電力線通訊系統是利用既有的配電網路來做傳輸，因此不需要再額外架設基礎設施。電力線原本的用途是用作電力輸送，因此在利用電力線通訊的過程中會遭受到多種干擾，而在窄頻電力線通訊系統中又以出現頻率不規律、會在短時間內產生大能量的脈衝雜訊影響最為嚴重。
本論文研究依據窄頻電力線G.hnem(Gigabit Home Networking for Energy Management)標準規格，在此標準使用的錯誤更正碼為卷積碼(Convolutional code)和里德-所羅門碼(Reed-solomon code)所組成的鏈接碼，此鏈接碼能同時擁有這兩種碼的特性。在窄頻電力線通訊系統中，除了固定的背景雜訊外，還存在著許多的雜訊干擾(如:脈衝雜訊)，會使系統的解碼能力降低。本論文將專注在分析如何降低脈衝雜訊對於系統的影響。利用不同偵測脈衝雜訊的方法，找到脈衝雜訊在系統中可能發生的數量，並將這個資訊代入到系統卷積碼的解碼過程中，藉此來改善解碼的可靠度並且提升系統整體性能。

Power Line Communication (PLC) system does not need additional cabling infrastructure because power line has been widely available. However, because power line is designed for power transmission, it suffers from various interferences during data communication. The impulse noise, which generates large energy in a short time, is the most serious impact in the PLC system.

This thesis is devoted to study the system design to reduce the impulse-noise impact over narrowband PLC system based on G.hnem (Gigabit Home Networking for Energy Management) standard. The G.hnem standard adopts the concatenated code, which composes of Reed Solomon code and convolutional code, for error-correction. This thesis first review various schemes to detect the impulse noise. Then, we propose a novel system design, which modifies the metrics of the convolutional decoder with the information of noise-power change due to the impulse noise detection, to improve the system performance.

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