2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)最新文献_第10页

Inter-Access Point Coordinated User and Beam Selection for mmWave Distributed MIMO Systems 毫米波分布式MIMO系统的接入点间协调用户和波束选择

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012948

Jun Shikida, K. Muraoka, Toshiki Takeuchi, N. Ishii

引用次数: 0

A Robust Few-Shot SEI Method Using Class-Reconstruction and Adversarial Training 基于类重构和对抗训练的鲁棒少弹SEI方法

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012716

Chao Liu, Xue Fu, Yunlu Ge, Yu Wang, Yun Lin, Guan Gui, H. Sari

引用次数: 1

Sensing-Assisted Robust Vehicle-to-Vehicle Communication with Multiple Antennas 基于多天线的传感辅助鲁棒车对车通信

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012722

Yanjie Pu, Zhiying Song, Fuxi Wen, Shenghua Zhou

引用次数: 0

Stochastic Geometry Analysis for RIS-Assisted Large-Scale Cellular Networks ris辅助大规模蜂窝网络的随机几何分析

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012854

Tianxiong Wang, Gaojie Chen, Mihai-Alin Badiu, J. Coon

引用次数: 0

Optimal Scheduling for Minimizing Peak Age of Information in Uplink Systems 最小上行系统信息峰值年龄的最优调度

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012764

Ridong Li, Junwei Lei, Qianying Zhou, Zhengchuan Chen, Min Wang, Zhong Tian

{"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}

引用次数: 0

PSO-Based Joint UAV Positioning and Hybrid Precoding in UAV-Assisted Massive MIMO Systems 无人机辅助大规模MIMO系统中基于pso的联合无人机定位与混合预编码

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10013077

M. Mahmood, Asil Koç, T. Le-Ngoc

{"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}

引用次数: 2

Optimal Index Code Design for IC-NOMA Transmission in VANETs VANETs中IC-NOMA传输索引码优化设计

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012949

Sreelakshmi Pazhoor, Jesy Pachat, Nujoom Sageer Karat, V. Joseph, P. Deepthi, B. Rajan

{"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}

引用次数: 0

Radio Frequency Fingerprints Extraction for LTE-V2X: A Channel Estimation Based Methodology LTE-V2X射频指纹提取:一种基于信道估计的方法

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012865

T. Chen, Hong Shen, A. Hu, Weihang He, Jie Xu, Hong-Mei Hu

{"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}

引用次数: 2

Multipath Ghost Target Identification for Automotive MIMO Radar 汽车MIMO雷达多径幽灵目标识别

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012904

Yunda Li, Xiaolei Shang

{"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}

引用次数: 3

Deep Reinforcement Learning for Over-the-Air Federated Learning in SWIPT-Enabled IoT Networks 支持swift的物联网网络中无线联合学习的深度强化学习

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall) Pub Date : 2022-09-01 DOI: 10.1109/VTC2022-Fall57202.2022.10012702

Xinran Zhang, Hui Tian, Wanli Ni, Mengying Sun

{"title":"Deep Reinforcement Learning for Over-the-Air Federated Learning in SWIPT-Enabled IoT Networks","authors":"Xinran Zhang, Hui Tian, Wanli Ni, Mengying Sun","doi":"10.1109/VTC2022-Fall57202.2022.10012702","DOIUrl":"https://doi.org/10.1109/VTC2022-Fall57202.2022.10012702","url":null,"abstract":"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.","PeriodicalId":326047,"journal":{"name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","volume":"26 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":"131832345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1