Pub Date : 2022-10-19DOI: 10.1109/ISWCS56560.2022.9940393
Paul Zheng, Yao Zhu, Yulin Hu, A. Schmeink
Managing queuing latency is crucial to achieve ultra-reliable low-latency communications (URLLC) in the future vehicle networks. In this work, we propose a novel joint power and resource allocation strategy to enhance the worst-case relia-bility by minimizing the network-wide maximum queue length. A constraint of a long-term energy budget is considered, as vehicles must simultaneously ensure other tasks. In addition, vehicle communications are assumed to have a heterogeneous nature and the distribution of extreme events may vary between vehicles, while in this work extreme value theory (EVT) is exploited to model these extreme events. Moreover, personalized federated learning is employed to learn the distribution while handling the heterogeneity among vehicles. Simulation results confirm that the proposed design reduces the length of the worst-case queuing latency and that, in comparison to traditional federated learning, the introduced personalized federated learning approach signif-icantly increases the estimation accuracy of local extreme event distribution without increasing the communication load.
{"title":"Data-driven Extreme Events Modeling for Vehicle Networks by Personalized Federated Learning: Invited Paper","authors":"Paul Zheng, Yao Zhu, Yulin Hu, A. Schmeink","doi":"10.1109/ISWCS56560.2022.9940393","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940393","url":null,"abstract":"Managing queuing latency is crucial to achieve ultra-reliable low-latency communications (URLLC) in the future vehicle networks. In this work, we propose a novel joint power and resource allocation strategy to enhance the worst-case relia-bility by minimizing the network-wide maximum queue length. A constraint of a long-term energy budget is considered, as vehicles must simultaneously ensure other tasks. In addition, vehicle communications are assumed to have a heterogeneous nature and the distribution of extreme events may vary between vehicles, while in this work extreme value theory (EVT) is exploited to model these extreme events. Moreover, personalized federated learning is employed to learn the distribution while handling the heterogeneity among vehicles. Simulation results confirm that the proposed design reduces the length of the worst-case queuing latency and that, in comparison to traditional federated learning, the introduced personalized federated learning approach signif-icantly increases the estimation accuracy of local extreme event distribution without increasing the communication load.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"37 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":"124953679","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/ISWCS56560.2022.9940398
F. J. Martín-Vega, G. Gómez, D. Morales-Jiménez, F. J. López-Martínez, M. Aguayo-Torres
In this paper, we investigate the distribution of the distance and azimuth angle between a reference node and a node randomly placed within a rectangular finite wireless network. As a result, we prove that there exists a non-negligible correlation between both random variables, that depends on the shape of the rectangle and on the location of the reference node. To characterize this dependence, we derive the joint distribution of distance and azimuth angle, which is expressed as the sum of a small number of closed-form terms. This expression has applications on the analysis of directional beamforming.
{"title":"Joint Distribution of Distance and Angle in Rectangular Finite Wireless Networks","authors":"F. J. Martín-Vega, G. Gómez, D. Morales-Jiménez, F. J. López-Martínez, M. Aguayo-Torres","doi":"10.1109/ISWCS56560.2022.9940398","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940398","url":null,"abstract":"In this paper, we investigate the distribution of the distance and azimuth angle between a reference node and a node randomly placed within a rectangular finite wireless network. As a result, we prove that there exists a non-negligible correlation between both random variables, that depends on the shape of the rectangle and on the location of the reference node. To characterize this dependence, we derive the joint distribution of distance and azimuth angle, which is expressed as the sum of a small number of closed-form terms. This expression has applications on the analysis of directional beamforming.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"77 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":"126227956","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/ISWCS56560.2022.9940362
Zhizheng Lu, Yu Han, Shi Jin, M. Matthaiou, Tony Q. S. Quek
In this paper, we propose an efficient near-field channel reconstruction and user localization scheme for extremely large-scale antenna array (ELAA) systems. Due to the non-negligible near-field effect in ELAA systems, a more realistic near-field multipath channel model, which incorporates the unequal path loss and the phase deviations across antennas and models line-of-sight (LoS), reflection, and scattering, is considered. A subarray hybrid beamforming architecture is further employed to reduce the cost of using ELAA. Based on the sparsity of the near-field channel in the joint angle-distance domain, a near-field Newtonized orthogonal matching pursuit algorithm is proposed to estimate the multipath parameters. Reconstruction of the near-field channel and positioning of the user can be achieved based on the estimated parameters. Our numerical results verify that the reconstructed channel is very close to the real near-field channel, and the user localization has high accuracy whether a LoS component exists or not, validating the effectiveness and reliability of the proposed scheme.
{"title":"Near-Field Channel Reconstruction and User Localization for ELAA Systems","authors":"Zhizheng Lu, Yu Han, Shi Jin, M. Matthaiou, Tony Q. S. Quek","doi":"10.1109/ISWCS56560.2022.9940362","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940362","url":null,"abstract":"In this paper, we propose an efficient near-field channel reconstruction and user localization scheme for extremely large-scale antenna array (ELAA) systems. Due to the non-negligible near-field effect in ELAA systems, a more realistic near-field multipath channel model, which incorporates the unequal path loss and the phase deviations across antennas and models line-of-sight (LoS), reflection, and scattering, is considered. A subarray hybrid beamforming architecture is further employed to reduce the cost of using ELAA. Based on the sparsity of the near-field channel in the joint angle-distance domain, a near-field Newtonized orthogonal matching pursuit algorithm is proposed to estimate the multipath parameters. Reconstruction of the near-field channel and positioning of the user can be achieved based on the estimated parameters. Our numerical results verify that the reconstructed channel is very close to the real near-field channel, and the user localization has high accuracy whether a LoS component exists or not, validating the effectiveness and reliability of the proposed scheme.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"64 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":"115687428","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/ISWCS56560.2022.9940371
Jiacheng Yao, Wei Xu, X. You, D. W. K. Ng, Jiewei Fu
In this paper, we consider the robust beamforming design for a reconfigurable intelligent surface (RIS) aided cell-free (CF) system by taking into account the channel state information (CSI) uncertainties of both the direct channel and cascaded channel at the transmitter. We jointly optimize the precoding at the access points (APs) and the phase shifts at the multiple RISs to maximize the worst-case system sum rate adopting a bounded CSI error model. By applying a series of transformations and approximations, the considered problem is decomposed into several subproblems via the block coordinate descent (BCD) algorithm. To address the nonconvexity arised in the subproblem of RIS phase shift optimization, we exploit the alternating direction method of multipliers (ADMM) to obtain a suboptimal solution. Furthermore, to reduce the computational complexity, we propose a new scheme that applies the ADMM framework to replace the BCD algorithm. Numerical results demonstrate the effectiveness of the proposed robust beamforming design and the importance of accurate cascaded channel estimation.
{"title":"Robust Beamforming Design for Reconfigurable Intelligent Surface-aided Cell-free Systems","authors":"Jiacheng Yao, Wei Xu, X. You, D. W. K. Ng, Jiewei Fu","doi":"10.1109/ISWCS56560.2022.9940371","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940371","url":null,"abstract":"In this paper, we consider the robust beamforming design for a reconfigurable intelligent surface (RIS) aided cell-free (CF) system by taking into account the channel state information (CSI) uncertainties of both the direct channel and cascaded channel at the transmitter. We jointly optimize the precoding at the access points (APs) and the phase shifts at the multiple RISs to maximize the worst-case system sum rate adopting a bounded CSI error model. By applying a series of transformations and approximations, the considered problem is decomposed into several subproblems via the block coordinate descent (BCD) algorithm. To address the nonconvexity arised in the subproblem of RIS phase shift optimization, we exploit the alternating direction method of multipliers (ADMM) to obtain a suboptimal solution. Furthermore, to reduce the computational complexity, we propose a new scheme that applies the ADMM framework to replace the BCD algorithm. Numerical results demonstrate the effectiveness of the proposed robust beamforming design and the importance of accurate cascaded channel estimation.","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":"129953600","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/ISWCS56560.2022.9940407
T. Ssettumba, R. Renna, L. Landau, R. D. Lamare
This paper proposes a cell-free massive multiple-input multiple-output (CF-mMIMO) architecture with joint list-based detection with soft interference cancellation (soft-IC) and access points (APs) selection. In particular, we derive a new closed-form expression for the minimum mean-square error receive filter while taking the uplink transmit powers and APs selection into account. This is achieved by optimizing the receive combining vector by minimizing the mean square error between the detected symbol estimate and transmitted symbol, after canceling the multi-user interference (MUI). By using low-density parity check (LDPC) codes, an iterative detection and decoding (IDD) scheme based on a message passing is devised. In order to perform joint detection at the central processing unit (CPU), the access points locally estimate the channel and send their received sample data to the CPU via the front haul links. In order to enhance the system's bit error rate performance, the detected symbols are iteratively exchanged between the joint detector and the LDPC decoder in log likelihood ratio form. Furthermore, we draw insights into the derived detector as the number of IDD iterations increase. Finally, the proposed list detector is compared with existing detection techniques.
{"title":"List-Based Detector and Access Points Selection in Cell-Free Massive MIMO Using LDPC Codes","authors":"T. Ssettumba, R. Renna, L. Landau, R. D. Lamare","doi":"10.1109/ISWCS56560.2022.9940407","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940407","url":null,"abstract":"This paper proposes a cell-free massive multiple-input multiple-output (CF-mMIMO) architecture with joint list-based detection with soft interference cancellation (soft-IC) and access points (APs) selection. In particular, we derive a new closed-form expression for the minimum mean-square error receive filter while taking the uplink transmit powers and APs selection into account. This is achieved by optimizing the receive combining vector by minimizing the mean square error between the detected symbol estimate and transmitted symbol, after canceling the multi-user interference (MUI). By using low-density parity check (LDPC) codes, an iterative detection and decoding (IDD) scheme based on a message passing is devised. In order to perform joint detection at the central processing unit (CPU), the access points locally estimate the channel and send their received sample data to the CPU via the front haul links. In order to enhance the system's bit error rate performance, the detected symbols are iteratively exchanged between the joint detector and the LDPC decoder in log likelihood ratio form. Furthermore, we draw insights into the derived detector as the number of IDD iterations increase. Finally, the proposed list detector is compared with existing detection techniques.","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":"130186193","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/ISWCS56560.2022.9940399
K. Wang, Yeqing Feng, Le Liang, Shi Jin
In this paper, we investigate the joint channel al-location and power control problem in vehicular networks. Considering the different quality-of-service (QoS) requirements for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) links, we transform the optimization problem using reinforcement learning (RL) and then propose a distributed resource allocation scheme based on the deep Q network (DQN) and deep determin-istic policy gradient (DDPG), which enables joint optimization of continuous power control and discrete channel allocation. Additionally, we consider the reward fluctuation caused by the strong dynamics of vehicular networks, and propose the advantage reward to alleviate this instability. Simulation results demonstrate that the proposed DQN-DDPG based resource allocation algorithm improves both the total capacity of V2I links and the payload delivery rate of V2V links, achieving higher QoS satisfaction compared to other baselines.
{"title":"Joint Spectrum Allocation and Power Control in Vehicular Networks Based on Reinforcement Learning","authors":"K. Wang, Yeqing Feng, Le Liang, Shi Jin","doi":"10.1109/ISWCS56560.2022.9940399","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940399","url":null,"abstract":"In this paper, we investigate the joint channel al-location and power control problem in vehicular networks. Considering the different quality-of-service (QoS) requirements for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) links, we transform the optimization problem using reinforcement learning (RL) and then propose a distributed resource allocation scheme based on the deep Q network (DQN) and deep determin-istic policy gradient (DDPG), which enables joint optimization of continuous power control and discrete channel allocation. Additionally, we consider the reward fluctuation caused by the strong dynamics of vehicular networks, and propose the advantage reward to alleviate this instability. Simulation results demonstrate that the proposed DQN-DDPG based resource allocation algorithm improves both the total capacity of V2I links and the payload delivery rate of V2V links, achieving higher QoS satisfaction compared to other baselines.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"88 40 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":"130795235","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/ISWCS56560.2022.9940394
Xidong Mu, Yuanwei Liu
The coexistence of the emerging semantic trans-mission and the conventional bit-based transmission in future networks. The semantic rate is considered for measuring the performance of the semantic transmission. To obtain a closed-form expression of the key parameter, namely the semantic similarity, we propose a data regression method, where the semantic similarity is approximated by a generalized logistic function. Using the obtained tractable function, we propose a novel semi non-orthogonal multiple access (semi-NOMA) scheme for enabling an access point simultaneously to send the semantic and bit streams to one semantics-interested user (S-user) and one bit-interested user (B-user). More specifically, the bit stream in semi-NOMA is split into two streams, one is transmitted with the semantic stream over the shared frequency sub-band and the other is transmitted over the separate orthogonal frequency sub-band. An optimal resource allocation procedure is derived for characterizing the boundary of the semantic-versus-bit (SvB) rate region achieved by the proposed semi-NOMA. Finally, our numerical results demonstrate that semi-NOMA is superior to both conventional NOMA and orthogonal multiple access schemes in the considered coexisting semantic and bit transmission.
{"title":"Semi-NOMA enabled Coexisting Semantic and Bit Communications","authors":"Xidong Mu, Yuanwei Liu","doi":"10.1109/ISWCS56560.2022.9940394","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940394","url":null,"abstract":"The coexistence of the emerging semantic trans-mission and the conventional bit-based transmission in future networks. The semantic rate is considered for measuring the performance of the semantic transmission. To obtain a closed-form expression of the key parameter, namely the semantic similarity, we propose a data regression method, where the semantic similarity is approximated by a generalized logistic function. Using the obtained tractable function, we propose a novel semi non-orthogonal multiple access (semi-NOMA) scheme for enabling an access point simultaneously to send the semantic and bit streams to one semantics-interested user (S-user) and one bit-interested user (B-user). More specifically, the bit stream in semi-NOMA is split into two streams, one is transmitted with the semantic stream over the shared frequency sub-band and the other is transmitted over the separate orthogonal frequency sub-band. An optimal resource allocation procedure is derived for characterizing the boundary of the semantic-versus-bit (SvB) rate region achieved by the proposed semi-NOMA. Finally, our numerical results demonstrate that semi-NOMA is superior to both conventional NOMA and orthogonal multiple access schemes in the considered coexisting semantic and bit transmission.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"134 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":"128816955","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/ISWCS56560.2022.9940431
Ruomei Sun, Yuhang Wu, Fuhui Zhou, Qihui Wu
The exploitation of non-orthogonal multiple access (NOMA) for the cognitive unmanned aerial vehicle (UAV) networks is promising to tackle the spectrum scarcity problem. However, the openness characteristic of the spectrum in the cognitive UAV networks makes the private information vulnerable to be eavesdropped. In this paper, a downlink UAV-assisted jamming cognitive UAV network with NOMA is studied to tackle this issue. In order to improve the secure performance of the networks, the trajectories and transmit power of the cognitive UAV and the jamming UAV are jointly optimized to maximize the average security rate of the secondary users. An alternative algorithm that employs the successive convex approximation (SCA) method is proposed to solve the challenging non-convex optimization problem. Furthermore, the simulation results show that the proposed scheme can significantly improve the system secure performance.
{"title":"Joint Trajectory Design and Resource Allocation for UAV-assisted Jamming NOMA Cognitive UAV Networks","authors":"Ruomei Sun, Yuhang Wu, Fuhui Zhou, Qihui Wu","doi":"10.1109/ISWCS56560.2022.9940431","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940431","url":null,"abstract":"The exploitation of non-orthogonal multiple access (NOMA) for the cognitive unmanned aerial vehicle (UAV) networks is promising to tackle the spectrum scarcity problem. However, the openness characteristic of the spectrum in the cognitive UAV networks makes the private information vulnerable to be eavesdropped. In this paper, a downlink UAV-assisted jamming cognitive UAV network with NOMA is studied to tackle this issue. In order to improve the secure performance of the networks, the trajectories and transmit power of the cognitive UAV and the jamming UAV are jointly optimized to maximize the average security rate of the secondary users. An alternative algorithm that employs the successive convex approximation (SCA) method is proposed to solve the challenging non-convex optimization problem. Furthermore, the simulation results show that the proposed scheme can significantly improve the system secure performance.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"38 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":"128959041","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/ISWCS56560.2022.9940262
Hei Victor Cheng, Wei Yu
This paper investigates a reconfigurable intelligent surface (RIS) aided communication scenario in which the RIS and the transmitter jointly send information to the receiver. While most studies of the RIS focus on its ability to beamform and boost the received signal-to-noise ratio (SNR), it is known that if the information data stream is also available at the RIS and can be modulated through the adjustable phases at the RIS, significant improvement in the multiplexing gain of the overall channel is possible. To achieve the theoretic multiplexing gain, this paper provides a symbol level precoding (SLP) approach for modulating data through the phases of the RIS. The SLP strategy is to set the received signal to be as close to the desired points in a constellation as possible. The idea is to directly make the received signal to be the symbols corresponding to the information to be transmitted and to design the transmitter and the reflective coefficients of the RIS so that the desired symbols are synthesized at the receiver. This strategy is formulated as an optimization problem and an augmented Lagrangian approach with the Riemannian conjugate gradient descent method is proposed to solve the optimization problem efficiently. Numerical simulation results show that the proposed method can achieve the theoretical multiplexing gain.
{"title":"Modulating Data Using Reconfigurable Intelligent Surface by Symbol Level Precoding","authors":"Hei Victor Cheng, Wei Yu","doi":"10.1109/ISWCS56560.2022.9940262","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940262","url":null,"abstract":"This paper investigates a reconfigurable intelligent surface (RIS) aided communication scenario in which the RIS and the transmitter jointly send information to the receiver. While most studies of the RIS focus on its ability to beamform and boost the received signal-to-noise ratio (SNR), it is known that if the information data stream is also available at the RIS and can be modulated through the adjustable phases at the RIS, significant improvement in the multiplexing gain of the overall channel is possible. To achieve the theoretic multiplexing gain, this paper provides a symbol level precoding (SLP) approach for modulating data through the phases of the RIS. The SLP strategy is to set the received signal to be as close to the desired points in a constellation as possible. The idea is to directly make the received signal to be the symbols corresponding to the information to be transmitted and to design the transmitter and the reflective coefficients of the RIS so that the desired symbols are synthesized at the receiver. This strategy is formulated as an optimization problem and an augmented Lagrangian approach with the Riemannian conjugate gradient descent method is proposed to solve the optimization problem efficiently. Numerical simulation results show that the proposed method can achieve the theoretical multiplexing gain.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"45 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":"121849878","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/ISWCS56560.2022.9940338
Ziying Wang, Chunshan Liu, Lou Zhao, Min Li
Millimeter-Wave (mm-wave) communications is an important element of 5G. Due to the high propagation loss of mm-wave signals, directional transmissions are required even in the initial access (IA), where the base station (BS) needs to broadcast the reference signals with beamforming to reach sufficient coverage ranges. Sequential scanning with narrow beams at the BS, without considering the non-uniform distribution of user equipment (UE) in the angular space, may lead to long IA delay at UEs. To reduce the IA delay, we propose a data-driven approach that learns the spatial distribution of UEs from the historical channels of UEs served by the BS and a beam identification method based on density-based spatial clustering of applications with noise (DBSCAN) to find the optimized set of beams to match to the distribution of the UEs. Two time resource allocation strategies are then investigated to evaluate the performance of IA based on the optimized beam set identified according to the UE distribution. Numerical results via realistic ray-tracing experiments demonstrate the performance improvement of the proposed approach over sequential beam training and omnidirectional training.
{"title":"Fast Millimeter-Wave Base Station Discovery via Data-driven Beam Training Optimization","authors":"Ziying Wang, Chunshan Liu, Lou Zhao, Min Li","doi":"10.1109/ISWCS56560.2022.9940338","DOIUrl":"https://doi.org/10.1109/ISWCS56560.2022.9940338","url":null,"abstract":"Millimeter-Wave (mm-wave) communications is an important element of 5G. Due to the high propagation loss of mm-wave signals, directional transmissions are required even in the initial access (IA), where the base station (BS) needs to broadcast the reference signals with beamforming to reach sufficient coverage ranges. Sequential scanning with narrow beams at the BS, without considering the non-uniform distribution of user equipment (UE) in the angular space, may lead to long IA delay at UEs. To reduce the IA delay, we propose a data-driven approach that learns the spatial distribution of UEs from the historical channels of UEs served by the BS and a beam identification method based on density-based spatial clustering of applications with noise (DBSCAN) to find the optimized set of beams to match to the distribution of the UEs. Two time resource allocation strategies are then investigated to evaluate the performance of IA based on the optimized beam set identified according to the UE distribution. Numerical results via realistic ray-tracing experiments demonstrate the performance improvement of the proposed approach over sequential beam training and omnidirectional training.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"16 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":"116979609","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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