Digital Communications and Networks最新文献

{"title":"Performance analysis of UAV-based mixed underwater PLC-RF systems","authors":"Shenghai Chen ,&nbsp;Liang Yang ,&nbsp;Xianfu Lei","doi":"10.1016/j.dcan.2022.11.015","DOIUrl":"10.1016/j.dcan.2022.11.015","url":null,"abstract":"<div><div>In this study, we analyzed the performance of an Unmanned Aerial Vehicle (UAV)-based mixed Underwater Power Line Communication-Radio Frequency (UPLC-RF) network. In this network, a buoy located at the sea is used as a relay to transmit signals from the underwater signal source to the UAV through the PLC link. We assume that the UPLC channel obeys a log-normal distribution and that the RF link follows the Rician distribution. Using this model, we obtained the closed-form expressions for the Outage Probability (OP), Average Bit-error-rate (ABER), and Average Channel Capacity (ACC). In addition, the asymptotic analysis of the OP and ABER was performed, and an upper bound for the average capacity was obtained. Finally, the analytical results were verified by Monte Carlo simulation thereby demonstrating the effect of impulse noise and the altitude of the UAV on network performance.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1332-1340"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47885792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AQROM: A quality of service aware routing optimization mechanism based on asynchronous advantage actor-critic in software-defined networks","authors":"Wei Zhou ,&nbsp;Xing Jiang ,&nbsp;Qingsong Luo ,&nbsp;Bingli Guo ,&nbsp;Xiang Sun ,&nbsp;Fengyuan Sun ,&nbsp;Lingyu Meng","doi":"10.1016/j.dcan.2022.11.016","DOIUrl":"10.1016/j.dcan.2022.11.016","url":null,"abstract":"<div><div>In Software-Defined Networks (SDNs), determining how to efficiently achieve Quality of Service (QoS)-aware routing is challenging but critical for significantly improving the performance of a network, where the metrics of QoS can be defined as, for example, average latency, packet loss ratio, and throughput. The SDN controller can use network statistics and a Deep Reinforcement Learning (DRL) method to resolve this challenge. In this paper, we formulate dynamic routing in an SDN as a Markov decision process and propose a DRL algorithm called the Asynchronous Advantage Actor-Critic QoS-aware Routing Optimization Mechanism (AQROM) to determine routing strategies that balance the traffic loads in the network. AQROM can improve the QoS of the network and reduce the training time via dynamic routing strategy updates; that is, the reward function can be dynamically and promptly altered based on the optimization objective regardless of the network topology and traffic pattern. AQROM can be considered as one-step optimization and a black-box routing mechanism in high-dimensional input and output sets for both discrete and continuous states, and actions with respect to the operations in the SDN. Extensive simulations were conducted using OMNeT++ and the results demonstrated that AQROM 1) achieved much faster and stable convergence than the Deep Deterministic Policy Gradient (DDPG) and Advantage Actor-Critic (A2C), 2) incurred a lower packet loss ratio and latency than Open Shortest Path First (OSPF), DDPG, and A2C, and 3) resulted in higher and more stable throughput than OSPF, DDPG, and A2C.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1405-1414"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44963829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance comparison of single-carrier and multi-carrier waveforms over terahertz wireless channels","authors":"Dongxuan He ,&nbsp;Zhi Zhang ,&nbsp;Hao Lin ,&nbsp;Zuomin Wu ,&nbsp;Yingpei Huang ,&nbsp;Zhaocheng Wang","doi":"10.1016/j.dcan.2023.07.001","DOIUrl":"10.1016/j.dcan.2023.07.001","url":null,"abstract":"<div><div>Terahertz (THz) wireless communication has been recognized as a powerful technology to meet the ever-increasing demand of ultra-high rate services. In order to achieve efficient and reliable wireless communications over THz bands, it is extremely necessary to find an appropriate waveform for THz communications. In this paper, performance comparison of various single-carrier and multi-carrier waveforms over THz channels will be provided. Specifically, first, a system model for terahertz communication is briefly described, which includes amplifier nonlinearity, propagation characteristic, phase noise, etc. Then, the transceiver architectures related to both single-carrier and multi-carrier waveforms are presented, as well as their corresponding signal processing techniques. To evaluate the suitability of the waveforms, key performance metrics concerning power efficiency, transmission performance, and computational complexity are provided. Simulation results are provided to compare and validate the performance of different waveforms, which demonstrate the outstanding performance of Discrete-Fourier-Transform spread Orthogonal Frequency Division Multiplexing (DFT-s-OFDM) to THz communications when compared to Cyclic Prefix-OFDM (CP-OFDM) and other single-carrier waveforms.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1297-1304"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43393650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability-aware swarm based multi-objective optimization for controller placement in distributed SDN architecture","authors":"Abeer A.Z. Ibrahim ,&nbsp;Fazirulhisyam Hashim ,&nbsp;Aduwati Sali ,&nbsp;Nor K. Noordin ,&nbsp;Keivan Navaie ,&nbsp;Saber M.E. Fadul","doi":"10.1016/j.dcan.2023.11.007","DOIUrl":"10.1016/j.dcan.2023.11.007","url":null,"abstract":"<div><div>The deployment of distributed multi-controllers for Software-Defined Networking (SDN) architecture is an emerging solution to improve network scalability and management. However, the network control failure affects the dynamic resource allocation in distributed networks resulting in network disruption and low resilience. Thus, we consider the control plane fault tolerance for cost-effective and accurate controller location models during control plane failures. This fault-tolerance strategy has been applied to distributed SDN control architecture, which allows each switch to migrate to next controller to enhance network performance. In this paper, the Reliable and Dynamic Mapping-based Controller Placement (RDMCP) problem in distributed architecture is framed as an optimization problem to improve the system reliability, quality, and availability. By considering the bound constraints, a heuristic state-of-the-art Controller Placement Problem (CPP) algorithm is used to address the optimal assignment and reassignment of switches to nearby controllers other than their regular controllers. The algorithm identifies the optimal controller location, minimum number of controllers, and the expected assignment costs after failure at the lowest effective cost. A metaheuristic Particle Swarm Optimization (PSO) algorithm was combined with RDMCP to form a hybrid approach that improves objective function optimization in terms of reliability and cost-effectiveness. The effectiveness of our hybrid RDMCP-PSO was then evaluated using extensive experiments and compared with other baseline algorithms. The findings demonstrate that the proposed hybrid technique significantly increases the network performance regarding the controller number and load balancing of the standalone heuristic CPP algorithm.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1245-1257"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139291489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent cache and buffer optimization for mobile VR adaptive transmission in 5G edge computing networks","authors":"Junchao Yang ,&nbsp;Ali Kashif Bashir ,&nbsp;Zhiwei Guo ,&nbsp;Keping Yu ,&nbsp;Mohsen Guizani","doi":"10.1016/j.dcan.2023.07.003","DOIUrl":"10.1016/j.dcan.2023.07.003","url":null,"abstract":"<div><div>Virtual Reality (VR) is a key industry for the development of the digital economy in the future. Mobile VR has advantages in terms of mobility, lightweight and cost-effectiveness, which has gradually become the mainstream implementation of VR. In this paper, a mobile VR video adaptive transmission mechanism based on intelligent caching and hierarchical buffering strategy in Mobile Edge Computing (MEC)-equipped 5G networks is proposed, aiming at the low latency requirements of mobile VR services and flexible buffer management for VR video adaptive transmission. To support <span>VR</span> content proactive caching and intelligent buffer management, users' behavioral similarity and head movement trajectory are jointly used for viewpoint prediction. The tile-based content is proactively cached in the MEC nodes based on the popularity of the VR content. Second, a hierarchical buffer-based adaptive update algorithm is presented, which jointly considers bandwidth, buffer, and predicted viewpoint status to update the tile chunk in client buffer. Then, according to the decomposition of the problem, the buffer update problem is modeled as an optimization problem, and the corresponding solution algorithms are presented. Finally, the simulation results show that the adaptive caching algorithm based on 5G intelligent edge and hierarchical buffer strategy can improve the user experience in the case of bandwidth fluctuations, and the proposed viewpoint prediction method can significantly improve the accuracy of viewpoint prediction by 15%.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1234-1244"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42527668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outage analysis of aerial semi-grant-free NOMA systems","authors":"Hongjiang Lei ,&nbsp;Chen Zhu ,&nbsp;Ki-Hong Park ,&nbsp;Imran Shafique Ansari ,&nbsp;Weijia Lei ,&nbsp;Hong Tang ,&nbsp;Kyeong Jin Kim","doi":"10.1016/j.dcan.2023.10.001","DOIUrl":"10.1016/j.dcan.2023.10.001","url":null,"abstract":"<div><div>In this paper, we analyze the outage performance of Unmanned Aerial Vehicles (UAVs)-enabled downlink Non-Orthogonal Multiple Access (NOMA) communication systems with the Semi-Grant-Free (SGF) transmission scheme. A UAV provides coverage services for a Grant-Based (GB) user and one Grant-Free (GF) user is allowed to utilize the same channel resource opportunistically. The analytical expressions for the exact and asymptotic Outage Probability (OP) of the GF user are derived. The results demonstrate that no-zero diversity order can be achieved only under stringent conditions on users' quality of service requirements. Subsequently, an efficient Dynamic Power Allocation (DPA) scheme is proposed to relax such data rate constraints. The analytical expressions for the exact and asymptotic OP of the GF user with the DPA scheme are derived. Finally, Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of the UAV's location and altitude on the OP of the GF user.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1529-1541"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135810412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of modified model of intelligent assembly digital twins based on optical fiber sensor network","authors":"Zhichao Liu ,&nbsp;Jinhua Yang ,&nbsp;Juan Wang ,&nbsp;Lin Yue","doi":"10.1016/j.dcan.2022.06.013","DOIUrl":"10.1016/j.dcan.2022.06.013","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Intelligent assembly of large-scale, complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing. During large-scale structural assembly processes, several bottleneck problems occur in the existing auxiliary assembly technology. First, the traditional LiDAR-based assembly technology is often limited by the openness of the manufacturing environment, in which there are blind spots, and continuous online assembly adjustment thus cannot be realized. Second, for assembly of large structures, a single-station LiDAR system cannot achieve complete coverage, which means that a multi-station combination method must be used to acquire the complete three-dimensional data; many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station, which means that the overall system's measurement and adjustment errors are increased greatly. Third, because of the large numbers of structural components contained in a large assembly, the accumulated errors may lead to assembly interference, but the LiDAR-assisted assembly process does not have a feedback perception capability, and thus assembly component loss can easily be caused when assembly interference occurs. Therefore, this paper proposes to combine an optical fiber sensor network with digital twin technology, which will allow the test data from the assembly entity state in the real world to be applied to the “twin” model in the virtual world and thus solve the problems with test openness and data transfer. The problem of station and perception feedback is also addressed and represents the main innovation of this work. The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time, and then completes real-time parameter adjustment of the virtual assembly based on the distributed data. Complex areas include areas that are laser-unreachable, areas with complex contact surfaces, and areas with large-scale bending deformations. An assembly condition monitoring system is designed based on the optical fiber sensor network, and an assembly condition monitoring algorithm based on multiple physical quantities is proposed. The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed. The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure. In the model optimization parameter module, a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data. The experiment simulates a large-scale structure assembly process, and performs virtual and real mapping for a variety of situations w","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1542-1552"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46696447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A low-complexity AMP detection algorithm with deep neural network for massive mimo systems","authors":"Zufan Zhang ,&nbsp;Yang Li ,&nbsp;Xiaoqin Yan ,&nbsp;Zonghua Ouyang","doi":"10.1016/j.dcan.2022.11.011","DOIUrl":"10.1016/j.dcan.2022.11.011","url":null,"abstract":"<div><div>Signal detection plays an essential role in massive Multiple-Input Multiple-Output (MIMO) systems. However, existing detection methods have not yet made a good tradeoff between Bit Error Rate (BER) and computational complexity, resulting in slow convergence or high complexity. To address this issue, a low-complexity Approximate Message Passing (AMP) detection algorithm with Deep Neural Network (DNN) (denoted as AMP-DNN) is investigated in this paper. Firstly, an efficient AMP detection algorithm is derived by scalarizing the simplification of Belief Propagation (BP) algorithm. Secondly, by unfolding the obtained AMP detection algorithm, a DNN is specifically designed for the optimal performance gain. For the proposed AMP-DNN, the number of trainable parameters is only related to that of layers, regardless of modulation scheme, antenna number and matrix calculation, thus facilitating fast and stable training of the network. In addition, the AMP-DNN can detect different channels under the same distribution with only one training. The superior performance of the AMP-DNN is also verified by theoretical analysis and experiments. It is found that the proposed algorithm enables the reduction of BER without signal prior information, especially in the spatially correlated channel, and has a lower computational complexity compared with existing state-of-the-art methods.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1375-1386"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44965846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel handover scheme for millimeter wave network: An approach of integrating reinforcement learning and optimization","authors":"Ruiyu Wang ,&nbsp;Yao Sun ,&nbsp;Chao Zhang ,&nbsp;Bowen Yang ,&nbsp;Muhammad Imran ,&nbsp;Lei Zhang","doi":"10.1016/j.dcan.2023.08.002","DOIUrl":"10.1016/j.dcan.2023.08.002","url":null,"abstract":"<div><div>The millimeter-Wave (mmWave) communication with the advantages of abundant bandwidth and immunity to interference has been deemed a promising technology to greatly improve network capacity. However, due to such characteristics of mmWave, as short transmission distance, high sensitivity to the blockage, and large propagation path loss, handover issues (including trigger condition and target beam selection) become much complicated. In this paper, we design a novel handover scheme to optimize the overall system throughput as well as the total system delay while guaranteeing the Quality of Service (QoS) of each User Equipment (UE). Specifically, the proposed handover scheme called O-MAPPO integrates the Reinforcement Learning (RL) algorithm and optimization theory. The RL algorithm known as Multi-Agent Proximal Policy Optimization (MAPPO) plays a role in determining handover trigger conditions. Further, we propose an optimization problem in conjunction with MAPPO to select the target base station. The aim is to evaluate and optimize the system performance of total throughput and delay while guaranteeing the QoS of each UE after the handover decision is made. The numerical results show the overall system throughput and delay with our method are slightly worse than that with the exhaustive search method but much better than that using another typical RL algorithm Deep Deterministic Policy Gradient (DDPG).</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1493-1502"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41564998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ECO++: Adaptive deep feature fusion target tracking method in complex scene","authors":"Yuhan Liu ,&nbsp;He Yan ,&nbsp;Qilie Liu ,&nbsp;Wei Zhang ,&nbsp;Junbin Huang","doi":"10.1016/j.dcan.2022.10.020","DOIUrl":"10.1016/j.dcan.2022.10.020","url":null,"abstract":"<div><div>Efficient Convolution Operator (ECO) algorithms have achieved impressive performances in visual tracking. However, its feature extraction network of ECO is unconducive for capturing the correlation features of occluded and blurred targets between long-range complex scene frames. More so, its fixed weight fusion strategy does not use the complementary properties of deep and shallow features. In this paper, we propose a new target tracking method, namely ECO++, using deep feature adaptive fusion in a complex scene, in the following two aspects: First, we constructed a new temporal convolution mode and used it to replace the underlying convolution layer in Conformer network to obtain an improved Conformer network. Second, we adaptively fuse the deep features, which output through the improved Conformer network, by combining the Peak to Sidelobe Ratio (PSR), frame smoothness scores and adaptive adjustment weight. Extensive experiments on the OTB-2013, OTB-2015, UAV123, and VOT2019 benchmarks demonstrate that the proposed approach outperforms the state-of-the-art algorithms in tracking accuracy and robustness in complex scenes with occluded, blurred, and fast-moving targets.</div></div>","PeriodicalId":48631,"journal":{"name":"Digital Communications and Networks","volume":"10 5","pages":"Pages 1352-1364"},"PeriodicalIF":7.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43434686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}