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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.


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EBPSK modulation with N = 10, θ = π, K = 2, A = B = 1 in (a) and SIF output with symbol “0” and “1” in (b).
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f1-sensors-13-04327: EBPSK modulation with N = 10, θ = π, K = 2, A = B = 1 in (a) and SIF output with symbol “0” and “1” in (b).

Mentions: From a unified expression perspective, all of these techniques are actually a special EBPSK system that is defined as follows:(1)g0(t)=Asin2πfct,0≤t<Tg1(t)={Bsin(2πfct+θ),0≤t<τ,0≤θ≤πAsin(2πfct),τ≤t<Twhere g0 and g1 are the modulation waveforms corresponding to bit “0” and bit “1”, respectively; T = N/fc is the bit duration, τ = K/fc is the phase modulation duration, fc is the carrier frequency, and θ is the modulating angle. If we set τ = T and θ = π, then Equation (1) becomes the classical binary phase shift keying (BPSK) modulation. Moreover, T controls the bit rate, (i.e., the bit rate with N = 5 is 4 times than with N = 20), so if we want to increase the bit rate, we can use a short bit duration N. As an example, Figure 1(a) below is the waveform of EBPSK modulation and Figure 1(b) is the waveform of SIF output.


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

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

EBPSK modulation with N = 10, θ = π, K = 2, A = B = 1 in (a) and SIF output with symbol “0” and “1” in (b).
© Copyright Policy
Related In: Results  -  Collection

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

f1-sensors-13-04327: EBPSK modulation with N = 10, θ = π, K = 2, A = B = 1 in (a) and SIF output with symbol “0” and “1” in (b).
Mentions: From a unified expression perspective, all of these techniques are actually a special EBPSK system that is defined as follows:(1)g0(t)=Asin2πfct,0≤t<Tg1(t)={Bsin(2πfct+θ),0≤t<τ,0≤θ≤πAsin(2πfct),τ≤t<Twhere g0 and g1 are the modulation waveforms corresponding to bit “0” and bit “1”, respectively; T = N/fc is the bit duration, τ = K/fc is the phase modulation duration, fc is the carrier frequency, and θ is the modulating angle. If we set τ = T and θ = π, then Equation (1) becomes the classical binary phase shift keying (BPSK) modulation. Moreover, T controls the bit rate, (i.e., the bit rate with N = 5 is 4 times than with N = 20), so if we want to increase the bit rate, we can use a short bit duration N. As an example, Figure 1(a) below is the waveform of EBPSK modulation and Figure 1(b) is the waveform of SIF output.

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