Liu, R.; Wang, P.; Wang, X. Design and Simulation of Soft Decision Decoding Based on Chaotic M-Ary Spread Spectrum System. Discover Applied Sciences 2024, 6, doi:10.1007/s42452-024-05849-7.
Liu, R.; Wang, P.; Wang, X. Design and Simulation of Soft Decision Decoding Based on Chaotic M-Ary Spread Spectrum System. Discover Applied Sciences 2024, 6, doi:10.1007/s42452-024-05849-7.
Liu, R.; Wang, P.; Wang, X. Design and Simulation of Soft Decision Decoding Based on Chaotic M-Ary Spread Spectrum System. Discover Applied Sciences 2024, 6, doi:10.1007/s42452-024-05849-7.
Liu, R.; Wang, P.; Wang, X. Design and Simulation of Soft Decision Decoding Based on Chaotic M-Ary Spread Spectrum System. Discover Applied Sciences 2024, 6, doi:10.1007/s42452-024-05849-7.
Abstract
In this paper, chaos sequence is used to replace the traditional Spread Spectrum sequence. From the perspective of the communication partner, a new method of generating the initial value of chaotic sequence is proposed, which is more suitable for the multi-base Spread Spectrum System and easy to extract. In order to further improve the error performance of the system and ensure the integrity of the system, an improved suboptimal soft information extraction method based on log-likelihood ratio (LLR) is proposed in the channel coding module, which can further improve the error performance of the system. On this basis, we choose the synchronization mode of multiple transmission of one reference signal to solve the problem that chaotic sequence is difficult to obtain synchronization because of its aperiodic characteristics. Finally, the system is simulated in the channel with low SNR. The simulation results show that chaotic sequence as Spread Spectrum code can make the signal transmit accurately in the worse channel environment. The performance gain of applying soft information decoding decision in the M-ary Spread Spectrum System with chaotic sequence as Spread Spectrum code can reach 5.2dB compared with the traditional Direct Spread Spectrum System.
Computer Science and Mathematics, Signal Processing
Copyright:
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