Joint channel estimation for TDS-OFDM based on Superimposed Training

Abstract

One of the orthogonal frequency division multiplexing (OFDM) schemes is the Time Domain Synchronous OFDM (TDS-OFDM) scheme, in which, the guard intervals between consecutive OFDM symbols contain Pseudo Noise (PN) sequences which are known to the receiver and are used for channel estimation and synchronization. In this paper, a joint channel estimation algorithm is proposed for TDS-OFDM scheme, the proposed algorithm is based on using a Data-Dependent Superimposed Training (ST) sequence to improve the channel estimation accuracy in TDS-OFDM by utilizing two sources for channel estimation, the PN sequence at the guard interval and the ST sequence added to the data-dependent sequence. Furthermore, a simple linear combination algorithm is used to combine the two channel estimation results. The simulation results of the proposed algorithm show improvement in the estimation accuracy and bit error rate (BER) with little excess in the receiver complexity while, conserving same spectral efficiency as conventional TDS-OFDM scheme.