用于多址中继信道的带联合点阵解码的非正交计算转发

Tzu-Yueh Tseng, Chung-Pi Lee, Shih-Chun Lin, Hsuan-Jung Su
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引用次数: 5

摘要

中继辅助多用户通信对于未来的5G系统至关重要。在本文中,我们考虑了双用户多址中继信道(MARC),其中两个用户在半双工中继的帮助下将消息发送到一个共同的目的地。在我们之前的工作中[1],基于解码和转发(DF)的晶格编码被证明对MARC是有效的。但是当用户到中继的链路较弱时,DF协议可能无法对中继上的所有用户进行解码。针对这一问题,我们提出了一种新的点阵编码,中继只需要解码用户点阵码字的整数加权和,用基于模的映射器重新映射,然后转发相应的码字。虽然中继的解码类似于正交计算转发协议,但我们放宽了以前的工作对中继传输时用户必须保持沉默以避免干扰的限制。关键是在目的地执行联合多用户点阵解码。这种联合译码策略不仅使相应的码设计复杂化,而且使误差分析复杂化。为了在中继上找到合适的目标联合解码器的整数加权和,我们还通过仔细地将非凸整数问题转换并松弛为凸整数问题来解决非凸整数问题。仿真结果表明,所提出的非正交晶格编码在各种信道设置下都优于现有的编码方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-orthogonal compute-and-forward with joint lattice decoding for the multiple-access relay channel
Relay-aided multiuser communications are crucial for future 5G systems. In this paper, we consider the two-user multiple access relay channel (MARC), in which two users transmit messages to a common destination with the assistance of a half-duplex relay. The decode-and-forward (DF) based lattice coding was shown to be effective for the MARC in our previous work [1]. However when the links from the users to the relay are weak, DF protocol may fail to decode all users at the relay. Aiming to solve this problem, we propose a new lattice coding where the relay only needs to decode an integer-weighted-sum of users' lattice codewords, re-maps it with a modulo-based mapper and then forwards the corresponding codeword. Although the decoding at the relay is akin to the orthogonal compute-and-forward protocol, we relax the restriction imposed by previous works that the users have to be silent when the relay is transmitting to avoid interference. The key ingredient is the joint multi-user lattice decoding performed at the destination. This jointly decoding strategy not only complicates the corresponding code design but also the error analysis. To find the proper integer-weighted-sum at the relay for the destination's joint decoder, we also solve a non-convex integer problem by carefully transforming and relaxing it to a convex one. Simulation results show that the proposed non-orthogonal lattice coding can outperform existing schemes in a variety of channel settings.
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