合作式通訊在近年受到更多研究關注，在新一代的行動通訊網路中，合作通訊有機會為整體帶來更高的資源使用效率。合作式中繼通訊的研究中，由中繼器所產生的多段式傳輸是主要的研究內容。從無線通訊技術發展至今，中繼器一直負責延伸訊號覆蓋率的任務，從一開始的功率放大前傳，到最新的電信規格使用解碼前傳。有別於上述的中繼器規格採用單一中繼器或串聯前傳，並排前傳的模式提供了令一個結合中繼器網路與時空碼的機會。多個中繼器使用時空編碼方式傳輸稱為分散式時空碼。近年來，時空碼的研究多在多天線上的運用，分散式時空碼利用座落不同座標的中繼器來做空間多樣性利用。也由於座標的分散性質，中繼器、發訊端、接收端三者之間的通道資訊必須在接收端完整蒐集。因此，我們提出採用濾波前傳中繼器，設計濾波器來組織領航訊符，使通道資訊座落於信號空間的正交位置。接收端則可在後端計算出各連結的通道資訊來解碼分散式時空碼。經設計過後的濾波器在效果上等同於分時、分頻以及分碼多工的型態來協助通道估測。為了檢驗實驗結果，推導了多重中繼器下分段通道估測的最小平方差誤差理論值，其結果與實驗數據吻合。為評估效能，推導了在多重中繼器下分段通道估測的Bayesian Cramér-Rao下限，可作為其他濾波前傳的分段通道檢估技術的評估指標，所提出的分段估測技術結合最小平方通道估測的結果也相當接近此下限。;Cooperative communication, which has attracted the attention of researchers in recent years, enables the efficient use of resources in mobile communication systems. The research of cooperative communication begin with relay generated multi-link transmission. From the simplest amplify-and-forward to the most complicated decode-and-forward, relay serves a role of extending the coverage ratio for wireless signal in a practical manner. Deploying a single relay or series connected relays is popular because of its simplicity. Conversely, employing parallel relays and space time coding is referred to as distributed space time coding (D-STC) can obtain the advantage of spatial diversity. In this research a disintegrated channel estimation technique is proposed to accomplish the spatial diversity that is supported by cooperative relays. The relaying strategy that is considered in this research is a filter-and-forward (FF) relaying method with superimposed training sequences to estimate backhaul and access channels separately. To reduce inter-relay interference, a generalized filtering technique is proposed and investigated. Unlike the interference suppression method that is commonly employed in conventional FF relay networks, a generalized filter multiplexes the superimposed training sequences from different relays to the destination by time-division multiplexing (TDM), frequency-division multiplexing (FDM) and code-division multiplexing (CDM) methods. The theoretical mean square errors (MSEs) of disintegrated channel estimation is derived and match to the simulation results. The Bayesian Cramer-Rao lower bounds (BCRBs) are derived as the estimation performance benchmark. The improvements offered by the proposed technique are verified by comprehensive computer simulation in conjunction with calculations of the derived BCRBs and the MSEs.
