Optimized diversity combining with imperfect channel estimation
In a communication system using receive diversity and linear combining in the presence of cochannel interference (CCI), optimum combining (OC) is known to give the best error performance since it maximizes the instantaneous signal-to-interference-plus-noise ratio of the combiner output, and consequently, in the presence of Gaussian interference plus noise, it minimizes the error rate. However, this is based on the assumption that a perfect estimate of the channel is available. Channel estimation methods in reality use some overhead. When the channel is time-invariant, the estimation error decreases with increase in the amount of overhead, like the number of pilot symbols. With the growing need for high data rate applications, the amount of overhead that can be allocated for the estimation of the channel needs to be reduced, and the channel estimation error cannot be ignored. In this situation, replacing the channel by its imperfect estimate in the OC weight vector no longer results in an optimum scheme. We have to find an optimum scheme based on the channel estimation method and the detection criterion, which results in what we call optimized diversity combining (ODC). Here we focus on ODC resulting from a pilot symbol based maximum likelihood (ML) channel estimation method applied to a correlated flat Rayleigh fading channel in the presence of CCI and additive noise. The channel is randomly time-invariant during the reception of pilot and data symbols. The decision rule, which is optimum in the ML sense, is derived using concepts of Gaussian and Wishart statistics. Numerical results show that ODC can per-form significantly better than OC with imperfect channnel estimates by appropriate choice of system parameters.
imperfect channel estimation optimized diversity combining (odc) characteristic function maximum likelihood estimate probability density function (pdf) pseudo-wishart distribution symbol error probability wishart distribution