Study of Implementation for Spatial Multiplexing in MIMO System

[[abstract]]摘要 在多輸入多輸出系統(MIMO)上，空間多工對於增加容量是一個重要的技術。然而，空間多工有著干擾和複雜的問題，因此我們去研究幾種不同空間多工的架構來減輕上述兩項問題，但在執行這種架構時具有較高的複雜性。 因此在保有完整優勢與效能前提下設計出複雜度低、製作成本低等好處的MIMO系統最近獲得了顯著的關注。基於以上原因，我們使用MIMO系統設計並實現降低最大似然檢測（MLD）系統之複雜度，並使其性能盡可能接近的最佳的MLD系統（全複雜度）。 在本論文中探討三種偵測器，分別為：最大似然偵測器 (Maximum Likelihood Detection，MLD)、最小均方誤差偵測器 (Minimum Mean Square Error， MMSE)，迫零等化器 (Zero Forcing equalizer，ZF)。我們透過在雷利衰減通道下模擬位元錯誤率的結果得知，MLD(最好)的效能比MMSE(次好)和ZF(最差)來得好很多，故本論文選擇MLD來做實現。[[abstract]]Abstract In the multi-input multi-output(MIMO) systems, spatial multiplexing is an important technique for increasing the capacity. However, the spatial multiplexing with interference and complex problem, so we went to study several different spatial multiplexing construct to mitigated it ,but in the implementation of such a system is the enormous complexity. Therefore, the design of low complexity, low cost, MIMO systems, to maintain the most comprehensive advantages and benefits of complex systems, has recently received significant attention. We designed and implemented to reduce complexity MIMO Maximum Likelihood Detection (MLD) system its performance is as close as possible to the optimum MLD system (full complexity). In this paper we explore three kinds of detectors, they are called: maximum likelihood detector (MLD), minimum mean square error detector (MMSE) and zero-forcing equalizer (ZF).Through our simulationsresult in Rayleigh fading channel bit error rate, rather thanMMSE (second best) and ZF (the worst), MLD has the best performance So I chose to achieve MLD.[[note]]碩