摘要
目前的科学研究表明,可见光在非视距链路下的通信误码率较高且信号常呈现稀疏性。针对此问题运用压缩感知技术进行信道估计,利用树状导频随机搜索导频优化算法,在得到优化后导频位置的同时,分别同压缩感知技术中的稀疏度自适应匹配追踪算法和多路径匹配追踪算法相结合,有效地改善系统的误码率。仿真结果显示,在导频优化算法加持下,当信噪比为30 dB、导频数目为32时,系统误码率为9×10^(-3);当信噪比为30 dB、导频数目为64时,系统误码率为6.9×10^(-3)。
Current scientific research shows that visible light has a high BER and often sparse signals for communication under non-visual links. To address this problem, compressed sensing technique is used to estimate the channel. It adopts random search pilot optimization algorithm of tree pilot to obtain the optimized pilot positions while combining with the sparsity adaptive matching tracking algorithm and multipath matching tracking algorithm in the compressed sensing technique, respectively, to effectively improve the BER of the system. Simulation results indicate that the BER of the system is 9×10^(-3)when the signal-tonoise ratio is 30dB and the pilot number is 32;and 6.9×10^(-3)when the signal-to-noise ratio is 30dB and the pilot number is 64, with the support of the pilot optimization algorithm.
作者
张振
李永伟
ZHANG Zhen;LI Yongwei(CETC POTEVIO Science&Technology Co.,Ltd.,Guangzhou Guangdong 510310,China)
出处
《通信技术》
2022年第12期1543-1546,共4页
Communications Technology
关键词
非对称限幅正交频分复用
压缩感知
导频优化
信道估计
asymmetric limiting optical-OFDM
compressed sensing
pilot optimization
channel estimation