Limits...
Nonlinear detection for a high rate extended binary phase shift keying system.

Chen XQ, Wu LN - Sensors (Basel) (2013)

Bottom Line: Simulation results showed that the performance achieved by the SVM detector is comparable to that of a conventional threshold decision (TD) detector.However, unlike the TD detector, the SVM detector concentrates not only on reducing the BER of the detector, but also on providing accurate posterior probability estimates (PPEs), which can be used as soft-inputs of the LDPC decoder.We find that the SVM is suitable for extended binary phase shift keying (EBPSK) signal detection and can provide accurate posterior probability for LDPC decoding.

View Article: PubMed Central - PubMed

Affiliation: School of Information Science and Engineering, University of Southeast, Nanjing 210096, China. xqchen@seu.edu.cn

ABSTRACT
The algorithm and the results of a nonlinear detector using a machine learning technique called support vector machine (SVM) on an efficient modulation system with high data rate and low energy consumption is presented in this paper. Simulation results showed that the performance achieved by the SVM detector is comparable to that of a conventional threshold decision (TD) detector. The two detectors detect the received signals together with the special impacting filter (SIF) that can improve the energy utilization efficiency. However, unlike the TD detector, the SVM detector concentrates not only on reducing the BER of the detector, but also on providing accurate posterior probability estimates (PPEs), which can be used as soft-inputs of the LDPC decoder. The complexity of this detector is considered in this paper by using four features and simplifying the decision function. In addition, a bandwidth efficient transmission is analyzed with both SVM and TD detector. The SVM detector is more robust to sampling rate than TD detector. We find that the SVM is suitable for extended binary phase shift keying (EBPSK) signal detection and can provide accurate posterior probability for LDPC decoding.

No MeSH data available.


Related in: MedlinePlus

The signals envelope of SIF output with SNR = −2 dB, N = 20 in (a) N = 5 in (b).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3673086&req=5

f4-sensors-13-04327: The signals envelope of SIF output with SNR = −2 dB, N = 20 in (a) N = 5 in (b).

Mentions: Figure 4 shows the signals envelope of SIF output with N = 20 in (a) and N = 5 in (b). If we use a short bit duration N, then ISI occurs, and the fuzzy interval between symbol “0” and “1” is large.


Nonlinear detection for a high rate extended binary phase shift keying system.

Chen XQ, Wu LN - Sensors (Basel) (2013)

The signals envelope of SIF output with SNR = −2 dB, N = 20 in (a) N = 5 in (b).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3673086&req=5

f4-sensors-13-04327: The signals envelope of SIF output with SNR = −2 dB, N = 20 in (a) N = 5 in (b).
Mentions: Figure 4 shows the signals envelope of SIF output with N = 20 in (a) and N = 5 in (b). If we use a short bit duration N, then ISI occurs, and the fuzzy interval between symbol “0” and “1” is large.

Bottom Line: Simulation results showed that the performance achieved by the SVM detector is comparable to that of a conventional threshold decision (TD) detector.However, unlike the TD detector, the SVM detector concentrates not only on reducing the BER of the detector, but also on providing accurate posterior probability estimates (PPEs), which can be used as soft-inputs of the LDPC decoder.We find that the SVM is suitable for extended binary phase shift keying (EBPSK) signal detection and can provide accurate posterior probability for LDPC decoding.

View Article: PubMed Central - PubMed

Affiliation: School of Information Science and Engineering, University of Southeast, Nanjing 210096, China. xqchen@seu.edu.cn

ABSTRACT
The algorithm and the results of a nonlinear detector using a machine learning technique called support vector machine (SVM) on an efficient modulation system with high data rate and low energy consumption is presented in this paper. Simulation results showed that the performance achieved by the SVM detector is comparable to that of a conventional threshold decision (TD) detector. The two detectors detect the received signals together with the special impacting filter (SIF) that can improve the energy utilization efficiency. However, unlike the TD detector, the SVM detector concentrates not only on reducing the BER of the detector, but also on providing accurate posterior probability estimates (PPEs), which can be used as soft-inputs of the LDPC decoder. The complexity of this detector is considered in this paper by using four features and simplifying the decision function. In addition, a bandwidth efficient transmission is analyzed with both SVM and TD detector. The SVM detector is more robust to sampling rate than TD detector. We find that the SVM is suitable for extended binary phase shift keying (EBPSK) signal detection and can provide accurate posterior probability for LDPC decoding.

No MeSH data available.


Related in: MedlinePlus