Journal of Communications and Information Networks最新文献

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Joint Beamforming Design for Reconfigurable Intelligent Surface-Assisted LEO Satellite Constellation Communication 可重构智能地面辅助LEO卫星星座通信联合波束形成设计
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207210
Wenfei Yao;Xiaoming Chen;Qi Wang
{"title":"Joint Beamforming Design for Reconfigurable Intelligent Surface-Assisted LEO Satellite Constellation Communication","authors":"Wenfei Yao;Xiaoming Chen;Qi Wang","doi":"10.23919/JCIN.2025.11207210","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207210","url":null,"abstract":"Low earth orbit (LEO) satellite constellation, as a typical non-terrestrial network (NTN), can provide ubiquitous connectivity for 6G wireless networks with low transmission delay. However, satellite communications (SATCOM) are still hampered by challenges such as scarcity of spectrum resources and significant path losses. In this paper, reconfigurable intelligent surfaces (RIS) are deployed to enhance the performance of long-distance satellite-terrestrial communication. Further, by exploring inter-satellite links, a joint active beamforming at satellites and passive beamforming at RIS design algorithm is proposed to improve the weighted sum rate (WSR) of satellite-terrestrial communication in the presence of inter-satellite interference due to spectrum sharing. Specifically, we adopt alternating optimization (AO) method to split the original problem into two sub-problems and then solve them step by step. Firstly, given passive beamforming at RIS, we solve the active beamforming design problem with a closed-form solution. Secondly, given the active beamforming, we design passive beamforming for RIS through the alternating direction method of the multipliers. Theoretical analysis and extensive numerical simulations demonstrate the effectiveness of our proposed algorithm in RIS-assisted LEO satellite constellation communications.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"254-267"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Scoring ISAC: Benchmarking Integrated Sensing and Communications via Score-Based Generative Modeling 得分ISAC:通过基于得分的生成建模对集成传感和通信进行基准测试
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207199
Lin Chen;Chang Cai;Huiyuan Yang;Xiaojun Yuan;Ying-Jun Angela Zhang
{"title":"Scoring ISAC: Benchmarking Integrated Sensing and Communications via Score-Based Generative Modeling","authors":"Lin Chen;Chang Cai;Huiyuan Yang;Xiaojun Yuan;Ying-Jun Angela Zhang","doi":"10.23919/JCIN.2025.11207199","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207199","url":null,"abstract":"Integrated sensing and communications (ISAC) is a key enabler for next-generation wireless systems, aiming to support both high-throughput communication and high-accuracy environmental sensing using shared spectrum and hardware. Theoretical performance metrics, such as mutual information (MI), minimum mean squared error (MMSE), and Bayesian Cramer-Rao bound (BCRB), play a key role in evaluating ISAC system performance limits. However, in practice, hardware impairments, multipath propagation, interference, and scene constraints often result in nonlinear, multimodal, and non-Gaussian distributions, making it challenging to derive these metrics analytically. Recently, there has been a growing interest in applying score-based generative models to characterize these metrics from data, although not discussed for ISAC. This paper provides a tutorial-style summary of recent advances in score-based performance evaluation, with a focus on ISAC systems. We refer to the summarized framework as scoring ISAC, which not only reflects the core methodology based on score functions but also emphasizes the goal of scoring (i.e., evaluating) ISAC systems under realistic conditions. We present the connections between classical performance metrics and the score functions and provide the practical training techniques for learning score functions to estimate performance metrics. Proof-of-concept experiments on target detection and localization validate the accuracy of score-based performance estimators against ground- truth analytical expressions, illustrating their ability to replicate and extend traditional analyses in more complex, realistic settings. This framework demonstrates the great potential of score-based generative models in ISAC performance analysis, algorithm design, and system optimization.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"224-245"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11207199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335302","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}
引用次数: 0
Integrated AI and Communications: A Two-Way Catalysis Toward 6G and Beyond 集成人工智能和通信:6G及以后的双向催化
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207211
Xiang Cheng;Jianan Zhang;Ning Ding;Nan Li;Yong Li;Tailin Wu;Wei Xu;Jun Zhang;Qi Sun
{"title":"Integrated AI and Communications: A Two-Way Catalysis Toward 6G and Beyond","authors":"Xiang Cheng;Jianan Zhang;Ning Ding;Nan Li;Yong Li;Tailin Wu;Wei Xu;Jun Zhang;Qi Sun","doi":"10.23919/JCIN.2025.11207211","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207211","url":null,"abstract":"Artificial intelligence (AI) and wireless communications are catalyzing each other's advancement as we approach 6G networks and beyond. This article presents a perspective on the two-way interplay between AI and communications—how AI techniques are revolutionizing communication network design (AI4Comm) and how emerging communication technologies are enabling and accelerating AI (Comm4AI). We discuss recent advances and outline the challenges in realizing an AI-native wireless ecosystem and propose a roadmap for integrating AI and communications, offering insights into a future where wireless communications and AI evolve together.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"191-200"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Joint Offloading Decision and Spectrum Assignment in D2D-Enhanced MEC Network: A Deep Reinforcement Learning Approach d2d增强MEC网络联合卸载决策与频谱分配:一种深度强化学习方法
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207207
Chenyang Yi;Yurong Qian;Wei Xu
{"title":"Joint Offloading Decision and Spectrum Assignment in D2D-Enhanced MEC Network: A Deep Reinforcement Learning Approach","authors":"Chenyang Yi;Yurong Qian;Wei Xu","doi":"10.23919/JCIN.2025.11207207","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207207","url":null,"abstract":"Due to the adaptability to dynamic environments and the capability of optimizing complex decision-making processes, deep reinforcement learning (DRL) has been recently applied to scheduling and resource allocation problems in wireless communications. In this paper, we propose a DRL-based joint task offloading and spectrum assignment approach in a device-to-device (D2D) enhanced mobile edge computing (MEC) scenario, where multiple resource devices (RDs) and an edge server collaboratively provide auxiliary task offloading services to task devices (TDs). Considering the time-varying wireless channel conditions, we formulate an optimization problem to jointly design the offloading decision and sequential spectrum assignment across multiple coherent time slots. The optimization objective is to minimize offloading latency while ensuring the offloading success rate for all TDs. To address this problem, we propose a two-step approach, comprising a game-based offloading matching (GBOM) to obtain the Nash equilibrium (NE) of offloading decisions, and a multi-agent DRL (MADRL) to solve the sequential spectrum assignment problem. Numerical results show that the proposed GBOM-MADRL algorithm mitigates the system offloading latency and improves the average probability of successful offloading.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"201-214"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Channel Measurement and Modeling for 380 MHz V2I Emergency Communications in Forested Scenarios 森林环境下380 MHz V2I应急通信信道测量与建模
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207205
Rong Yuan;Wenchi Cheng;Wei Guo;Dan Fei;Haoran Chen;Yayun Ao;Yudong Fang
{"title":"Channel Measurement and Modeling for 380 MHz V2I Emergency Communications in Forested Scenarios","authors":"Rong Yuan;Wenchi Cheng;Wei Guo;Dan Fei;Haoran Chen;Yayun Ao;Yudong Fang","doi":"10.23919/JCIN.2025.11207205","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207205","url":null,"abstract":"Emergency communication in forested environments encounters extremely complex propagation conditions, whose channel characteristics cannot be accurately captured by conventional models designed for urban scenarios. This paper conducts field measurements and modeling for 380 MHz vehicle-to-infrastructure (V2I) links in the primeval forest of the Greater Khingan Mountains. Through joint analysis of large-scale and small-scale channel characteristics, we systematically reveal the signal attenuation, fading mechanisms, and delay spread behavior in such environments. Results indicate that for path loss modeling, the Alpha-Beta model outperforms the Close-In model in characterizing the rapid attenuation in dense foliage. Small-scale fading is predominantly Rayleigh-distributed, while Ricean fading only dominates in the initial stage, with its K-factor decreasing significantly as distance increases. The root mean square (RMS) delay spread ranges from 0 to 450 ns, follows a log-normal distribution, and is markedly larger than in urban scenarios. Based on these observations, a parametric tapped-delay-line (TDL) model is developed, effectively quantifying multipath delay, power decay, and fading characteristics. The proposed model can reproduce realistic propagation features in simulations, offering theoretical support for emergency communication system planning and optimization, as well as engineering guidance for enhancing communication reliability and coverage in disaster rescue scenarios.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"276-286"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
LLM-Enhanced Pilot-Free OTFS Transceiver for High-Mobility Communications 用于高移动通信的llm增强型无导频OTFS收发器
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207204
Jiaming Cheng;Wei Chen;Bowen Yang;Bo Ai
{"title":"LLM-Enhanced Pilot-Free OTFS Transceiver for High-Mobility Communications","authors":"Jiaming Cheng;Wei Chen;Bowen Yang;Bo Ai","doi":"10.23919/JCIN.2025.11207204","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207204","url":null,"abstract":"The advent of 6G wireless networks demands highly reliable communication in extreme mobility scenarios while maintaining stringent spectral efficiency. Conventional orthogonal time frequency space (OTFS) systems rely on pilot-assisted channel estimation, which incurs significant overhead and limits throughput. In this paper, we propose a novel pilot-free OTFS transceiver empowered by large language models (LLMs) to overcome these challenges. Our end-to-end (E2E) framework integrates artificial intelligence (AI)-driven constellation geometric shaping (GS) at the transmitter with an LLM-enhanced neural receiver (LLM-Rx) that performs implicit channel estimation and data detection directly in the delay-Doppler (DD) domain. A dual-branch receiver architecture combines convolutional feature extraction with a pretrained GPT-2 backbone, enabling context-aware joint estimation and detection. Extensive simulations demonstrate that the proposed design achieves 14.3% higher spectral efficiency and significantly lower bit error rate (BER) than pilot-assisted linear transceivers and other existing schemes.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"215-223"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An Analytic Hierarchy Process Based Access Control Algorithm for Zero-Trust Architecture 基于层次分析法的零信任体系结构访问控制算法
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207209
Yuan Liu;Jun Yan;Wei Wang
{"title":"An Analytic Hierarchy Process Based Access Control Algorithm for Zero-Trust Architecture","authors":"Yuan Liu;Jun Yan;Wei Wang","doi":"10.23919/JCIN.2025.11207209","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207209","url":null,"abstract":"With the rapid development of Internet technology, the network access control has received much attention, especially for zero-trust architecture (ZTA). In this paper, an analytic hierarchy process (AHP) based access control algorithm using machine learning and Bayesian probability is proposed. Firstly, the actual access control problem is formulated as the AHP model which decomposes the decision-related elements into the goal layer, the criterion layer and the alternative layer. To obtain more accurate feature weights, the XGBoost model is introduced to compute the importance score of each feature. And the pairwise comparison matrix is constructed. Then, by calculating the maximum eigenvalue and corresponding eigenvector of the matrix, the single hierarchy sorting is achieved. Moreover, the consistency verification is proposed to ensure the matrix consistency. Next, a Bayesian probability method is used to calculate the conditional weights of allowed access and denied access for the attribute values of each feature. And the total hierarchy sorting is achieved. Last, the optimal threshold is determined by the Youden index. Compared with the threshold, the access control is estimated. Experimental results illustrated that the proposed algorithm performs better than some existing methods.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"268-275"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Data Detectors for Massive MIMO Systems Using Enhanced Acceleration Overrelaxation and Special Matrices Structures 基于增强加速度超松弛和特殊矩阵结构的海量MIMO系统数据检测器
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207200
Mahmoud A. Albreem;Shaikha Alobeidli;Saeed Abdallah
{"title":"Data Detectors for Massive MIMO Systems Using Enhanced Acceleration Overrelaxation and Special Matrices Structures","authors":"Mahmoud A. Albreem;Shaikha Alobeidli;Saeed Abdallah","doi":"10.23919/JCIN.2025.11207200","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207200","url":null,"abstract":"Massive multiple-input multiple-output (MIMO) is a cornerstone technology in beyond 5G (B5G) communication systems due to its ability to achieve exceptional power and spectral efficiency. The development of low-complexity detectors for massive MIMO remains a key area of research, driven by the need to strike a balance between performance and computational complexity, especially as the number of antennas increases at both the transmitter and receiver. In this paper, we propose efficient initialization methods to address these challenges. Instead of the conventional diagonal matrix, we employ the stair matrix and the band matrix in the initialization of the proposed detector based on accelerated overrelaxation. We also employ successive overrelaxation, Gauss-Seidel, and Jacobi methods to improve the performance of the proposed detector. The initialization scaling factors are based on the spectral radius of the iteration matrix. The proposed detectors are evaluated using diverse massive MIMO configurations and multiple modulation schemes and under both perfect and imperfect channel state information (CSI). Extensive simulations show that the proposed detectors achieve significant performance enhancements accompanied by a remarkable reduction in computational complexity, making them highly suitable for practical large-scale systems.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"299-310"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Incentive Mechanism Design for Asynchronous Federated Learning in Vehicular Networks 车载网络异步联合学习激励机制设计
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207208
Libo Shi;Haitao Zhao;Qin Wang;Ying Zhang;Kongrui Tang;Jinyu Liu;Hongbo Zhu
{"title":"Incentive Mechanism Design for Asynchronous Federated Learning in Vehicular Networks","authors":"Libo Shi;Haitao Zhao;Qin Wang;Ying Zhang;Kongrui Tang;Jinyu Liu;Hongbo Zhu","doi":"10.23919/JCIN.2025.11207208","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207208","url":null,"abstract":"The inherent stochasticity of mobile users' (MUs') request moments and data processing durations, coupled with the aggregated bandwidth constraints during peak moments, often limits the performance of synchronous federated learning (FL) systems. To overcome these challenges, this paper proposes an incentive mechanism for asynchronous federated learning (AFL) systems within a Stackelberg game framework. In this model, MUs function as both consumers of communication resources and providers of computational services. Additionally, we derive a closed-form solution for determining the optimal number of local iterations and employ Newton's method for numerical iteration to optimize the rewards for the cloud network controller (CNC). The numerical results demonstrate the effectiveness of the proposed scheme in enhancing system performance.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"246-253"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Guesswork Analysis of Guessing Decoding of Short Codes 短码猜测译码的猜测分析
Journal of Communications and Information Networks Pub Date : 2025-09-01 DOI: 10.23919/JCIN.2025.11207212
Jifan Liang;Yanzhi Chen;Xiao Ma
{"title":"Guesswork Analysis of Guessing Decoding of Short Codes","authors":"Jifan Liang;Yanzhi Chen;Xiao Ma","doi":"10.23919/JCIN.2025.11207212","DOIUrl":"https://doi.org/10.23919/JCIN.2025.11207212","url":null,"abstract":"This paper addresses: how many guesses are needed for maximum-likelihood (ML) performance by guessing decoding of short binary linear block codes—guessing random additive noise decoding (GRAND) and guessing codeword decoding (GCD)? We show the required guesswork depends weakly on code structure: codes with the same length n and dimension k and comparable ML performance need a similar number of guesses. For random codes, the GRAND guesswork is on the order ε<inf>RCU</inf>2<sup>n-k</sup><sup>—</sup>, where ε<inf>RCU</inf> is the random-coding union bound, tightening the trivial order 2<sup>n-k</sup>. We derive a universal upper bound on the number of (partial) test error patterns (TEPs), which is then evaluated accurately with a saddlepoint approximation. Analysis and simulations show that, in terms of guesswork, GCD never exceeds and often improves on GRAND, notably at low rates. To further reduce guesswork, we introduce an ordered-statistics decoder with local constraints (LC-OSD), derived by extending the most reliable basis and incorporating an early stopping rule. To reduce the decoding latency, we propose a parallel LC-OSD that utilizes pre-stored TEPs. Simulations of binary images of Reed-Solomon codes, which approach the randomcoding union (RCU) bound, confirm our analysis and demonstrate the superiority of soft-weight ordering over Hamming-weight ordering.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"10 3","pages":"287-298"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145335334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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