The Maximum-A-Posteriori-probability (MAP) demodulation of recursive FQPSK-B in the presence of Additive White Gaussian Noise (AWGN) channel was first presented. Required in the iterative detection of Serial Concatenation of Convolutional coded Recursive FQPSK (SCCRFQPSK), the bit extrinsic Log-Likelihood Ratio (ex-LLR) of FQPSK demodulation was also derived. Secondly, aiming at weakening the phenomena of positive feedback during the iterative detection of SCCRFQPSK, the bit ex-LLR of FQPSK demodulation was appropriately adjusted by linear weighted processing. By Monte Carlo simulation, it was concluded that the optimal weighting factor of the weighted SCCRFQPSK system was 0.7, and it got 0.3dB Signal-to-Noise Ratio (SNR) gain at a Bit Error Rate (BRE) of 10-5 at 4 iterations. The simulation results indicate that the proposed method can not only accelerate the decoding convergence and improve the performance of the SCCRFQPSK system, but also reduce the delay. To a certain extent, it can deal with the deep space communication with low SNR caused by long distance.
To improve the efficiency of the Bit Flipping (BF), a weighted gradient descent bit-flipping decoding algorithm based on average magnitude was proposed for Low Density Parity Check (LDPC) code. The average magnitude of the information nodes was first introduced as the reliability of the parity checks, which was used to weigh the bipolar syndrome, and then an effective bit-flipping function was obtained. Simulation was conducted at Bit-Error Rate (BER) of 10-5 under an Additive White Gaussian Noise (AWGN) channel, and coding gains of 0.08 and 0.29 dB were achieved in comparison to conventional weighted Gradient Descent Bit-Flipping (GDBF) and Reliability Ratio based Weighted Gradient Descent Bit-Flipping (RRWGDBF) algorithms while the average number of decoding iterations was reduced by 72.6% and 9.3%, respectively. The simulation results show that the improved algorithm outperforms the conventional algorithms while average decoding number is also reduced. It indicates that this new scheme can better balance error-correcting ability, decoding complexity and delay, which can be applied to high-speed communication system with high real-time requirement.