Yang, Boran;
Zhang, Xiaoxu;
Hao, Li;
Lei, Xianfu;
Masouros, Christos;
(2025)
Covariance-Based Block Gibbs Sampling for Massive MIMO Grant-Free Random Access.
IEEE Transactions on Vehicular Technology
10.1109/tvt.2025.3640008.
(In press).
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Abstract
In this work, we study the active user detection and channel estimation problem in massive multiple-input multiple-output (MIMO) grant-free random access systems. To exploit the favorable propagation condition and inherent sparsity of massive MIMO channel induced by antenna array enlargement and sporadic user activity, we develop a covariance-based compressed sensing framework, in which a generalized truncated spike-and-slab prior is formulated to model the covariance signal, and two low-complexity Gibbs sampling (GS) strategies are proposed to numerically approximate the hyperparameters. First, a block GS (BGS) algorithm is developed by splitting the target signal into multiple sub-blocks and performing block-wise sampling in low-dimensional spaces. Then, a covariance-free BGS (CoFe-BGS) algorithm is proposed to reduce the complexity of matrix inversion in the block sampling procedure. The computational advantages of BGS and CoFe-BGS are supported by complexity analysis. Simulation results show that the proposed algorithms outperform the standard GS method and other counterparts.
| Type: | Article |
|---|---|
| Title: | Covariance-Based Block Gibbs Sampling for Massive MIMO Grant-Free Random Access |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/tvt.2025.3640008 |
| Publisher version: | https://doi.org/10.1109/tvt.2025.3640008 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Vectors , Sparse matrices , Covariance matrices , Massive MIMO , Approximation algorithms , Matrix converters , Complexity theory , Indexes , Bayes methods , Simulation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10218827 |
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