Pub Date : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012948
Jun Shikida, K. Muraoka, Toshiki Takeuchi, N. Ishii
Millimeter wave (mmWave) distributed multiple-input multiple-output (MIMO), which is also known as cell-free massive MIMO, is a promising technology for beyond 5G. To improve system capacity in mmWave distributed MIMO systems, a coordinated scheme between distributed access points (APs) is required. In this paper, we evaluate the throughput performance of precoding across multiple APs under channel aging and compare it with that of inter-AP coordinated user and beam selection to clarify the inter-AP coordinated scheme suitable for practical mmWave distributed MIMO systems. Simulation results show that the inter-AP coordinated user and beam selection achieves a higher throughput performance than the precoding. Moreover, to make the inter-AP coordinated user and beam selection more practical, we propose a coordinated selection method using reference signal received power (RSRP) database. Simulation results show that the proposed method improves the 5%-tile user throughput by 17% compared to the coordinated selection without using the RSRP database.
{"title":"Inter-Access Point Coordinated User and Beam Selection for mmWave Distributed MIMO Systems","authors":"Jun Shikida, K. Muraoka, Toshiki Takeuchi, N. Ishii","doi":"10.1109/VTC2022-Fall57202.2022.10012948","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012948","url":null,"abstract":"Millimeter wave (mmWave) distributed multiple-input multiple-output (MIMO), which is also known as cell-free massive MIMO, is a promising technology for beyond 5G. To improve system capacity in mmWave distributed MIMO systems, a coordinated scheme between distributed access points (APs) is required. In this paper, we evaluate the throughput performance of precoding across multiple APs under channel aging and compare it with that of inter-AP coordinated user and beam selection to clarify the inter-AP coordinated scheme suitable for practical mmWave distributed MIMO systems. Simulation results show that the inter-AP coordinated user and beam selection achieves a higher throughput performance than the precoding. Moreover, to make the inter-AP coordinated user and beam selection more practical, we propose a coordinated selection method using reference signal received power (RSRP) database. Simulation results show that the proposed method improves the 5%-tile user throughput by 17% compared to the coordinated selection without using the RSRP database.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121560716","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012716
Chao Liu, Xue Fu, Yunlu Ge, Yu Wang, Yun Lin, Guan Gui, H. Sari
Specific emitter identification (SEI) is a promising physical layer authentication technique based on unintentionally hardware impairments of transmitters. These impairments are independent of the data’s content, so they are difficult to forge and analyze. Recently, most deep learning (DL) based SEI methods have been proposed, and have shown their great performance. However, these methods are big data-driven which means they have poor performance with limited training samples, and the vulnerability of neural networks to adversarial attacks is also a problem worth considering. In this paper, we propose an innovative few-shot SEI method based on class-reconstruction classification network and adversarial training (CRCN-AT) without the support of auxiliary dataset. Simulation results show that the proposed method achieves better identification performance and robustness in few-shot scenarios compared to traditional methods. The Pytorch code is released at https://github.comLIUC-000/CRCN-AT.
{"title":"A Robust Few-Shot SEI Method Using Class-Reconstruction and Adversarial Training","authors":"Chao Liu, Xue Fu, Yunlu Ge, Yu Wang, Yun Lin, Guan Gui, H. Sari","doi":"10.1109/VTC2022-Fall57202.2022.10012716","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012716","url":null,"abstract":"Specific emitter identification (SEI) is a promising physical layer authentication technique based on unintentionally hardware impairments of transmitters. These impairments are independent of the data’s content, so they are difficult to forge and analyze. Recently, most deep learning (DL) based SEI methods have been proposed, and have shown their great performance. However, these methods are big data-driven which means they have poor performance with limited training samples, and the vulnerability of neural networks to adversarial attacks is also a problem worth considering. In this paper, we propose an innovative few-shot SEI method based on class-reconstruction classification network and adversarial training (CRCN-AT) without the support of auxiliary dataset. Simulation results show that the proposed method achieves better identification performance and robustness in few-shot scenarios compared to traditional methods. The Pytorch code is released at https://github.comLIUC-000/CRCN-AT.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132417037","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012722
Yanjie Pu, Zhiying Song, Fuxi Wen, Shenghua Zhou
We propose a sensing-assisted dynamic beamforming method for robust vehicle-to-vehicle (V2V) communication between neighboring vehicles. For the proposed method, the main beam is directly steered towards the intended receivers and searching steps are not required. To maximize transmission throughput and avoid connection interruption caused by sensing uncertainties, higher directional gain for the interested field-of-view and lower sidelobe are expected. The problem is formulated as an array pattern synthesis problem that can be solved efficiently with the widely used semi-definite relaxation (SDR) methods.
{"title":"Sensing-Assisted Robust Vehicle-to-Vehicle Communication with Multiple Antennas","authors":"Yanjie Pu, Zhiying Song, Fuxi Wen, Shenghua Zhou","doi":"10.1109/VTC2022-Fall57202.2022.10012722","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012722","url":null,"abstract":"We propose a sensing-assisted dynamic beamforming method for robust vehicle-to-vehicle (V2V) communication between neighboring vehicles. For the proposed method, the main beam is directly steered towards the intended receivers and searching steps are not required. To maximize transmission throughput and avoid connection interruption caused by sensing uncertainties, higher directional gain for the interested field-of-view and lower sidelobe are expected. The problem is formulated as an array pattern synthesis problem that can be solved efficiently with the widely used semi-definite relaxation (SDR) methods.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134006952","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012854
Tianxiong Wang, Gaojie Chen, Mihai-Alin Badiu, J. Coon
In this paper, we analyze the coverage probability of a reconfigurable intelligent surface (RIS) aided cellular network with the theory of stochastic geometry. A Poisson cluster process (PCP) is applied to model the positions of transmitters (TXs) and RISs, capturing their spatial correlations. Considering the general Nakagami-m fading channel model, we derive the approximate distributions of the composite channel gains with RIS-assisted transmission, representing the desired signal channel and the interference channel, respectively. The coverage probability of the typical user is then obtained. The derived coverage probability is in a closed form, which can be evaluated efficiently. Simulation results are presented to show that the presented analysis is effective, demonstrate the significant performance gains brought by the passive beamforming of a RIS with a large number of elements, and show the impact of TX density on the performance of the proposed system.
{"title":"Stochastic Geometry Analysis for RIS-Assisted Large-Scale Cellular Networks","authors":"Tianxiong Wang, Gaojie Chen, Mihai-Alin Badiu, J. Coon","doi":"10.1109/VTC2022-Fall57202.2022.10012854","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012854","url":null,"abstract":"In this paper, we analyze the coverage probability of a reconfigurable intelligent surface (RIS) aided cellular network with the theory of stochastic geometry. A Poisson cluster process (PCP) is applied to model the positions of transmitters (TXs) and RISs, capturing their spatial correlations. Considering the general Nakagami-m fading channel model, we derive the approximate distributions of the composite channel gains with RIS-assisted transmission, representing the desired signal channel and the interference channel, respectively. The coverage probability of the typical user is then obtained. The derived coverage probability is in a closed form, which can be evaluated efficiently. Simulation results are presented to show that the presented analysis is effective, demonstrate the significant performance gains brought by the passive beamforming of a RIS with a large number of elements, and show the impact of TX density on the performance of the proposed system.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122186825","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}
Age of information (AoI) is proposed to characterize the freshness of information. Since it describes the time elapsed since the information is generated, it can accurately characterize the freshness of the information. Most of the existing studies have focused on the average AoI of systems, but time-sensitive applications such as industrial control systems and sensing networks have strict requirements for information freshness. We consider the scenario of multi-terminal wireless uplink with random packet arrivals and study the system average peak AoI (PAoI) minimization and maximum PAoI minimization problem. First we derive a closed expression of the system average PAoI and sufficient and necessary conditions of the optimal policy, from which an optimal ratio based no butter policy (OR-NB) is developed. We further generalize it to a system design method to make the average PAoI of all terminals satisfy the corresponding hard constraints. In addition, a maximum expected peak AoI (EPAoI) increasing probability minimization policy is proposed to minimize the maximum PAoI, which is proved to be near-optimal.
提出了信息时代(Age of information, AoI)来表征信息的新鲜度。由于它描述了自信息生成以来经过的时间，因此它可以准确地表征信息的新鲜度。现有的研究大多集中在系统的平均AoI上，但工业控制系统和传感网络等时间敏感应用对信息新鲜度有严格的要求。考虑随机分组到达的多终端无线上行场景，研究了系统平均峰值AoI (PAoI)最小化和最大PAoI最小化问题。首先导出了系统平均PAoI的封闭表达式和最优策略的充要条件，并由此导出了基于最优比率的无黄油策略(OR-NB)。我们进一步将其推广为一种系统设计方法，使所有终端的平均pai满足相应的硬约束。此外，提出了一种最大期望峰值AoI (EPAoI)增加概率最小化策略来最小化最大期望峰值AoI，并证明该策略是接近最优的。
{"title":"Optimal Scheduling for Minimizing Peak Age of Information in Uplink Systems","authors":"Ridong Li, Junwei Lei, Qianying Zhou, Zhengchuan Chen, Min Wang, Zhong Tian","doi":"10.1109/VTC2022-Fall57202.2022.10012764","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012764","url":null,"abstract":"Age of information (AoI) is proposed to characterize the freshness of information. Since it describes the time elapsed since the information is generated, it can accurately characterize the freshness of the information. Most of the existing studies have focused on the average AoI of systems, but time-sensitive applications such as industrial control systems and sensing networks have strict requirements for information freshness. We consider the scenario of multi-terminal wireless uplink with random packet arrivals and study the system average peak AoI (PAoI) minimization and maximum PAoI minimization problem. First we derive a closed expression of the system average PAoI and sufficient and necessary conditions of the optimal policy, from which an optimal ratio based no butter policy (OR-NB) is developed. We further generalize it to a system design method to make the average PAoI of all terminals satisfy the corresponding hard constraints. In addition, a maximum expected peak AoI (EPAoI) increasing probability minimization policy is proposed to minimize the maximum PAoI, which is proved to be near-optimal.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130330644","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10013077
M. Mahmood, Asil Koç, T. Le-Ngoc
This work studies the joint design of hybrid pre-coding (HP) and optimal positioning of unmanned aerial vehicle (UAV) relay in a millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems to maximize the spectral and energy efficiencies. The UAV operates as a flying wireless relay, expanding a base station’s coverage and delivering capacity boost to a group of users/devices that are obscured by obstructions. We explore the geometry-based mmWave channel model for the UAV-User link and propose joint HP and UAV positioning scheme (JHPP). In particular, the RF beamformer is designed using singular value decomposition (SVD) of channel matrix by incorporating users’ angle-of-departure (AoD) information to reduce the number of radio frequency (RF) chains, and the baseband (BB) precoder is designed using regularized zero-forcing (RZF) technique to mitigate MU interference. Then, using a particle swarm optimization-based location algorithm (PSO-L), a constrained optimization problem with the goal of maximizing the achievable sum-rate (ASR) is constructed for the optimal UAV placement in the given search space. Illustrative results show that the integration of a UAV relay considerably enhances the performance of mmWave MU-mMIMO systems when the BS is remote. Moreover, compared to UAV random placement in the given flying span, PSO-L based UAV positioning has higher spectral/energy efficiency. Finally, the use of a hemispherical array (HSA) configuration at UAV relay can further increase the performance when compared to uniform rectangular array (URA).
{"title":"PSO-Based Joint UAV Positioning and Hybrid Precoding in UAV-Assisted Massive MIMO Systems","authors":"M. Mahmood, Asil Koç, T. Le-Ngoc","doi":"10.1109/VTC2022-Fall57202.2022.10013077","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10013077","url":null,"abstract":"This work studies the joint design of hybrid pre-coding (HP) and optimal positioning of unmanned aerial vehicle (UAV) relay in a millimeter-wave (mmWave) multi-user massive multiple-input multiple-output (MU-mMIMO) systems to maximize the spectral and energy efficiencies. The UAV operates as a flying wireless relay, expanding a base station’s coverage and delivering capacity boost to a group of users/devices that are obscured by obstructions. We explore the geometry-based mmWave channel model for the UAV-User link and propose joint HP and UAV positioning scheme (JHPP). In particular, the RF beamformer is designed using singular value decomposition (SVD) of channel matrix by incorporating users’ angle-of-departure (AoD) information to reduce the number of radio frequency (RF) chains, and the baseband (BB) precoder is designed using regularized zero-forcing (RZF) technique to mitigate MU interference. Then, using a particle swarm optimization-based location algorithm (PSO-L), a constrained optimization problem with the goal of maximizing the achievable sum-rate (ASR) is constructed for the optimal UAV placement in the given search space. Illustrative results show that the integration of a UAV relay considerably enhances the performance of mmWave MU-mMIMO systems when the BS is remote. Moreover, compared to UAV random placement in the given flying span, PSO-L based UAV positioning has higher spectral/energy efficiency. Finally, the use of a hemispherical array (HSA) configuration at UAV relay can further increase the performance when compared to uniform rectangular array (URA).","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131040413","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012949
Sreelakshmi Pazhoor, Jesy Pachat, Nujoom Sageer Karat, V. Joseph, P. Deepthi, B. Rajan
Vehicular ad hoc network (VANET), is a developing platform with massive data demands for infotainment services in recent years. Index Coded NOMA (IC-NOMA) is a spectral efficient transmission method that can be used in VANETs. IC-NOMA applies the concepts of non-orthogonal multiple access (NOMA) over the index coded data to increase spectrum and power efficiency. In NOMA, far user does not get access to the near user data, while near user can successfully decode far user data. Therefore, the IC-NOMA demands a novel design of index code for improved bandwidth efficiency. This work considers the design of index code for NOMA when the user demands in VANET follows the data distribution of one-sided symmetric neighboring consecutive side information single unicast index coding problem (SNC-SUICP). For this setup, we develop an optimal closed form index coding (IC) solution which can bring in additional bandwidth savings through NOMA. The improved performance of the proposed IC-NOMA transmission scheme when compared with one-sided SNC-SUICP in terms of bandwidth efficiency is demonstrated.
车载自组网(Vehicular ad hoc network, VANET)是近年来发展起来的具有海量数据需求的信息娱乐服务平台。索引编码NOMA (IC-NOMA)是一种适用于VANETs的高效光谱传输方法。IC-NOMA在索引编码数据上应用了非正交多址(NOMA)的概念，以提高频谱和功率效率。在NOMA中，远用户无法访问近用户数据，而近用户可以成功解码远用户数据。因此，IC-NOMA需要一种新的索引码设计来提高带宽效率。本文考虑了VANET中用户需求遵循单侧对称相邻连续侧信息数据分布的NOMA索引编码设计问题(SNC-SUICP)。对于这种设置，我们开发了一个最佳的封闭形式索引编码(IC)解决方案，它可以通过NOMA带来额外的带宽节省。与单侧SNC-SUICP相比，所提出的IC-NOMA传输方案在带宽效率方面有所提高。
{"title":"Optimal Index Code Design for IC-NOMA Transmission in VANETs","authors":"Sreelakshmi Pazhoor, Jesy Pachat, Nujoom Sageer Karat, V. Joseph, P. Deepthi, B. Rajan","doi":"10.1109/VTC2022-Fall57202.2022.10012949","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012949","url":null,"abstract":"Vehicular ad hoc network (VANET), is a developing platform with massive data demands for infotainment services in recent years. Index Coded NOMA (IC-NOMA) is a spectral efficient transmission method that can be used in VANETs. IC-NOMA applies the concepts of non-orthogonal multiple access (NOMA) over the index coded data to increase spectrum and power efficiency. In NOMA, far user does not get access to the near user data, while near user can successfully decode far user data. Therefore, the IC-NOMA demands a novel design of index code for improved bandwidth efficiency. This work considers the design of index code for NOMA when the user demands in VANET follows the data distribution of one-sided symmetric neighboring consecutive side information single unicast index coding problem (SNC-SUICP). For this setup, we develop an optimal closed form index coding (IC) solution which can bring in additional bandwidth savings through NOMA. The improved performance of the proposed IC-NOMA transmission scheme when compared with one-sided SNC-SUICP in terms of bandwidth efficiency is demonstrated.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132495228","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012865
T. Chen, Hong Shen, A. Hu, Weihang He, Jie Xu, Hong-Mei Hu
The vehicle-to-everything (V2X) technology has recently drawn attention from both academic and industrial areas. However, the openness of the wireless communication system makes it more vulnerable to identity impersonation and information tampering. How to employ the powerful radio frequency fingerprint (RFF) identification technology in V2X systems turns out to be a vital and challenging task. In this paper, we propose a novel RFF extraction method for Long Term Evolution-V2X (LTE-V2X) systems. In order to conquer the difficulty of extracting transmitter RFF in the presence of wireless channel and receiver noise, we first estimate the wireless channel which excludes the RFF. Then, we remove the impact of the wireless channel based on the channel estimate and obtain initial RFF features. Finally, we conduct RFF denoising to enhance the quality of the initial RFF. Simulation and experiment results both demonstrate that our proposed RFF extraction scheme achieves a high identification accuracy. Furthermore, the performance is also robust to the vehicle speed.
{"title":"Radio Frequency Fingerprints Extraction for LTE-V2X: A Channel Estimation Based Methodology","authors":"T. Chen, Hong Shen, A. Hu, Weihang He, Jie Xu, Hong-Mei Hu","doi":"10.1109/VTC2022-Fall57202.2022.10012865","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012865","url":null,"abstract":"The vehicle-to-everything (V2X) technology has recently drawn attention from both academic and industrial areas. However, the openness of the wireless communication system makes it more vulnerable to identity impersonation and information tampering. How to employ the powerful radio frequency fingerprint (RFF) identification technology in V2X systems turns out to be a vital and challenging task. In this paper, we propose a novel RFF extraction method for Long Term Evolution-V2X (LTE-V2X) systems. In order to conquer the difficulty of extracting transmitter RFF in the presence of wireless channel and receiver noise, we first estimate the wireless channel which excludes the RFF. Then, we remove the impact of the wireless channel based on the channel estimate and obtain initial RFF features. Finally, we conduct RFF denoising to enhance the quality of the initial RFF. Simulation and experiment results both demonstrate that our proposed RFF extraction scheme achieves a high identification accuracy. Furthermore, the performance is also robust to the vehicle speed.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132735591","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012904
Yunda Li, Xiaolei Shang
We consider the problem of angle estimation and ghost target identification for automotive multiple-input multiple-output (MIMO) radar in multipath scenarios. Firstly, we establish the multipath propagation model for the case of horizental MIMO arrays, and divide the multipath into two categories, i.e., Type 1: multipath with direction-of-arrival (DOA) $neq$ direction-of-departure (DOD); Type 2: multipath with DOA$=$DOD. In the presence of multipath, the different DOA and DOD angles corrupt the notion of virtual array for MIMO radar, making angle estimation a major challenge. To jointly estimate the DOA and DOD of the target reflections, including both the direct path and multipath scenarios, we introduce a multipath iterative adaptive approach (MP-IAA), which possesses the super resolution, low sidelobe level, and robust properties for DOA and DOD estimation. Then, the Type 1 multipath with DOA$neq$DOD can be directly identified based on the MP-IAA’s DOA and DOD estimates. Regarding to the Type 2 multipath with DOA$=$DOD, we solve the triangle relationships to identify the corresponding ghost targets. Numerical examples are provided to demonstrate the effectiveness of the proposed algorithm for angle estimation and ghost target identification using automotive MIMO radar.
{"title":"Multipath Ghost Target Identification for Automotive MIMO Radar","authors":"Yunda Li, Xiaolei Shang","doi":"10.1109/VTC2022-Fall57202.2022.10012904","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012904","url":null,"abstract":"We consider the problem of angle estimation and ghost target identification for automotive multiple-input multiple-output (MIMO) radar in multipath scenarios. Firstly, we establish the multipath propagation model for the case of horizental MIMO arrays, and divide the multipath into two categories, i.e., Type 1: multipath with direction-of-arrival (DOA) $neq$ direction-of-departure (DOD); Type 2: multipath with DOA$=$DOD. In the presence of multipath, the different DOA and DOD angles corrupt the notion of virtual array for MIMO radar, making angle estimation a major challenge. To jointly estimate the DOA and DOD of the target reflections, including both the direct path and multipath scenarios, we introduce a multipath iterative adaptive approach (MP-IAA), which possesses the super resolution, low sidelobe level, and robust properties for DOA and DOD estimation. Then, the Type 1 multipath with DOA$neq$DOD can be directly identified based on the MP-IAA’s DOA and DOD estimates. Regarding to the Type 2 multipath with DOA$=$DOD, we solve the triangle relationships to identify the corresponding ghost targets. Numerical examples are provided to demonstrate the effectiveness of the proposed algorithm for angle estimation and ghost target identification using automotive MIMO radar.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133371660","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 : 2022-09-01DOI: 10.1109/VTC2022-Fall57202.2022.10012702
Xinran Zhang, Hui Tian, Wanli Ni, Mengying Sun
As a distributed machine learning paradigm, federated learning (FL) has been regarded as a promising candidate to preserve user privacy in Internet of Things (IoT) networks. Leveraging the waveform superposition property of wireless channels, over-the-air FL (AirFL) achieves fast model aggregation by integrating communication and computation via concurrent analog transmissions. To support sustainable AirFL among energy-constrained IoT devices, we consider that the base station (BS) adopts simultaneous wireless information and power transfer (SWIPT) to distribute global model and charge local devices in each communication round. To maximize the long-term energy efficiency (EE) of AirFL, we investigate a resource allocation problem by jointly optimizing the time division, transceiver beamforming, and power splitting in SWIPT-enabled IoT networks. Considering such multiple closely-coupled continuous valuables, we propose a deep reinforcement learning (DRL) algorithm based on twin delayed deep deterministic (TD3) policy to smartly make downlink and uplink communication strategies with the coordination between the BS and devices. Simulation results show that the proposed TD3 algorithm obtains about 41% EE improvement compared to traditional optimization method and other DRL algorithms.
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