Physical Communication最新文献

{"title":"Hybrid FSO/RF and UWOC system for enabling terrestrial–underwater communication: Performance analysis","authors":"Neha Payal,&nbsp;Devendra Singh Gurjar","doi":"10.1016/j.phycom.2024.102540","DOIUrl":"10.1016/j.phycom.2024.102540","url":null,"abstract":"<div><div>This work examines the performance of the terrestrial–underwater communication system utilizing hybrid free space optics (FSO)/radio-frequency (RF) and underwater wireless optical communication (UWOC) links. Here, the base station communicates with the underwater vehicle via a decode-and-forward (DF) based relay (buoy) in two phases. In the first phase, a hybrid FSO/RF link is used to transmit signal to the buoy, where the RF link acts as an alternative link to increase the reliability of the system, and in the next phase, the buoy forwards signal to the underwater vehicle through the UWOC link. To enhance the reliability of the RF link, the buoy is deployed with multiple antennas, and it exploits a maximal ratio combining scheme on the received RF signals. The analysis takes into consideration some primary variables that influence the system’s performance, such as atmospheric turbulence, attenuation, temperature gradient, air bubbles, water salinity variations, pointing errors, and detection techniques. Closed-form expressions for the outage probability, system throughput, and average channel capacity in terms of the Meijer-<span><math><mi>G</mi></math></span> and bivariate Fox-<span><math><mi>H</mi></math></span> functions are derived. Simulation results are presented to validate the analytical expressions and disclose valuable findings.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"68 ","pages":"Article 102540"},"PeriodicalIF":2.0,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657979","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":"Enhancing performance of end-to-end communication system using Attention Mechanism-based Sparse Autoencoder over Rayleigh fading channel","authors":"Safalata S. Sindal,&nbsp;Y.N. Trivedi","doi":"10.1016/j.phycom.2024.102534","DOIUrl":"10.1016/j.phycom.2024.102534","url":null,"abstract":"<div><div>Deep learning has revolutionized communication systems by introducing innovative approaches to address channel impairments through end-to-end models. Autoencoders, a type of deep learning architecture, are adept at learning compact data representations. However, conventional autoencoders in end-to-end models can suffer from overfitting, which limits their effectiveness in noisy communication environments. To address this issue, we propose a Sparse Autoencoder-based (SAE) model that enforces sparsity and promotes the extraction of robust features. Despite its effectiveness, the SAE model may still lack the ability to focus on the most relevant features of the input data. To overcome this limitation, we further introduce an Attention Mechanism-based Sparse Autoencoder (ASA) model. This model integrates the feature extraction capabilities of a sparse autoencoder with an attention mechanism that selectively highlights informative features of the signal. Through simulations, we demonstrate that both proposed models significantly improve <span><math><mi>M</mi></math></span>-PSK and <span><math><mi>M</mi></math></span>-QAM communication system performance. When trained at 7 dB, both proposed models exhibit significant performance improvements at higher testing average SNRs. Our results show that the SAE model outperforms the conventional Maximum Likelihood Detection (MLD) model and baseline autoencoder systems but suffers from error floor issues. The SAE model suffers from an error floor at average SNRs beyond 16 dB for BPSK and 14 dB for higher-order modulation schemes. As the value of <span><math><mi>M</mi></math></span> increases, the performance gap between the MLD and the proposed SAE model narrows. The ASA model, however, effectively mitigates the error floor observed in the SAE model for all values of <span><math><mi>M</mi></math></span> and across all modulation schemes. This research highlights the benefits of integrating an attention mechanism with SAE, resulting in enhanced robustness and reliability in communication systems characterized by improved accuracy and reduced error rates.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"67 ","pages":"Article 102534"},"PeriodicalIF":2.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663718","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":"Modified fractional power allocation for downlink cell-free massive MIMO systems","authors":"Xiaohui Zhang,&nbsp;Dongle Wang,&nbsp;Ling Xing,&nbsp;Honghai Wu","doi":"10.1016/j.phycom.2024.102537","DOIUrl":"10.1016/j.phycom.2024.102537","url":null,"abstract":"<div><div>Cell-free massive multiple-input multiple-output (mMIMO) significantly improves the spectral efficiency (SE) performance compared to conventional centralized mMIMO through its distributed antenna architecture. Fractional power allocation (FPA) algorithm is widely used for scalable power control with good performance in downlink (DL) of cell-free mMIMO. In this paper, we propose modified FPA (MFPA) and generalized FPA (GFPA) strategies for centralized and distributed precoding in the DL of cell-free networks, respectively. For the former, we abandon the traditional normalization of precoding vectors and introduce three adjustment parameters, which can dynamically adjust the power allocation of the DL according to the actual channel conditions. Regarding the latter, the GFPA strategy finds effective channel factors suitable for various distributed precoding schemes and correlates them with the power allocation coefficients of each user equipment (UE), enabling power allocation to adapt to multiple precoding schemes. Analysis and simulation results demonstrate that, under the MFPA strategy, UEs with poorer channel conditions can achieve higher SE, but at the expense of other UEs with better channel conditions. Under the GFPA strategy, UEs with better channel conditions experience significant SE improvements without sacrificing UEs performance with poorer channel conditions.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"67 ","pages":"Article 102537"},"PeriodicalIF":2.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663714","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":"Clustering based strategic 3D deployment and trajectory optimization of UAVs with A-star algorithm for enhanced disaster response","authors":"Humairah Hamid,&nbsp;G.R. Begh","doi":"10.1016/j.phycom.2024.102536","DOIUrl":"10.1016/j.phycom.2024.102536","url":null,"abstract":"<div><div>A broad spectrum of communication and information technologies is currently being investigated for their potential applications in disaster management. A high level of situational awareness, combined with a prompt and accurate response, is essential for the preservation of life during catastrophe scenarios. This study presents a novel communication strategy employing Unmanned Aerial Vehicles (UAVs) as aerial base stations for providing connectivity to the affected area. The system takes advantage of the flexibility and quick deployment characteristics of UAVs. The main focus is to determine the optimal UAV deployment along with trajectory planning to ensure connectivity in areas where conventional base stations are inaccessible. The proposed system employs two types of UAVs: cluster UAVs which act as stationary base stations and relay UAVs acting as mobile base stations. A three-step strategy is proposed to find the suitable location of cluster UAVs, optimize their height and power, and find the optimal trajectory of the relay UAVs to maximize the percentage of users served. Gaussian Mixture Model (GMM) clustering is employed to determine the optimal horizontal location of cluster UAVs. An optimization problem is framed for finding out the optimal height and power for cluster UAVs. Heuristic-based A-star algorithm is used to find out the trajectory of the relay UAVs which can efficiently minimize the overall path length while avoiding obstacles. The simulation results confirm the effectiveness of the proposed approach and demonstrate the performance enhancement by comparing it with the benchmark schemes.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"67 ","pages":"Article 102536"},"PeriodicalIF":2.0,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663707","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":"Joint RSU and agent vehicle cooperative localization using mmWave sensing","authors":"Yuanxin Liu ,&nbsp;Demin Li ,&nbsp;Xuemin Chen","doi":"10.1016/j.phycom.2024.102535","DOIUrl":"10.1016/j.phycom.2024.102535","url":null,"abstract":"<div><div>In vehicle networks, accurate vehicle localization is crucial. This paper proposes a joint roadside unit (RSU) and agent vehicles cooperative localization framework based on dual-function radar-communication (DFRC) technology. It utilizes unscented Kalman filtering (UKF) to process DFRC signals and obtain vehicle status information. To improve the angle prediction accuracy of the agent vehicle, an angle fusion estimation scheme based on the maximum likelihood algorithm is proposed. Furthermore, a weighted method is introduced within the joint RSU and agent vehicle cooperative localization to enhance vehicle localization accuracy. Experimental results demonstrate that the proposed angle fusion scheme reduces angle estimation error, and the joint RSU and agent vehicle localization framework significantly improves vehicle localization accuracy.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"67 ","pages":"Article 102535"},"PeriodicalIF":2.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663715","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":"Reconfigurable Intelligent Surfaces Assisted NLOS Radar Anti Jamming Using Deep Reinforcement Learning","authors":"Muhammad Majid Aziz,&nbsp;Aamir Habib,&nbsp;Adnan Zafar","doi":"10.1016/j.phycom.2024.102533","DOIUrl":"10.1016/j.phycom.2024.102533","url":null,"abstract":"<div><div>The complexity of the radar environment increases with technological advancement, especially when considering the difficulties presented by repeating jammers. These jammers can impede radar detection, especially when they create false targets in non-line-of-sight (NLOS) situations. This study focuses on optimizing the phase shifts of Reconfigurable Intelligent Surfaces (RIS) to address the problem of NLOS between a target and radar for detection in order to address these NLOS issues. Specifically, we investigate RIS phase shift optimization using a Genetic Algorithm (GA) to address the challenges posed by repeating jammers across various dynamic scenarios. Our objective is to increase the radar system’s ability to detect actual targets in non-LOS scenarios when repeater jammers are present in the environment. According to the experimental results, this method offers a practical way to mitigate the effects of repeater jammers by improving radar detection performance in NLOS environments.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"67 ","pages":"Article 102533"},"PeriodicalIF":2.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663706","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":"Integrated sensing and communications waveform design: Fundamentals, applications, challenges","authors":"Zhongqiang Luo ,&nbsp;Zaiqiang Wang","doi":"10.1016/j.phycom.2024.102532","DOIUrl":"10.1016/j.phycom.2024.102532","url":null,"abstract":"<div><div>Integrated Sense of Communication (ISAC) is gradually becoming one of the core technologies in the sixth-generation mobile communication system. ISAC enhances spectrum efficiency and reduces equipment size, costs, and power consumption while minimizing interference between the two functions. The technology is introduced in terms of historical background and definition, application scenarios, current problems of ISAC technology, and the development history of ISAC technology. The latest research progress of ISAC technology is summarized in terms of waveform design, introducing sensing-centered waveform design, communication-centered waveform design, and sensing-communication joint waveform design, respectively. The ISAC waveform performance index introduces the performance aspects that need attention in waveform design to achieve improvement. It presents the application of ISAC technology in some recent emerging technologies and the current challenges and future outlook of ISAC waveform design.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"67 ","pages":"Article 102532"},"PeriodicalIF":2.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663713","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}