Journal of Communications and Information Networks最新文献_第2页

Quick and Good: A DRL Based Communication-Caching-Energy Joint Optimization Scheme for Prolonging the Lifetime of UAV Assisted IoE 快速与良好：基于DRL的延长无人机辅助物联网寿命的通信-缓存-能量联合优化方案

Journal of Communications and Information Networks Pub Date : 2024-12-01 DOI: 10.23919/JCIN.2024.10820159

Chun Zhu;Guilong Zhu;Jie Yang;Miao Liu;Zheng Shi

{"title":"Quick and Good: A DRL Based Communication-Caching-Energy Joint Optimization Scheme for Prolonging the Lifetime of UAV Assisted IoE","authors":"Chun Zhu;Guilong Zhu;Jie Yang;Miao Liu;Zheng Shi","doi":"10.23919/JCIN.2024.10820159","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10820159","url":null,"abstract":"The rapid increase in the number of Internet of things (IoT) devices has led to significant access pressure, making network energy consumption and communication load key challenges. Edge caching, cooperative communication, and energy management technologies have proven to be effective in alleviating these issues. This paper investigates a unmanned aerial vehicle (UAV)-assisted Internet of everything (IoE) architecture that integrates caching, communication, and energy management. A collaborative communication-caching-energy optimization scheme is proposed, which involves the joint operation of the UAV and base station (BS) to pre-cache content required by ground users, thus minimizing system energy consumption. We model the joint optimization of content caching, communication, and energy consumption as a Markov decision process (MDP), transforming it into a long-term optimization problem solvable by deep reinforcement learning. Based on the simple deep Q-network (DQN), we design a dynamic content placement strategy that jointly optimizes communication, caching, and energy consumption. Simulation results demonstrate that the proposed method, compared to branch and bound (B&B), particle swarm optimization (PSO), genetic algorithm (GA), and random algorithms, not only approaches the optimal solution most closely, effectively reducing system energy consumption, but also exhibits the lowest time complexity.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 4","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912490","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

AeroLOBE: A Deep Learning-Based Novel Load Balancer for Aerial Communication to Enhance the Performance of 6G Networks AeroLOBE：一种基于深度学习的新型空中通信负载均衡器，可提高6G网络的性能

Journal of Communications and Information Networks Pub Date : 2024-12-01 DOI: 10.23919/JCIN.2024.10820167

Tushar Vrind;Debabrata Das

{"title":"AeroLOBE: A Deep Learning-Based Novel Load Balancer for Aerial Communication to Enhance the Performance of 6G Networks","authors":"Tushar Vrind;Debabrata Das","doi":"10.23919/JCIN.2024.10820167","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10820167","url":null,"abstract":"While the low-altitude platform (LAP)-based aerial cells help improve the coverage and capacity for the telecom operator, the deployment and management of the aerial fleet is a non-trivial problem from both a capital expenditure (CAPEX) and an operational expenditure (OPEX) perspective. On the one hand, it is critical to keep the fleet size to a minimum to reduce CAPEX, while on the other hand, it is critical to optimally associate user equipment (UE) with aerial cells in order to maximize the use of aerial cell resources and serve more pieces of UE. Existing research on balancing UE load among aerial cells discusses mechanisms like coverage and capacity optimization. To the best of our knowledge, this is the first time we have treated the forecasted data traffic volume for each user as well as inter-UE traffic consideration to jointly optimize capacity maximization for aerial cells, latency minimization in inter-UE communication, and aerial fleet size minimization. To this end, we present a deep learning-based novel aerial load balancer (AeroLOBE) for aerial communication using a novel constraint fractional group multiple knapsack problem (F-GMKP) formulation and the knapsack optimization (KO) for associating users to LAPs, thereby enhancing performance for the network. Through mathematical modelling and extensive simulation, we show that AeroLOBE reduces the latency of inter-UE communication by over 39% and improves the resource utilization by over 10%, while keeping the blocking rate and fleet reduction targets similar or marginally better than the available load balancing schemes in the literature.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 4","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912488","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

Sonar Echo Simulation Technology Based on Array Phase Weight Estimation 基于阵相权估计的声纳回波仿真技术

Journal of Communications and Information Networks Pub Date : 2024-12-01 DOI: 10.23919/JCIN.2024.10820164

Jun Liu;Shenghua Gong;Tong Zhang;Wenxue Guan;Zhenxiang Zhao

{"title":"Sonar Echo Simulation Technology Based on Array Phase Weight Estimation","authors":"Jun Liu;Shenghua Gong;Tong Zhang;Wenxue Guan;Zhenxiang Zhao","doi":"10.23919/JCIN.2024.10820164","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10820164","url":null,"abstract":"Sonar locates underwater targets by receiving reflected sound waves. However, the complex marine environment makes it difficult to set targets in appropriate locations and conditions. The sonar echo simulator has the function of simulating sonar detection target echo signals. As a cutting-edge technology, underwater backscatter has led to the emergence of array based acoustic reflection systems. The research on sonar echo simulators based on backscatter technology has promoted the solution of problems such as target echo modeling, sonar arrival direction estimation, and echo directional transmission. In response to the above problems, this paper designs an end-to-end sonar echo simulator system array phase estimation sonar echo simulation system (APE-SESS), which can independently complete high-resolution real-time direction of arrival (DOA) estimation and generate directional simulation echo based on the array structure. Dual branch convolutional neural network (DB-CNN) is proposed in the system to estimate the direction of the signal array and directly obtain the phase weights containing azimuth information. Comparing DB-CNN with conventional methods and classic underwater DOA network models based on classification problems, the results show that DB-CNN exhibits stability, small error, and high real-time performance under different signal-to-noise ratio (SNR). The proposed APE-SESS has end-to-end characteristics, real-time angle estimation, and azimuth simulation functions.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 4","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912364","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

Waveform Design for Wireless Powered and Backscatter Hybrid Communication System 无线供电与反向散射混合通信系统的波形设计

Journal of Communications and Information Networks Pub Date : 2024-12-01 DOI: 10.23919/JCIN.2024.10820158

Yuxin Ding;Bin Rao;Jie Hu

{"title":"Waveform Design for Wireless Powered and Backscatter Hybrid Communication System","authors":"Yuxin Ding;Bin Rao;Jie Hu","doi":"10.23919/JCIN.2024.10820158","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10820158","url":null,"abstract":"For the waveform design and research of wireless powered and backscatter hybrid communication system, it is crucial to balance energy harvesting with ensuring communication rate performance. Considering the communication needs of traditional users in the hybrid communication system is particularly practical. In this paper, we study the model of wireless powered and backscatter hybrid communication system, while also taking the traditional orthogonal frequency division multiplexing (OFDM) user system into account. We jointly design the transmitting signal waveform and the backscatter signal waveform to ensure the communication performance of the traditional user while simultaneously enhancing the communication and energy transmission performance of the hybrid communication system. We maximize the signal-to-noise ratio (SNR) at the receiver by jointly optimizing the amplitude and phase of the transmitted signal waveform from the radio frequency (RF) source and the reflection coefficient of the backscatter device (BD). Furthermore, we use geometric programming methods to solve the problem. The simulation results confirm the effectiveness of the proposed scheme.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 4","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912582","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

Cost-Effective Federated Learning-Based Approach for SINR Prediction in Cellular-Connected UAVs 基于成本效益的基于联邦学习的蜂窝连接无人机SINR预测方法

Journal of Communications and Information Networks Pub Date : 2024-12-01 DOI: 10.23919/JCIN.2024.10820163

Ibrahem Mouhamad;Dushantha Nalin K. Jayakody;Dejan Vukobratovic

{"title":"Cost-Effective Federated Learning-Based Approach for SINR Prediction in Cellular-Connected UAVs","authors":"Ibrahem Mouhamad;Dushantha Nalin K. Jayakody;Dejan Vukobratovic","doi":"10.23919/JCIN.2024.10820163","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10820163","url":null,"abstract":"This study introduces a novel approach to empower cellular-connected unmanned aerial vehicles (UAVs) in predicting signal quality. The proposed prediction model leverages data collected by the UAVs, addressing privacy concerns and ensuring effectiveness, while taking into account the constraints of UAVs. A unique three-step approach is proposed, which integrates a detailed physical ray-tracing (RT) method, deep learning, and federated learning (FL) for continuous learning and field adaptation. A dual input feature fusion convolutional neural network (DIFF-CNN) model is proposed, which is pretrained on RT data and fine-tuned using data collected by the UAVs via FL. The proposed model demonstrates superior performance and robustness to data sparsity compared to traditional machine learning algorithms. Notably, the model achieves a root mean squared error of 0.837 dB and an R-squared of 97.7% for signal-to-interference-plus-noise ratio (SINR) prediction after the fine-tuning step in the fixed-altitude scenario, but performance drops with uniform altitude distribution, highlighting the impact of flying height on fine-tuning. The research indicates that the proposed approach can enhance performance while reducing training rounds by 35% to 90%, thus mitigating FL overheads. Future research could explore efficiency gains by using different pretrained models tailored to specific flying heights.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 4","pages":"374-389"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912584","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

FCLA-DT: Federated Continual Learning with Authentication for Distributed Digital Twin-Based Industrial IoT FCLA-DT：基于分布式数字孪生的工业物联网联邦持续学习与认证

Journal of Communications and Information Networks Pub Date : 2024-12-01 DOI: 10.23919/JCIN.2024.10820161

Yingjie Xia;Xuejiao Liu;Yunxiao Zhao;Yun Wang

{"title":"FCLA-DT: Federated Continual Learning with Authentication for Distributed Digital Twin-Based Industrial IoT","authors":"Yingjie Xia;Xuejiao Liu;Yunxiao Zhao;Yun Wang","doi":"10.23919/JCIN.2024.10820161","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10820161","url":null,"abstract":"Digital twin (DT) technology is currently pervasive in industrial Internet of things (IoT) applications, notably in predictive maintenance scenarios. Prevailing digital twin-based predictive maintenance methodologies are constrained by a narrow focus on singular physical modeling paradigms, impeding comprehensive analysis of diverse factory data at scale. This paper introduces an improved method, federated continual learning with authentication for distributed digital twin-based industrial IoT (FCLA-DT). This decentralized strategy ensures the continual learning capability vital for adaptive and real-time decision-making in complex industrial predictive maintenance systems. An authentication scheme based on group signature is introduced to enable the verification of digital twin identities during inter-twin collaborations, avoiding unauthorized access and potential model theft. Security analysis shows that FCLA-DT can enable numerous nodes to collaborate learning without compromising individual twin privacy, thereby ensuring group authentication in the cooperative distributed industrial IoT. Performance analysis shows that FCLA-DT outperforms traditional federated learning methods with over 95% fault diagnosis accuracy and ensures the privacy and authentication of digital twins in multi-client task learning.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 4","pages":"362-373"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912392","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

AIoT for Aircraft Final Assembly: An Intelligent and Collaborative Framework 用于飞机总装的人工智能物联网：智能协作框架

Journal of Communications and Information Networks Pub Date : 2024-09-01 DOI: 10.23919/JCIN.2024.10707102

Cheng Ren;Xiaojing Wen;Xinping Guan;Cailian Chen;Yehan Ma

{"title":"AIoT for Aircraft Final Assembly: An Intelligent and Collaborative Framework","authors":"Cheng Ren;Xiaojing Wen;Xinping Guan;Cailian Chen;Yehan Ma","doi":"10.23919/JCIN.2024.10707102","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10707102","url":null,"abstract":"Aircraft final assembly line (AFAL) involves thousands of processes that must be completed before delivery. However, the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery time. While the advent of artificial intelligence of things (AIoT) technologies has introduced advancements in certain AFAL scenarios, systematically enhancing the intelligence level of the AFAL and promoting the widespread deployment of artificial intelligence (AI) technologies remain significant challenges. To address these challenges, we propose the intelligent and collaborative aircraft assembly (ICAA) framework, which integrates AI technologies within a cloud-edge-terminal architecture. The ICAA framework is designed to support AI-enabled applications in the AFAL, with the goal of improving assembly efficiency at both individual and multiple process levels. We analyze specific demands across various assembly scenarios and introduce corresponding AI technologies to meet these demands. The three-tier ICAA framework consists of the assembly field, edge data platform, and assembly cloud platform, facilitating the collection of heterogeneous terminal data and the deployment of AI technologies. The framework enhances assembly efficiency by reducing reliance on manual labor for individual processes and fostering collaboration across multiple processes. We provide detailed descriptions of how AI functions at each level of the framework. Furthermore, we apply the ICAA framework to a real AFAL, focusing explicitly on the flight control system testing process. This practical implementation demonstrates the effectiveness of the framework in improving assembly efficiency and promoting the adoption of AIoT technologies.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 3","pages":"262-276"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397329","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

Design and Implementation of NOMA Backscatter Communication with Low-Precision Oscillators 利用低精度振荡器设计和实现 NOMA 后向散射通信

Journal of Communications and Information Networks Pub Date : 2024-09-01 DOI: 10.23919/JCIN.2024.10707107

Kun Zhang;Zhongye Cao;Huixin Dong;Zhiqing Luo;Luanjian Bian;Wei Wang

引用次数: 0

Pilot-Free End-to-End Underwater Acoustic Communication System Based on Autoencoder 基于自动编码器的无先导端到端水下声学通信系统

Journal of Communications and Information Networks Pub Date : 2024-09-01 DOI: 10.23919/JCIN.2024.10707108

Yizhe Wang;Deqing Wang;Liqun Fu

引用次数: 0

Intra-Band LTE Backscatter 带内 LTE 背向散射

Journal of Communications and Information Networks Pub Date : 2024-09-01 DOI: 10.23919/JCIN.2024.10707100

Wenhui Li;Meng Jin;Xiaohua Tian

{"title":"Intra-Band LTE Backscatter","authors":"Wenhui Li;Meng Jin;Xiaohua Tian","doi":"10.23919/JCIN.2024.10707100","DOIUrl":"https://doi.org/10.23919/JCIN.2024.10707100","url":null,"abstract":"Due to the continuity of long term evolution (LTE) downlink traffic, LTE signal has been considered as a promising excitation signal for ubiquitous backscatter communication. But this continuity also brings challenges in performing self-interference cancellation. Existing backscatter designs commonly use frequency shifting to move backscattered signal away from the entire excitation band to avoid self-interference. However, due to the continuity of LTE signal, LTE bands are occupied continuously. So, there is no enough white spectrum for frequency shifting. To solve this problem, we in this paper propose a novel LTE backscatter design, which can avoid self-interference without leveraging extra spectrum. Our idea is proposed based on a full understanding of the LTE resource grid, where we find that although a band is occupied by an excitation signal, there are still reserved resource elements in the traffic. We can leverage such resource elements as in-band white space to transmit backscatter signal. Meanwhile, we address the self-cancellation issue caused by double sideband modulation, and deal with the aligning issue. Our design is evaluated using a testbed of backscatter hardware and software defined radio (SDR). The results show that our system achieves a distance of 24 m for line-of-sight (LOS) transmit-to-tag communication. Besides, we demonstrate that our system can operate on off-the-shelf eNodeB. It can achieve reliable backscatter in multi-path scenarios, with a power consumption 6.3 times less than its least counterpart.","PeriodicalId":100766,"journal":{"name":"Journal of Communications and Information Networks","volume":"9 3","pages":"207-218"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397324","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