Title :
Blind identification of binary LDPC codes for M-QAM signals
Author :
Tian Xia ; Hsiao-Chun Wu ; Shin Yu Chang ; Xian Liu ; Huang, Scott C-H
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Louisiana State Univ., Baton Rouge, LA, USA
Abstract :
In this paper, we propose a blind binary low-density parity-check (LDPC) encoder identification scheme for M-quadrature amplitude modulation (M-QAM) signals. The expectation-maximization (EM) algorithm is developed to estimate the unknown signal amplitude, noise variance, and phase offset for M-QAM signals. The a posteriori probabilities (APPs) of the coded bits are obtained from the APPs of the transmitted symbols according to the M-QAM mapper. Monte Carlo simulation results demonstrate the effectiveness of our proposed new blind binary LDPC encoder identification scheme for different modulation orders. The average iteration number needed for the EM algorithm to converge is also investigated for different modulation orders.
Keywords :
Monte Carlo methods; amplitude estimation; binary codes; blind source separation; expectation-maximisation algorithm; iterative methods; parity check codes; quadrature amplitude modulation; signal detection; APP; EM algorithm; M-QAM signals; M-quadrature amplitude modulation; Monte Carlo simulation; a posteriori probability; blind binary LDPC encoder identification scheme; expectation-maximization algorithm; iteration number; low density parity check; modulation orders; noise variance; phase offset; transmitted symbols; unknown signal amplitude estimation; Noise; Parity check codes; Quadrature amplitude modulation; Receivers; Wireless communication; Wireless sensor networks; Blind encoder identification; expectation-maximization; low-density parity-check (LDPC) codes; quadrature amplitude modulation;
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
DOI :
10.1109/GLOCOM.2014.7037355