Joint Detection and Velocity Estimation in OFDM-ISAC Cell-Free Massive MIMO Networks

2026-04-20

AI Summary

This work addresses the degradation in sensing performance caused by Doppler effects in cell-free massive MIMO OFDM-ISAC systems by proposing a Doppler-aware joint framework for target detection and three-dimensional velocity estimation. It is the first to explicitly model three-dimensional bistatic Doppler geometry in cell-free ISAC and introduces a user–target-centric access point association mechanism. Leveraging the generalized likelihood ratio test, the framework integrates coarse grid search, gradient-based optimization, and particle swarm optimization (PSO) to strike an effective balance between estimation accuracy and computational complexity. Experimental results demonstrate that the proposed PSO-assisted detector significantly outperforms baseline methods in highly dynamic scenarios, effectively mitigating sensing SNR loss due to Doppler mismatch, with performance further enhanced as the number of OFDM subcarriers increases.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper develops a Doppler-aware sensing framework for cell-free massive MIMO (CF-mMIMO) networks operating under OFDM-based integrated sensing and communication (ISAC). The framework explicitly incorporates the 3D-bistatic Doppler geometry across distributed access points (APs) into a generalized likelihood ratio test (GLRT) detector. To address the scalability, a user-target-centric AP association approach is utilized. The 3D tangential components of the target's velocity vector are estimated, and several search and optimization strategies, including coarse grid search, gradient-based refinement, and particle swarm optimization (PSO), are developed and evaluated. The Doppler-aware GLRT statistic and receive sensing signal-to-noise ratio (SNR) are derived. Simulation results demonstrate that the proposed PSO-aided detector achieves the most favorable accuracy-complexity trade-off, while Doppler mismatch can cause substantial sensing-SNR degradation in high-mobility scenarios. Additionally, leveraging more OFDM subcarriers enhances frequency-domain diversity and yields further sensing-SNR gains.

Problem

• Doppler-aware sensing
• cell-free massive MIMO
• OFDM-ISAC
• joint detection and velocity estimation
• 3D-bistatic Doppler

Innovation

• Doppler-aware sensing
• cell-free massive MIMO
• OFDM-ISAC
• velocity estimation
• generalized likelihood ratio test