estimation

Abstract. With the purpose of supplying the demand of faster and more reliable communication, multiple-input multiple-output (MIMO) systems in conjunction with Or-thogonal Frequency Division Multiplexing (OFDM) are sub-ject of extensive research. Successful Decoding requires an accurate channel estimate at the receiver, which is gained ei-ther by evaluation of reference symbols which requires des-ignated resources in the transmit signal or decision-directed approaches. The latter offers a convenient way to maximize bandwidth efficiency, but it suffers from error propagation due to the dependency between the decoding of the current data symbol and the calculation of the next channel estimate. In our contribution we consider linear smoothing techniques to mitigate error propagation by the introduction of backward dependencies in the decision-based channel estimation. De-signed as a post-processing step, frame repeat requests can be lowered by applying this technique if the data is insensi-tive to latency. The problem of high memory requirements of FIR smoothing in the context of MIMO-OFDM is ad-dressed with an recursive approach that acquires minimal re-sources with virtual no performance loss. Channel estimate normalized mean square error and bit error rate (BER) per-formance evaluations are presented. For reference, a median filtering technique is presented that operates on the MIMO time-frequency grids of channel coefficients to reduce the peak-like outliers produced by wrong decisions due to un-successful decoding. Performance in terms of Bit Error Rate is compared to the proposed smoothing techniques