- 學位論文
降低多輸入多輸出系統偵測複雜度之新方法
New approaches for reduced complexity MIMO detection
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摘要
近年來為了因應高速傳輸速率的需求，而新興的無線標準技術（例如: IEEE 802.11n 或 WiMAX）中最被看好的技術之一便是利用多重輸入及多重輸出 （Multiple-input multiple-output，簡稱 MIMO）的系統。其通道的傳輸能力將隨著天線的個數等比例的成長，並基於空間多工（spatial multiplexing）能夠提供較大的通道容量（channel capacity）。不過在真實的無線通訊應用中 MIMO 通道會隨著時間而有所變動，所以各個演算法的工作效能，皆會因此而有相當程度的衰減。第一部份裡，對於空間複用增益的利用進一步提出了一個有效的解決方法，藉由對濾波器最 佳化最小變異數（minimum variance，簡稱 MV）的準則來進行偵測，並以廣義旁波 帶消除（generalized sidelobe cancellation，簡稱 GSC）的架構適應性的實現 MV 的偵測準則，在配合即時更新通道資訊（channel state information，簡稱 CSI）以 Householder 轉換取代 GSC 中的訊號匹配濾波器（signal matched filter）和阻斷矩陣（blocking matrix），如此一來訊號匹配濾波器和阻斷矩陣可以跟隨 MIMO 通道進 行更新，避免適應性系統因為通道突然改變而造成發散。由系統的模擬中可以發現，論文中所提出適應性 MV 的偵測方法會比傳統適應性最小均方誤差（Minimum mean-square error ，簡稱 MMSE），更適合在變動的環境下。 另外在無線通訊應用中 MIMO 通道會隨著時間而改變，為了偵測訊號所求的權 重就得不斷的運算下去。如此一來複雜度便會往上提升許多，因此降低複雜度便是一個重要的課題之一。第二部份中，以依次干擾消除（order successive interferencecancellation，簡稱 OSIC）演算法，搭配改良匹配濾波器（Matched filter，簡稱 MF）演算法為架構之新方法來實現 OSIC-ZF，因為 OSIC-ZF 的計算複雜度，如果在時變的環境下複雜度的計算便會提高許多。而 OSIC-MF 是利用訊號經過 MF 再乘上適當的權重，來消去非目的訊號的干擾。並且能在有限的效能損失下，有效的降低複雜度。我們會把複雜度的運算分為權重更新和接收訊號處理兩方面，討論在快速或緩慢變動的環境下，通道的改變會造成哪些重要的影響。由結果可知隨著天線數 目的增加，彼此間的差異也會更加明顯。
並列摘要
Multiple-input multiple-output (MIMO) wireless communication technology has gained much attention in recent years due to its potential to increase the system throughput quite significantly. It is well-understood that the usage of spatial multiplexing can provide the capacity gain which is proportional to the number of antennas used. In the first part of the thesis, we present an efficient detection scheme for spatial multiplexing over time-varying MIMO channels. The filter weights for detection are optimized by the minimum variance (MV) criterion. The resultant MV detector is adaptively realized with the generalized sidelobe canceller (GSC) structure. With the up-to-date channel state information (CSI), we show that the signal matched filter and blocking matrix in GSC can be determined through the use of the Householder transformation. The advantage of this approach is that it avoids the abrupt changes in the adaptive process whenever the signal matched filter and blocking matrix are updated according to the changing MIMO channel. Simulations reveal that the proposed adaptive MV detector can outperform the conventional adaptive minimum mean-squared- error (MMSE) detector over time-varying channel environments. On the other hand, over time-varying MIMO communication channels, the filter weights are usually required to be updated very frequently. This increases the computational complexity and energy consumption unavoidably. In second part of the thesis, we propose a reduced complexity implementation for the order successive interference cancellation (OSIC)-type equalization scheme based on the zero-forcing (ZF) criterion. The derived structure consists of matched filters (MF), interference cancellation filters and data recovery filters. Simulations show that the proposed scheme can effectively reduce the computational complexity while keeping most of the performance. The complexity of updating the weights and processing the receiving signals is discussed separately. We find that as the number of antennas increases, the complexity saving of the proposed scheme becomes more observable.
參考文獻
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