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331789","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":"Widely Linear Processing Improves the Throughput of Nonorthogonal User Access","authors":"A. A. Nasir;H. D. Tuan;H. V. Poor;L. Hanzo","doi":"10.1109/OJCOMS.2025.3581847","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3581847","url":null,"abstract":"The quality-of-service (QoS) provided by wireless communication networks can be upgraded by the technique of non-orthogonal multiple-access (NOMA) in tandem with widely linear beamforming (WLB), which uses a pair of beamformers for each information symbol. Conventionally, rate-fairness among the users is achieved by maximizing the users’ minimal throughput (max-min throughput optimization). However, this is computationally challenging, as each iteration requires solving a high-dimensional convex optimization problem, even for small networks. We circumvent this by maximizing the geometric mean (GM) of the users’ throughput (GM-throughput maximization) and design novel algorithms based on iterating closed-form expressions are developed, which are shown to be hundreds of times more computationally efficient than the existing algorithms that are based on convex-solvers. The proposed algorithms are developed for both conventional wireless networks and networks requiring ultra-reliable and low-latency communications (URLLC).","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5395-5413"},"PeriodicalIF":6.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045687","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581586","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":"Guest Editorial Special Section on Generative AI and Large Language Models Enhanced 6G Wireless Communication and Sensing","authors":"Jiacheng Wang;Geng Sun;Dusit Niyato;Hina Tabassum;Gabriel-Miro Muntean;Nelson Fonseca","doi":"10.1109/OJCOMS.2025.3571515","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3571515","url":null,"abstract":"","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"0-2"},"PeriodicalIF":6.3,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11044318","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323028","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":"Enhanced Signal-to-Noise Ratio Estimation in Optical Fiber Communications: A Pilot-Based Approach","authors":"Mohamed Al-Nahhal;Ibrahim Al-Nahhal;Sunish Kumar Orappanpara Soman;Octavia A. Dobre","doi":"10.1109/OJCOMS.2025.3581473","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3581473","url":null,"abstract":"This paper presents two innovative, pilot-assisted, neural network (NN)-based signal-to-noise ratio (SNR) estimators for application in optical fiber communications. These estimators, termed pilot-assisted feature complexity reduction (PAF-CR) and pilot-assisted feature accuracy enhancement (PAF-AE), are designed to jointly estimate both linear and non-linear SNR components. The architectures of these proposed estimators employ feedforward NNs (FFNNs) for the SNR estimation, with PAF-CR utilizing a two-hidden layer FFNN and PAF-AE employing a single-hidden layer FFNN. Novel features are extracted from pilot signals to utilize the pilot overhead in transmitted signals, such as mean absolute error and mean signed deviation, which statistically measure the error between transmitted and received pilot signals. Additionally, features are directly extracted from the received data signal, such as average absolute deviation, entropy, and arithmetic mean, to capture its statistical dispersion characteristics. The proposed features are carefully selected to effectively capture the characteristics of both linear and non-linear SNR components. The estimation accuracy of the SNR components achieved by the proposed estimators is evaluated using the normalized root mean square error and the standard deviation of the estimation errors. A comprehensive computational complexity analysis of the proposed PAF-CR and PAF-AE estimators is conducted, expressed in terms of real-valued multiplications and additions. Numerical results illustrate that the proposed PAF-CR and PAF-AE estimators achieve a favorable trade-off between the SNR estimation accuracy and computational complexity compared with existing literature estimators. The proposed PAF-CR offers significant computational complexity reduction with a slight enhancement in estimation accuracy, while the proposed PAF-AE provides substantial estimation accuracy improvement while slightly decreasing computational complexity.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5552-5567"},"PeriodicalIF":6.3,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11045136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597773","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":"Adaptive Throughput Optimization in Multi-Rate IEEE 802.11 WLANs via Multi-Agent Deep Reinforcement Learning","authors":"Ming-Chu Chou;Cheng-Feng Hung;Chin-Ya Huang;Chih-Heng Ke","doi":"10.1109/OJCOMS.2025.3580886","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3580886","url":null,"abstract":"As wireless networks become increasingly important in modern society, their application scenarios are becoming more diverse and complex. However, the heterogeneity of nodes and transmission conditions presents significant challenges to existing wireless strategies and traditional centralized AI methods, making it difficult to meet user demands for network throughput. This paper proposes a distributed architecture based on multi-agent reinforcement learning combined with deep reinforcement learning. Agents are deployed on individual transmission nodes, enabling distributed observation and autonomous decision-making, while the access point provides feedback derived from the network performance resulting from their individual decisions. By experimentally comparing centralized and distributed architectures in multi-rate environments, this paper analyzes trade-offs in scalability and network performance. Additional experiments conducted under dynamic network conditions with node mobility and static scenarios involving a larger number of coexisting nodes further validate the system’s robustness and adaptability. The analysis of training loss trends shows that although the distributed architecture incurs a higher training cost, it achieves improved throughput. In particular, the distributed method outperforms the centralized method by nearly 30% when the number of nodes is relatively small, and maintains a 5–10% performance advantage as the network continues to scale.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5384-5394"},"PeriodicalIF":6.3,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039654","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581583","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":"Efficient Interference Management Design for NTN/TN Co-Existence in HAP-Based 6G Networks","authors":"Muhammet Kirik;Aseel Alkana’Neh;Liza Afeef;Hüseyin Arslan","doi":"10.1109/OJCOMS.2025.3580452","DOIUrl":"https://doi.org/10.1109/OJCOMS.2025.3580452","url":null,"abstract":"High-altitude platforms (HAPs) are critical for 6th generation (6G) networks, particularly in autonomous flying ad-hoc networks (FANETs). However, their extensive coverage areas cause severe co-channel interference (CCI) when overlapping with terrestrial networks (TNs) that share the same frequency bands as mandated by 3rd Generation Partnership Project (3GPP). To address this, we propose a novel three-phase interference mitigation design that operates without requiring non-terrestrial network (NTN)/TN coordination. First, subspace-based blind channel estimation extracts the channel state information (CSI) of the aggressor base station (BS). Next, an optimized sparse codebook is designed using the estimated victim channel to suppress interference and enhance spectral efficiency. Finally, the codebook is utilized for pilot-assisted data transmission, ensuring reliable communication despite CCI. Mathematical analysis and numerical results validate the proposed method, demonstrating significant reductions in CCI and inter-carrier interference (ICI), maintained similar level of peak-to-average power ratio (PAPR), and enhanced signal-to-interference-plus-noise ratio (SINR), making it a scalable and efficient solution for non-terrestrial network (NTN)/terrestrial network (TN) co-existence in 6G networks.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":"6 ","pages":"5434-5449"},"PeriodicalIF":6.3,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144581737","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}