Joint Spectrum Partitioning and Power Allocation for Energy Efficient Semi-Integrated Sensing and Communications

TL;DR

This paper introduces joint spectrum partitioning and power allocation schemes to enhance energy efficiency and performance in semi-integrated sensing and communication systems supporting multiple services.

Contribution

It proposes novel joint resource allocation schemes that optimize sensing and communication performance while considering service priorities and QoS constraints.

Findings

Joint convexity of the spectrum partitioning problem.

Non-convexity of the power allocation problem and its optimal solution.

Numerical results demonstrate the schemes' effectiveness and reveal insights on service priorities.

Abstract

With spectrum resources becoming congested and the emergence of sensing-enabled wireless applications, conventional resource allocation methods need a revamp to support communications-only, sensing-only, and integrated sensing and communication (ISaC) services together. In this letter, we propose two joint spectrum partitioning (SP) and power allocation (PA) schemes to maximize the aggregate sensing and communication performance as well as corresponding energy efficiency (EE) of a semi-ISaC system that supports all three services in a unified manner. The proposed framework captures the priority of the distinct services, impact of target clutters, power budget and bandwidth constraints, and sensing and communication quality-of-service (QoS) requirements. We reveal that the former problem is jointly convex and the latter is a non-convex problem that can be solved optimally by exploiting fractional and parametric programming techniques. Numerical results verify the effectiveness of proposed schemes and extract novel insights related to the impact of the priority and QoS requirements of distinct services on the performance of semi-ISaC networks.