Optimizing 6G Integrated Sensing and Communications (ISAC) via Expert Networks

TL;DR

This paper introduces an MoE-based framework to optimize 6G ISAC systems, enhancing sensing accuracy and robustness by selectively activating specialized experts, addressing resource constraints in integrated sensing and communication.

Contribution

It proposes a novel MoE architecture for ISAC, integrating expert networks with gating mechanisms to improve sensing performance under resource limitations.

Findings

Increased target detection accuracy

Enhanced robustness in sensing tasks

Effective resource utilization in ISAC systems

Abstract

Integrated Sensing and Communications (ISAC) is one of the core technologies of 6G, which combines sensing and communication functions into a single system. However, limited computing and storage resources make it impractical to combine multiple sensing models into a single device, constraining the system's function and performance. Therefore, this article proposes enhancing ISAC with the mixture of experts (MoE) architecture. Rigorously, we first investigate ISAC and MoE, including their concepts, advantages, and applications. Then, we explore how MoE can enhance ISAC from the perspectives of signal processing and network optimization. Building on this, we propose an MoE based ISAC framework, which uses a gating network to selectively activate multiple experts in handling sensing tasks under given communication conditions, thereby improving the overall performance. The case study demonstrates that the proposed framework can effectively increase the accuracy and robustness in detecting targets by using wireless communication signal, providing strong support for the practical deployment and applications of the ISAC system.