International Journal of Communication Systems最新文献_第4页

Joint Optimization of Channel Bonding and Transmit Power Using Optimized Actor–Critic Deep Reinforcement Learning for Wireless Networks

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-10 DOI: 10.1002/dac.70049

Rajender Singh Yadav, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

{"title":"Joint Optimization of Channel Bonding and Transmit Power Using Optimized Actor–Critic Deep Reinforcement Learning for Wireless Networks","authors":"Rajender Singh Yadav, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla","doi":"10.1002/dac.70049","DOIUrl":"https://doi.org/10.1002/dac.70049","url":null,"abstract":"<div>\u0000 \u0000 <p>A high-capacity channel access mechanism is desirable for future Wi-Fi networks. This process must address two factors: channel bonding and spatial reuse. Channel bonding increases the transmission capacity of access points (APs), and in spatial reuse, the APs adjust their transmit power and clear channel assessment threshold (CCAT) to allow them to communicate simultaneously with nearby APs. For efficient channel access, simultaneous optimization is required regarding channel bonding and spatial reuse. To resolve this, a novel optimal Actor–Critic Deep Reinforcement Learning (OAC-DRL) algorithm is proposed to select the optimal AP's channel bonding policy, transmit power, and CCAT under random traffic and channel conditions. OAC-DRL incorporates an actor and critic network and a reward-shaping mechanism to regulate the optimal channel bonding policy for a wireless network. The inclusion of reward shaping reduces the learning time to obtain the optimal actions, whereas the optimality of the original optimal policy remains unchanged. The OAC-DRL algorithm is implemented using the Python. The experimental results show that the OAC-DRL algorithm minimizes queue lengths better under realistic traffic loads. In addition, the OAC-DRL algorithm transmits 4.82% more packets per time slot than other learning algorithms.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 7","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143595249","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}

引用次数: 0

Optimizing Wearable Textile Antennas for Accurate Long-Range Localization Using Interpretable Generalized Additive Neural Network

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-10 DOI: 10.1002/dac.70038

Perumalsamy Sasireka, Govindaraju Kavya

{"title":"Optimizing Wearable Textile Antennas for Accurate Long-Range Localization Using Interpretable Generalized Additive Neural Network","authors":"Perumalsamy Sasireka, Govindaraju Kavya","doi":"10.1002/dac.70038","DOIUrl":"https://doi.org/10.1002/dac.70038","url":null,"abstract":"<div>\u0000 \u0000 <p>The wearable monopole antenna is for long-range localization at the specific frequencies of 915 and 923 MHzwas built on a Rogers Duroid platform. It provides great efficiency, directed radiation, and low specific absorption rate (SAR) values, ensuring safety compliance. Real-world tests revealed a 3-dB gain in signal strength and a 1.5-km localization range. This makes the antenna a promising option for dependable LoRa-based tracking in a variety of environments. In this manuscript, optimizing wearable textile antennas for accurate long-range localization using interpretable generalized additive neural network (OWTA-ALRL-IGANN) is proposed. The IGANN is used to predict the <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>S</mi>\u0000 <mn>11</mn>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {S}_{11} $$</annotation>\u0000 </semantics></math> response of the antenna. As therefore, antenna performance is increased, design time is decreased, and complex data interactions can be managed more easily. Finally, the performance of OWTA-ALRL-IGANN method attains 19.11%, 17.21%, and 18.24% higher bandwidth; 18.23%, 19.20%, and 17.20% higher SAR; and 16.11%, 17.19%, and 15.21% lower return loss when comparing with existing techniques like machine learning–optimized wearable antenna for LoRa localization (ML-OWA-LL), optimization of a compact wearable LoRa patch antenna for vital sign monitoring in WBAN medical applications utilizing ML (LoRa-VSM-WBAN-ML), and a compact textile monopole antenna for monitoring the healing of bone fractures utilizing un-supervised machine learning algorithm (CTMA-BF-UMLA), respectively.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594919","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}

引用次数: 0

Network Traffic Prediction Based on Decomposition and Combination Model

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-08 DOI: 10.1002/dac.70056

Lian Lian

{"title":"Network Traffic Prediction Based on Decomposition and Combination Model","authors":"Lian Lian","doi":"10.1002/dac.70056","DOIUrl":"https://doi.org/10.1002/dac.70056","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, a combination model based on complementary ensemble empirical mode decomposition (CEEMD) is proposed. First, CEEMD is applied to decompose original network traffic to generate high-frequency component, low-frequency component, and residual component. Then, the high-frequency components are modeled and predicted using bi-directional long short-term memory (BiLSTM). The low-frequency components and the residual component are modeled and predicted using autoregressive integrated moving average (ARIMA). Meanwhile, considering that the BiLSTM model is influenced by the hyperparameters, an Improved Bald Eagle Search (IBES) algorithm is proposed and applied to optimize three hyperparameters of BiLSTM, avoiding the blindness and subjectivity of manual selection of parameters. Finally, the prediction values of BiLSTM and ARIMA model are summed to obtain the final predicted value of network traffic. The comparisons with other models proved that the proposed network traffic prediction model is closer to the real data, with the optimal performance indicators, which is very suitable for high precision occasions.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143571422","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}

引用次数: 0

Iterative Sparse Interference Cancelation Algorithm for Massive MIMO Uplink System

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-08 DOI: 10.1002/dac.70058

Qing-Yang Guan

引用次数: 0

A Combined Model WAPI Indoor Localization Method Based on UMAP

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-05 DOI: 10.1002/dac.70034

Jiasen Zhang, Xiaoxun Yang, Wei Zhu, Dongjie Wu, Jiashan Wan, Na Xia

{"title":"A Combined Model WAPI Indoor Localization Method Based on UMAP","authors":"Jiasen Zhang, Xiaoxun Yang, Wei Zhu, Dongjie Wu, Jiashan Wan, Na Xia","doi":"10.1002/dac.70034","DOIUrl":"https://doi.org/10.1002/dac.70034","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid advancement of the Internet, indoor localization technology has gained increasing importance across various fields. However, the complexity of indoor environments presents significant challenges for achieving precise positioning using GPS or BeiDou systems. As a result, there is a growing demand for innovative localization methods that deliver high accuracy, improved security, and cost-effectiveness. In this study, a dataset comprising 9291 fingerprints collected from a building was processed and split into training and test sets in a 7:3 ratio. To facilitate feature extraction, four algorithms—UMAP, LDA, PCA, and SVD—were employed. Subsequently, six machine learning models (KNN, Random Forest, ANN, SVM, GBDT, and XgBoost) were trained on the training set and evaluated on the test set to compare their performance with different feature extraction algorithms. The objective was to identify the most effective feature extraction method. Model performance was assessed using three metrics: average error, coefficient of determination, and accuracy. Finally, a stacking ensemble model was developed, incorporating the six models as primary learners and selecting the five models with superior predictive performance as secondary learners. This approach aimed to enhance the localization accuracy. UMAP feature extraction significantly improved the prediction accuracy of the indoor localization model, whereas the stacking ensemble model, combining KNN, GBDT, XgBoost, ANN, Random Forest, and SVM as primary learners and Random Forest as the secondary learner, achieved the highest localization accuracy, with an error of approximately 1.48 m.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554817","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}

引用次数: 0

Real-Time Mobile Data Traffic and Noise Monitoring System for AI Data Prediction Using Open Source Frame Work

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-05 DOI: 10.1002/dac.70052

E. Selvamanju, V. Baby Shalini

{"title":"Real-Time Mobile Data Traffic and Noise Monitoring System for AI Data Prediction Using Open Source Frame Work","authors":"E. Selvamanju, V. Baby Shalini","doi":"10.1002/dac.70052","DOIUrl":"https://doi.org/10.1002/dac.70052","url":null,"abstract":"<div>\u0000 \u0000 <p>The predictive analysis of mobile network traffic is important for future generation cellular networks. Knowing user requests in advance enables the system to allocate resources in the best way possible. In this manuscript, Real-Time Mobile Data Traffic and Noise monitoring System for AI Data Prediction Using open Source Frame Work (RMTNMS-OSF) is proposed. Unlike previous studies that primarily remained theoretical, this research aims to identify areas with the highest demand for 5G internet service and also promptly provide the information to IT professionals. This is significant because of the high demand for internet services among tech professionals working from home in rural areas. This developed software now utilizes HTML, OpenLayers, and real-time spatial location data along with the Google Satellite Map API as its base layer to detect user locations as well as to ensure uninterrupted high-speed internet service. The innovation of this proposed RMTNMS-OSF model lies in the integration of AI-driven predictive models with real-time geospatial data processing to optimize network performance in rural areas by dynamically predicting network demand, detecting congestion, and preventing data loss using cost-effective open-source technology, and this mark up a significant advancement in mobile network traffic prediction and resource allocation. The performance of the proposed RMTNMS-OSF method is evaluated with existing methods.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554818","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}

引用次数: 0

EFLB-IIoT: Enhanced Flow Control and Load Balancing Approach for SDN-Enabled Industrial Internet-of-Things

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-05 DOI: 10.1002/dac.70043

Santosh Kumar, Aruna Malik

{"title":"EFLB-IIoT: Enhanced Flow Control and Load Balancing Approach for SDN-Enabled Industrial Internet-of-Things","authors":"Santosh Kumar, Aruna Malik","doi":"10.1002/dac.70043","DOIUrl":"https://doi.org/10.1002/dac.70043","url":null,"abstract":"<div>\u0000 \u0000 <p>Software-defined networks (SDN) provide an efficient network architecture by enhancing global network monitoring and performance through the separation of the control plane from the data plane. In extensive SDN implementations for the Internet-of-Things (IoT), achieving high scalability and reducing controller load necessitates deploying multiple distributed controllers that collaboratively manage the network. Each controller oversees a subset of switches and gathers information about these switches and their interconnections, which can lead to imbalances in link and controller loads. Addressing these imbalances is crucial for improving quality of service (QoS) in SDN-enabled Industrial Internet-of-Things (IIoT) environments. In this paper, we present the NP-hardness of the link and controller load balancing routing (LCLBR) problem within IIoT. To tackle this issue, we propose an enhanced flow control and load balancing approach for SDN-enabled Industrial Internet-of-Things (EFLB-IIoT). EFLB-IIoT is an approximation-based technique that effectively maintains network activity among distributed controllers. Simulation results indicate that our proposed strategy reduces the maximum link load by 76% and the maximum controller response time by 85% compared to existing techniques, demonstrating superior performance over state-of-the-art methods.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554327","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}

引用次数: 0

Flamingo Lyrebird Optimization-Based Holistic Approach for Improving RFID-WSN Integrated Network Lifetime

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-05 DOI: 10.1002/dac.70036

V. Rajesh, A. Kaleel Rahuman

{"title":"Flamingo Lyrebird Optimization-Based Holistic Approach for Improving RFID-WSN Integrated Network Lifetime","authors":"V. Rajesh, A. Kaleel Rahuman","doi":"10.1002/dac.70036","DOIUrl":"https://doi.org/10.1002/dac.70036","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless sensor networks (WSNs) are considered a key foundation for high-level Internet of Things (IoT) practices. Moreover, WSNs depend on transmission for data transfer among sink modules and sensor nodes or intermediate points in the system. However, in WSN, there are several interruptions during the transmission of data. Further, storage space, network bandwidth, and processing power are limited, and hence, it is significant to enhance data distribution to improve network performance. Therefore, this paper devised a new approach known as the Flamingo Lyrebird Optimization Algorithm (FLOA) to improve radio frequency identification (RFID)-WSN integrated network lifetime. Firstly, the network topology of WSN-RFID is simulated, and then cluster head (CH) selection is performed by FLOA in terms of multiobjective fitness, namely, energy, network lifetime, and inter- and intracluster distance. Here, FLOA is formed by integrating Flamingo Search Optimization (FSA) and Lyrebird Optimization Algorithm (LOA). After this, the energy-efficient multipath routing is performed by utilizing FLOA, where link life time (LLT) and energy are predicted using a gated recurrent unit (GRU). Furthermore, FLOA attained the maximum performance with network lifetime and energy of 820.11, 0.923 J, and minimum delay of 0.211 s.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554326","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}

引用次数: 0

Design and Implementation of Heterogeneous Route Selection Algorithm for Delay Minimization in VANET

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-03 DOI: 10.1002/dac.70032

Cloudin Swamynathan, John Deva Prasanna D. S, K. Anusha

{"title":"Design and Implementation of Heterogeneous Route Selection Algorithm for Delay Minimization in VANET","authors":"Cloudin Swamynathan, John Deva Prasanna D. S, K. Anusha","doi":"10.1002/dac.70032","DOIUrl":"https://doi.org/10.1002/dac.70032","url":null,"abstract":"<div>\u0000 \u0000 <p>Data dissemination is a promising use in Vehicular Ad hoc NETworks (VANETs), where messages are jointly carried and delivered by vehicles toward their destinations at defined points. Vehicles find it challenging to select the target uplink node among the roadside units (RSU) put in VANETs due to the RSU coverage, traffic intensity, and other sophisticated and dynamic affecting factors. In this study, a new adaptive vehicle clustering method is proposed that attempts to reduce the power consumption of automobiles. It dynamically distributes the computational assets of every virtual machine within the automobile. The <i>mimosa pudica</i> clustering optimization algorithm (MPCOA) is used to identify the ideal clustering number to reduce the overall energy consumption of the cars, and the clustering head is chosen based on the direction the vehicles are going, their weighted mobility, and their entropy. A cluster head (CH) oversees all intercluster and intracluster communication. Some factors to gauge the effectiveness of a network include the load on every CH, the lifespan of the cluster, and the overall number of clusters in the network. The new cluster is well suited for this type of huge data, in which they are separated into similarity, variations, and neighborhoods as different types of VANET features along with their combinational groups. Using a test bed and numerous simulations, the suggested system efficacy is assessed. Conducting a performance study and comparing the test bed findings to the simulation results provides a thorough understanding of the performance and viability of the proposed MPCOA-based system.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535873","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}

引用次数: 0

Research and Implementation of a Hybrid MIMO Detection Algorithm

IF 1.7 4区计算机科学

International Journal of Communication Systems Pub Date : 2025-03-03 DOI: 10.1002/dac.70051

Xinwei Li, Wei Chen, Zhuhua Hu, Qingbo Zhai, Biao Long

{"title":"Research and Implementation of a Hybrid MIMO Detection Algorithm","authors":"Xinwei Li, Wei Chen, Zhuhua Hu, Qingbo Zhai, Biao Long","doi":"10.1002/dac.70051","DOIUrl":"https://doi.org/10.1002/dac.70051","url":null,"abstract":"<div>\u0000 \u0000 <p>Multiple-input multiple-output (MIMO) technology plays a crucial role in the field of wireless communications. As one of the key technologies, MIMO signal detection ensures the reliability of communication systems and achieves high throughput transmission. In this paper, to find a high-performance and low-complexity detection algorithm, a hybrid detection algorithm is proposed based on the K-best detection algorithm. The hybrid algorithm employs the minimum mean square error (MMSE) linear detection algorithm combined with sorted QR decomposition (SQRD) for preprocessing, followed by signal detection using the K-best detection algorithm. Compared with the traditional K-best detection algorithm, the proposed method shows significant performance improvement. To address the computational complexity issue caused by the fixed K value in each layer of the hybrid detection algorithm, an adaptive threshold algorithm is introduced to select an appropriate K value for each layer, significantly reducing the algorithm's complexity. On the hardware implementation level, not only is the overall algorithm architecture optimized but a lookup table (LUT) based sorting algorithm is also proposed to address the sorting delay issue in the hybrid detection algorithm. Comprehensive analysis shows that this detector, implemented in a 28-nm process, achieves a throughput of 4.8 Gbps at a clock frequency of 769 MHz, presenting a significant advantage compared with other literature.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 6","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535868","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}

引用次数: 0