Downlink SCMA Codebook Design with Low Error Rate by Maximizing Minimum Euclidean Distance of Superimposed Codewords
Chinwei Huang, Borching Su, Tingyi Lin, Yenming Huang

TL;DR
This paper introduces a novel iterative algorithm to design SCMA codebooks that maximize the minimum Euclidean distance, leading to improved error rate performance in downlink scenarios relevant to 5G/NR.
Contribution
It proposes the first known method to optimize SCMA codebooks by MED maximization, outperforming existing codebooks in downlink error rate performance.
Findings
Achieves larger MED than previous codebooks.
Demonstrates improved BER in downlink 5G/NR scenarios.
Provides an upper bound on MED via dual problem.
Abstract
Sparse code multiple access (SCMA), as a codebook-based non-orthogonal multiple access (NOMA) technique, has received research attention in recent years. The codebook design problem for SCMA has also been studied to some extent since codebook choices are highly related to the system's error rate performance. In this paper, we approach the SCMA codebook design problem by formulating an optimization problem to maximize the minimum Euclidean distance (MED) of superimposed codewords under power constraints. While SCMA codebooks with a larger MED are expected to obtain a better BER performance, no optimal SCMA codebook in terms of MED maximization, to the authors' best knowledge, has been reported in the SCMA literature yet. In this paper, a new iterative algorithm based on alternating maximization with exact penalty is proposed for the MED maximization problem. The proposed algorithm, when…
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