隨著工業4.0時代的到來，大規模多輸入多輸出(Massive Multiple-Input Multiple-Output, Massive MIMO)的技術開創了無線通訊的新紀元。截至目前為止，其已經在一些4G基地台上得到了成功的應用。未來，它也將是5G通訊能否實現的關鍵技術之一。在多小區多使用者大規模多輸入多輸出網路(Multi-cell Multi-user Massive MIMO Networks)中，是以時分雙工(Time-Division Duplexing, TDD)的模式運行，且每個基站(Base Station, BS)使用多根天線共同為每個小區中的多個單天線用戶終端(User Terminals, UTs)提供服務。由於無線系統的時變特性和大量 UTs需要在小區之間重複使用導頻信號，互相傳輸相同訓練導頻的UTs會相互惡化彼此的通道，進而導致資料傳輸性能的下降。在另一方面，品質較差的非理想硬體組件的應用，容易對通道估計產生非線性硬體損傷。鑑於上述在傳統Massive MIMO 系統中導頻污染與硬體非線性的嚴重性，本研究特別專注於可達率(Achievable Rate)的部分，對上述議題加以探討與改進。我們使用最大比合併(Maximum Ratio Combining, MRC) 和最小均方誤差 (Minimum-Mean-Squared-Error, MMSE) 估計器，在空間不相關的萊斯衰減(Rician Fading)情況下分析計算每個上行頻譜效率(Spectral Efficiency, SE)。接下來，我們對每種方法進行比較，並測量導頻污染和硬體非線性對通道估計的影響。此外，我們設計了圖形使用者界面以方便模擬各種模型。我們所建立的使用者界面，能讓非程式設計者和程式設計者，在無需修改程式原始碼的情況下修改模擬所需的設定。模擬結果顯示在每種情境的比較下，導頻污染的影響比硬體失真更為嚴重。

With the advent of the Industry 4.0 era, Massive MIMO (Massive Multiple-Input Multiple-Output) techniques have been created a new epoch of wireless communication. So far, it has been successfully applied to some 4G Base Stations. In the future, it will also be one of the critical technologies for the realization of 5G communication. In Multi-cell Multi-user Massive MIMO Networks, our system operates in Time-Division Duplexing (TDD) mode, and each Base Station (BS) uses multiple antennas to jointly serve multiple single-antenna User Terminals (UTs) in each cell. Due to the time-varying characteristic of wireless systems and the large number of UTs having to reuse the pilot signals across the cells, UTs mutually transmitting the same training pilot deteriorate each other’s channel, thus resulting in a degradation in the performance of data transmission. On the other hand, the application of non-ideal hardware components of lesser quality is prone to nonlinear hardware impairments on channel estimation. Considering the seriousness of the above-mentioned pilot pollution and hardware nonlinearity in the conventional massive MIMO systems, this study discusses and simulates them under various scenarios, particularly focusing on achievable rates. We analytically compute the uplink Spectral Efficiency (SE) with Minimum-Mean-Squared-Error (MMSE) estimators under spatially uncorrelated Rician fading. Next, we make an analogy for each approach and measure the impact of pilot contamination and hardware nonlinearities on the channel estimation. In addition, we design a graphical user interface to facilitate the simulation of various models and generate results for specific scenarios. Simulation results indicate the comparison outcome for each scenario shows that the impact of pilot contamination is more severe than that of the hardware distortion.

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