Research On Channel Estimation Based On Compressed Sensing For Visible Light Communication System

The visible light communication(VLC)is a way to emit light signals modulated at high speed to modulate and transmit information by using light-emitting diodes.Because of with rich spectrum resources,high security,low cost and resistance to electromagnetic interference,the VLC has become a research hotspot in recent years.But one of the main challenges limiting the high-speed transmission of VLC systems is the limited bandwidth of LED.Orthogonal Frequency Division Multiplexing(OFDM)and Multiple Input Multiple Output(MIMO)technologies are viable options to overcome LED bandwidth limitations and increase VLC transmission data rates.In the MIMO-OFDM VLC system,both data transmission and demodulation require accurate channel state information,so accurate and effective channel estimation is an effective guarantee for successful transmission of information.Traditional channel estimation methods,such as least squares(LS),require a large number of pilot signals,resulting in low spectrum utilization.To improve spectrum efficiency,the channel estimation based on compressed sensing has been widely utilized in radio frequency communications.In the VLC link,the channel contains both line-of-sight(LOS)and non-line-of-sight(NLOS).Like the radio frequency communication channel,it is with certain sparseness.Therefore,The channel estimation technique based on compressed sensing can be applied to the VLC system.In this study,we propose a channel estimation method based on compressed sensing for MIMO-OFDM VLC,and verify that through experiments,compared with traditional methods,the compressed sensing algorithm can improve the performance of channel estimation and improve the spectrum utilization.The main research contents of this dissertation are as follows:(1)This dissertation introduces the basic principles of VLC and analyzes the sparsity of its channel model.The key technologies of MIMO and OFDM were analyzed,and their advantages were fully combined in VLC system application.(2)Compressed sensing was introduced from three aspects: sparse representation of signal,design of measurement matrix,and reconstruction of signal.The application of compressed sensing in the direction of channel estimation was analyzed by combining the theoretical knowledge.(3)The sparse channel models of OFDM and MIMO-OFDM were analyzed.Four common signal reconstruction algorithms to reconstruct the channel information were studied and verified by experiments of OFDM-VLC system and MIMO-OFDM VLC system.The results show that,compared with the traditional method,the proposed channel estimation based on compressed sensing has better BER performance and can reduce pilot overhead.