Research On Key Technologies For Blind Demodulation Of PCMA Signals

Aimed at the problem of blind demodulation of PCMA signals, This paper focuses on the SNR estimation, time delay estimation, blind separation algorithm based on SIC and blind separation algorithm in complex coding, etc.1. Aimed at the SNR estimation for PCMA, on the basis of the SNR research of single-channel signal, this paper presents a SNR algorithm of PCMA signals based on subspace decomposition. Studied three methods of decomposing signal subspace and noise subspace, and compared the performance of different methods by simulation experiments.2. Aimed at the time delay estimation of the PCMA signals, this paper propose a data-aided algorithm. The whole estimation process is divided into rough delay estimation based on data-aided and accurate delay estimation based on maximum-likelihood. This new algorithm overcomes the drawbacks of the traditional ones in avoiding radiation based on maximum-likelihood for time delay estimation, improves searching methods with eliminating the delay blur, and raises the estimation accuracy. Derivate and analyses the performance bound to provide the theoretical basis for capability. The algorithm is more sensitive to the difference between delays, little sensitive to frequency offsets. And the simulation results verify the effectiveness and practicality of the proposed algorithm.3. Aimed at the high complexity problem of the PCMA signals blind separation in non-cooperative communication, based on the serial interference cancellation algorithm, constructed single-channel co-frequency signals’ channel receiver model, this paper proposed a low complexity blind separation algorithm based on SIC, and processed the channel truncation during the channel reconstruction in the original part and ending part, avoid the loss of separation performance. The simulation experiments show that the algorithm has similar performance with traditional algorithms, but its complexity is reduced by two-thirds, and it is not sensitive to the frequency offset.4. Aimed at the problem of the PCMA signals blind separation in LDPC coding in present, this paper proposed an iteration processing algorithm based on factor graph decoding and SIC, under the premise of parameter estimation and channel reconstruction. The algorithm improved the separation performance with decoding feedback in the course of demodulation, with special emphasis on the information interaction between demodulation and decoding, as well as the impact of the channel parameters on the performance of demodulation. Simulation results show that, a gain of about 2 dB in signal-noise ratio can be obtained for QPSK signals after two iterations with LDPC codes.