Joint Device Detection, Channel Estimation, and Data Decoding with Collision Resolution for MIMO Massive Unsourced Random Access

TL;DR

This paper proposes a joint device detection, channel estimation, and data decoding algorithm for MIMO massive unsourced random access, utilizing a two-part data scheme, belief propagation, and collision resolution to improve efficiency and accuracy.

Contribution

It introduces a novel joint DAD-CE-DD algorithm with a two-part data scheme, integrated interference management, and collision resolution for enhanced performance in URA systems.

Findings

Significant performance improvement over existing methods.

Reduced complexity with belief propagation-based decoding.

Effective collision resolution using energy detection and sliding window protocol.

Abstract

In this paper, we investigate a joint device activity detection (DAD), channel estimation (CE), and data decoding (DD) algorithm for multiple-input multiple-output (MIMO) massive unsourced random access (URA). Different from the state-of-the-art slotted transmission scheme, the data in the proposed framework is split into only two parts. A portion of the data is coded by compressed sensing (CS) and the rest is low-density-parity-check (LDPC) coded. In addition to being part of the data, information bits in the CS phase also undertake the task of interleaving pattern design and channel estimation (CE). The principle of interleave-division multiple access (IDMA) is exploited to reduce the interference among devices in the LDPC phase. Based on the belief propagation (BP) algorithm, a low-complexity iterative message passing (MP) algorithm is utilized to decode the data embedded in these two phases separately. Moreover, combined with successive interference cancellation (SIC), the proposed joint DAD-CE-DD algorithm is performed to further improve performance by utilizing the belief of each other. Additionally, based on the energy detection (ED) and sliding window protocol (SWP), we develop a collision resolution protocol to handle the codeword collision, a common issue in the URA system. In addition to the complexity reduction, the proposed algorithm exhibits a substantial performance enhancement compared to the state-of-the-art in terms of efficiency and accuracy.