Research On Sparse Code Multiple Access Technology In Satellite Communication System

At present,most communications rely on terrestrial wireless mobile communications.When the terminals are far away or in remote mountainous areas and other complex environments,ground communications alone may have poor communication quality or even fail to provide services.In order to solve such problems,satellite communications have emerged.At present,there are more and more researches on satellite communications,but the limited power,spectrum resource and long delay caused by the long distance between two communication points have brought serious challenges.In order to improve the capacity and spectrum utilization of satellite communication systems,multiple access can be studied as a key technology.This thesis investigates the performance of sparse code multiple access(SCMA)in satellite communication systems.This thesis first studies the performance of sparse codes under satellite channels.Based on the sparse code multiple-access technology,a downlink model of SCMA in a satellite communication system is established.This model supposes that superimposed signals are sent on the satellite side and arrives at the ground station through satellite channel.Then the fading characteristics of satellite channel are analyzed,including free space propagation loss,atmospheric absorption loss,ionosphere and tropospheric flicker,rain attenuation loss,and Doppler shift.Model C channel models are introduced.Finally,the performance simulation analysis of SCMA under the satellite channel is performed.The results show that SCMA has good performance in satellite communication system and can be used as one of multiple access technologies.In geostationary-earth-orbit(GEO)satellite communication systems,the SCMA detection algorithm is studied.The traditional MPA algorithm,as the most basic detection algorithm for SCMA,has good performance but high complexity.Based on this,a maxlog MPA algorithm is proposed,which uses a logarithmic domain and takes an approximate maximum value for calculation.Although the complexity is reduced,the loss of some information in the calculation process causes system performance to be degraded.Therefore,an incomplete iterative MPA algorithm is proposed,and some users use fewer iterations for decoding,which results in a significant reduction in system complexity.However,because of incomplete iterations,the system performance tends to be degraded compared to traditional MPA.Then there is a codebook optimization allocation strategy to redistribute user codebooks based on channel gain information,thereby improving system performance.The optimized codebook allocation and incomplete iterative MPA detection are combined,and the simulation results show that this joint method not only improves system performance but also reduces complexity.The convergence of the detection algorithm also determines the complexity of the system.The serial MPA algorithm speeds up the system's convergence by serially updating messages between nodes,reducing the number of iterations required by the system to reduce system complexity.However,serial processing brings the problem of longer delay.In order to solve this problem,a serial-parallel combination detection is proposed.Although the delay can be reduced to a certain extent,the introduction of traditional MPA increases the complexity of the system.Therefore,an improved serialparallel MPA is proposed,which is detected through the combination of serial MPA and incomplete iterative MPA.After simulation analysis,the improved algorithm can reduce both delay and complexity.