Training-based channel estimation for continuous flat fading BLAST

Abstract

The Bell Labs layered space-time (BLAST) architecture provides high capacity wireless communications in rich scattering environments. Training sequences are transmitted periodically to estimate the channel. We compare the performance without channel tracking to the performance with interpolation-based channel tracking. The optimal training interval, training length and the maximum throughput are found through computer simulations for both schemes as functions of the Doppler frequency and the number of antennas. We show that the throughput is significantly improved with channel tracking for fast continuous fading channels. However channel tracking increases the computation complexity for data detection. A sub-optimal detection algorithm with lower complexity is proposed and investigated.