PCMA信号盲分离算法研究及实现

发布时间：2019-04-21 09:10

【摘要】：成对载波多址接入(Paired Carrier Multiple Access,PCMA)技术作为一种卫星通信多址复用技术,因其频谱利用率高、抗截获能力强的特点,正获得日益广泛的应用。本文在深入研究粒子滤波算法的基础上,通过基于后验概率的粒子筛选改进算法,有效降低了算法计算量,实现了第三方单通道截获PCMA混合信号的盲分离。针对通信双方符号速率存在偏差时难以实现混合信号分离的情况,本文给出了有效的解决方法。具体工作如下:(1)针对传统粒子滤波算法因粒子轨迹数量庞大所带来的计算量大的缺陷,通过对两路信号符号对后验概率的近似取值,利用基于后验概率的粒子筛选改进算法不断将对后验概率贡献较小的粒子轨迹进行筛除,改进算法大大减少了算法执行过程中的粒子轨迹数量,有效降低了算法的计算量。利用卫星信道中相位偏移、时延等参数的慢变特性,结合卫星通信数据分帧处理的方法,将传统算法中信道参数和符号的联合估计改变为分步估计。首先,利用少量观测数据运用粒子滤波改进算法估计出信道参数,然后利用所得信道参数基于最大似然准则实现两路信号符号对的分离。通过MATLAB仿真,结果表明该算法可以实现两路信号符号速率相同下的PCMA信号盲分离。(2)针对PCMA混合信号中两路信号的符号速率存在偏差时,两路信号的时延会产生滑动,当时延滑动超过一个符号时,对应的符号序列会发生变化,从而无法对混合信号进行正确分离的情况,本文利用符号速率存在偏差时PCMA混合信号中两路信号符号对的配对规律,通过修改混合信号基带模型和重新建立状态转移方程,对粒子采样和粒子权重值更新过程进行了改进,通过MATLAB仿真,结果表明该算法可以实现两路信号符号速率存在偏差下的PCMA信号盲分离。(3)将基于粒子滤波的单通道PCMA混合信号盲分离改进算法进行了C语言实现。通过模块化处理,增强了程序的可移植性,为算法的DSP实现打下了坚实的基础。本文通过对传统粒子滤波算法进行改进,大大降低了算法的计算量,实现了不同符号速率下的单通道PCMA混合信号盲分离。通过大量MATLAB环境下系统级的仿真,表明了改进算法的性能达到了课题预期指标。
[Abstract]:Pairwise carrier multiple access (Paired Carrier Multiple Access,PCMA) technology is becoming more and more widely used because of its high spectrum efficiency and strong anti-interception capability as a satellite communication multi-access multiplexing technology. Based on the in-depth study of particle filter algorithm, a modified particle filter algorithm based on posterior probability is proposed in this paper, which effectively reduces the computational complexity of the algorithm and realizes the blind separation of third-party single-channel intercepted PCMA mixed signals. In view of the fact that it is difficult to separate mixed signals when there is deviation in symbol rate between two communication parties, an effective solution is given in this paper. The specific work is as follows: (1) in view of the large number of particle trajectories caused by the traditional particle filter algorithm, the approximate value of the posterior probability of the two signal symbols is obtained. An improved particle screening algorithm based on posterior probability is used to continuously remove the particle tracks which contribute less to the posterior probability. The improved algorithm greatly reduces the number of particle trajectories in the implementation of the algorithm and effectively reduces the computational complexity of the algorithm. Based on the slow variation of parameters such as phase offset and time delay in satellite channel, the joint estimation of channel parameters and symbols in the traditional algorithm is changed to step-by-step estimation by combining the method of satellite communication data framing. Firstly, the channel parameters are estimated by particle filter improved algorithm using a small amount of observation data, and then the two signal symbol pairs are separated based on the maximum likelihood criterion using the obtained channel parameters. The results of MATLAB simulation show that the algorithm can achieve blind separation of two signals with the same symbol rate. (2) when there is a deviation in the symbol rates of two signals in the mixed PCMA signal, the delay of the two signals will slide. At that time, when more than one symbol is delayed, the corresponding symbol sequence will change, which makes it impossible to separate the mixed signal correctly. In this paper, we use the matching law of the two symbol pairs in the PCMA mixed signal when the symbol rate is deviated. By modifying the mixed signal baseband model and re-establishing the state transfer equation, the particle sampling and the particle weight value updating process are improved, and simulated by MATLAB. The results show that the algorithm can achieve blind separation of PCMA signals with two signal symbol rate deviations. (3) A single channel PCMA mixed signal blind separation algorithm based on particle filter is implemented in C language. Modular processing enhances the portability of the program and lays a solid foundation for the DSP implementation of the algorithm. By improving the traditional particle filter algorithm, the computational complexity of the algorithm is greatly reduced, and the blind separation of single-channel PCMA mixed signals with different symbol rates is realized. The system-level simulation in a large number of MATLAB environment shows that the performance of the improved algorithm reaches the expected target of the project.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TN911.7

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