Compressive Sensing based channel estimation for TFT-OFDM system

Abstract

Channel estimation is one of the big challenge, ever since high resolution channel estimation can significantly improve the equalization at the receiver and consequently enhance the communication quality. Since TDS-OFDM performance suffer from fading channels with long delays and has issue supporting high order modulations like 256 QAM, which cannot accommodate the emerging ultra high definition TV services. The major challenging task in multiple input multiple output (MIMO)/OFDM systems is to design a good channel estimation method with less computational complexity and lower value of bit error rate (BER). To overcome the problem in OFDM a high accurate, low complexity compressive sensing based channel estimation method in CS-OFDM is proposed. Compressive sensing (CS) based channel estimation namely Auxiliary information based Subspace Pursuit (ASP) in TFT-OFDM systems gives high accuracy and lower complexity. This channel estimation method is based on two steps. Firstly by using time domain training sequence (TS) path delay can be estimated. Then secondly by using a small amount of frequency domain pilots inserted into the OFDM data block channel cab be perfectly estimated. The auxiliary information obtained in the first step are used to reduce the complexity of classical SP algorithms and also reduce the number of pilots require for channel estimation. Simulation results shows that proposed ASP algorithm outperforms the conventional DPN-OFDM and TDS-OFDM schemes. Also the proposed algorithm gives lower BER, high speed, high reliability for both local and long distance telephony services, and supports high order modulation like 256 QAM.