Integrated Sensing and Communication for Edge Inference With End-to-End Multi-View Fusion

Xibin Jin, Guoliang Li, Shuai Wang, Miaowen Wen, Chengzhong Xu, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Integrated sensing and communication (ISAC) is a promising solution to accelerate edge inference via the dual use of wireless signals. However, this paradigm needs to minimize the inference error and latency under ISAC co-functionality interference, for which the existing ISAC or edge resource allocation algorithms become inefficient, as they ignore the inter-dependency between low-level ISAC designs and high-level inference services. This letter proposes an inference-oriented ISAC (IO-ISAC) scheme, which minimizes upper bounds on end-to-end inference error and latency using multi-objective optimization. The key to our approach is to derive a multi-view inference model that accounts for both the number of observations and the angles of observations, by integrating a half-voting fusion rule and an angle-aware sensing model. Simulation results show that the proposed IO-ISAC outperforms other benchmarks in terms of both accuracy and latency.

Original languageEnglish (US)
Pages (from-to)2040-2044
Number of pages5
JournalIEEE Wireless Communications Letters
Volume13
Issue number8
DOIs
StatePublished - 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Keywords

  • Edge inference
  • integrated sensing and communication
  • multi-view fusion

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