Abstract
The third generation partnership project (3GPP) long term evolution (LTE) uses high performance strategies such as adaptive link adaptation, multiuser resource scheduling and adaptive MIMO precoding to enhance effective utilization of the availably radio resources. These processes require the transmitter to have an accurate knowledge of the channel state information (CSI). This is typically provided via feedback from the receiver. Due to processing and feedback delays, the CSI used at the transmitter is outdated leading to performance degradation causing a decrease in the overall system capacity. Channel prediction can be used to alleviate this problem. The minimum mean square error (MMSE) has been proven to have high performance in channel estimation and prediction. However this superior performance is accompanied by a high computational complexity. In this paper, we present a low complexity approximate MMSE (AMMSE) algorithm for channel prediction in block fading channels. Simulation results indicate that our proposed algorithm offers superior performance compared to the recursive least squares and normalized least mean square techniques and comparable performance to the full complexity MMSE algorithm.
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