Pub Date : 2025-04-01DOI: 10.23919/JCN.2025.000029
{"title":"Open access publishing agreement","authors":"","doi":"10.23919/JCN.2025.000029","DOIUrl":"https://doi.org/10.23919/JCN.2025.000029","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"133-135"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011503","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Direct transmissions in cognitive radio networks (CRNs) can be easily obstructed by obstacles and channel uncertainty and thus cognitive transmitters normally increase the transmission power to guarantee the quality of service; however, it can deplete limited-capacity batteries and degrade long-term performance. These issues can be solved by reflecting signals to cognitive users (CUs) using a reconfigurable intelligent surface (RIS) and setting appropriate transmission powers. This study investigates RIS-aided downlink of non-orthogonal multiple access (NOMA) CRNs, where RIS can reconstruct transmission environments and a wireless powered-cognitive base station (CBS) opportunistically uses a licensed channel allowing multi-user transmissions in the same frequency and time block. Under stochastic properties of energy harvesting, wireless channels, and primary network behavior, we aim to optimize the assigned power of CUs and RIS phase-shifts jointly to maximize the sum-rate of CRNs. To this end, we formulate an optimization problem as a Markov decision process (MDP) framework. Subsequently, a deep deterministic policy gradient (DDPG) algorithm is adopted to cope with highdimensional continuous states and action spaces in time-varying environments. Simulation results are presented to confirm the superior performance of the proposed scheme over benchmark schemes in which orthogonal multiple access (OMA), long-term, and myopic optimizations are considered.
{"title":"RIS-aided transmissions in energy-harvesting cognitive radio networks: A DRL approach","authors":"Hoang Thi Huong Giang;Pham Duy Thanh;Tran Nhut Khai Hoan;Haneul Ko;Sangheon Pack","doi":"10.23919/JCN.2025.000016","DOIUrl":"https://doi.org/10.23919/JCN.2025.000016","url":null,"abstract":"Direct transmissions in cognitive radio networks (CRNs) can be easily obstructed by obstacles and channel uncertainty and thus cognitive transmitters normally increase the transmission power to guarantee the quality of service; however, it can deplete limited-capacity batteries and degrade long-term performance. These issues can be solved by reflecting signals to cognitive users (CUs) using a reconfigurable intelligent surface (RIS) and setting appropriate transmission powers. This study investigates RIS-aided downlink of non-orthogonal multiple access (NOMA) CRNs, where RIS can reconstruct transmission environments and a wireless powered-cognitive base station (CBS) opportunistically uses a licensed channel allowing multi-user transmissions in the same frequency and time block. Under stochastic properties of energy harvesting, wireless channels, and primary network behavior, we aim to optimize the assigned power of CUs and RIS phase-shifts jointly to maximize the sum-rate of CRNs. To this end, we formulate an optimization problem as a Markov decision process (MDP) framework. Subsequently, a deep deterministic policy gradient (DDPG) algorithm is adopted to cope with highdimensional continuous states and action spaces in time-varying environments. Simulation results are presented to confirm the superior performance of the proposed scheme over benchmark schemes in which orthogonal multiple access (OMA), long-term, and myopic optimizations are considered.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"78-91"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-04-01DOI: 10.23919/JCN.2025.000019
Song Luo;Pengyi Zeng;Chao Ma;Yifei Wei
With the rapid growth of the Industrial Internet of Things (IIoT), more and more devices are connecting to the network, generating vast amounts of data, including sensors, actuators, and controllers. Traditional anomaly detection methods often rely on centralized data collection, leading to concerns about privacy leakage and data centralization. To address these challenges, approaches that combine federated learning (FL) with blockchain technology offer an efficient, scalable solution. These methods enable automatic scaling based on system size, adapting to increasing devices and data traffic. However, the limitations of fixed shards and security risks associated with the aggregation of data from different shards introduce new issues. To overcome these challenges, this paper proposes a self-adaptive blockchain sharding strategy, based on IIoT device grouping, which jointly optimizes the number of shards and the security of model updates. This optimization is modeled as a Markov Decision Process (MDP), with deep reinforcement learning (DRL) used to determine the optimal device sharding parameters. Furthermore, a joint committee mechanism is introduced to ensure secure cross-shard transactions, while a federated learning filtering mechanism (Fed-Filt) is applied to enhance the accuracy and security of global model aggregation by screening out malicious nodes. In the clustering experiments, the proposed method shows significant improvements in clustering quality metrics such as Normalized Mutual Information (NMI), Adjusted Rand Index (ARI), Adjusted Mutual Information (AMI), and silhouette score, with faster convergence. Experimental results demonstrate that under 25% and 50% malicious node scenarios, the proposed algorithm can effectively resist poisoning attacks and achieve stable convergence, outperforming the traditional FedAvg algorithm. Specifically, with 50% malicious nodes, the accuracy is improved by approximately 27.8%, and the method exhibits strong resistance and recovery capabilities.
{"title":"Anomaly detection for industrial Internet of Things devices based on self-adaptive blockchain sharding and federated learning","authors":"Song Luo;Pengyi Zeng;Chao Ma;Yifei Wei","doi":"10.23919/JCN.2025.000019","DOIUrl":"https://doi.org/10.23919/JCN.2025.000019","url":null,"abstract":"With the rapid growth of the Industrial Internet of Things (IIoT), more and more devices are connecting to the network, generating vast amounts of data, including sensors, actuators, and controllers. Traditional anomaly detection methods often rely on centralized data collection, leading to concerns about privacy leakage and data centralization. To address these challenges, approaches that combine federated learning (FL) with blockchain technology offer an efficient, scalable solution. These methods enable automatic scaling based on system size, adapting to increasing devices and data traffic. However, the limitations of fixed shards and security risks associated with the aggregation of data from different shards introduce new issues. To overcome these challenges, this paper proposes a self-adaptive blockchain sharding strategy, based on IIoT device grouping, which jointly optimizes the number of shards and the security of model updates. This optimization is modeled as a Markov Decision Process (MDP), with deep reinforcement learning (DRL) used to determine the optimal device sharding parameters. Furthermore, a joint committee mechanism is introduced to ensure secure cross-shard transactions, while a federated learning filtering mechanism (Fed-Filt) is applied to enhance the accuracy and security of global model aggregation by screening out malicious nodes. In the clustering experiments, the proposed method shows significant improvements in clustering quality metrics such as Normalized Mutual Information (NMI), Adjusted Rand Index (ARI), Adjusted Mutual Information (AMI), and silhouette score, with faster convergence. Experimental results demonstrate that under 25% and 50% malicious node scenarios, the proposed algorithm can effectively resist poisoning attacks and achieve stable convergence, outperforming the traditional FedAvg algorithm. Specifically, with 50% malicious nodes, the accuracy is improved by approximately 27.8%, and the method exhibits strong resistance and recovery capabilities.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"92-102"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011497","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-04-01DOI: 10.23919/JCN.2025.000015
Xi Liu;Jun Liu;Changqing Du;Xiuhua Zeng;Weidong Li
Vehicle computing holds great potential to provide computation, communication, sensing, and data storage. To accelerate the application of vehicle computing, we address the problem of resource allocation and pricing in vehicle computing (PAPVC), in which the vehicle, as a resource provider, provides heterogeneous resources to serve users through access points or the internet. In our model, each user has multiple tasks of different values under budget constraints, and vehicles have different costs. We formulate the RAPVC problem in a reverse auction-based setting, where a user is regarded as an auctioneer, and the vehicles are regarded as the participants in the auction. However, the vehicle providers are self-interested, and they can submit untrue declarations to maximize the utility. Thus, we aim to design a truthfulness mechanism to maximize group efficiency. We propose a greedy mechanism to solve the PAPVC problem. We then show the proposed mechanism is truthful; that is, our proposed mechanism drives the system into an equilibrium. In addition, we show the proposed mechanism achieves individual rationality, consumer sovereignty, budget feasibility, and computation efficiency. Furthermore, we analyze the approximation ratio of the proposed approximation algorithm. Simulation results indicate that the average percent gap between solutions obtained by the proposed mechanism and optimal solutions is 22%.
{"title":"Budget-feasible truthful mechanism for resource allocation and pricing in vehicle computing","authors":"Xi Liu;Jun Liu;Changqing Du;Xiuhua Zeng;Weidong Li","doi":"10.23919/JCN.2025.000015","DOIUrl":"https://doi.org/10.23919/JCN.2025.000015","url":null,"abstract":"Vehicle computing holds great potential to provide computation, communication, sensing, and data storage. To accelerate the application of vehicle computing, we address the problem of resource allocation and pricing in vehicle computing (PAPVC), in which the vehicle, as a resource provider, provides heterogeneous resources to serve users through access points or the internet. In our model, each user has multiple tasks of different values under budget constraints, and vehicles have different costs. We formulate the RAPVC problem in a reverse auction-based setting, where a user is regarded as an auctioneer, and the vehicles are regarded as the participants in the auction. However, the vehicle providers are self-interested, and they can submit untrue declarations to maximize the utility. Thus, we aim to design a truthfulness mechanism to maximize group efficiency. We propose a greedy mechanism to solve the PAPVC problem. We then show the proposed mechanism is truthful; that is, our proposed mechanism drives the system into an equilibrium. In addition, we show the proposed mechanism achieves individual rationality, consumer sovereignty, budget feasibility, and computation efficiency. Furthermore, we analyze the approximation ratio of the proposed approximation algorithm. Simulation results indicate that the average percent gap between solutions obtained by the proposed mechanism and optimal solutions is 22%.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"103-118"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011505","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-04-01DOI: 10.23919/JCN.2024.000065
Xiaojia Chen;Chunlong He;Xingquan Li
The effectiveness of passive reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) may be limited by significant path loss. Active RIS addresses the “multiplicative fading” observed in traditional passive RIS systems. However, the absence of a radio frequency chain in the RIS poses challenges in acquiring necessary channel state information (CSI) at the base station (BS). We investigates an active RIS-assisted SWIPT system with partial CSI. By optimizing transmit and reflection beamforming concurrently, the RIS and BS minimize power consumption while meeting requirements for information and energy receivers, along with a rate outage constraint for the Eve. Simulation results show that active RIS approach offers a promising solution to mitigate power loss and improve overall SWIPT system performance.
{"title":"Active RIS aided SWIPT secure communication system with partial CSI","authors":"Xiaojia Chen;Chunlong He;Xingquan Li","doi":"10.23919/JCN.2024.000065","DOIUrl":"https://doi.org/10.23919/JCN.2024.000065","url":null,"abstract":"The effectiveness of passive reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) may be limited by significant path loss. Active RIS addresses the “multiplicative fading” observed in traditional passive RIS systems. However, the absence of a radio frequency chain in the RIS poses challenges in acquiring necessary channel state information (CSI) at the base station (BS). We investigates an active RIS-assisted SWIPT system with partial CSI. By optimizing transmit and reflection beamforming concurrently, the RIS and BS minimize power consumption while meeting requirements for information and energy receivers, along with a rate outage constraint for the Eve. Simulation results show that active RIS approach offers a promising solution to mitigate power loss and improve overall SWIPT system performance.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"70-77"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011502","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-04-01DOI: 10.23919/JCN.2025.000018
Jihyeon Yun;Bon-Jun Ku;Daesub Oh;Changhee Joo
In low Earth orbit (LEO) satellite networks, multiple satellites contend for limited frequency resources when they provide downlink services to ground users, necessitating efficient interference management. Particularly when there are multiple LEO service providers that do not explicitly exchange messages, satellites should learn about per-channel per-user interference. The problem is very challenging due to high learning complexity increasing with user population and time-varying interference caused by satellite orbiting. By exploiting reinforced learning (RL) techniques, we develop a low-complexity learning scheme that effectively allocate resources in respond to time-varying interference in multi-user multi-channel LEO satellite networks. The proposed scheme employs a hierarchical structure that aggregates information, reducing the complexity substantially, and enables the learning during short contact time. We demonstrate through simulations that our proposed scheme improves the sample efficiency and enhances throughput performance through successful interference management.
{"title":"Hierarchical learning for interference management in multi-user LEO satellite networks","authors":"Jihyeon Yun;Bon-Jun Ku;Daesub Oh;Changhee Joo","doi":"10.23919/JCN.2025.000018","DOIUrl":"https://doi.org/10.23919/JCN.2025.000018","url":null,"abstract":"In low Earth orbit (LEO) satellite networks, multiple satellites contend for limited frequency resources when they provide downlink services to ground users, necessitating efficient interference management. Particularly when there are multiple LEO service providers that do not explicitly exchange messages, satellites should learn about per-channel per-user interference. The problem is very challenging due to high learning complexity increasing with user population and time-varying interference caused by satellite orbiting. By exploiting reinforced learning (RL) techniques, we develop a low-complexity learning scheme that effectively allocate resources in respond to time-varying interference in multi-user multi-channel LEO satellite networks. The proposed scheme employs a hierarchical structure that aggregates information, reducing the complexity substantially, and enables the learning during short contact time. We demonstrate through simulations that our proposed scheme improves the sample efficiency and enhances throughput performance through successful interference management.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"119-126"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011499","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-04-01DOI: 10.23919/JCN.2025.000028
{"title":"Information for authors","authors":"","doi":"10.23919/JCN.2025.000028","DOIUrl":"https://doi.org/10.23919/JCN.2025.000028","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"128-132"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011506","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-04-01DOI: 10.23919/JCN.2025.000017
Ping Zhang;Qing Zhang;Tengfei Ma;Muhua Liu;Ji Zhang;Jiechang Wang
Internet of medical things (IoMT) is the application of the Internet of things in the medical industry, which enables the storage and processing of patients' medical data. Due to the sensitivity and confidentiality of medical data, security requirements for medical IoT must simultaneously protect data privacy and patient confidentiality. Group signature schemes can satisfy these requirements simultaneously. Serving as a fundamental cryptographic tool, they allow for the anonymous signing of messages. In this paper, based on the Chinese remainder theorem (CRT) and combined with techniques such as trap sampling, orthogonal sampling, and Gaussian sample preimage, a lattice-based group signature scheme is constructed. Compared with existing group signature schemes, this scheme does not require modification of already generated keys when adding or removing members, thus enabling rapid addition or removal of group members. Security analysis demonstrates that this scheme meets anonymity, unforgeability, and resistance against collusion attacks. Finally, the scheme is applied to the model construction of medical IoT to ensure the security and integrity of private data.
医疗物联网（Internet of medical things, IoMT）是物联网在医疗行业的应用，实现了对患者医疗数据的存储和处理。由于医疗数据的敏感性和保密性，医疗物联网的安全要求必须同时保护数据隐私和患者机密。群签名方案可以同时满足这些要求。作为基本的加密工具，它们允许对消息进行匿名签名。本文以中国剩余定理为基础，结合陷阱采样、正交采样和高斯样本预像等技术，构造了一种基于格的群签名方案。与现有的群签名方案相比，该方案在添加或删除成员时不需要修改已经生成的密钥，从而可以快速添加或删除组成员。安全性分析表明，该方案具有匿名性、不可伪造性和抗合谋攻击能力。最后，将该方案应用于医疗物联网的模型构建中，以保证私有数据的安全性和完整性。
{"title":"Lattice-based group signature scheme and its application in IoMT","authors":"Ping Zhang;Qing Zhang;Tengfei Ma;Muhua Liu;Ji Zhang;Jiechang Wang","doi":"10.23919/JCN.2025.000017","DOIUrl":"https://doi.org/10.23919/JCN.2025.000017","url":null,"abstract":"Internet of medical things (IoMT) is the application of the Internet of things in the medical industry, which enables the storage and processing of patients' medical data. Due to the sensitivity and confidentiality of medical data, security requirements for medical IoT must simultaneously protect data privacy and patient confidentiality. Group signature schemes can satisfy these requirements simultaneously. Serving as a fundamental cryptographic tool, they allow for the anonymous signing of messages. In this paper, based on the Chinese remainder theorem (CRT) and combined with techniques such as trap sampling, orthogonal sampling, and Gaussian sample preimage, a lattice-based group signature scheme is constructed. Compared with existing group signature schemes, this scheme does not require modification of already generated keys when adding or removing members, thus enabling rapid addition or removal of group members. Security analysis demonstrates that this scheme meets anonymity, unforgeability, and resistance against collusion attacks. Finally, the scheme is applied to the model construction of medical IoT to ensure the security and integrity of private data.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 2","pages":"59-69"},"PeriodicalIF":2.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11011504","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-02-01DOI: 10.23919/JCN.2025.000004
Chen Chen;Fengfan Yang;Hongjun Xu;Lawrence Muthama Paul
In this manuscript, inspired by the special construction of generalized Reed-Solomon (GRS) codes, we prove that any linear block code can be contained by a high-dimensional GRS code from the perspective of the isomorphism between the code space and the polynomial space. Then, a new code family, named quasi-GRS codes, is constructed, which can exactly contain a GRS code of lower 1-dimensional (1-D) and be contained by a higher 1-D GRS code. Furthermore, the exhaustive search approach is developed to assist in selecting the quasi-GRS code with the optimal code weight distribution. In addition, a multi-step simplified maximum likelihood decoding (MSS-MLD) is proposed to efficiently decode the quasi-GRS coding scheme, whose decoding complexity is significantly reduced at an acceptable performance loss compared to the optimal MLD. From the Monte-Carlo simulation, the optimized quasi-GRS coding scheme outperforms the existing non-binary Bose-Chaudhuri-Hocquenghem (BCH) coding scheme with a similar code rate by a margin of over 1 dB at the high signal-to-noise (SNR) region under identical channel conditions.
{"title":"Optimized design of quasi-GRS codes with multi-step simplified MLD","authors":"Chen Chen;Fengfan Yang;Hongjun Xu;Lawrence Muthama Paul","doi":"10.23919/JCN.2025.000004","DOIUrl":"https://doi.org/10.23919/JCN.2025.000004","url":null,"abstract":"In this manuscript, inspired by the special construction of generalized Reed-Solomon (GRS) codes, we prove that any linear block code can be contained by a high-dimensional GRS code from the perspective of the isomorphism between the code space and the polynomial space. Then, a new code family, named quasi-GRS codes, is constructed, which can exactly contain a GRS code of lower 1-dimensional (1-D) and be contained by a higher 1-D GRS code. Furthermore, the exhaustive search approach is developed to assist in selecting the quasi-GRS code with the optimal code weight distribution. In addition, a multi-step simplified maximum likelihood decoding (MSS-MLD) is proposed to efficiently decode the quasi-GRS coding scheme, whose decoding complexity is significantly reduced at an acceptable performance loss compared to the optimal MLD. From the Monte-Carlo simulation, the optimized quasi-GRS coding scheme outperforms the existing non-binary Bose-Chaudhuri-Hocquenghem (BCH) coding scheme with a similar code rate by a margin of over 1 dB at the high signal-to-noise (SNR) region under identical channel conditions.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 1","pages":"40-49"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10923676","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
Pub Date : 2025-02-01DOI: 10.23919/JCN.2025.000002
Ken Long;Hongjun Liu
Hybrid precoding is a crucial technique for massive multiple-input multiple-output (MIMO) systems owing to its capability to offer an adequate beamforming gain while reducing the hardware cost. However, the nonconvex objective functions and constraints pose great challenges to hybrid precoders design. The conventional precoding method that contains a two-step process including channel estimation and precoding design based on such estimate is not necessarily optimal to tackle this problem. In this article, a transformer-empowered approach waiving high-dimensional channel estimation is proposed to design precoders with the goal of simplifying the complicated hybrid precoding problem into the optimization of neural network structure. Specifically, the proposed approach learns channel sensing from uplink pilots and then operates downlink hybrid precoding depended on interleaved-polymerization-transformer-based analog precoding network (IPTAP-Net) which decomposes on a peruser basis and conventional linear digital precoding algorithm to reduce computational complexity in multi-user systems. Simulations show that the proposed methodology acquires remarkable performance improvement and strong robustness, as compared to state-of-the-art hybrid precoding schemes. Furthermore, proposed approach develops a generalizable talent for manifold multi-user cells.
{"title":"Transformer-enabled hybrid precoding for TDD large-scale antenna arrays systems with channel sensing","authors":"Ken Long;Hongjun Liu","doi":"10.23919/JCN.2025.000002","DOIUrl":"https://doi.org/10.23919/JCN.2025.000002","url":null,"abstract":"Hybrid precoding is a crucial technique for massive multiple-input multiple-output (MIMO) systems owing to its capability to offer an adequate beamforming gain while reducing the hardware cost. However, the nonconvex objective functions and constraints pose great challenges to hybrid precoders design. The conventional precoding method that contains a two-step process including channel estimation and precoding design based on such estimate is not necessarily optimal to tackle this problem. In this article, a transformer-empowered approach waiving high-dimensional channel estimation is proposed to design precoders with the goal of simplifying the complicated hybrid precoding problem into the optimization of neural network structure. Specifically, the proposed approach learns channel sensing from uplink pilots and then operates downlink hybrid precoding depended on interleaved-polymerization-transformer-based analog precoding network (IPTAP-Net) which decomposes on a peruser basis and conventional linear digital precoding algorithm to reduce computational complexity in multi-user systems. Simulations show that the proposed methodology acquires remarkable performance improvement and strong robustness, as compared to state-of-the-art hybrid precoding schemes. Furthermore, proposed approach develops a generalizable talent for manifold multi-user cells.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 1","pages":"23-31"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10923678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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}
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