Physical Communication最新文献

{"title":"Minimizing distortion and enhancing security in Rayleigh fading channels","authors":"Hafsat Muhammad Bashir ,&nbsp;Yunquan Dong ,&nbsp;James Msughter Adeke","doi":"10.1016/j.phycom.2025.102679","DOIUrl":"10.1016/j.phycom.2025.102679","url":null,"abstract":"<div><div>The trade-off between security, reliability, and distortion in a direct communication link with an eavesdropper is investigated by adjusting both the transmission power and the transmission rate, which affects the distortion size of the distortion-limited coding. This involves encoding data at a predetermined rate with Channel Side Information (CSI) to ensure successful data recovery within a defined distortion threshold. Using higher transmit power and coding rates effectively minimizes average distortion but increases intercept probability, whereas opting for lower transmit power and coding rates reduces interception probability while amplifying signal distortion. Thus, we investigate the distortion-intercept probability trade-off across feasible transmit powers and transmission intervals. For a Rayleigh fading channel, we derived a closed-form expression for the IP and calculated the maximum power when transmitting with a fixed power such that the intercept probability is below a threshold. We also present a water-filling-based power allocation to minimize the average distortion under some intercept probability requirements. With the proposed method, both numerical and Monte Carlo simulation demonstrate that employing a power control strategy reduces the average distortion and intercept probability to 78% and 50%, respectively, showcasing the effectiveness of the approach.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102679"},"PeriodicalIF":2.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fair channel allocation in IEEE 802.11p for high throughput and low-latency","authors":"Lopamudra Hota,&nbsp;Bibhudatta Sahoo,&nbsp;Arun Kumar","doi":"10.1016/j.phycom.2025.102683","DOIUrl":"10.1016/j.phycom.2025.102683","url":null,"abstract":"<div><div>The emergence of Intelligent Transportation Systems (ITS) necessitates reliable and efficient connectivity among vehicles. The IEEE 802.11p standard with one control channel and six service channels operating in 75-MHz spectrum at 5.9 GHz is responsible for fair channel access for V2X communication. Nevertheless, issues like latency and network congestion continue to exist, requiring dynamic channel allocation techniques. To ensure proper operation of Vehicular Ad hoc NETworks (VANETs), Medium Access Control (MAC) plays a vital role. This paper proposes an efficient channel allocation algorithm for the MAC layer of VANET to overcome the stringent demand of throughput and delay. The channel allocation policy adapts to the dynamic vehicular environment. The paper focuses on time slot allocation for fair channel access by avoiding transmission collision between two RSUs. Then the channel allocation is designed as a knapsack problem, where the packets are given priority to access the channel based on their weight factor. A Deep Reinforcement Learning (DRL) Asynchronous Advantage Actor Critic (A3C) algorithm is used to solve the knapsack problem. By utilizing the A3C algorithm, optimal policy is achieved that learns the environment for channel allocation, enabling real-time adaptations to varying network conditions and vehicular mobility patterns. The algorithm handles high-dimensional state and action spaces, allowing for improved decision-making based on current channel utilization and packet prioritization. The proposed framework presents a high-throughput, low-latency channel allocation model that effectively addresses the stringent demands of both safety and non-safety packets, ensuring timely transmission of critical messages. Extensive simulation results prove the efficacy of the proposed algorithm High Throughput Low Latency- Actor-Critic MAC (HTLL-ACMAC) over existing algorithms. The performance evaluation demonstrates that the proposed model reduces the delay by approximately 13%, and maximizes the network throughput by approximately 38% compared to baseline models.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102683"},"PeriodicalIF":2.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full-duplex (FD) two-way device-to-device (D2D) communications based on dual IRSs","authors":"Shiguo Wang ,&nbsp;Chang Lin ,&nbsp;Rukhsana Ruby ,&nbsp;Xiukai Ruan ,&nbsp;Qingyong Deng","doi":"10.1016/j.phycom.2025.102675","DOIUrl":"10.1016/j.phycom.2025.102675","url":null,"abstract":"<div><div>For device-to-device (D2D) communications in the internet of things (IoT), when the direct links between terminals are unavailable owing to obstacles or severe fading, deploying intelligent reflecting surfaces (IRSs) is a promising solution to reconfigure channel environments for enhancing signal coverage and system capacity. In this paper, to improve system spectrum and energy efficiency, a novel full-duplex (FD) D2D communication model with dual IRSs is presented, where two IRSs are deployed closely to two FD transceivers for assisting the exchange of information between them. Given the budget of total transmit power, maximizing the achievable sum-rate of such IRS-assisted FD two-way system is formulated to optimize the precoding at the two transceivers and the phase shifts at the two IRSs. For such a coupled non-convex problem, we decouple it into two subproblems successfully, which can be solved in an alternate manner with low complexity. Simulation results are presented to validate the superior performance of the proposed D2D communication model compared to the existing models and similar optimization schemes.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102675"},"PeriodicalIF":2.0,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143790861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cooperative sensing performance of multi-satellite uplink systems","authors":"Xiaorui Zhang,&nbsp;Yi Tao,&nbsp;Xuanhe Yang,&nbsp;Shuai Wang,&nbsp;Gaofeng Pan,&nbsp;Jianping An","doi":"10.1016/j.phycom.2025.102678","DOIUrl":"10.1016/j.phycom.2025.102678","url":null,"abstract":"<div><div>As global communication needs continue to grow, the scarcity of spectrum resources and the increase in interference underscore the importance of cognitive satellite communication systems. However, existing research has notable shortcomings in addressing uplink multi-satellite cooperative sensing performance in highly dynamic scenarios, particularly regarding multi-node cooperative detection performance while considering factors such as attenuation. Furthermore, there is a lack of in-depth discussion concerning analysis and fusion strategy design. To address these challenges, this paper proposes a method that combines Monte Carlo simulation with theoretical analysis, taking into account signal attenuation, distance uncertainty, and noise uncertainty, to conduct a comprehensive study of uplink multi-satellite cooperative sensing performance. Specifically, we employed soft fusion technology using Square Law Combining (SLC) and hard fusion technology utilizing various rules and conducted simulation experiments. The research results indicate that different fusion methods can both enhance and diminish signal detection performance. The analysis and simulation results presented in this paper validate the effectiveness of the proposed method, offering significant references for the selection and design of multi-node cooperative detection strategies across various scenarios involving low Earth orbit satellite constellations.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102678"},"PeriodicalIF":2.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectrum sensing based on graph mixture statistic","authors":"Li Yang ,&nbsp;Guobing Hu ,&nbsp;Bin Gu ,&nbsp;Shanshan Wu","doi":"10.1016/j.phycom.2025.102686","DOIUrl":"10.1016/j.phycom.2025.102686","url":null,"abstract":"<div><div>Graph transformation-based spectrum sensing algorithms have demonstrated effectiveness in enhancing detection performance with limited samples. However, existing methods primarily rely on topological features derived from a single graph constructed using either the power spectrum (PS) or the autocorrelation function (ACF). This approach overlooks the potential benefits of integrating information from multiple graphs. Moreover, these methods often fail to effectively combine topological features with the statistical properties of the original signals, resulting in reduced detection performance in low signal-to-noise ratio (SNR) environments and fading channels. To address these limitations, we propose a novel spectrum sensing algorithm based on graph mixture graph statistic. Our method employs quantization-based graph transformation to generate two distinct subgraphs from the block sums of the PS (BSPS) and the ACF. We define the vertex probability vector of the BSPS and the mean and standard deviation sum of the ACF quantization subsets as the respective graph signals. By calculating the Laplacian quadratic form for the BSPS-based graph and the one-hop graph filter statistic for the ACF-based graph, we derive a graph mixture statistic that serves as a new detection criterion. Simulations demonstrate that our proposed approach outperforms existing methods with only a modest increase in computational complexity.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102686"},"PeriodicalIF":2.0,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143833070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resource allocation scheme for multi-cluster NOMA-SWIPT systems with multiple IRSs","authors":"Xiaorong Jing ,&nbsp;Ningyue Chen ,&nbsp;Hongqing Liu","doi":"10.1016/j.phycom.2025.102677","DOIUrl":"10.1016/j.phycom.2025.102677","url":null,"abstract":"<div><div>To address the challenge of providing seamless cellular connectivity for a massive number of Internet-of-Things (IoT) devices within limited resources, this paper integrates non-orthogonal multiple access (NOMA), simultaneous wireless information and power transfer (SWIPT), and intelligent reflecting surface (IRS) technologies. Considering practical factors such as imperfect channel state information (CSI), non-ideal successive interference cancellation (SIC), and non-linear energy harvesting (EH), this paper constructs a multi-cluster NOMA-SWIPT transmission model assisted by multiple IRSs. For this model, with the aim of maximizing system energy efficiency (EE) under constraints such as maximum base station (BS) transmit power, IRS reflection phase shifts, minimum transmission rate, and minimum energy harvesting (EH), a non-convex resource allocation problem is formulated. The solution to this problem requires the joint optimization of the BS transmit beamforming vectors, IRS reflection phase shifts, and power splitting (PS) ratios. To address this challenge, the original problem is initially decomposed into three non-convex sub-problems. Subsequently, by employing Schur’s complement, the S-procedure, General sign-definiteness, and successive convex approximation (SCA), these non-convex sub-problems are transformed into solvable convex optimization sub-problems. Finally, an alternating iterative method is proposed to solve these sub-problems, thereby addressing the original resource allocation problem. Simulation results validate not only the convergence of the robust resource allocation scheme based on alternating iteration but also demonstrate that leveraging the close-range coverage of IRSs can significantly enhance system energy efficiency, even under non-ideal SIC and imperfect CSI conditions.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102677"},"PeriodicalIF":2.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resilient multi-UAV path planning for effective and reliable information collection","authors":"Yunfei Liu ,&nbsp;Yang Chen ,&nbsp;Mian Hu ,&nbsp;Wenhao Zhang","doi":"10.1016/j.phycom.2025.102685","DOIUrl":"10.1016/j.phycom.2025.102685","url":null,"abstract":"<div><div>UAV technology provides opportunities for regional information collection in complex and dynamic environments. In many large-scale or intricate scenarios, such as widespread natural disasters, UAVs often encounter challenges in wirelessly transmitting collected data in real time, which may compromise the timeliness and relevance of the information. Additionally, UAV malfunctions or failures can result in the loss of critical data from specific target points. Therefore, when planning flight paths of multiple UAVs, it becomes essential to coordinate their flight paths to maintain data freshness while minimizing the risk of data loss. In this paper, we introduce a resilient path planning strategy to proactively respond to potential UAV failures. Our approach seeks to reduce discrepancies in the total volume of information carried by individual UAVs, therefore reducing the risk of substantial information loss. Given that traditional weighting methods often heavily rely on subjective coefficient settings, we have established a multi-objective resilient path planning model for multi-UAV information collection scenarios. To optimize UAV flight paths, we propose an improved non-dominated sorting whale optimization algorithm, which provides a more robust and adaptive solution to UAV coordination. Experimental results validated the effectiveness of the constructed mathematical model. Comparative analysis demonstrates that the Pareto front solutions generated by the proposed algorithm hold significant advantages in terms of distribution and uniformity.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102685"},"PeriodicalIF":2.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anti-UAV detection and identification technology: Fundamentals, methods and challenges","authors":"Lan Xu ,&nbsp;Zhongqiang Luo","doi":"10.1016/j.phycom.2025.102676","DOIUrl":"10.1016/j.phycom.2025.102676","url":null,"abstract":"<div><div>The rapid development of unmanned aerial vehicle (UAV) technology has driven its widespread application in military, commercial, and civilian domains, such as surveillance, logistics, and disaster response. However, this growing popularity has also raised serious security and privacy concerns, as UAVs can be misused for smuggling, espionage, terrorism, and other illegal activities. As a result, anti-UAV detection and identification technologies have become a critical research area for monitoring, identifying, and mitigating the threats posed by rogue drones. This paper provides a comprehensive review of the latest advancements in anti-UAV detection and identification technologies. To deepen the understanding of these technologies, the paper first introduces the UAV system (UAS) framework and its corresponding anti-UAV systems. Subsequently, it presents an in-depth analysis of the primary detection and identification methods, including those based on image processing, radio frequency (RF) signals, radar, infrared characteristics, acoustic features, and multi-modal fusion. The advantages, limitations, and application scenarios of each method are systematically compared and summarized. Furthermore, this paper identifies the major challenges faced by current anti-UAV detection technologies, such as detection accuracy, range, robustness, and cost, and explores potential directions for future research and development. By synthesizing these insights, this paper aims to provide researchers and practitioners with a comprehensive understanding of the current state of the art in anti-UAV technologies, serving as a valuable reference to advance research progress and foster innovation in this critical field.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102676"},"PeriodicalIF":2.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"JOPCNN-based hybrid precoding/combining algorithm for millimeter wave communication systems","authors":"Fulai Liu ,&nbsp;Hong Cao ,&nbsp;Yuchen Wu ,&nbsp;Baozhu Shi ,&nbsp;Ruiyan Du","doi":"10.1016/j.phycom.2025.102674","DOIUrl":"10.1016/j.phycom.2025.102674","url":null,"abstract":"<div><div>To enhance the wideband hybrid precoding/combining (HPC) performance, this paper presents an antenna selection-based joint optimization HPC algorithm, namely JOPCNN. In the proposed algorithm, a JOPCNN framework is constructed to obtain the optimal analog precoder and combiner. Specially, the JOPCNN includes antenna selection convolutional neural network(ASCNN) and hybrid precoding/combining convolutional neural network (HPCCNN) subnetworks. Firstly, to improve spectral efficiency(SE) while reducing hardware cost and complexity of the system, the purpose of the ASCNN is to get the best antenna arrays. Subsequently, by employing the analog phase matrix as a label, the HPCCNN subnetwork is able to output the best analog precoder and combiner while adhering to the constant modulus restriction. Meanwhile, in order to better extract the amplitude, phase, and carrier-related information of the channel, a 3-dimensional convolutional neural network(3DCNN) is introduced into the proposed JOPCNN model. Finally, the digital coder can be solved by employing the resulting analog coder. Simulation findings indicate that the suggested approach performs better in SE than comparable algorithms.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102674"},"PeriodicalIF":2.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DRL-based RIS-assisted Integrated Sensing and Communication Joint design of beamforming and reflection phase shift","authors":"Zaiqiang Wang ,&nbsp;Zhongqiang Luo ,&nbsp;Yiting Lei","doi":"10.1016/j.phycom.2025.102669","DOIUrl":"10.1016/j.phycom.2025.102669","url":null,"abstract":"<div><div>As one of the key application scenarios of the sixth generation of mobile communications (6G), various industries have partially researched Integrated Sensing and Communication (ISAC). ISAC can combine the functions of communications and radar to achieve the sharing of the hardware platform and unlimited radio spectrum. In the complex environment of the ISAC system, when encountering signal fading and energy loss, reconfigurable intelligent surfaces (RIS) can be used to assist ISAC communications, providing a solution for efficient communications and high-precision sensing for future 6G systems. Currently, most joint beamforming designs for RIS-assisted ISAC systems adopt traditional methods. The core idea is to achieve resource allocation and beam steering through mathematical modeling and optimization theory. This study proposes a joint beamforming design scheme using deep reinforcement learning (DRL). Based on the DRL framework, the soft actor-critic (SAC) algorithm is adopted to achieve a low-complexity scheme to solve the non-convex optimization problem in RIS-assisted ISAC systems. Simulation results show the effectiveness of the DRL-based method in RIS-assisted ISAC systems and demonstrate that the proposed algorithm can maximize the guaranteed communication rate of users while achieving perception of the surrounding environment.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"71 ","pages":"Article 102669"},"PeriodicalIF":2.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}