Message-Passing Receiver Design for Joint Channel Estimation and Data Decoding in Uplink Grant-Free SCMA Systems

TL;DR

This paper introduces a low-complexity message-passing receiver for uplink grant-free SCMA systems that jointly estimates channels and decodes data without prior user activity knowledge, improving detection accuracy and bit-error-rate.

Contribution

It proposes a novel belief propagation-based receiver using expectation propagation for joint channel estimation and data decoding in grant-free SCMA systems, reducing complexity.

Findings

High user activity detection accuracy

Improved bit-error-rate performance

Linear complexity decoding

Abstract

The conventional grant-based network relies on the handshaking between base station and active users to achieve dynamic multi-user scheduling, which may cost large signaling overheads as well as system latency. To address those problems, the grant-free receiver design is considered in this paper based on sparse code multiple access (SCMA), one of the promising air interface technologies for 5G wireless networks. With the presence of unknown multipath fading, the proposed receiver blindly performs joint channel estimation and data decoding without knowing the user activity in the network. Based on the framework of belief propagation (BP), we formulate a messagepassing receiver for uplink SCMA that performs joint estimation iteratively. However, the direct application of BP for the multivariable detection problem is complex. Motivated by the idea of approximate inference, we use expectation propagation to project the intractable distributions into Gaussian families such that a linear complexity decoder is obtained.Simulation results show that the proposed receiver can detect active users in the network with a high accuracy and can achieve an improved bit-error-rate performance compared with existing methods.