Accelerating Edge Intelligence via Integrated Sensing and Communication

TL;DR

This paper introduces an integrated sensing and communication (ISAC) approach to accelerate edge intelligence by merging data collection and upload stages, optimizing beamforming to minimize errors and improve efficiency.

Contribution

It proposes a novel ISAC framework that combines sensing and communication, along with a globally optimal beamforming design to enhance edge intelligence performance.

Findings

ISAC always benefits when sample generation time exceeds upload time.

The ISAC gain can vanish or turn negative if generation time is less.

A sufficient condition for positive ISAC gain is derived.

Abstract

Realizing edge intelligence consists of sensing, communication, training, and inference stages. Conventionally, the sensing and communication stages are executed sequentially, which results in excessive amount of dataset generation and uploading time. This paper proposes to accelerate edge intelligence via integrated sensing and communication (ISAC). As such, the sensing and communication stages are merged so as to make the best use of the wireless signals for the dual purpose of dataset generation and uploading. However, ISAC also introduces additional interference between sensing and communication functionalities. To address this challenge, this paper proposes a classification error minimization formulation to design the ISAC beamforming and time allocation. The globally optimal solution is derived via the rank-1 guaranteed semidefinite relaxation, and performance analysis is performed to quantify the ISAC gain over that of conventional edge intelligence. Simulation results are provided to verify the effectiveness of the proposed ISAC-assisted edge intelligence system. Interestingly, we find that ISAC is always beneficial, when the duration of generating a sample is more than the duration of uploading a sample. Otherwise, the ISAC gain can vanish or even be negative. Nevertheless, we still derive a sufficient condition, under which a positive ISAC gain is feasible.