基于压缩感知的可见光通信定位一体化系统性能分析

Performance analysis of visible light communication and positioningintegrated system based on compressed sensing

为了降低到达时间(time of arrival, TOA)算法的接收信号采样率需求,基于正交频分复用(orthogonal frequency division multiplexing, OFDM)系统中信号具有频谱稀疏性的特点,提出了基于压缩感知算法的可见光通信定位一体化系统。仿真结果表明,采用压缩感知算法后,通信系统仅需原始采样率为100 MHz时数据量的60%即可使误码率降至10-3以下,定位系统仅需原始采样率为800 MHz时数据量的2.1%即可准确估计收发端距离,远低于采样定理所需数据量,证明了所提算法的优越性。此外,在引入噪声后,通过提高压缩感知算法的测量数据比例,一体化系统仍能在奈奎斯特采样率以下保持良好的通信与定位性能。

To reduce the demand of received signals’sampling rate in the time of arrival(TOA)algorithm,the paper proposes a visible light communication and positioning integrated system based on compressed sensing algorithm and orthogonal frequency division multiplexing(OFDM)system,which exhibits spectral sparsity of the signal.Simulation results show that after using the compressed sensing algorithm,the communication system requires 60%of the data volume when the original sampling rate is 100 MHz to reduce the bit error rate to below 10-3,and the positioning system requires 2.1%of the data volume when the original sampling rate is 800 MHz to accurately estimate the distance between the receiver and the transmitter,which is much lower than the number of points required by the sampling theorem and proves the superiority of the compressed sensing algorithm.In addition,after the introduction of noise,the integrated system maintains strong communication and localization performance below the Nyquist sampling rate by increasing the measured data ratios.