Nonlinear Demodulation and Channel Coding in EBPSK Scheme

The extended binary phase shift keying (EBPSK) is an efficient modulation technique, and a special impacting filter (SIF) is used in its demodulator to improve the bit error rate (BER) performance. However, the conventional threshold decision cannot achieve the optimum performance, and the SIF bring...

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Main Authors: Xianqing Chen, Lenan Wu
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1100/2012/180469
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spelling doaj-aa79adc95cdf46219caf10b237500ac72020-11-25T00:15:26ZengHindawi LimitedThe Scientific World Journal1537-744X2012-01-01201210.1100/2012/180469180469Nonlinear Demodulation and Channel Coding in EBPSK SchemeXianqing Chen0Lenan Wu1School of Information Science and Engineering, University of Southeast, 2 Sipailou, Nanjing 210096, ChinaSchool of Information Science and Engineering, University of Southeast, 2 Sipailou, Nanjing 210096, ChinaThe extended binary phase shift keying (EBPSK) is an efficient modulation technique, and a special impacting filter (SIF) is used in its demodulator to improve the bit error rate (BER) performance. However, the conventional threshold decision cannot achieve the optimum performance, and the SIF brings more difficulty in obtaining the posterior probability for LDPC decoding. In this paper, we concentrate not only on reducing the BER of demodulation, but also on providing accurate posterior probability estimates (PPEs). A new approach for the nonlinear demodulation based on the support vector machine (SVM) classifier is introduced. The SVM method which selects only a few sampling points from the filter output was used for getting PPEs. The simulation results show that the accurate posterior probability can be obtained with this method and the BER performance can be improved significantly by applying LDPC codes. Moreover, we analyzed the effect of getting the posterior probability with different methods and different sampling rates. We show that there are more advantages of the SVM method under bad condition and it is less sensitive to the sampling rate than other methods. Thus, SVM is an effective method for EBPSK demodulation and getting posterior probability for LDPC decoding.http://dx.doi.org/10.1100/2012/180469
collection DOAJ
language English
format Article
sources DOAJ
author Xianqing Chen
Lenan Wu
spellingShingle Xianqing Chen
Lenan Wu
Nonlinear Demodulation and Channel Coding in EBPSK Scheme
The Scientific World Journal
author_facet Xianqing Chen
Lenan Wu
author_sort Xianqing Chen
title Nonlinear Demodulation and Channel Coding in EBPSK Scheme
title_short Nonlinear Demodulation and Channel Coding in EBPSK Scheme
title_full Nonlinear Demodulation and Channel Coding in EBPSK Scheme
title_fullStr Nonlinear Demodulation and Channel Coding in EBPSK Scheme
title_full_unstemmed Nonlinear Demodulation and Channel Coding in EBPSK Scheme
title_sort nonlinear demodulation and channel coding in ebpsk scheme
publisher Hindawi Limited
series The Scientific World Journal
issn 1537-744X
publishDate 2012-01-01
description The extended binary phase shift keying (EBPSK) is an efficient modulation technique, and a special impacting filter (SIF) is used in its demodulator to improve the bit error rate (BER) performance. However, the conventional threshold decision cannot achieve the optimum performance, and the SIF brings more difficulty in obtaining the posterior probability for LDPC decoding. In this paper, we concentrate not only on reducing the BER of demodulation, but also on providing accurate posterior probability estimates (PPEs). A new approach for the nonlinear demodulation based on the support vector machine (SVM) classifier is introduced. The SVM method which selects only a few sampling points from the filter output was used for getting PPEs. The simulation results show that the accurate posterior probability can be obtained with this method and the BER performance can be improved significantly by applying LDPC codes. Moreover, we analyzed the effect of getting the posterior probability with different methods and different sampling rates. We show that there are more advantages of the SVM method under bad condition and it is less sensitive to the sampling rate than other methods. Thus, SVM is an effective method for EBPSK demodulation and getting posterior probability for LDPC decoding.
url http://dx.doi.org/10.1100/2012/180469
work_keys_str_mv AT xianqingchen nonlineardemodulationandchannelcodinginebpskscheme
AT lenanwu nonlineardemodulationandchannelcodinginebpskscheme
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