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Batch Gradient Descent-based Optimization of WMMSE for Rate Splitting Strategy 基于批量梯度下降的WMMSE速率分割策略优化
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940341
Zhijie Wang, Ruhui Ma, Hongjian Shi, Liwei Lin, Haibing Guan
{"title":"Batch Gradient Descent-based Optimization of WMMSE for Rate Splitting Strategy","authors":"Zhijie Wang, Ruhui Ma, Hongjian Shi, Liwei Lin, Haibing Guan","doi":"10.1109/ISWCS56560.2022.9940341","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940341","url":null,"abstract":"Rate Splitting (RS) multiple access is a general and robust multiple access framework for downlink multi-antenna communication systems, which splits each user's message into common and private parts, and superposes the common message and the private message for transmission. To find the transmit beamforming design, the Alternate Optimization Weighted Minimize MSE (AO-WMMSE) algorithm is often used as one of the approaches to maximize WSR due to its low computational complexity and good convergence. However, AO-WMMSE is inefficient in large-scale calculations and when the number of users and antennas is large. We propose a Batch Gradient Descent-based Weighted Minimum MSE (BGD-WMMSE) method rapidly optimize the linear precoder for large-scale data computing. Simulations show that BGD-WMMSE can achieve the same size of maximum achievable rate region as AO-WMMSE in one-layer RS deployment.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132297227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Low-Complexity Cross-Domain OAMP Detector for OTFS: (Invited Paper) 面向OTFS的低复杂度跨域OAMP检测器(特邀论文)
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940366
Haifeng Wen, W. Yuan, N. Wu, Jinming Wen
{"title":"A Low-Complexity Cross-Domain OAMP Detector for OTFS: (Invited Paper)","authors":"Haifeng Wen, W. Yuan, N. Wu, Jinming Wen","doi":"10.1109/ISWCS56560.2022.9940366","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940366","url":null,"abstract":"Orthogonal time frequency space (OTFS) modulation is an emerging technique for reliable communications in high-mobility environments. Designing low-complexity detectors with good error rate performance is a critical research problem for OTFS. To address this problem, a low-complexity cross-domain orthogonal approximate message passing (OAMP) de-tector is proposed. In specific, by utilizing the block-diagonal property of the time-domain effective channel matrix, an SVD-based orthogonal linear estimator with low complexity is designed, followed by an orthogonal nonlinear estimator performed in the delay-Doppler domain with the help of the cross-domain message passing. We prove that the proposed detector has the potential to achieve Bayes optimality. The state evolution of the cross-domain OAMP detector is also derived. Numerical results show that the proposed detector outperforms classic detectors.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"306 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132959995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Exploiting Lens Antenna Arrays in Uplink mmWave MU-MIMO Networks: Joint Beamforming Optimization 利用上行毫米波MU-MIMO网络中的透镜天线阵列:联合波束形成优化
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940256
Chongjun Ouyang, Haoman Xu, Xujie Zang, Hongwen Yang
{"title":"Exploiting Lens Antenna Arrays in Uplink mmWave MU-MIMO Networks: Joint Beamforming Optimization","authors":"Chongjun Ouyang, Haoman Xu, Xujie Zang, Hongwen Yang","doi":"10.1109/ISWCS56560.2022.9940256","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940256","url":null,"abstract":"This paper considers a lens antenna array-assisted millimeter wave (mmWave) multiuser multiple-input multiple-output (MU-MIMO) system. The base station's beam selection matrix and user terminals' phase-only beamformers are jointly designed with the aim of maximizing the uplink sum rate. In order to deal with the formulated mixed-integer optimization problem, a penalty dual decomposition (PDD)-based iterative algorithm is developed via capitalizing on the weighted minimum mean square error (WMMSE), block coordinate descent (BCD), and minorization-maximization (MM) techniques. Moreover, a low-complexity sequential optimization (SO)-based algorithm is proposed at the cost of a slight sum rate performance loss. Numerical results demonstrate that the proposed methods can achieve higher sum rates than state-of-the-art methods.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116716843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
GraphHO: A Graph-based Handover Optimization System for Cellular Networks 基于图的蜂窝网络切换优化系统
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940345
L. Yang, Min Cheng, Jun Qu, Zhitang Chen
{"title":"GraphHO: A Graph-based Handover Optimization System for Cellular Networks","authors":"L. Yang, Min Cheng, Jun Qu, Zhitang Chen","doi":"10.1109/ISWCS56560.2022.9940345","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940345","url":null,"abstract":"Handover optimization is an important task for the load balancing and mobility robustness in cellular networks. However, the cells in a cellular network often overlap and present strong interactions with nearby neighborhood. This renders the handover optimization a challenging problem. In this paper, we propose a novel graph convolutional neural network to capture the complex interaction between overlapping cells. With this graph model, we further develop a contextual bandit solution to optimize the handover efficiency of a cellular networks. Practical challenges derived from the real-world deployment, such as noisy environment and safety constraint, are also well-investigated and addressed. Extensive experiments in a simulation platform and a real-world cellular network demonstrate that our solution can significantly improve the network quality without a prejudice of network stability.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121972005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Deep Learning with a Self-Adaptive Threshold for OTFS Channel Estimation 基于自适应阈值的深度学习OTFS信道估计
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940260
Xiaoqi Zhang, W. Yuan, Chang Liu, F. Liu, Miaowen Wen
{"title":"Deep Learning with a Self-Adaptive Threshold for OTFS Channel Estimation","authors":"Xiaoqi Zhang, W. Yuan, Chang Liu, F. Liu, Miaowen Wen","doi":"10.1109/ISWCS56560.2022.9940260","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940260","url":null,"abstract":"The recently developed orthogonal time frequency space (OTFS) technology has proved its capability to cope with the fast time-varying channels in high-mobility scenarios. In particular, the channel model in the delay-Doppler (DD) domain has a sparse representation, and its associated channel estimation can be realized by adopting one embedded pilot scheme. However, it may face performance degradation in scenarios with unknown and burst noise. In this paper, we develop a deep learning (DL)-based method to deal with complicated noise. In particular, we consider the sparsity of the OTFS channel and propose a deep residual shrinkage network (DRSN) to implicitly learn the residual noise for recovering the channel information. In addition, to further improve the channel estimation accuracy, we adopt a self-adaptive threshold to eliminate the irrelevant features to ensure channel sparsity. Simulation results verify the effectiveness of our proposed DRSN-based approach in complicated noise scenarios.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128767214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Learning Statistically Robust MIMO Detection with Imperfect CSI 不完全CSI下的统计鲁棒MIMO检测学习
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940387
Yi Sun, Hong Shen, Wei Xu, Chunming Zhao
{"title":"Learning Statistically Robust MIMO Detection with Imperfect CSI","authors":"Yi Sun, Hong Shen, Wei Xu, Chunming Zhao","doi":"10.1109/ISWCS56560.2022.9940387","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940387","url":null,"abstract":"For multi-input multi-output (MIMO) systems, the detection performance can be severely deteriorated by the channel state information (CSI) uncertainties. In this paper, we propose a learnable robust MIMO detector by taking the statistics of CSI imperfection into account. Specifically, we first formulate a robust maximum likelihood (ML) detection problem and then develop an alternating direction method of multipli-ers (ADMM) based solution, which involves the calculations of closed-form expressions in each iteration. Furthermore, a model-driven neural network is established by unfolding the derived ADMM algorithm whose penalty parameters are learned via offline training. Simulation results demonstrate that the proposed network can considerably outperform the conventional mismatched ML detector and even approach the optimal robust ML detector with only 5 layers.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117280001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A DNN-based Decoding Scheme for Communication Transmission System over AWGN Channel 基于dnn的AWGN信道通信传输系统译码方案
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940380
Meilin He, Yanchao Lei, Huina Song, Zhirui Hu, Peng Pan, Haiquan Wang
{"title":"A DNN-based Decoding Scheme for Communication Transmission System over AWGN Channel","authors":"Meilin He, Yanchao Lei, Huina Song, Zhirui Hu, Peng Pan, Haiquan Wang","doi":"10.1109/ISWCS56560.2022.9940380","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940380","url":null,"abstract":"A communication transmission system with channel coding and deep neural network (DNN)-based decoding is considered. A DNN-based decoding scheme is proposed for reliable transmission. The decoding scheme is accomplished by efficient local decoding at all the neurons and interactions in the input, hidden and output layer. Specifically, firstly, the nonlinear operations at each neuron and the linear operations of the weights and biases at each edge are performed by the local decoding. Secondly, the weights and biases are updated by gradient descent (GD) algorithm, based on the estimated loss value. This process above is performed iteratively until the message sequence has been recovered. Simulation results show that our proposed decoding scheme performs well. Moreover, our decoding scheme performs significantly better than the conventional hard decision.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131693879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Downlink IP Throughput Modeling and Prediction with Deep Neural Networks 基于深度神经网络的下行链路IP吞吐量建模与预测
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940405
Jianhang Zhu, Jiajie Huang, Jie Gong, Zhen Liu, Zixu Wang, Yang Li, Yibin Kang
{"title":"Downlink IP Throughput Modeling and Prediction with Deep Neural Networks","authors":"Jianhang Zhu, Jiajie Huang, Jie Gong, Zhen Liu, Zixu Wang, Yang Li, Yibin Kang","doi":"10.1109/ISWCS56560.2022.9940405","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940405","url":null,"abstract":"With the development of machine learning, deep neural networks are widely used in wireless communication systems for modeling and prediction. Neural networks have powerful data fitting capability and are suitable for complex multi-factor communication scenarios. The downlink IP throughput, defined as the payload data volume on IP level per elapsed time unit on the Uu interface, is an important performance metric for the quality of service experienced by the end user. In this paper, we propose a deep neural network-based modeling approach to predict the downlink IP throughput. Real-trace data of cellular systems, i.e., user-uploaded data including physical layer measurement, user scheduling information, user throughput and so on, are used for model training and testing. The experimental results show that our proposed model performs well for downlink IP throughput prediction.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130685681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Energy-efficient Federated Edge Learning for Internet of Vehicles via Rate-Splitting Multiple Access 基于分频多址的车联网节能联邦边缘学习
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940330
Sheng Z. Zhang, Shiyao Zhang, L. Yeung
{"title":"Energy-efficient Federated Edge Learning for Internet of Vehicles via Rate-Splitting Multiple Access","authors":"Sheng Z. Zhang, Shiyao Zhang, L. Yeung","doi":"10.1109/ISWCS56560.2022.9940330","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940330","url":null,"abstract":"Rate-Splitting Multiple Access (RSMA) has recently found favor in the multi-antenna-aided wireless network. Considering the heterogeneous demands and the qualities of Channel State Information at the Transmitter (CSIT), RSMA is crucial for advancing the quality of Internet of Vehicles (IoV) operations. However, it is challenging to incorporate RSMA into IoV operations under realistic autonomous driving constraints. To tackle this problem, we propose an RSMA-based IoV system to achieve energy-efficient Federated Edge Learning (FEEL) downlink broadcasting for autonomous driving. Specifically, the proposed framework is designed for transmitting the unicast control messages to the IoV platoon, as well as for broadcasting the global FEEL model to each vehicle. Thus, Non-Orthogonal Unicasting and Multicasting (NOUM) transmission is considered, where the unicast control message for vehicular platoons and broadcast FEEL model for autonomous driving can be transmitted simultaneously. Given the non-convexity of the formulated problems, a Successive Convex Approximation (SCA) approach is developed for solving the FEEL-based downlink problem. The simulation results show that our proposed RSMA-based IoV system can outperform the Multi-User Linear Precoding (MU-LP) by means of the NOUM and conventional Non-Orthogonal Multiple Access (NOMA) system that only supports unicast. In addition, the SCA method is shown to generate near-optimal solutions in reduced computation time.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127617265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Time-delay Estimation of Coherent GPR Signal by Using Sparse Frequency Sampling and IMUSIC Method 基于稀疏频率采样和IMUSIC方法的相干探地雷达信号时延估计
2022 International Symposium on Wireless Communication Systems (ISWCS) Pub Date : 2022-10-19 DOI: 10.1109/ISWCS56560.2022.9940436
Huimin Pan, Jingjing Pan, Xiaofei Zhang
{"title":"Time-delay Estimation of Coherent GPR Signal by Using Sparse Frequency Sampling and IMUSIC Method","authors":"Huimin Pan, Jingjing Pan, Xiaofei Zhang","doi":"10.1109/ISWCS56560.2022.9940436","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940436","url":null,"abstract":"Time-delay estimation (TDE) using the ground penetrating radar (GPR) signal contains important information about the stratified media structure. TDE trend to be challenging in the scenarios of coherent, overlapping signals and limited bandwidth of GPR. This paper proposes a decoherence method based on improved multiple signal classification (IMUSIC) with a specified symmetric sparse sampling structure for TDE in the thin pavement and limited bandwidth GPR scenarios. Compared with uniform sampling, this method is sensitive to overlapping and weak multiple echoes, with fewer sampling points and lower computational complexity. Simulation results demonstrate the advantages of the proposed method over various existing methods including the interpolation method and Orthogonal matching pursuit (OMP) when dealing with overlapping and coherent signals.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123836306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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