Multi-Access Edge Computing Empowered Integrated Hybrid Sensing and Communication: A Computation-Efficient Design

Integrated sensing and communication (ISAC) system has been emerged as a crucial paradigm for addressing the growing demand of emerging wireless applications that require both ultra-reliable data transmission and high-precision sensing. However, due to the limited computation capability of ISAC devices, the large amount of collected sensing data is difficult to be timely processed. In this paper, we consider that the ISAC device can offload the sensing data to a group edge helper nodes via multi-access edge computing to improve the efficiency of sensing data processing. We propose a multi-access edge computing empowered ISAC with hybrid active and passive sensing, in which the ISAC device can perform passive sensing through the sensing reflected signal from the edge helper nodes while performing active sensing. To investigate this problem, we formulate a joint optimization of the transmit beamforming for active sensing, passive sensing and offloading, as well as the computation rates of both the ISAC device and the edge helper nodes, with the objective of maximizing the total computation rates for the sensing data. Despite the non-convexity of the formulated problem, we propose an efficient algorithm to obtain its solutions. Simulation results validate the performance advantages of our multi-access edge computing empowered integrated hybrid sensing and communication.

I. Introduction

With the Internet of Things (IoT), artificial intelligence (AI), and communications technologies converging at an unprecedented pace, 6G wireless networks are poised to revolutionize the way that we interact with others and surroundings. The emerging immersive services such as autonomous driving, Metaverse, and digital twins introduce innovative use cases that rely on high-throughput low-latency communications and precise sensing capabilities. These applications necessitate both ultra-reliable data transmission and high-precision sensing, which poses a significant challenge to traditional wireless systems [1]. Integrated sensing and communication (ISAC), which allows simultaneous data transmission and sensing information collection via the integrated signal over the same spectrum, has been considered as a spectrum-efficient paradigm for addressing the conflict between these growing demands and stringent wireless resources. Thus, ISAC attracts wide research interests [2]–[5]. Although the great potential of ISAC in improving the spectrum efficiency and resource utilization, the large amount of collected sensing data is difficult to be processed timely due to the limited computation capability of ISAC devices, which necessitates an efficient manner for sensing data processing.