基于線性預(yù)測(cè)的盲最小均方誤差均衡器
Blind MMSE Equalizer Based on Linear Prediction
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摘要: 盲過(guò)采樣均衡器僅用二階統(tǒng)計(jì)量便可減小碼間干擾，該文采用線性預(yù)測(cè)方法，提出了一種盲最小均方誤差(MMSE)均衡器。該方法不需要先估計(jì)信道，可直接利用過(guò)采樣的接收信號(hào)均衡信道。此外，該均衡器可采用遞推最小二乘算法自適應(yīng)地實(shí)現(xiàn)，具有較高的計(jì)算效率。仿真結(jié)果表明，該均衡器比基于線性預(yù)測(cè)的盲置零均衡器有更小的符號(hào)估計(jì)均方誤差。
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關(guān)鍵詞:
- 碼間干擾; 盲均衡; 線性預(yù)測(cè); 過(guò)采樣均衡器
Abstract: Blind fractionally spaced equalizers can reduce intersymbol interference using only second-order statistics. A blind MMSE equalizer based on linear prediction is presented in this paper. It can directly equalize the channel from the fractionally sampled observations without performing channel identification. In addition, it can be implemented efficiently using the RLS algorithm. Simulation results show that the blind MMSE equalizer has smaller mean-square error of symbol estimation than the corresponding zero-forcing equalizer. -
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