面向物联网无人机通信的短突发CPM信号盲均衡算法

Blind equalization algorithm of short burst CPM signal for UAV communication in Internet of Things

针对物联网无人机通信中短突发连续相位调制(continuous phase modulation, CPM)盲均衡算法复杂度高、收敛差等问题,提出了一种基于期望最大化-维特比(expectation maximization Viterbi, EMV)的盲均衡算法。首先,将Lazy维特比算法嵌入到期望最大化(expectation maximization, EM)算法的迭代过程中,得到一种低复杂度的盲均衡算法;然后,基于盲信道捕获(blind channel-acquisition, BCA)方法构建了一组初值集,克服了算法对初值的敏感性,同时提升了信道估计的收敛性能。理论分析和实验结果表明,所提的盲均衡算法能够有效兼顾收敛性和计算复杂度,相比传统方法,在性能损失很小的条件下可大幅度降低计算成本,并且具有良好的鲁棒性。

Aiming at the problem of high complexity and poor convergence of blind equalization algorithm of short burst continuous phase modulation(CPM)in unmanned aerial vehicle communication in Internet of Things,an expectation maximization Viterbi(EMV)blind equalization algorithm is proposed.Firstly,a low-complexity blind equilibrium algorithm is obtained by embedding the Lazy Viterbi algorithm in the iterative process of the expectation maximization(EM)algorithm,and then a set of initial value is designed based on the blind channel-acquisition(BCA)method,which overcomes the proposed algorithm’s sensitivity for the initial value and improve the convergence performance of channel estimation.Theoretical analysis and simulation results show that compared with traditional methods,the proposed blind equalization algorithm can take into account both convergence and computational complexity,and greatly reduce the computational cost under the condition of small performance loss,and has good robustness.