Pan Zihao, Xie Chen, Wang Heng, Wei Yimin, Guo Daoxing
College of Communication Engineering, Army Engineering University of PLA, Nanjing 210001, China.
Sensors (Basel). 2022 Aug 29;22(17):6508. doi: 10.3390/s22176508.
With the surge of Internet of Things (IoT) applications using unmanned aerial vehicles (UAVs), there is a huge demand for an excellent complexity/power efficiency trade-off and channel fading resistance at the physical layer. In this paper, we consider the blind equalization of short-continuous-phase-modulated (CPM) burst for UAV-aided IoT. To solve the problems of the high complexity and poor convergence of short-burst CPM blind equalization, a novel turbo blind equalization algorithm is proposed based on establishing a new expectation-maximization Viterbi (EMV) algorithm and turbo scheme. Firstly, a low complexity blind equalization algorithm is obtained by applying the soft-output Lazy Viterbi algorithm within the EM algorithm iteration. Furthermore, a set of initializers that achieves a high global convergence probability is designed by the blind channel-acquisition (BCA) method. Meanwhile, a soft information iterative process is used to improve the system performance. Finally, the convergence, bit error rate, and real-time performance of iterative detection can be further improved effectively by using improved exchange methods of extrinsic information and the stopping criterion. The analysis and simulation results show that the proposed algorithm achieves a good blind equalization performance and low complexity.
随着使用无人机（UAV）的物联网（IoT）应用的激增，在物理层对出色的复杂度/功率效率权衡以及信道衰落抗性有巨大需求。在本文中，我们考虑用于无人机辅助物联网的短连续相位调制（CPM）突发的盲均衡。为了解决短突发CPM盲均衡的高复杂度和收敛性差的问题，基于建立新的期望最大化维特比（EMV）算法和Turbo方案，提出了一种新颖的Turbo盲均衡算法。首先，通过在EM算法迭代中应用软输出Lazy维特比算法获得低复杂度盲均衡算法。此外，通过盲信道获取（BCA）方法设计了一组具有高全局收敛概率的初始化器。同时，使用软信息迭代过程来提高系统性能。最后，通过使用改进的外部信息交换方法和停止准则，可以有效地进一步提高迭代检测的收敛性、误码率和实时性能。分析和仿真结果表明，所提出的算法实现了良好的盲均衡性能和低复杂度。
