Time-varying distributed MIMO-OFDM channel subblock estimation based on slepian basis

To improve the performance of time-varying distributed multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, a subblock-wise channel estimation scheme based on discrete prolate spheroidal basis expansion model (DPS-BEM) is proposed. The time-varying channel is well captured by the DPS-BEM, exploiting the unknown channel slepian correlation. The time-variations of the subblock DPS-BEM coefficients are likely much slower than that of the channel. Thus, the DPS-BEM is more convenient to track in time-varying environments. The DPS-BEM coefficients are estimated via subblock-wise, based on time-multiplexed periodically transmitted training symbols. Simulation results show that the proposed algorithm can effectively improve the channel estimation performance.