陕西省教育厅科研项目 ( 18JK0341)、 西安市科技创新指导项目 ( 201805030YD8CG14 ( 12))、 陕西 省 重 点 产 业 创 新 项 目(2017ZDCXL-GY-06-01）资助
光信号在大气湍流信道中传输时会引起信号衰落和光强闪烁等现象,接收端采用固定阈值检测无法正确恢复出基带信 号,需要对接收信号判决阈值进行自适应调整。 自适应阈值检测技术能够有效抑制大气湍流效应,是改善无线光通信系统的误 码性能、提高系统可靠性的重要手段,其检测性能主要针对阈值检测算法和反馈机制等方面进行优化和改进。 回顾自适应阈值 检测技术的发展历程,从无线光通信系统结构出发,根据贝叶斯最大似然估计和最大后验概率准则,推导了接收信号的最优判 决阈值模型,通过比较接收信号和最优判决阈值解调出基带信号。 分析了基于最小均方误差滤波、卡尔曼滤波和渐消卡尔曼滤 波 3 种算法的典型自适应阈值检测模型,分别适用于平稳输入信号和非平稳输入信号,同时介绍了西安理工大学在自适应阈值 检测领域使用高阶累积量代替传统二阶统计量的相关研究工作,最后对未来该领域发展趋势进行总结和展望,可为未来无线光 通信自适应阈值检测技术的研究和发展提供一定的参考借鉴。
The transmission of optical signals in atmospheric turbulent channels causes signal fading and light intensity flicker, and the baseband signal cannot be recovered correctly by fixed threshold detection at the receiving end, so adaptive adjustment of the received signal decision threshold is required. Adaptive threshold detection technology can effectively suppress the atmospheric turbulence effect, which is an important means to improve the bit error rate performance of optical wireless communication systems and enhance system reliability. Its detection performance is mainly optimized and improved for the threshold detection algorithm and feedback mechanism. Reviewing the development process of adaptive threshold detection technology, starting from the structure of optical wireless communication system, deriving the optimal decision threshold model for the received signal based on Bayesian maximum likelihood estimation and maximum posterior probability criteria, and the realization of baseband signal demodulation by comparing the received signal with the optimal decision threshold. The typical adaptive threshold detection models based on the minimum mean square error filter, Kalman filter and fading Kalman filter are analyzed, which are suitable for stationary input signals and non-stationary input signals respectively. At the same time, the related research work of Xi′ an University of Technology using high-order cumulants instead of traditional second-order statistics in the field of adaptive threshold detection is introduced. Finally, the future development trend of this field is summarized and foreseen, which can provide some reference for the future research and development of adaptive threshold detection technology for optical wireless communication.