| Popis: |
In upcoming 4 th generation mobile systems using multiple antennas, knowledge of the speed of the mobile will help allocate adaptively scarce system resources to users. Due to insufficient scattering in the propagation environment or insufficient antenna spacing on either the transmitter or receiver, Multiple Input Multiple Output (MIMO) channels are often correlated. Velocity estimation in MIMO channels has not received much attention up to now. On the other hand, a large number of schemes have been developed for velocity estimation in Single Input Single Output (SISO) systems. Some of these schemes can be categorized as Autocorrelation Function (ACF) based schemes. These ACF based schemes are easy to implement and give accurate velocity estimates. In this thesis, we focus on extending this existing class of ACF based velocity estimation schemes to correlated MIMO channels. This way, the benefits of ACF based schemes can be derived in commonly occurring correlated MIMO channels. In the first part of the thesis, we first establish a performance reference by determining the performance of ACF based schemes in uncorrelated MIMO channels. Then we analyze the performance of ACF based schemes in correlated MIMO channel using the full antenna set. Some loss in the accuracy of velocity estimates is observed compared to the case of the uncorrelated MIMO channel. To recover this loss, we then present a channel decorrelation based recovery scheme. The second part of the thesis studies the extension of ACF based schemes to the case of correlated MIMO channels with antenna selection. The performance of the ACF based schemes in this case is analyzed. In this case, a degradation of performance larger than the case of the full antenna set is noticed. Thereafter a recovery scheme based on channel decorrelation is presented. This scheme partially recovers the degradation in accuracy of velocity estimates. Thus the work performed in this thesis enables us to obtain accurate estimates of velocity in correlated MIMO channels |
