# Pilot Allocation and Receiver Design for Cell-Free Massive MIMO ISAC Systems

## TL;DR

This paper presents a novel pilot allocation framework and a Gaussian belief propagation receiver design for cell-free massive MIMO ISAC systems, enhancing both communication and sensing performance with reduced complexity.

## Contribution

It introduces a manifold optimization-based pilot allocation and a GaBP-based receiver, improving system sum rate, sensing capabilities, and computational efficiency in CF-mMIMO ISAC systems.

## Key findings

- Achieves communication performance comparable to state-of-the-art algorithms.
- Provides superior sensing capabilities due to unimodular pilot design.
- Reduces computational complexity with the GaBP-based receiver.

## Abstract

This paper tackles two key challenges in cell-freemassive multiple input multiple output (CF-mMIMO) systems:efficient pilot allocation and practical receiver design. To thisend, we introduce a novel pilot allocation framework leveragingmanifold optimization to maximize the system sum rate, wherepilot sequences are designed as nearly orthogonal sequences. Theproposed pilot design enforces unimodularity constraints in thefrequency domain, ensuring pilots are suitable for both communi-cation and sensing tasks. Additionally, a gaussian belief propaga-tion (GaBP)-based receiver is introduced, providing near-optimaldetection performance with substantially reduced computationalcomplexity. Simulation results demonstrate that the proposedpilot allocation method achieves communication performancecomparable to state-of-the-art (SotA) algorithms, while deliveringsuperior sensing capabilities due to its unimodular pilot design.The GaBP-based receiver achieves robust performance andlower complexity compared to conventional approaches. Thesecontributions advance the practical deployment of CF-mMIMOfor integrated sensing and communications (ISAC).