Iterative SNR estimation using a priori information

被引：1
|
作者：
Nie Yuanfei [1 ]
Ge Jianhua [1 ]
Wang Yong [1 ]
机构：
[1] Xidian Univ, State Key Lab Integrated Serv Networks, Xian, Peoples R China
来源：
DIGITAL SIGNAL PROCESSING | 2009年 / 19卷 / 02期
基金：
美国国家科学基金会;
关键词：
Signal-to-noise ratio (SNR); Expectation maximization (EM); Cramer-Rao bound (CRB); Turbo-like system; BICM; CONSTELLATIONS; CHANNELS; MISMATCH;
D O I：
10.1016/j.dsp.2008.07.003
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A class iterative signal-to-noise ratio (SNR) estimation algorithm is proposed in this paper. The data samples are governed by a given distribution with a priori. The expectation maximization (EM) algorithm is applied to iteratively maximize the likelihood function so as to realize the SNR estimation. Cramer-Rao bounds (CRB) with different a priori are compared for binary phase shift keying and orthogonal phase shift keying systems, which show the potential of the SNR estimator in turbo-like systems. In high-order modulations, simulation results show that the reduced-complexity iterative method with equal a priori has better performance in middle or high SNR region than the foregone. ones. Moreover, the new method with feedback information is the best when its iteration number is 4 and extrinsic information larger than 0.4. These methods are applied in the bit-interleaved coded modulation with iterative decode (BICM-ID) system to validate the effect of the proposed methods. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码：278 / 286
页数：9
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