Set-Membership適應性濾波器應用於虛擬多重輸入多重輸出之訊號偵測

Signal Detection Using Set-Membership Adaptive Filter for Virtual MIMO based Wireless Sensor Networks

李冠毅(Li, Guanyi)

指導教授 ： 胡家彰

國立中正大學/工學院/通訊工程學系/碩士(2012年)

摘要

多重輸入多重輸出(multiple-input multiple-output, MIMO) 通訊系統，即為在傳送端與接收端使用多根天線進行訊號傳輸。然而在無線感測網路(wireless sensor networks, WSNs)中，感測網路的節點由於體積較小並且每個節點只裝置一根天線，因此感測網路中各個節點之間合作式的交換資料並且把資料傳給資料收集器，形成一個虛擬多重輸入多重輸出(virtual multiple-input multiple-output, VMIMO)的系統架構為近年來討論的重點。為了改善NLMS (Normalized Least Mean Square)演算法的收斂問題及降低RLS (Recursive Least Square)適應性演算法的複雜度，本論文使用SMF(Set-Membership Filtering)的架構設計一組VMIMO系統的接收機，把SMF的架構應用到NLMS和RLS演算法來做比較，模擬結果顯示當採用SMF的架構來做演算法的更新時，可以有效的降低複雜度並且達到優異的效能。

關鍵字

多重輸入多重輸出 ； 無線感測網路 ； 虛擬多重輸入多重輸出 ； 適應性濾波器 ； SMF

並列摘要

In multiple-input multiple-output (MIMO) communication systems, the transmitter and receiver use multiple antennas to decrease the error rate of the transmitted signals effectively. However, in wireless sensor networks (WSNs), the nodes in a sensor network have small size and each node is equipped an antenna. A virtual multiple-input multiple-output (VMIMO) architecture is proposed recently, which allows cooperatively data exchange among each node in a sensor network and then transmits data to a data gathering node (DGN). We consider to apply the adaptive filter to design a VMIMO receiver. In order to improve the convergence problem of the normalized least mean square (NLMS) and reduce the complexity of the recursive least square (RLS), the method of set-membership filtering (SMF) is applied to the NLMS, and RLS adaptive algorithms. Finally, simulation results show that the SMF is able to reduce the computational complexity effectively and achieve a better bit-error-rate (BER) performance.

並列關鍵字

MIMO ； WSNs ； VMIMO ； Adaptive filter ； Set-membership filtering

參考文獻

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