由於無線網路的大量配置以及多媒體傳輸頻寬的大量需求，嚴重的干擾及大量頻寬的需求成為目前寬頻通訊主要的關切點。有鑒於此，在這篇論文，我們發展高頻譜效率的通訊系統，並利用信號的特殊結構進行參數的估測，追蹤以及信號偵測。我們提出數種低複雜度且高準確度的演算法來聯合估測及追蹤重要的無線通信通道的重要參數。

首先，本論文的第一個論述，提出一個高頻譜效率的多使用者多輸入多輸出正交分頻多工干擾網路，接著我們開發兩個陣列天線協助的演算法以及一個信號偵測演算法。所開發演算法主要以階層式樹狀結構的方式來估測三個通道參數：頻率偏移、延遲以及方位角度選擇性。利用階層式時-空拆解技術結合了估測法與濾波器，以建立一個階層式的樹狀結構，交替估測時間及空間上的參數。另外在階層式的樹狀結構估測過程中，時間及空間上的參數可自動的配對，並無須再另外使用配對演算法。之後，基於這些估測的參數，我們進一步提出基於去除多重存取干擾以及同頻道干擾為基礎的信號偵測程序。

本論文的第二個論述是針對交錯式正交分頻多工存取/空間多重存取通訊系統上鏈部份提出聯合頻率偏移及方位角的估測演算法。在此通訊系統中，頻率的同步以及信號的偵測益趨困難。然而，交錯式正交分頻多工係統具有頻率上的週期性，因此重複利用堆疊技巧可以產生Vandermonde 結構，並以子空間的方法輪流進行頻率偏移及方位角的估測。此外，為了加強估測準確度以及降低運算量，加入時間濾波器及波束形成濾波器漸進式分解原信號，使原本多用戶的信號逐漸變為單一用戶極少干擾的信號，進而加強估測的準確度。

本論文的第三個論述是提出低複雜度二維方位追蹤演算法，新的演算法混合追蹤及波束形成技術將高維度的追蹤演算法拆解成三級一維度的追蹤演算法，在角度的追蹤器之間，由前一級估測的參數所建立的濾波器來對入射信號進行分群，進而加強追蹤的準確性。整體複雜度較傳統的二維追蹤演算法為低，但有較高的效能。

此外，我們也對上述各個論述，針對不同的無線通訊環境，進行計算機模擬與效能分析，結果顯示我們所提出的參數估測及追蹤演算法確實能夠提供低複雜度極高效能的品質。

In this thesis, we proposed several effective, yet low complexity algorithms to
jointly estimate and track channel parameters in wireless communication systems. The investigation and contribution of the thesis include the followings:
First, an antenna-array-assisted algorithm to mitigate the mutual interference,
frequency acquisition and detect data in a multiuser multiple-input-multipleoutput (MIMO) orthogonal frequency division multiplexing (OFDM)interference network is proposed. The algorithm begins with the estimation of three channel parameters: frequency offsets, delays and angle selectivity. To make a good use of the array signal characteristics, these three parameters are estimated in a frequency/delay-angle-frequency/delay (FAF) tree structure, in which two frequency/delay estimations and one angle estimation are employed alternatively.
One special feature in the FAF tree structure is that temporal filtering or spatial beamforming is invoked between the parameter estimations to decompose signals so as to enhance the estimation accuracy. Thereafter, based on these parameter estimates, a data detection procedure is developed to mitigate both multiple access interference (MAI) and co-channel interference (CCI).
Second, an efficient algorithm for joint estimation of carrier frequency offsets (CFOs) and directions of arrival (DOAs) in interleaved orthogonal frequency division multiple access/space division multiple access (OFDMA/SDMA) uplink systems is proposed. The algorithm utilizes the signal structure by estimating the CFOs and DOAs in a hierarchical tree structure in which CFO estimation and DOA estimation are performed alternately in three stages. Moreover, to enhance the estimation accuracy and reduce the computational overhead, a temporal filtering process and a spatial beamforming process are invoked in between the CFO and DOA estimations to progressively decompose the signals into subgroups containing a single interference-mitigated signal.
Third, we present a low complexity, yet accurate adaptive algorithm for the tracking of two-dimensional (2-D) direction of arrival (DOAs) based on a uniform rectangular array (URA). The new algorithm is a novel hybrid of tracking and beamforming processes by making use of three stages of one-dimensional (1-D) DOA tracking algorithms - in a hierarchical tree structure - to determine the two DOA components iteratively in a coarse-fine manner. In between every other 1-D DOA tracking algorithm, a complementary orthogonal beamforming process is invoked to partition the incoming signals into appropriate groups to enhance the tracking accuracy. Since the new algorithm only involves the 1-D subspacebased DOA tracking algorithm, the overall complexity is substantially less than the direct two-dimensional (2-D) extension of the existing 1-D DOA tracking algorithms, which requires an update of higher-dimensional vectors followed by a higher-dimensional eigendecomposition or a 2-D search.
Simulations show that these proposed algorithms can provide satisfactory estimation and tracking performance in various scenarios. As a whole, these new
algorithms strike a good balance between performance and complexity as compared
with previous works.

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