多使用者大量多輸入多輸出系統被視為在未來第五代無線通訊系統中重要的技術，隨著基地台配置大量的傳輸天線，能量的消耗量會變成一個值得注意的議題，每一根傳輸天線連接著一對高解析度的數位類比訊號轉換器，這些轉換器會消耗大量的能量，因此提出量化預處理技術降低訊號轉換器的解析度以達到將能量限制在可容忍範圍內的效果，目前存在各式各樣高運算複雜度的演算法可以達到合意的位元錯誤率的表現，這篇論文針對一位元預編碼處理提出增益控制晶格簡化演算法，結合簡單傳統的多輸入多輸出搜尋方式和晶格簡化降低運算複雜度並且使得通道達到完全多樣化的表現，在晶格簡化的處理過程中，訊號的能量會被周密地調整用以得到在位元錯誤率的表現上大量的提升，模擬結果顯示這篇論文提出的演算法在位元錯誤率以及運算複雜度上都有好的表現。

Massive multi-user multiple-input multiple-output systems are widely believed to be
an important technique in the coming fifth generation wireless communication systems.
Power consumption becomes an issue worthy of much attention since the base station is
equipped woth massive transmitting antennas. Each of the antennas is connected with
a pair of high resolution converters. These converters make significant contributions to

power consumption. In order to keep the power in a tolerable level, the quantized pre-
coding technique was proposed to reduce the resolution of the data converters. Various

algorithms with high computation complexity were proposed to achieve desirable bit-
error-rate performances. This thesis proposes a gain-controlled lattice-reduction-aided

K-best algorithm for the 1-bit precoding processing. A simple traditional MIMO search

method was proposed to combine the lattice reduction to reduce computation complex-
ity and make the channel achieve full diversity performance. In the lattice reduction

preprocessing, the gains of the signal vectors in the lattice reduction domain are care-
fully controlled to obtain a considerable improvement in the BER performances. The

simulation results show that the proposed algorithm acquires good performances in the
aspects of both BER performance and computation complexity.

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