A Low-Complexity CRC-Based Decoding Algorithm for SLM-ML OFDM Systems

被引：7

作者：

Li, Junbing ^{[1
]}

Zeng, Xiaoping ^{[1
]}

Yin, Congji ^{[1
]}

Luo, Qi ^{[1
]}

Li, Guojun ^{[2
]}

机构：

[1] Chongqing Univ, Sch Microelect & Commun Engn, Chongqing 400044, Peoples R China

[2] Chongqing Univ Posts & Telecommun, Lab Reliable Informat Transmiss, Chongqing 400065, Peoples R China

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2021年 / 10卷 / 06期

关键词：

Peak to average power ratio; Receivers; Indexes; Wireless communication; Maximum likelihood decoding; Computational modeling; Signal to noise ratio; Maximum likelihood detection; computational complexity; CRC; SLM; SI; POWER RATIO REDUCTION;

D O I：

10.1109/LWC.2020.3042676

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this letter, a low-complexity selected mapping (SLM) algorithm without phase sequence index information, e.g., side information (SI), is proposed. Different from the SLM algorithm without SI using maximum likelihood (ML), the proposed algorithm uses cyclic redundancy check (CRC) to terminate the decoding calculation in advance. Meanwhile, a small amount of known information is adopeted to assist CRC and a simpler phase sequence set is applied to the SLM. The calculation complexity and bit error rate (BER) of typical algorithms are compared with different phase sequence groups under several different channel conditions. As a result, lower computation complexity is obtained with the same peak to average power ratio (PAPR) suppression effect and no BER increase.

引用

页码：1144 / 1147

页数：4

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