基于SCMA和卷积编码的联合检测译码算法

随着卫星星座及卫星数量的不断增多, 卫星测控中海量用户多址问题亟待解决。稀疏码分多址接入(sparse code multiple access, SCMA)技术能在有限信道资源上承载更多用户, 有望解决大规模卫星的多址测控问题。针对传统的SCMA译码方式——消息传递算法(massage passing algorithm, MPA)译码性能不理想的问题, 提出基于SCMA和卷积编码的联合检测译码(joint detection and decoding, JDD)算法, 进行多轮对数似然信息的更新以及多卫星数据交叉提供概率域的迭代, 以提高系统译码性能。分析和仿真结果表明, 采用基于SCMA和卷积编码的JDD算法可有效提高天基测控系统用户容量, 并保证在算法复杂度适中的情况下有效提高系统误比特性能。

Joint detection and decoding algorithm based on SCMA and convolution coding

With the increasing number of satellite constellations and satellites,it is urgent to solve the problem of multiple access for a large number of users in satellite tracking,telemetry and command(TTC).Sparse code multiple access(SCMA)technology can carry more users on limited channel resources,which is expected to solve the problem of multiple access of large-scale satellites in TTC.Aiming at the unsatisfactory decoding performance of traditional SCMA decoding method——massage passing algorithm(MPA),a novel joint detection and decoding(JDD)algorithm based on SCMA and convolutional coding is proposed to update multiple rounds of logarithmic likelihood information and provide iteration in probability domain for multi-satellite data crossover,so as to improve the decoding performance of the system.Analysis and simulation results show that the JDD algorithm based on SCMA and convolutional coding can effectively improve the user capacity of the space-based TTC system and the bit error performance of the system under the condition of the moderate algorithm complexity.