2-Step phase rotation estimation for Low-PAPR signal transmission using blind selected mapping

Amnart Boonkajay, F. Adachi
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引用次数: 8

Abstract

Blind selected mapping (blind SLM) can effectively reduce the peak-to-average power ratio (PAPR) of both orthogonal frequency division multiplexing (OFDM) and single-carrier (SC) signals without side-information transmission. In typical blind SLM, maximum likelihood (ML) estimation is applied to find the de-mapping phase rotation sequence which gives the lowest Euclidean distance among all possible sequences, resulting in very high computational complexity. In this paper, we introduce a novel low-complexity 2-step estimation suitable for blind SLM. In the first step, the phase rotation sequence achieving the lowest Euclidean distance is searched by using the Viterbi algorithm. In the second step, verification and correction are carried out to choose a phase rotation sequence stored in the codebook, which has the lowest Hamming distance from the estimated sequence in the first step. It is confirmed by computer simulation that our proposed 2-step estimation achieves similar BER performance to the transmission without SLM and the transmission with blind SLM with the conventional ML estimation, but the proposed estimation technique requires much less complexity.
基于盲选择映射的低papr信号传输两步相位旋转估计
盲选择映射(Blind SLM)可以有效地降低正交频分复用(OFDM)和无侧信息传输的单载波(SC)信号的峰均功率比(PAPR)。在典型的盲SLM中,采用极大似然估计来寻找在所有可能序列中给出最小欧氏距离的反映射相旋转序列,这导致了很高的计算复杂度。本文提出了一种适用于盲单点线性模型的低复杂度二步估计方法。第一步,利用Viterbi算法搜索达到最小欧氏距离的相位旋转序列;第二步进行验证和校正,选择存储在码本中的与第一步估计序列汉明距离最小的相位旋转序列。计算机仿真结果表明,本文提出的两步估计与无SLM传输和盲SLM传输的误码率性能相当,但所提出的估计技术的复杂度要低得多。
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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