Cooperative Base Station Assignment and Resource Allocation for 6G ISAC Network

TL;DR

The paper tackles joint resource management for a multi-BS ISAC network with moving targets and ISAC users. It introduces CBARA, a cooperative BS assignment and resource allocation framework that optimizes the posterior Cramér-Rao bound (PCRLB) for sensing and the achievable rate for communications, using a two-step heuristic plus alternating optimization. By relaxing the inverse Fisher information via an auxiliary variable and solving subproblems with CVX, CBARA achieves substantial performance gains compared to classic schemes, closely approaching exhaustive search results while offering favorable computational complexity. The work advances practical design for 6G ISAC deployments by enabling dynamic, scalable, and balanced C&S performance in decentralized, multi-BS settings.

Abstract

In the upcoming 6G networks, integrated sensing and communications (ISAC) will be able to provide a performance boost in both perception and wireless connectivity. This paper considers a multiple base station (BS) architecture to support the comprehensive services of data transmission and multi-target sensing. In this context, a cooperative BS assignment and resource allocation (CBARA) strategy is proposed in this paper, aiming at jointly optimizing the communication and sensing (C&S) performance. The posterior Cramer-Rao lower bound and the achievable rate with respect to transmit power and bandwidth are derived and utilized as optimization criteria for the CBARA scheme. We develop a heuristic alternating optimization algorithm to obtain an effective sub-optimal solution for the non-convex optimization problem caused by multiple coupled variables. Numerical results show the effectiveness of the proposed solution, which achieves a performance improvement of 117% in communication rate and 40% in sensing accuracy, compared to the classic scheme.

Figures (10)

• Figure 1: An illustration of multi-BS ISAC network.
• Figure 2: Geometric distribution of multiple BSs, sensing targets and ISAC user, where the orrows represent the movement directions of objects and the dashed lines represent the trajectories.
• Figure 3: C&S performance with different values of scale factor $\eta$.
• Figure 4: Power and bandwidth allocation results with different value of $\eta$ for Target 1, Target 2 and ISAC 3.
• Figure 5: BS assignment and resource allocation results with $\eta$ = 0.7.