使用分散式低密度奇偶校驗碼之壓縮傳送合作式通訊

Compressed-and-forward cooperation with distributed LDPC coding

呂姵璁(Pei-Tsung Lu)

指導教授 ： 吳文榕

國立交通大學/電機學院/電信工程系所/碩士(2009年)

https://doi.org/10.6842/NCTU.2009.00569

摘要

文獻指出合作式通訊(cooperative communication)是一種有效探索虛擬空間多樣度的方法。除了傳統的放大傳送(AF)跟解碼傳送(DF)外，壓縮傳送(CF)也被提議為合作式通訊的一種對策。壓縮傳送的方式為：中繼端(relay)將傳送位元的Log-Likelihood Ratio (LLR)值先經量化、觀察或是估計後再傳送給終點端(destination)。在本篇論文中，我們提議用壓縮傳送的結構搭配分散式低密度奇偶校驗碼來做分析。傳統的壓縮傳送使用的是BPSK的調變方式且在中繼端的吞吐量比較低。為了解決這個問題，我們提議在中繼端使用QAM的調變方式。為了達到這個目的，我們必須估計每個位元LLR的分布情形。接著我們將此分布情況模擬成高斯混和(Gaussian Mixture)並使用EM algorithm來識別高斯混和分布中不知道的參數。模擬顯示所提出的壓縮傳送結構在性能上勝過放大傳送和解碼傳送。

關鍵字

低密度奇偶校驗碼 ； 合作式通訊

並列摘要

Cooperative communication has been shown to be an effective way to explore virtual spatial diversity. Except for conventional amplify-and-forward (AF) and decode-and-forward (DF), the compressed-and-forward (CF) has been proposed for the cooperative strategy. In CF, the relay forwards the quantized/observed/estimated data information, which is usually the LLR values of the transmit bits, to the destination. In this thesis, we propose a CF scheme with distributed LDPC coding. Conventional CF only uses BPSK modulation at the relay and the throughput in the relay link is low. To solve the problem, we propose to use a QAM modulation at the relay. To do that, we have to estimate the distribution of the likelihood-ratio (LLR) of each information bit. We then model the distributions as Gaussian mixtures, and use the expectation-maximization (EM) algorithm for the identification of the unknown parameters. Simulations show that the proposed CF scheme can outperform AF and DF.

並列關鍵字

LDPC coding ； cooperation

參考文獻

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