在快速衰減通道下，單載波區塊傳送系統在接收端的等化,除了時域上符元間的干擾還有頻域上虛擬載波之間的干擾。原本在非時變通道中的等化技術由於虛擬載波的問題而無法直接應用。而文獻中針對快速衰減通道的技術，目前常見的有最小均方誤差線性等化器，以及最小均方誤差連續干擾消除，前者錯誤率表現不佳，但複雜度較低，而後者錯誤率頗佳，但複雜度相當高。本論文中，我們將原本設計於非時變通道上的迭代區塊決策回授等化器延伸至時變通道，希望能延續其複雜度低的優點並有不錯的錯誤率效能。我們根據最小均方誤差準則來設計等化器；因等化器的參數需要估計傳送信號和決策信號之間的相關性，本論文亦探討估計相關性的方法。
模擬結果顯示，我們提出的方法和最小均方誤差線性等化器相比，只需付出些許額外的複雜度就能有顯著的錯誤率改善。而和最小均方誤差連續干擾消除相比：在錯誤率部分，當通道變化較快時，錯誤率較高，但在通道變化較慢時，有相近的錯誤率效能；而複雜度部分，比最小均方誤差連續干擾消除低很多。

In fast fading channels, the single-carrier block transmission systems suffer from not only the inter-symbol interference (ISI) in the time domain, but also the virtual inter-carrier interference (virtual ICI) in the frequency domain. Therefore, equalization techniques originally designed for slow fading channels can’t be effectively applied for fast fading channels. In the literature, equalization algorithms that cope with fast fading channels include the time-domain minimum mean square error linear equalizer (MMSE-LE) and minimum mean square successive interference cancellation (MMSE-SIC). The former has a much lower complexity than the latter, at the cost of a poor bit error rate (BER) performance. In the thesis, in order to achieve a better trade-off between performance and complexity, we extend the iterative block decision feedback equalizer (IBDFE), originally designed for slow fading channels only, to fast fading channels. We design the equalizer according to the MMSE criterion. Since the equalizer coefficients require the knowledge of the correlation between the detected symbols and the transmitted symbols, methods of estimating the correlation are also investigated in the thesis.
Simulation results show that, compared with MMSE-LE, the proposed algorithm achieves a significant BER performance improvement with only a slight increase in complexity. Compared with MMSE-SIC, the proposed method has a worse BER performance in channels with a larger Doppler spread, but has a quite similar performance in channels with a smaller Doppler spread; but in both cases, the proposed algorithm has a much lower complexity.

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