Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940416
Qiushuo Hou, Mengyuan Lee, Guanding Yu, Yunlong Cai
Generally speaking, artificial intelligent (AI) models are trained under special learning hypotheses, especially the one that statistics of the training data are static during the training stage. However, the distribution of the channel state information (CSI) is constantly changing in real wireless communication environments. Therefore, it is essential to study the dynamic deep learning (DL) technology for wireless communications. In this paper, we investigate a beamforming design problem by maximizing the weighted sum rate in episodically dynamic wireless environment, where the CSI distribution changes over periods and maintains stationary within each period. In order to effectively solve this problem, a novel framework named meta-gating network is proposed, which can achieve three important goals, i.e., seamlessly, quickly and continuously. Specifically, the proposed framework consists of an inner network and an outer network, both of them are implemented by graph neural networks (GNNs). To achieve the former two goals, we propose a training method by combining the model-agnostic meta learning (MAML) algorithm with the unsupervised training. Following this training method, the outer network can help the inner network learn good initialization and then fast adapt to the different channels. As for the goal of ‘continuously’, we design an element-wise gating operation to multiply the outputs of the inner and outer networks, aiming at the selection activation of the inner network. Simulation results demonstrate that the proposed meta-gating GNN can well achieve the three important goals compared with the existing state-of-the-art algorithms.
{"title":"Learning to Optimize Resource in Dynamic Wireless Environment via Meta-Gating Graph Neural Network","authors":"Qiushuo Hou, Mengyuan Lee, Guanding Yu, Yunlong Cai","doi":"10.1109/ISWCS56560.2022.9940416","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940416","url":null,"abstract":"Generally speaking, artificial intelligent (AI) models are trained under special learning hypotheses, especially the one that statistics of the training data are static during the training stage. However, the distribution of the channel state information (CSI) is constantly changing in real wireless communication environments. Therefore, it is essential to study the dynamic deep learning (DL) technology for wireless communications. In this paper, we investigate a beamforming design problem by maximizing the weighted sum rate in episodically dynamic wireless environment, where the CSI distribution changes over periods and maintains stationary within each period. In order to effectively solve this problem, a novel framework named meta-gating network is proposed, which can achieve three important goals, i.e., seamlessly, quickly and continuously. Specifically, the proposed framework consists of an inner network and an outer network, both of them are implemented by graph neural networks (GNNs). To achieve the former two goals, we propose a training method by combining the model-agnostic meta learning (MAML) algorithm with the unsupervised training. Following this training method, the outer network can help the inner network learn good initialization and then fast adapt to the different channels. As for the goal of ‘continuously’, we design an element-wise gating operation to multiply the outputs of the inner and outer networks, aiming at the selection activation of the inner network. Simulation results demonstrate that the proposed meta-gating GNN can well achieve the three important goals compared with the existing state-of-the-art algorithms.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"76 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":"121687111","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940408
Na Zhao, Qing Chang, Yunlong Wang, Xiaoyu Shen, Yuan Shen
Existing joint sensing and communication technique functionally separates sensing from communication, making it difficult to improve the performance of dual functions and extend to the network paradigm. To simultaneously improve the performance of target sensing and data detection, we propose a data-aided joint target sensing and data detection scheme in this paper, which can be divided into three phases. In the first pilot phase, we derive the performance limits of time delay in the multiple reflected path scenario, which are shown to be inversely proportional to the waveform coefficient with separable multipath. In the second data transmission phase, we evaluate the data detection performance using the minimum mean squared error detector via the uncertainty channel. In the third data-aided phase, we derive the sensing performance when reusing the detected data symbols with the decoding error via error analysis. Finally, simulation results are provided to show the performance improvements for both sensing and communication.
{"title":"On the Performance Improvements of Data-aided Joint Sensing and Communication","authors":"Na Zhao, Qing Chang, Yunlong Wang, Xiaoyu Shen, Yuan Shen","doi":"10.1109/ISWCS56560.2022.9940408","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940408","url":null,"abstract":"Existing joint sensing and communication technique functionally separates sensing from communication, making it difficult to improve the performance of dual functions and extend to the network paradigm. To simultaneously improve the performance of target sensing and data detection, we propose a data-aided joint target sensing and data detection scheme in this paper, which can be divided into three phases. In the first pilot phase, we derive the performance limits of time delay in the multiple reflected path scenario, which are shown to be inversely proportional to the waveform coefficient with separable multipath. In the second data transmission phase, we evaluate the data detection performance using the minimum mean squared error detector via the uncertainty channel. In the third data-aided phase, we derive the sensing performance when reusing the detected data symbols with the decoding error via error analysis. Finally, simulation results are provided to show the performance improvements for both sensing and communication.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"3 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":"115319916","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940326
Xu Deng, Peng Sun, A. Boukerche, Lianghua Song
In recent years, data-driven and AI-based intelligent transportation systems have been greatly developed to alleviate the public's concern about the increasingly severe traffic congestion and traffic safety issues. For supporting various safety-related ITS applications, vehicular edge computing (VEC) has been proposed as a promising technology that can effectively provide computing power and storage capacity support for vehicles in close proximity. However, in the face of the instability of communication between vehicles and other devices caused by the high-speed motion of vehicles and the complex relative motion between vehicles, how to effectively realize the relatively stable arithmetic power sharing between vehicles and edge computing devices is a critical problem that must be solved to realize VEC. Therefore, in this paper, we propose a distributed online offloading method, called Candidate Utilization-based Deep Reinforcement Learning (CU-DRL) algorithm, by exploiting the deep reinforcement learning technique. We further evaluate and demonstrate the effectiveness and correctness of the proposed CU-DRL model through simulations.
{"title":"CU-DRL: A Novel Deep Reinforcement Learning-assisted Offloading Scheme for Supporting Vehicular Edge Computing","authors":"Xu Deng, Peng Sun, A. Boukerche, Lianghua Song","doi":"10.1109/ISWCS56560.2022.9940326","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940326","url":null,"abstract":"In recent years, data-driven and AI-based intelligent transportation systems have been greatly developed to alleviate the public's concern about the increasingly severe traffic congestion and traffic safety issues. For supporting various safety-related ITS applications, vehicular edge computing (VEC) has been proposed as a promising technology that can effectively provide computing power and storage capacity support for vehicles in close proximity. However, in the face of the instability of communication between vehicles and other devices caused by the high-speed motion of vehicles and the complex relative motion between vehicles, how to effectively realize the relatively stable arithmetic power sharing between vehicles and edge computing devices is a critical problem that must be solved to realize VEC. Therefore, in this paper, we propose a distributed online offloading method, called Candidate Utilization-based Deep Reinforcement Learning (CU-DRL) algorithm, by exploiting the deep reinforcement learning technique. We further evaluate and demonstrate the effectiveness and correctness of the proposed CU-DRL model through simulations.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"216 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":"121113775","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}
In this paper, we focus on the optimal beamformer design for rate splitting multiple access (RSMA)-aided multiple-input single-output (MISO) visible light communication (VLC) networks. First, we derive the closed-form lower bounds of the achievable rate of each user, which are the first theoretical bound of achievable rate for RSMA-aided VLC networks. Second, we investigate the optimal beamformer design for RSMA-aided VLC networks to maximize the sum rate under the optical and electrical power constraints. Since this optimal problem is non-convex, a concave-convex procedure (CCCP)-based iterative algorithm is proposed to approximate the non-convex term by the convex lower bound at each iteration. Thus, the optimal beamformer design problem can be solved iteratively until convergence, and a high-quality suboptimal solution can be obtained. In addition, we show that the proposed algorithms of RSMA-aided networks can achieve superior performance compared with space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA).
{"title":"Rate Splitting Multiple Access-Aided MISO Visible Light Communications","authors":"Shuai Ma, Guanjie Zhang, Zhi Zhang, Rongyan Gu, Youlong Wu, Shiyin Li","doi":"10.1109/ISWCS56560.2022.9940414","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940414","url":null,"abstract":"In this paper, we focus on the optimal beamformer design for rate splitting multiple access (RSMA)-aided multiple-input single-output (MISO) visible light communication (VLC) networks. First, we derive the closed-form lower bounds of the achievable rate of each user, which are the first theoretical bound of achievable rate for RSMA-aided VLC networks. Second, we investigate the optimal beamformer design for RSMA-aided VLC networks to maximize the sum rate under the optical and electrical power constraints. Since this optimal problem is non-convex, a concave-convex procedure (CCCP)-based iterative algorithm is proposed to approximate the non-convex term by the convex lower bound at each iteration. Thus, the optimal beamformer design problem can be solved iteratively until convergence, and a high-quality suboptimal solution can be obtained. In addition, we show that the proposed algorithms of RSMA-aided networks can achieve superior performance compared with space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA).","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"28 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":"127452685","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940411
Xiaoyu Zhang, Haobo Zhang, Hongliang Zhang, Liang Liu, Boya Di
Parameter estimation is a fundamental task for radar sensing, which is traditionally realized by phased array based radars. However, due to the power-consuming hardware components such as phase shifters, the size of the phased array is constrained given the available power for the radar system, thus leading to a limited estimation precision of phased array based radars. To address this issue, we propose the holographic radar system enabled by the reconfigurable holographic surface (RHS), which is a novel type of metamaterial antenna with simple hardware and low power consumption. Since the desired beams of the RHS are generated by controlling the amplitudes of the signals radiated by the RHS elements, traditional beamforming schemes developed for phased arrays do not fit any more. Therefore, we develop a new beamforming scheme for the RHS-based parameter estimation. In more detail, we derive and analyze the Cramér-Rao bound (CRB) to evaluate the lower bound of estimation error. A CRB minimization problem is then formulated to optimize the estimation precision, and an RHS amplitude optimization algorithm is designed to solve the problem. Simulation results show that for the same power consumption, the estimation precision of the proposed holographic radar can outperform that of the phased array counterpart.
{"title":"Parameter Estimation for Reconfigurable Holographic Surfaces enabled Radars","authors":"Xiaoyu Zhang, Haobo Zhang, Hongliang Zhang, Liang Liu, Boya Di","doi":"10.1109/ISWCS56560.2022.9940411","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940411","url":null,"abstract":"Parameter estimation is a fundamental task for radar sensing, which is traditionally realized by phased array based radars. However, due to the power-consuming hardware components such as phase shifters, the size of the phased array is constrained given the available power for the radar system, thus leading to a limited estimation precision of phased array based radars. To address this issue, we propose the holographic radar system enabled by the reconfigurable holographic surface (RHS), which is a novel type of metamaterial antenna with simple hardware and low power consumption. Since the desired beams of the RHS are generated by controlling the amplitudes of the signals radiated by the RHS elements, traditional beamforming schemes developed for phased arrays do not fit any more. Therefore, we develop a new beamforming scheme for the RHS-based parameter estimation. In more detail, we derive and analyze the Cramér-Rao bound (CRB) to evaluate the lower bound of estimation error. A CRB minimization problem is then formulated to optimize the estimation precision, and an RHS amplitude optimization algorithm is designed to solve the problem. Simulation results show that for the same power consumption, the estimation precision of the proposed holographic radar can outperform that of the phased array counterpart.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"32 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":"125883945","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940328
Zhicheng Xiao, Yulin Hu, Chao Shen, B. Ai, A. Schmeink
In this paper, we study a multiple-input single-output (MISO) assisted multi-user downlink network. To support low-latency communications, the transmissions to massive users are coded by finite blocklength (FBL) codes. For such network, an efficient power allocation design is provided to optimize the sum throughput. In particular, we first characterize the FBL throughput performance, following which a power allocation problem is formulated aiming at maximizing the sum throughput in the FBL regime. To address the formulated non-convex problem, we separate the complex expression of the objective function into two parts and then conduct different tight convex approximation methods, with which, an efficient successive convex approximation (SCA)-based approach is introduced. Simulation results validate our analytical model and reveal that the proposed approach converges effectively and achieve the performance close to results of the exhaustive search. Furthermore, we evaluate the impacts of blocklength, number of transmitter antennas, power constraints and number of users on the system performance.
{"title":"Sum Throughput Maximization for MISO-Assisted Multi-User Downlink Transmissions in the FBL Regime","authors":"Zhicheng Xiao, Yulin Hu, Chao Shen, B. Ai, A. Schmeink","doi":"10.1109/ISWCS56560.2022.9940328","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940328","url":null,"abstract":"In this paper, we study a multiple-input single-output (MISO) assisted multi-user downlink network. To support low-latency communications, the transmissions to massive users are coded by finite blocklength (FBL) codes. For such network, an efficient power allocation design is provided to optimize the sum throughput. In particular, we first characterize the FBL throughput performance, following which a power allocation problem is formulated aiming at maximizing the sum throughput in the FBL regime. To address the formulated non-convex problem, we separate the complex expression of the objective function into two parts and then conduct different tight convex approximation methods, with which, an efficient successive convex approximation (SCA)-based approach is introduced. Simulation results validate our analytical model and reveal that the proposed approach converges effectively and achieve the performance close to results of the exhaustive search. Furthermore, we evaluate the impacts of blocklength, number of transmitter antennas, power constraints and number of users on the system performance.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"80 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":"129008201","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940403
Ruoxi Chong, M. Mohammadi, H. Ngo, S. Cotton, M. Matthaiou
We investigate the spectral efficiency (SE) of an uplink multi-user multiple-input multiple-output (MIMO) system with orthogonal time frequency space (OTFS) modulation. Two multiple access schemes are considered hereafter, namely, delay division multiple access (DDMA) and Doppler division multiple access (DoDMA). To avoid multi-user interference (MUI), we separate the delay Doppler (DD) domain resource blocks assigned to different users by guard bands. We design a minimum-mean-square-error (MMSE) receiver to combine the received signals for the detection of different users. We analyze the SE for the considered MIMO-OTFS system and quantify the performance gains achieved over a MIMO system with orthogonal frequency-division multiple access (OFDMA). Our simulation results demonstrate a noticeable improvement in the performance of MIMO-OTFS over MIMO-OFDMA.
{"title":"On the Spectral Efficiency of MMSE-based MIMO OTFS Systems","authors":"Ruoxi Chong, M. Mohammadi, H. Ngo, S. Cotton, M. Matthaiou","doi":"10.1109/ISWCS56560.2022.9940403","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940403","url":null,"abstract":"We investigate the spectral efficiency (SE) of an uplink multi-user multiple-input multiple-output (MIMO) system with orthogonal time frequency space (OTFS) modulation. Two multiple access schemes are considered hereafter, namely, delay division multiple access (DDMA) and Doppler division multiple access (DoDMA). To avoid multi-user interference (MUI), we separate the delay Doppler (DD) domain resource blocks assigned to different users by guard bands. We design a minimum-mean-square-error (MMSE) receiver to combine the received signals for the detection of different users. We analyze the SE for the considered MIMO-OTFS system and quantify the performance gains achieved over a MIMO system with orthogonal frequency-division multiple access (OFDMA). Our simulation results demonstrate a noticeable improvement in the performance of MIMO-OTFS over MIMO-OFDMA.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":" 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132094265","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940386
Bingqian Zhu, Baoyin Bian, Yehua Zhang, Wenmeng Li, Lang Li, Jing Jiang, Hua Zhang, Jun-Bo Wang
Ultra-reliable low-latency communication (URLLC) is a popular scenario in 6G wireless networks, which is also chal-lenging. In this paper, a downlink multiple-input single-output (MISO) URLLC system, which has a multiple-antenna base station (BS) and multiple single-antenna users was considered. With the objective of minimizing the total power, an algorithm about resource allocation and beamforming design was proposed. In the finite blocklength system, the objective issue is non-convex due to the constraints of decoding error probability, which makes computing complex. Hence, a path-following algorithm which is based on the successive convex approximation (SCA) was proposed. Numerical results are analyzed to verify the efficiency of the algorithm we proposed.
{"title":"Resource Allocation and Beamforming design for Downlink MISO-URLLC Systems","authors":"Bingqian Zhu, Baoyin Bian, Yehua Zhang, Wenmeng Li, Lang Li, Jing Jiang, Hua Zhang, Jun-Bo Wang","doi":"10.1109/ISWCS56560.2022.9940386","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940386","url":null,"abstract":"Ultra-reliable low-latency communication (URLLC) is a popular scenario in 6G wireless networks, which is also chal-lenging. In this paper, a downlink multiple-input single-output (MISO) URLLC system, which has a multiple-antenna base station (BS) and multiple single-antenna users was considered. With the objective of minimizing the total power, an algorithm about resource allocation and beamforming design was proposed. In the finite blocklength system, the objective issue is non-convex due to the constraints of decoding error probability, which makes computing complex. Hence, a path-following algorithm which is based on the successive convex approximation (SCA) was proposed. Numerical results are analyzed to verify the efficiency of the algorithm we proposed.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"333 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":"133557900","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}
Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940404
Jiabei Sun, Lou Zhao, Chunshan Liu, Yu'e Gao
In this paper, we propose a sensing-based two-timescale channel estimation algorithm for reconfigurable intelligent surface (RIS) assisted multi-user hybrid millimeter wave systems. The proposed channel estimation algorithm aims to separately estimate the base station (BS)-RIS and RIS-user channels instead of estimating the cascaded BS-RIS-user channel with a limited number of radio frequency chains equipped at the BS. In particular, we first cooperatively acquire parameters of the BS-RIS channel, e.g., the line-of-sight component and the equivalent channel state information (CSI) of the BS-RIS channel, via sensing methods by both transmitting and receiving sensing signals at the BS once over the large timescale. Then, users transmit orthogonal training sequences to the BS while RIS elements are sequentially turned on for obtaining CSIs of time-varying RIS-user channels over the small timescale. Our analytical and simulation results show that the proposed channel estimation algorithm can effectively estimate RIS-user channels with hybrid architecture at the cost of a reasonable training overhead.
{"title":"Sensing-based Two-timescale Channel Estimation for RIS-assisted Hybrid Millimeter Wave Systems","authors":"Jiabei Sun, Lou Zhao, Chunshan Liu, Yu'e Gao","doi":"10.1109/ISWCS56560.2022.9940404","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940404","url":null,"abstract":"In this paper, we propose a sensing-based two-timescale channel estimation algorithm for reconfigurable intelligent surface (RIS) assisted multi-user hybrid millimeter wave systems. The proposed channel estimation algorithm aims to separately estimate the base station (BS)-RIS and RIS-user channels instead of estimating the cascaded BS-RIS-user channel with a limited number of radio frequency chains equipped at the BS. In particular, we first cooperatively acquire parameters of the BS-RIS channel, e.g., the line-of-sight component and the equivalent channel state information (CSI) of the BS-RIS channel, via sensing methods by both transmitting and receiving sensing signals at the BS once over the large timescale. Then, users transmit orthogonal training sequences to the BS while RIS elements are sequentially turned on for obtaining CSIs of time-varying RIS-user channels over the small timescale. Our analytical and simulation results show that the proposed channel estimation algorithm can effectively estimate RIS-user channels with hybrid architecture at the cost of a reasonable training overhead.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"7 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":"129371200","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}
High precision network sensing and localization is an important task in 6G wireless communications, where the millimeter-wave (mmWave) / terahertz (THz) extremely large-scale multiple-input-multiple-output (XL-MIMO) technique is expected to be deployed to further boost system capacity. However, the ever-increasing bandwidth and array aperture in mmWave/THz XL-MIMO induce the challenging near-field beam squint effect. In this paper, we propose a reconfigurable intelligent surface (RIS) assisted localization (RISAL) paradigm in near-field conditions. Specifically, the polar-domain gradient descent algorithm and multiple signal classification (MUSIC) algorithm are applied to RISAL, which is able to realize high precision localization under the near-field beam squint effect. Simulation results demonstrate the superiority of the proposed algorithm. With the proposed localization algorithm, the angle accuracy can be 1 to 2 orders of magnitude higher than existing algorithms, and centimeter-level distance accuracy can be achieved.
{"title":"Reconfigurable Intelligent Surface Assisted Localization Over Near-Field Beam Squint Effect","authors":"Zhuoran Li, Ziwei Wan, Keke Ying, Yikun Mei, Malong Ke, Zhen Gao","doi":"10.1109/ISWCS56560.2022.9940428","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940428","url":null,"abstract":"High precision network sensing and localization is an important task in 6G wireless communications, where the millimeter-wave (mmWave) / terahertz (THz) extremely large-scale multiple-input-multiple-output (XL-MIMO) technique is expected to be deployed to further boost system capacity. However, the ever-increasing bandwidth and array aperture in mmWave/THz XL-MIMO induce the challenging near-field beam squint effect. In this paper, we propose a reconfigurable intelligent surface (RIS) assisted localization (RISAL) paradigm in near-field conditions. Specifically, the polar-domain gradient descent algorithm and multiple signal classification (MUSIC) algorithm are applied to RISAL, which is able to realize high precision localization under the near-field beam squint effect. Simulation results demonstrate the superiority of the proposed algorithm. With the proposed localization algorithm, the angle accuracy can be 1 to 2 orders of magnitude higher than existing algorithms, and centimeter-level distance accuracy can be achieved.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"1 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":"131174053","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}
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