English

Performance Analysis and Power Allocation for Massive MIMO ISAC Systems

Signal Processing 2025-03-19 v3

Abstract

Integrated sensing and communications (ISAC) is envisioned as a key feature in future wireless communications networks. Its integration with massive multiple-input-multiple-output (MIMO) techniques promises to leverage substantial spatial beamforming gains for both functionalities. In this work, we consider a massive MIMO-ISAC system employing a uniform planar array with zero-forcing and maximum-ratio downlink transmission schemes combined with monostatic radar-type sensing. Our focus lies on deriving closed-form expressions for the achievable communications rate and the Cram\'er--Rao lower bound (CRLB), which serve as performance metrics for communications and sensing operations, respectively. The expressions enable us to investigate important operational characteristics of massive MIMO-ISAC, including the mutual effects of communications and sensing as well as the advantages stemming from using a very large antenna array for each functionality. Furthermore, we devise a power allocation strategy based on successive convex approximation to maximize the communications rate while guaranteeing the CRLB constraints and transmit power budget. Extensive numerical results are presented to validate our theoretical analyses and demonstrate the efficiency of the proposed power allocation approach.

Keywords

Cite

@article{arxiv.2411.10723,
  title  = {Performance Analysis and Power Allocation for Massive MIMO ISAC Systems},
  author = {Nhan Thanh Nguyen and Van-Dinh Nguyen and Hieu V. Nguyen and Hien Quoc Ngo and A. Lee Swindlehurst and Markku Juntti},
  journal= {arXiv preprint arXiv:2411.10723},
  year   = {2025}
}

Comments

This paper has been accepted by IEEE Transaction on Signal Processing

R2 v1 2026-06-28T20:02:08.522Z