應用於多點傳輸系統之接收器的適應性演算法

Abstract

3GPP LTE-A利用多基地台合作(coordinated multi-point, CoMP)傳送技術，來解決3GPP LTE系統為了增加波峰頻譜效益，採用MIMO空間多工，卻因為基地台之間的干擾，造成位於基地台邊際的使用者之傳輸效益降低的問題。在多基地台、多使用者上皆有多根天線(multi-Tx multi-Rx, MTMR MIMO)的系統，每個基地台會把要傳給不同使用者的資料同時傳送，當使用multi-user MIMO precoding消除同個基地台內資料流互相干擾時，MTMR MIMO系統和傳統單一基地台、單一使用者的MIMO系統擁有相同估測資料流的方法。理論上，最大概似機率演算法在MIMO系統能夠估測出最接近傳送端所送的訊號，但是此法將負擔難以承受的運算複雜度。所以本篇論文利用次序性干擾消除為基礎的最小均方誤差演算法執行初始估測，再以SNR與SINR為依據，判斷信號受雜訊影響的多寡和初始估測是否可靠，來決定二次估測的搜尋範圍以及是否需要執行二次估測，假設需要二次估測，便對通道矩陣H執行QR分解，讓演算法可以一次估測一根天線，在估測每根天線時，搜尋初始估測值以及M-ary QAM調變星座圖上位於初始估測值鄰近的數點，完成每根天線的估測時，都保留M組最有可能的組合，直到最終找出最有可能的一組，在複雜度與估測效能取得較佳的平衡，稱為”以MMSE-OSIC結合QRD-M的適應性演算法”。

3GPP long term evolution-advanced (LTE-A) applies coordinated multi-point (CoMP) to solve the problem of 3GPP LTE which introduces multiple-input multiple-output (MIMO) spatial multiplexing to increase the peak spectrum efficiency but loses the effectiveness of the site edge users by inter-site interference (ISI). In multi-Tx multi-Rx (MTMR) MIMO system, each eNodeB transmits the data for different users simultaneously. When applying multi-user MIMO precoding to eliminate the intra-site interference, the data detection scheme of MTMR MIMO is the same as traditional single-eNodeB single-user MIMO. The optimal detection of MIMO system is understood to be achieved by maximum-likelihood (ML) detection in theory. However, the computation complexity of ML detection is prohibitive. In this paper, we use minimum-mean-square-error based ordered successive interference cancellation (MMSE-OSIC) solution as an initial guess. Then, judge the order of severity of the signal under the influence of noise and the reliability of initial estimation in accordance with SNR and SINR. Use the judgment to decide the search region for the second estimation and whether to perform the second estimation or not. If yes, apply the QR decomposition to the channel matrix and we can detect the symbol of one antenna at a time. For every antenna we detect, we perform a search over only several points around the MMSE-OSIC solution point of M-ary QAM constellation. Find the M most significant symbol combinations every time we finish the detection, and get the most significant symbol combination at the end. This scheme of detection which makes a tradeoff between complexity and efficiency is called “adaptive detection combined MMSE-OSIC with QRD-M.”