在快速時變且多重路徑通道下使用白化處理於殘留載波間干擾和通道雜訊的正交分頻多工訊號接收

Abstract

在正交分頻多工(OFDM)通訊系統下，載波頻率飄移或通道時變導致載波間干擾(ICI) 和傳輸效能的衰減。當載波頻率非常高或用戶端移動速度很快時，這個 問題特別嚴重。載波間干擾讓通道矩陣不再只有對角方向有值，這種情形使得正 交分頻多工信號接收變得很困難。理論上，一個最佳的訊號偵測器應該考慮所有 的載波間干擾項。但是考慮複雜度和穩健前提下，習知的方法通常只有針對集中 於對角項附近的主要項補償， 而且將未被補償的殘存載波(residual ICI)間干擾視為通道白色雜訊的一部分。 本論文利用能帶近似法(band approximation)將含有載波間干擾(ICI)的訊號劃 分成三個部份， 其中包含一主要訊號、一殘留的載波間干擾(residual ICI)以及一通道雜訊。透過公式逼近、理論推導和通道模擬的方法讓我們觀察到相鄰次載波之殘留的載波間干擾(residual ICI)具有高度的正規化相關性之統計特性， 並且特別的是，我們可根據該統計特性將因考量接收器的複雜度而不得不被捨棄之殘留的載波間干擾(residual ICI)項全部考慮進去。甚至，我們發現該相鄰次載波之殘留的載波間干擾(residual ICI)的正規化相關性在幾乎所有實際應用的系統參數下是不變的， 該系統參數包含最大督普勒頻率位移(maximum Doppler shift)、多重路徑通道數據(multipath channel profile) 、功率頻譜密度(power spectral density)、正交分頻多工系統之取樣週期(sampling period)、離散傅利葉轉換之長度(DFT size)、正交性分頻多工系統之符號週期(symbol period)以及平均傳送符號能(average transmitted symbol energy)。以上的發現說明了該相鄰次載波之殘留的載波間干擾(residual ICI)高度的正規化相關性和容易估計的特性非常適合應用於實際通訊系統接收。 利用該統計特性，透過針對殘留的載波間干擾(residual ICI) 和通道雜訊進行 白化處理的一接受器可以得到非常低的雜訊底(noise floor)， 進而使通訊系統具有很好的傳輸性能，例如電腦模擬顯示採用最大可能序列估計(maximum-likelihood sequence estimation, MLSE)的接收器並且考慮上述白化處理用於該相鄰載波之殘留的載波間干擾(residual ICI)可以降低位元誤差率(BER)之誤差底(error floor) 數個級數(order)， 可明顯看出利用該統計特性結合傳統接收偵測方法對於提升通訊系統之接收效能有很大的貢獻。 更近一步，本論文提供一個考慮上述白化程序用於“相鄰載波所殘留的載波 間干擾”的線性最小均方誤差(LMMSE)和遞迴線性最小均方誤差接收器。相對於 最大可能序列估計，這個方法在良好的偵測性能和低複雜度間提供另一折衷選 擇。

Orthogonal frequency-division multiplexing (OFDM) is a popular broadband wireless transmission technique, but its performance can suffer severely from the intercarrier interference (ICI) induced by fast channel variation arising from high-speed motion. Existing ICI countermeasures usually address a few dominant ICI terms only and treat the residual similar to white noise. We show that the residual ICI has high normalized autocorrelation and that this normalized autocorrelation is insensitive to the maximum Doppler frequency and the multipath channel profile, the OFDM sample period, the discrete Fourier transform (DFT) size, the OFDM symbol time, the transmitted symbol energy. Consequently, the residual ICI plus noise can be whitened in a nearly channel-independent manner, leading to significantly improved detection performance. Simulation results confirm the theoretical analysis. As a result, a whitening transform for the residual ICI plus noise can be obtained based solely on the ICI-to-noise ratio. Such a transform can be used in association with many different signal detection schemes to significantly improve the detection performance. In particular, they show that the proposed technique can significantly lower the ICI-induced error floor by several orders of magnitude in maximum-likelihood sequence estimation (MLSE) designed to address a few dominant ICI terms. For QPSK, the proposed method can lower the error floor induced by ICI to under 10^−6 with MLSE that takes into account two nearest-neighbor ICI terms with perfect channel state information (CSI). Furthermore, we consider linear minimum mean-square error (LMMSE) and iterative LMMSE detection with the above partial whitening of additive disturbance, together with soft decision feedback. The method is shown to provide good performance-complexity tradeoff compared to other ICI countermeasures.