Abstract
For paired carrier multiple access (PCMA) signals, a new single-channel blind separation on neural network was proposed. Firstly, the sample waveforms (three symbols) which contains different bit information are constructed, secondly, the time-frequency spectrum of each sample under the different influences of the trailing symbols is Intercepted, finally, the characteristic data of the spectrum as the input data, and the two-bit sequence in each sample as the output data to be trained, network trains these data repeatedly to complete the construction of separation model. The receiver carries on window truncation to the time-frequency spectrum of PCMA signal, neural network recognize the characteristic data of these spectrums to realizes the separation of bit sequences. Experimental results show that this algorithm has lower complexity than PSP algorithm, and the accuracy of it is close to PSP algorithm (L=5).
Highlights
In recent years, the linear mixed signal blind separation technology is used more and more widely in the field of signal processing, especially under single-channel reception, the problem of blind separation of co-frequency mixed signals has become a hot topic[1]
The single-channel blind separation technology can be applied to the problem of thirdparty reception of the paired carrier multiple access (PCMA) signal
Particle filter [2] and per-survivor processing (PSP) algorithm [3] are the main traditional algorithms to realize the separation of single channel simultaneous digital mixed signal, for the case of long constraint codes, Liao Canhui [4] and others use the idea of SOVA to make the PSP separation algorithm output the soft information of symbols, this method has achieved better separation performance
Summary
The linear mixed signal blind separation technology is used more and more widely in the field of signal processing, especially under single-channel reception, the problem of blind separation of co-frequency mixed signals has become a hot topic[1]. The single-channel blind separation technology can be applied to the problem of thirdparty reception of the PCMA (paired carrier multiple access) signal. Particle filter [2] and per-survivor processing (PSP) algorithm [3] are the main traditional algorithms to realize the separation of single channel simultaneous digital mixed signal, for the case of long constraint codes, Liao Canhui [4] and others use the idea of SOVA (soft output Viterbi algorithm) to make the PSP separation algorithm output the soft information of symbols, this method has achieved better separation performance. The traditional separation algorithm still has high complexity、slow convergence speed, and unstable separation performance, this paper presents a single-channel blind separation technique of co-frequency mixed signal based on BP neural network, neural networks have multiple transport layers and each transport layer contains multiple neurons, so the trained neural network has stable performance and has strong computing power[6]. The traditional separation algorithm still has high complexity、slow convergence speed, and unstable separation performance, this paper presents a single-channel blind separation technique of co-frequency mixed signal based on BP neural network, neural networks have multiple transport layers and each transport layer contains multiple neurons, so the trained neural network has stable performance and has strong computing power[6]. it can make up for the lack of performance of traditional algorithms, and the separation of information sequences is quite fast
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