應用基因演算法於OFDMA系統之聯合通道估計與多用戶偵測

Joint Channel Estimation and Multi-user Detection for OFDMA Systems Using Genetic Algorithm

呂翊僑(Yi-Chiao Lu)

指導教授 ： 譚旦旭

國立臺北科技大學/電資學院/電機工程系研究所/碩士(2011年)

https://doi.org/10.6841/NTUT.2011.00278

摘要

在正交分頻多重存取(OFDM）系統中，多用戶干擾(Multiple-access Interference, MAI)是惡化系統效能的一個關鍵因素。本論文應用基因演算法(Genetic Algorithm, GA)同時進行通道估計和多用戶偵測(Joint Channel Estimation and Multi-user Detection, JCEMUD)。為了進一步提升GA的搜尋能力，我們結合模擬退火法(Simulated Annealing, SA)的機率函數至GA中，稱其為SA-based Mutation GA (SAM-GA)。根據實驗結果顯示，本論文提出的SAM-GA在均方誤差(Mean Square Error, MSE)及位元錯誤率(Bit Error Rate, BER)表現上，皆可有效改善傳統GA於聯合通道估計與多用戶偵測之效能。

關鍵字

正交分頻多重存取 ； 通道估計 ； 多用戶偵測 ； 基因演算法 ； 模擬退火

並列摘要

In orthogonal frequency division multiple access (OFDMA) system the multiple access interference (MAI) is a critical factor that significantly degrades system performance. In this research the genetic algorithm (GA) is employed for joint channel estimation and multi-user detection. For improving exploration and exploitation strengths of GA, a GA-based approach called SAM-GA is developed by incorporating the simulated annealing (SA) to mutation operation. Experimental result demonstrates that the proposed SAM-GA scheme achieves the best performance in terms of mean squared error (MSE) and bit error rate (BER) for joint channel estimation and multi-user detection in the OFDMA system as compared to other schemes.

並列關鍵字

Orthogonal Frequency Division Multiple Access(OFDMA) ； Multi-user Detection (MUD) ； Channel Estimation ； Genetic Algorithm(GA) ； Simulated Annealing(SA)

參考文獻

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