面向车联网的感知辅助通信的大规模MIMO-OTFS鲁棒传输方案

王为栋; 高晖; 粟欣; 肖立民; 索士强; 龚秋莎

doi:10.11959/j.issn.2096-3750.2023.00363

您当前的位置：

首页 >

文章列表页 >

面向车联网的感知辅助通信的大规模MIMO-OTFS鲁棒传输方案

理论与技术 | 更新时间：2024-08-16

- 面向车联网的感知辅助通信的大规模MIMO-OTFS鲁棒传输方案
- A massive MIMO-OTFS robust transmission scheme for vehicular networks using sensing-assisted communication
- 物联网学报 2023年7卷第4期页码：39-51
- 作者机构：
  
  1. 北京邮电大学可信分布式计算与服务教育部重点实验室，北京 100876
  2. 清华大学电子工程系，北京 100084
  3. 中信科移动通信技术股份有限公司，北京 100083
- 作者简介：
  
  [ "王为栋（1999- ），男，北京邮电大学可信分布式计算与服务教育部重点实验室硕士生，主要研究方向为无线通信、通感一体" ]
  [ "高晖（1984- ），男，博士，北京邮电大学可信分布式计算与服务教育部重点实验室副教授，主要研究方向为毫米波大规模天线系统、智能超表面通信、智能无线通信与网络、通感一体" ]
  [ "粟欣（1962- ），男，博士，清华大学电子工程系教授，主要研究方向为宽带无线接入、自组织网络、软件无线电、协作通信" ]
  [ "肖立民（1970- ），男，博士，清华大学电子工程系副研究员，主要研究方向为信道测量与建模、无线移动通信和宽带无线传输技术" ]
  [ "索士强（1975- ），男，中信科移动通信技术股份有限公司创新中心副总经理，主要研究方向为超大规模天线、人工智能、通信与感知融合" ]
  [ "龚秋莎（1977- ），女，中信科移动通信技术股份有限公司工程师，主要研究方向为移动通信的网络架构、物理层关键技术" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(62071071)
- DOI：10.11959/j.issn.2096-3750.2023.00363
  中图分类号： TN92
- 纸质出版日期：2023-12-20，
  
  网络出版日期：2023-12，
- 稿件说明：
移动端阅览
王为栋, 高晖, 粟欣, 等. 面向车联网的感知辅助通信的大规模MIMO-OTFS鲁棒传输方案[J]. 物联网学报, 2023,7(4):39-51.

WEIDONG WANG, HUI GAO, XIN SU, et al. A massive MIMO-OTFS robust transmission scheme for vehicular networks using sensing-assisted communication. [J]. Chinese journal on internet of things, 2023, 7(4): 39-51.
王为栋, 高晖, 粟欣, 等. 面向车联网的感知辅助通信的大规模MIMO-OTFS鲁棒传输方案[J]. 物联网学报, 2023,7(4):39-51. DOI： 10.11959/j.issn.2096-3750.2023.00363.

WEIDONG WANG, HUI GAO, XIN SU, et al. A massive MIMO-OTFS robust transmission scheme for vehicular networks using sensing-assisted communication. [J]. Chinese journal on internet of things, 2023, 7(4): 39-51. DOI： 10.11959/j.issn.2096-3750.2023.00363.

摘要

面向车联网多用户通感一体系统，提出了一种感知辅助通信的大规模多输入多输出正交时频空鲁棒传输方案。由于实际雷达感知精度有限，基于感知参数重构的信道状态信息（CSI

channel state information）存在误差，系统的传输性能也会随之下降。对此，所提方案首先在发射端基于感知参数在时延多普勒域重构CSI，并考虑CSI误差设计鲁棒波束成形方案。其次，在接收端利用感知参数觉知用户间干扰及信道估计误差，并将所觉知的干扰误差以解析式的方式融入接收机中完成鲁棒设计。仿真结果表明，所提方案可以在CSI非理想情况下有效降低系统误码率，增加用户的数据接收速率，提升系统的整体性能。

Abstract

For a multi-user integrated sensing and communication system in the network of vehicles

a robust sensing-assisted communication massive multiple-input multiple-output (MIMO) orthogonal time frequency space (OTFS) transmission scheme was proposed.Due to the limited sensing accuracy of the radar

errors existed in the channel state information (CSI) reconstructed based on sensing parameters.The transmission performance decreased as a result.To address this issue

the CSI in the delay doppler domain was reconstructed based on the sensing parameters by the transmitter firstly.And a robust beam forming scheme was designed considering the CSI error.Secondly

the channel estimation error and inter user interference were perceived by receivers based on sensing parameters.Then the robust receiver was designed by incorporating the perceived interference errors into the signal detector in an analytical way.Finally

numerical simulation results show that the proposed method effectively reduces the system bit error rate and increases the data reception rate of users.The proposed method improves the overall system performance in this situation.

关键词

正交时频空通感一体技术信号检测器鲁棒波束成形

Keywords

orthogonal time frequency spaceintegrated sensing and communicationsignal detectorrobust beamforming

references

WONG V W S, SCHOBER R, NG D W K ,et al. Key technologies for 5G wireless systems[M]. Cambridge: Cambridge university press, 2017.

YUAN W J, LI S Y, XIANG L ,et al. Distributed estimation framework for beyond 5G intelligent vehicular networks[J]. IEEE Open Journal of Vehicular Technology, 2020(1): 190-214.

SIEGEL J E, ERB D C, SARMA S E . A survey of the connected vehicle landscape—architectures,enabling technologies,applications,and development areas[J]. IEEE Transactions on Intelligent Transportation Systems, 2017,19(8): 2391-2406.

LU N, CHENG N, ZHANG N ,et al. Connected vehicles:solutions and challenges[J]. IEEE Internet of Things Journal, 2014,1(4): 289-299.

WYMEERSCH H, SECO-GRANADOS G, DESTINO G ,et al. 5G mmWave positioning for vehicular networks[J]. IEEE Wireless Communications, 2017,24(6): 80-86.

KUUTTI S, FALLAH S, KATSAROS K ,et al. A survey of the state-of-the-art localization techniques and their potentials for autonomous vehicle applications[J]. IEEE Internet of Things Journal, 2018,5(2): 829-846.

ZHANG J A, RAHMANM L, WU K ,et al. Enabling joint communication and radar sensing in mobile networks:a survey[J]. arXiv Print,2020:arXiv:2006:2006.07559..

LIU F, MASOUROS C, PETROPULU A P ,et al. Joint radar and communication design:applications,state-of-the-art,and the road ahead[J]. IEEE Transactions on Communications, 2020,68(6): 3834-3862.

SHI C G, WANG F, SELLATHURAI M ,et al. Power minimization-based robust OFDM radar waveform design for radar and communication systems in coexistence[J]. IEEE Transactions on Signal Processing, 2018,66(5): 1316-1330.

SEN S, NEHORAI A . Adaptive OFDM radar for target detection in multipath scenarios[J]. IEEE Transactions on Signal Processing, 2011,59(1): 78-90.

HADANI R, RAKIB S, TSATSANIS M ,et al. Orthogonal time frequency space modulation[C]// Proceedings of 2017 IEEE Wireless Communications and Networking Conference (WCNC). Piscataway:IEEE Press, 2017: 1-6.

LI S Y, YUAN J H, YUAN W J ,et al. Performance analysis of coded OTFS systems over high-mobility channels[J]. IEEE Transactions on Wireless Communications, 2021,20(9): 6033-6048.

DU Z, LIU F, YUAN W J ,et al. Integrated sensing and communications for V2I networks:dynamic predictive beam forming for extended vehicle targets[J]. IEEE Transactions on Wireless Communications, 2023,22(6): 3612-3627.

CORREAS-SERRANO A, PETROV N, GONZALEZ-HUICI M ,et al. Comparison of radar receivers for OFDM and OTFS waveforms[C]// Proceedings of 2022 19th European Radar Conference (EuRAD). Piscataway:IEEE Press, 2022: 1-4.

GAUDIO L, KOBAYASHI M, BISSINGER B ,et al. Performance analysis of joint radar and communication using OFDM and OTFS[C]// Proceedings of 2019 IEEE International Conference on Communications Workshops (ICC Workshops). Piscataway:IEEE Press, 2019: 1-6.

ZHANG K, YUAN W, LI S ,et al. Radar sensing via OTFS signaling:a delay Doppler signal processing perspective[J]. arXiv Print,2023:arXiv:2301:2301.09909.

WU K, ZHANG J A, HUANG X J ,et al. OTFS-based joint communication and sensing for future industrial IoT[J]. IEEE Internet of Things Journal, 2023,10(3): 1973-1989.

DEHKORDI S K, GAUDIO L, KOBAYASHI M ,et al. Beam-space MIMO radar for joint communication and sensing with OTFS modulation[J]. IEEE Transactions on Wireless Communications, 2023(99): 1.

YUAN W J, WEI Z Q, LI S Y ,et al. Integrated sensing and communication-assisted orthogonal time frequency space transmission for vehicular networks[J]. IEEE Journal of Selected Topics in Signal Processing, 2021,15(6): 1515-1528.

ZHANG W L, LI H R, MU P C ,et al. Robust multi-branch space–time beam forming for OFDM system with interference[J]. Digital Signal Processing, 2017(65): 63-70.

GAUDIO L, KOBAYASHI M, CAIRE G ,et al. On the effectiveness of OTFS for joint radar parameter estimation and communication[J]. IEEE Transactions on Wireless Communications, 2020,19(9): 5951-5965.

NGO H Q . Massive MIMO:fundamentals and system designs[M]. Linköping University Electronic Press, 2015.

SRIVASTAVA S, SINGH R K, JAGANNATHAM A K ,et al. Delay-Doppler and angular domain 4D-sparse CSI estimation in OTFS aided MIMO systems[J]. IEEE Transactions on Vehicular Technology, 2022,71(12): 13447-13452.

SRIVASTAVA S, SINGH R K, JAGANNATHAM A K ,et al. OTFS transceiver design and sparse doubly-selective CSI estimation in analog and hybrid beam forming aided mm Wave MIMO systems[J]. IEEE Transactions on Wireless Communications, 2022,21(12): 10902-10917.

GUO W, ZHANG W L, MU P C ,et al. High-mobility wideband massive MIMO communications:Doppler compensation,analysis and scaling laws[J]. IEEE Transactions on Wireless Communications, 2019,18(6): 3177-3191.

CHIRIYATH A R, PAUL B, BLISS D W . Radar-communications convergence:coexistence,cooperation,and co-design[J]. IEEE Transactions on Cognitive Communications and Networking, 2017,3(1): 1-12.

PATOLE S M, TORLAK M, WANG D ,et al. Automotive radars:a review of signal processing techniques[J]. IEEE Signal Processing Magazine, 2017,34(2): 22-35.

FRIEDLANDER B . On transmit beamforming for MIMO radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012,48(4): 3376-3388.

LUO Z Q, MA W K, SO A M C ,et al. Semidefinite relaxation of quadratic optimization problems[J]. IEEE Signal Processing Magazine, 2010,27(3): 20-34.

HUANG Z X, ZHENG B X, ZHANG R . Transforming fading channel from fast to slow:IRS-assisted high-mobility communication[C]// Proceedings of ICC 2021 - IEEE International Conference on Communications. Piscataway:IEEE Press, 2021: 1-6.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据