International Journal of Communication Systems最新文献

{"title":"Advanced Estimation and Feedback of Wireless Channels State Information for 6G Communication via Recurrent Conditional Wasserstein Generative Adversarial Network","authors":"Rajesh Kedarnath Navandar,&nbsp;Arun Ananthanarayanan,&nbsp;Shubhangi Milind Joshi,&nbsp;Nookala Venu","doi":"10.1002/dac.70033","DOIUrl":"https://doi.org/10.1002/dac.70033","url":null,"abstract":"<div>\u0000 \u0000 <p>In this manuscript, an Advanced Estimation and Feedback of Wireless Channels State Information for sixth generation (6G) Communication via Recurrent Conditional Wasserstein Generative Adversarial Network (AEF-WCSI-6G-RCWGAN) is proposed. Deep Learning (DL) based channel estimation algorithm using Recurrent Conditional Wasserstein Generative Adversarial Network (RCWGAN) is estimated the channel parameters in 6G, such as channel gains and delays from received signals, which is crucial for effective communication and resource allocation. The primary purpose of this paper is to discuss key issues and possible solutions in DL-based wireless channel estimation and channel state information (CSI) feedback including the DL model selection, training data acquisition and neural network design for 6G. The deep learning-dependent channel estimator refines the predicted channel output, which is subsequently used for increase the efficacy and dependability of the communication scheme. The proposed AEF-WCSI-6G-RCWGAN is implemented and the performance metrics, like Detection Success Probability, Mean Square Error (MSE), and Normalized Mean Square Error (NMSE) are analyzed. Finally, the performance of the proposed AEF-WCSI-6G-RCWGAN method achieves 30.73%, 28.35%, and 29.62% higher Detection Success Probability, 25.73%, 28.05%, and 24.62% lower MSE when compared with existing methods: towards DL-assisted wireless channel estimate and CSI feedback for sixth generation (WCE-CSI-6G-GAN), an effectual deep neural network channel state estimate for Orthogonal frequency-division multiplexing (OFDM)wireless systems (CSE-WS-BiLSTM), and distributed machine learning dependent downlink channel estimate for reconfigurable intelligent surfaces supported wireless communications (DCE-AWC-HDCENet) methods, respectively.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513728","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":"Dynamic Packet Routing Algorithm Based on Multidimensional Information and Multiagent Reinforcement Learning","authors":"Linliang Zhang,&nbsp;Ruifang Du,&nbsp;Zhiqiang Hao,&nbsp;Shuo Li,&nbsp;Zhiguo Hu","doi":"10.1002/dac.70039","DOIUrl":"https://doi.org/10.1002/dac.70039","url":null,"abstract":"<div>\u0000 \u0000 <p>Packet routing is one of the critical factors that affect network performance and security, with the goal of finding the optimal path for network packets from the source node to the destination node. However, with the diversification of network architectures, the differences in network application requirements, and the time-varying characteristics of network topologies, the limitations of traditional model- and rule-based routing algorithms in terms of computational overhead and flexibility are becoming increasingly apparent. This paper designs a packet routing strategy based on multiagent deep reinforcement learning (MIMRL). In MIMRL, each router node is abstracted as an independent agent with its own neural network. Multidimensional data such as the current location of the data packet, the number of nodes in the network, the length of the data packet received at the current location node, and the set of neighboring nodes are used as inputs to the neural network. Combined with a segmented reward function, the optimal routing action is determined. Experimental results under different network loads in static and dynamic networks show that the MIMRL algorithm significantly outperforms the benchmark algorithm in multiple metrics such as average delivery time and proportion of full capacity nodes.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143513659","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":"NeuroSync: A Novel Neural Network Architecture for Time Series Forecasting of Vehicle Traffic Data Over 5G and Beyond","authors":"Timothy Dkhar,&nbsp;Chandrasen Pandey,&nbsp;Sharmila A. J. Francis,&nbsp;Diptendu Sinha Roy,&nbsp;Ashish Kr Luhach","doi":"10.1002/dac.70035","DOIUrl":"https://doi.org/10.1002/dac.70035","url":null,"abstract":"<div>\u0000 \u0000 <p>The efficient management and prediction of urban traffic flow are paramount in the age of beyond 5G smart cities and advanced transportation systems. Traditional methods often fail to handle the nonlinear and dynamic nature of traffic data, necessitating more advanced solutions. This paper introduces <i>NeuroSync</i>, a novel neural network architecture designed to leverage the strengths of spiking neuron layers and gated recurrent units (GRUs) combined with temporal pattern attention mechanisms to effectively forecast traffic patterns. The architecture is specifically tailored to address the complexities inherent in nonstationary urban traffic datasets, capturing both spatial and temporal relationships within the data. <i>NeuroSync</i> not only outperforms traditional forecasting models such as ARIMA and exponential smoothing but also shows significant improvement over contemporary neural network approaches like LSTM, CNN, Seq2Seq, RNN, GRU, Transformer, and Autoencoder in terms of mean squared error (MSE) and mean absolute error (MAE). The model's efficacy is demonstrated through extensive experiments with real-world traffic data, underscoring its potential to enhance urban mobility management and support the infrastructure of intelligent transportation systems.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143496996","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":"Energy-Effective Optimal Routing–Driven Hybrid Optimizations–Enabled IoT-Based Wearable Wireless Body Area Network","authors":"I. Gethzi Ahila Poornima,&nbsp;Sravanthi Dontu,&nbsp;M. Maheswaran,&nbsp;Rohith Vallabhaneni","doi":"10.1002/dac.70037","DOIUrl":"https://doi.org/10.1002/dac.70037","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless body area networks (WBAN) are considerably playing a remarkable role in healthcare monitoring systems with the capacity to provide real-time information about patients. The challenging factor about WBAN is providing a better energy efficiency system with higher reliability. For better monitoring of health, wearable IoT smart devices are utilized. To achieve this, the work focused on energy-effective clustering and optimal routing with an improved optimization algorithm. The proposed work combines the Levy Flight and Frilled Lizard Optimization (LF²ZO) algorithm. The Levy flight strategy is used to enhance the exploration stages of FLO for the optimal energy-efficient routing system. This proposed method mitigates energy expenditure with high transmission reliability. The cluster formation in the area is effectuated with the Dynamic Self-executing Active Cross-propagated (DSAC) method with various factors such as Murkowski distance, Euclidian distance, and the desired number of clusters. Based on the connectivity and residual energy, the cluster head (CH) is selected using the Momentum Sparrow Search (MSS) algorithm. With the precise selection of CH, the transmission number and energy are reduced within interclustering and intraclustering. Simulation outcomes validate the robustness of the proposed work with the remarkable improvement of the network's lifespan with a higher packet delivery ratio. The energy expenditure is also lower and provides a promising solution for the optimal routing system. This work provides better sustainability of WBAN for the healthcare monitoring system.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489759","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":"QDND: Quorum-Based Energy Efficiency Aware Directional Neighbor Discovery in Ad Hoc Millimeter Wave Wireless Networks","authors":"Tingpei Huang,&nbsp;Bairen Zhang,&nbsp;Tiantian Zhang,&nbsp;Jianhang Liu,&nbsp;Shibao Li","doi":"10.1002/dac.70005","DOIUrl":"https://doi.org/10.1002/dac.70005","url":null,"abstract":"<div>\u0000 \u0000 <p>In ad hoc millimeter wave (mmWave) wireless networks, nodes typically use directional antennas to cope with their high path loss problem. Directional neighbor discovery is a crucial technology in the first step of establishing the mmWave communication network. However, directional antennas introduce new challenges to the neighbor discovery: beam alignment and heterogeneous operating mode problems. Meanwhile, the continuous neighbor discovery process leads to significant energy consumption. To solve the above challenges, this paper introduces a directional neighbor discovery algorithm QDND with an adjustable duty cycle based on the Grid Quorum system. Firstly, we design a duty cycle adaptive control algorithm to avoid continuous neighbor discovery processes. Secondly, we propose a sector scanning algorithm to guarantee the beam alignment. Finally, we design an operating mode scheduling algorithm to enable two neighbors to work in different operating modes simultaneously. We conduct extensive simulations under different network scenarios to validate the performance of the QDND. The numerical analysis and simulation results show that QDND outperforms existing directional neighbor discovery algorithms in terms of ATTD and MTTD in different numbers of nodes, beamwidths, and duty cycles.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489757","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":"On Outage Performance and Ergodic Capacity Analysis of Two User NOMA in a Cooperative Cognitive Radio Network With an Energy Harvesting Relay","authors":"Alok Baranwal,&nbsp;Hritwika Sarkar,&nbsp;Shashibhushan Sharma,&nbsp;Sumit Kundu","doi":"10.1002/dac.70015","DOIUrl":"https://doi.org/10.1002/dac.70015","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, a dual-hop cooperative nonorthogonal multiple access (NOMA) scheme is investigated in which two independent sources communicate simultaneously with their respective destinations over Rayleigh fading channel sharing a common time switching relay (TSR)-based energy harvesting decode and forward (DF) relay in an underlay cognitive radio network (CRN). A TSR protocol is used at the relay for harvesting energy from the signals of the two sources. After successful decoding the symbols of the sources using successive interference cancellation (SIC), the relay transmits a superposition coded (SC) composite signal to the destinations following downlink NOMA where SIC is performed at the destinations. Novel analytical expressions on outage probability of each user pair, system outage probability, and ergodic capacity of each user pair are derived. The transmit power allocation of each source satisfying an outage constraint of PU is obtained by solving a transcendental equation. A statistical distribution of the power harvested at the relay from two independent sources is also presented. Impact of tolerable interference threshold at the PU receiver, constraint on PU outage is indicated on outage and ergodic capacity of users. Monte Carlo simulation is performed using a testbed developed in MATLAB, and simulation results agree well with analytical results.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481365","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":"Indoor Ultrasonic Localization Using Artificial Rabbit Optimization Algorithm and BP Neural Network","authors":"Jia Chaochuan,&nbsp;Hua Rui,&nbsp;Yang Ting,&nbsp;Fu Maosheng,&nbsp;Zhou Xiancun,&nbsp;Huang Zhendong","doi":"10.1002/dac.70044","DOIUrl":"https://doi.org/10.1002/dac.70044","url":null,"abstract":"<div>\u0000 \u0000 <p>Although traditional BP neural networks have shown some improvement in ultrasonic indoor localization accuracy, it has a tendency to fall into the problem of local optimal solutions, which limits the localization accuracy. To address this issue, we propose the use of the artificial rabbit optimization (ARO) algorithm as an optimization strategy. The ARO algorithm dynamically adjusts and searches for weights and thresholds during the initialization and training of BP neural networks to find the global optimal solution. This approach efficiently explores the weight space and enhances the BP neural network's performance in ultrasonic localization tasks. Experiments have confirmed that the hybrid ARO-BP localization algorithm performs well in matching predicted trajectories with actual positions, especially in a 3D localization scenario constructed by six base stations. The algorithm produces excellent results in both line-of-sight (LOS) and non–line-of-sight (NLOS) environments, which are typical indoor settings. The ARO-BP neural network effectively reduces the average localization error and ensures high-precision localization under various transmission conditions and obstacle effects. In NLOS conditions, the positioning accuracy is improved by 16.05% with four tags and 10.92% with six tags, resulting in an average error reduction of 8.02 cm. The ARO-BP algorithm enhances positioning accuracy by 13.99% with four tags and 21.76% with six tags, resulting in an average error reduction of 12.01 cm. In conclusion, ARO-BP significantly improves the accuracy of ultrasonic localization in both LOS and NLOS indoor environments with reflections and diffractions. This advancement provides a new direction for the development of indoor positioning technology and is expected to lead to significant progress in practical applications within related fields.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481367","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":"Sectorially Sorted Densely Packed 12-Port MIMO Antenna With Improved Isolation Metrics","authors":"Asutosh Mohanty,&nbsp;Jyoti Ranjan Panda,&nbsp;Sudhakar Sahu","doi":"10.1002/dac.70040","DOIUrl":"https://doi.org/10.1002/dac.70040","url":null,"abstract":"<div>\u0000 \u0000 <p>An intuitive approach for investigating densely packed 12-port multi-input-multi-output (MIMO) antenna is investigated with improved isolation performance. Conventional dipole antenna elements are sectorially triangulated in a (3:3:3:3) manner that are sorted into cross-shaped profile corners asserting a premium footprint. This unique topology has been acknowledged to achieve effective impedance matching and simultaneously reduce mutual coupling in the proposed cross-coupled estate avoiding any additive decoupling network. The investigation shows that dipole arrays are coupled with a lumped L-C-L arrangement, whose dominant inductive resonance are stabilized by the center-fed capacitance. The arrangement has the inherent advantage of stable impedance bandwidth (6.5–7.5) GHz and effective decoupling between radiating elements with isolation magnitude ranges (24–30) dB. The simulated performance counterparts are meticulously experimented on a fabricated prototype to observe the potential scattering, isolation, and radiation parameters. The far-field envelope correlation coefficient between antenna elements shows minimal magnitude &lt; 0.02, exhibiting its potential for diversity parameters. The radiation peak gain shows 7.5 dBi with stable omni-directive patterns in the principal operating planes with maximum radiative efficiency (60–70)%, finding its applicability for mid-band advanced (5G) applications.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475571","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":"Evolutionary LightGBM-Based Intrusion Detection System for IoT Networks","authors":"Khushi Singal,&nbsp;Nisha Kandhoul,&nbsp;Sanjay K. Dhurander","doi":"10.1002/dac.70031","DOIUrl":"https://doi.org/10.1002/dac.70031","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid growth of the Internet of Things (IoT), securing interconnected devices is becoming increasingly critical. This paper introduces the <i>LightShield</i> intrusion detection system (IDS) to enhance intrusion detection in IoT environments using high-performance computing. <i>LightShield</i> features preprocessing of IoT data, <i>ReliefF</i> algorithm for feature selection, and a novel detection model based on <i>LightGBM</i>, a gradient boosting framework. The system leverages GPU acceleration for faster model validation, enabling real-time monitoring. By adapting to IoT characteristics, <i>LightShield</i> provides flexible, scalable defense against evolving cyber threats. Results show its potential to improve security in <i>IoT</i> ecosystems, offering valuable insights into anomaly-based intrusion detection and the future of secure <i>IoT</i> networks. The binary classification model displayed exceptional precision with a <i>99.82</i>% accuracy in detecting potential attacks, and the multiclass classification model achieved a commendable <i>97.25</i>% accuracy in classifying distinct attack types.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143456020","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":"User Scheduling With Limited Feedback for Multi-Cell MU-Massive MIMO FDD Networks Deployment: From Performance Tradeoff Perspective","authors":"Dukhishyam Sabat,&nbsp;Prabina Pattanayak,&nbsp;Akhilesh Kumar,&nbsp;Ganesh Prasad","doi":"10.1002/dac.70021","DOIUrl":"https://doi.org/10.1002/dac.70021","url":null,"abstract":"<div>\u0000 \u0000 <p>Feedback of channel state information (CSI) from users to base station (BS) is very vital for efficient user scheduling (US) in frequency division duplexing (FDD)–based massive multiple-input multiple-output (mMIMO) systems. The feedback overhead is one of the major bottlenecks for multi-user (MU) mMIMO systems as it increases with number of antennas and users. In the multicellular scenario, each and every BS schedules appropriate set of users based on the limited CSI feedback received from the users for achieving better throughput and fairness which are the prime objectives for such communication systems. To achieve the higher throughput, better fairness, and better scheduling gain with the least CSI, in this article, user grouping–based scheduling (UGS) strategy for multi-cell MU mMIMO FDD system is considered. The proposed UGS scheme achieves a better trade-off between the two prime objectives, that is, throughput and fairness. Moreover, hybrid precoding architecture is also used for this system as practically radio frequency (RF) chains are usually less in number to support less implementation complexity and budget. Our approach utilizes the angle of departure (AoD)–based adaptive codebook for controlling the amount of feedback. The variation of AoD is slow in nature as compared to path gains of the channel, which controls the feedback overhead. The proposed UGS using AoD codebook with limited channel feedback involves determining the beamspace path co-ordinates of each user from the AoD information fed back by users and then group the users into sets based on the AoD CSI. Specifically, UGS scheme is applied to reduce inter-user and inter-group interferences. By integrating an AoD adaptive subspace codebook with a hybrid precoding architecture and focusing on the dual objectives of maximizing throughput and fairness, we offer a novel solution that addresses the key challenges of inter-cell interference and limited CSI feedback. The numerical experiments show the effectiveness of the proposed UGS scheme for fifth generation and beyond wireless networks deployment.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 5","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447103","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}