SEMI-blind spatio-temporal channel identification and interference cancellation in TDMA cellular systems

In wireless communications, spatial (via antenna arrays) and temporal (excess bandwidth) diversity may be exploited to simultaneously equalize a user of interest while canceling or reducing (cochannel) interfering users. This can be done using the classical Viterbi algorithm after a noise-plus-interference whitening operation. Cochannel interference cancellation for TDMA cellular systems remains an important issue in the migration from second to third generation systems such as EDGE. In fact, interference cancellation becomes even more important because denser symbol constellations get used and performance requirements increase as data services get introduced. The receiver depends on the channel for the user of interest, to be estimated with a training sequence, and contains a blind interference cancellation part. The critical part is the channel estimation. The usual least-squares method may lead to poor estimates in high interference environments. Significant improvements result from the Maximum-Likelihood and suboptimal techniques investigated here.