Deep Learning-Based Cramér-Rao Bound Optimization for Integrated Sensing and Communication in Vehicular Networks

Xiaoqi Zhang, Weijie Yuan, Chang Liu, Jun Wu, Zhongjie Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Integrated sensing and communication (ISAC) is capable of achieving both heterogeneous connectivity and highly accurate sensing performance in vehicular networks through effective beamforming design at the roadside unit (RSU). In the traditional paradigm, the first step is predicting the kinematic parameters of each vehicle and then designing the optimal beamforming matrix, which requires excessively large computational complexity. To tackle this issue, this paper proposes a deep learning (DL)-based method that bypasses explicit channel estimation and directly optimizes beamformers to minimize the Cramér-Rao Bound (CRB) of radar sensing while guaranteeing an acceptable level of achievable communication rate. This is achieved by leveraging the convolutional and long short-term memory (CLSTM) neural networks to implicitly capture the features of historical channels, thereby improving the ISAC system performance. Finally, simulation results demonstrate that the proposed approach can satisfy the pre-defined requirement of achievable rate, while simultaneously achieving sensing performance that approaches the perfect beamforming bound.

Original languageEnglish
Title of host publication2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages646-650
Number of pages5
ISBN (Electronic)9781665496261
DOIs
Publication statusPublished - Nov 2023
Event24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023 - Shanghai, China
Duration: 25 Sept 202328 Sept 2023

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

Conference

Conference24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023
Country/TerritoryChina
CityShanghai
Period25/09/2328/09/23

Keywords

  • beamforming
  • convolutional and long short-term memory (CLSTM)
  • Deep learning
  • ISAC
  • vehicular networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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