毫米波大規模多輸入多輸出寬頻系統對於提供快速的無線數據傳輸非常有吸引力，都卜勒頻率隨著高載波頻率線性增加而導致通道快速的變化，通道狀態資訊將會很快過時，使得獲取準確的通道狀態資訊十分具有挑戰性。由於系統在毫米波高頻段進行傳輸，且由於通道狀態資訊隨著天線數量的增加而成長，在大規模多輸入多輸出毫米波系統中，預測通道的複雜度會大量提升。在本篇論文中，針對毫米波寬頻頻率選擇性通道，我們提出基於奇異值分解以及角度旋轉的兩種通道預測方法。利用提出的通道預測方法可以有效降低預測複雜度，補償過時的通道狀態資訊，使系統達到更高的頻譜效益。此外，我們分析了各種預測方法的均方誤差以及預測複雜度，最後利用模擬結果比較提出方法與現有方法的性能，並深入探討各關鍵參數對於系統性能之影響。

The wideband communications over Millimeter Wave (mmWave) band using Massive Multi-Input Multi-Output (MIMO) are attractive to provide ultra-fast wireless data delivery. However, acquiring accurate Channel State Information (CSI) is challenging for wideband mmWave systems because linearly increased Doppler frequency with the high carrier frequency will cause rapidly time-varying channels. Besides, the amount of CSI becomes extraordinarily large when a large antenna array is employed, resulting in a significant increase on the prediction complexity. In this thesis, we focus on the channel prediction for wideband mmWave channels and propose two new prediction approaches based on Singular Value Decomposition (SVD) and angle rotation that are shown to reduce the prediction complexity and improve the prediction accuracy for the mmWave wideband system in frequency-selective channels. Besides, we analyse the Mean Squared Error (MSE) performance and prediction complexity of the proposed prediction methods. Simulation results are presented to evaluate the performance of the proposed methods in comparison with existing approaches and get insights into the system performance subject to numerous key parameters.

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