Performance Analysis of Joint Active User Detection and Channel Estimation for Massive Connectivity

Jia Cheng Jiang, Hui Ming Wang, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This paper considers joint active user detection (AUD) and channel estimation (CE) for massive connectivity scenarios with sporadic traffic. The state-of-art method under a Bayesian framework to perform joint AUD and CE in such scenarios is approximate message passing (AMP). However, the existing theoretical analysis of AMP-based joint AUD and CE can only be performed with a given fixed point of the AMP state evolution function, lacking the analysis of AMP phase transition and Bayes-optimality. In this paper, we propose a novel theoretical framework to analyze the performance of the joint AUD and CE problem by adopting the replica method in the Bayes-optimal condition. Specifically, our analysis is based on a general channel model, which reduces to particular channel models in multiple typical MIMO communication scenarios. Our theoretical framework allows ones to measure the optimality and phase transition of AMP-based joint AUD and CE as well as to predict the corresponding performance metrics under our model. To reify our proposed theoretical framework, we analyze two typical scenarios from the massive random access literature, i.e., the isotropic channel scenario and the spatially correlated channel scenario. Accordingly, our performance analysis produces some novel results for both the isotropic Raleigh channel and the spatially correlated channel case.

Original languageEnglish (US)
Pages (from-to)3647-3662
Number of pages16
JournalIEEE Transactions on Signal Processing
Volume70
DOIs
StatePublished - 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Joint active user detection and channel estimation
  • Massive random access
  • Performance analysis
  • Replica method
  • massive MIMO

Fingerprint

Dive into the research topics of 'Performance Analysis of Joint Active User Detection and Channel Estimation for Massive Connectivity'. Together they form a unique fingerprint.

Cite this