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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Online Access: | http://dx.doi.org/10.1100/2012/180469 |
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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 |
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