Enhanced Codebook of Sparse Vector Coding Based on Mean-Variance Trade-Off Model for URLLC

IF 3.7 3区计算机科学 Q2 TELECOMMUNICATIONS

IEEE Communications Letters Pub Date : 2025-04-11 DOI:10.1109/LCOMM.2025.3559985

Yifei Yang;Changju Chen;Pengcheng Zhu

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引用次数: 0

Abstract

Sparse Vector Coding (SVC) is a novel coding scheme of short packet transmission in Ultra-Reliable Low-Latency Communication (URLLC). SVC is usually modeled as a standard Compressed Sensing (CS) model, so the column correlation coefficient of the encoding dictionary will directly determine the decoding performance. Starting from the point of view of optimizing codebook, this letter will first model the minimization of the maximum column correlation coefficient as a linear integer programming (LIP) problem, and obtain a tighter solution than existing studies. Then, the optimization objective was transformed into statistical parameters of column correlation coefficient distribution and modeled as mean-variance trade-off model, which was a convex optimization problem and optimized by Semi-Definite Programming (SDP) and Modern Portfolio Theory (MPT) respectively, improving the Block Error Ratio (BLER) performance about 1dB and reduced the computational complexity. Simulation results verify the effectiveness of the above algorithms and improve the decoding performance effectively.

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基于均值方差权衡模型的URLLC稀疏矢量编码增强码本

稀疏矢量编码（SVC）是超可靠低延迟通信（URLLC）中短包传输的一种新型编码方案。SVC通常被建模为标准的压缩感知（Compressed Sensing， CS）模型，因此编码字典的列相关系数将直接决定解码性能。本文从优化码本的角度出发，首先将最大列相关系数的最小化建模为线性整数规划（LIP）问题，并获得比现有研究更严格的解。然后，将优化目标转化为列相关系数分布的统计参数，建立均值方差权衡模型，作为一个凸优化问题，分别采用半确定规划（SDP）和现代投资组合理论（MPT）进行优化，使块错误率（BLER）性能提高约1dB，降低了计算复杂度。仿真结果验证了上述算法的有效性，有效地提高了译码性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Letters 工程技术-电信学

CiteScore

8.10

自引率

7.30%

发文量

590

审稿时长

2.8 months

期刊介绍： The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.