本文選題：大規(guī)模MIMO + 空間自由度　； 參考：《西安電子科技大學(xué)》2014年碩士論文

【摘要】：相對傳統(tǒng)多輸入多輸出（MIMO）系統(tǒng)而言，大規(guī)模MIMO系統(tǒng)可以通過采用數(shù)目龐大的多天線陣列獲得較大的分集增益，使系統(tǒng)的容量和能效獲得很大提升，是第5代（5G）移動通信系統(tǒng)的核心技術(shù)之一。 本文圍繞大規(guī)模MIMO技術(shù)展開研究，首先介紹了大規(guī)模MIMO系統(tǒng)的關(guān)鍵技術(shù)，包括大規(guī)模MIMO下線性多用戶預(yù)編碼，接收端信號檢測算法和采用2D天線陣列的3D波束賦形。接著，，重點分析了大規(guī)模MIMO多用戶場景的系統(tǒng)容量，引入了空間自由度（DOF），推導(dǎo)了一定空間自由度下的近似系統(tǒng)遍歷容量解析表達(dá)式。接著，在此基礎(chǔ)上，研究了基于容量最大化的用戶數(shù)優(yōu)化問題，提出一種基于二分法的大規(guī)模MIMO用戶數(shù)優(yōu)化算法，并進(jìn)行仿真分析。最后，針對大規(guī)模MIMO采用線陣尺寸過于龐大的問題，給出了采用2D天線陣的3D波束賦形技術(shù)方法，通過粒子群算法（PSO）優(yōu)化波束下傾角并進(jìn)行波束的功率分配，在保證低復(fù)雜度的前提下優(yōu)化了系統(tǒng)容量。
[Abstract]:Compared with traditional multiple-input multiple-output (MIMO) systems, large scale MIMO systems can obtain large diversity gains by using a large number of multi-antenna arrays, which can greatly improve the capacity and energy efficiency of the systems. It is one of the core technologies of the 5 th generation (5 G) mobile communication system. This paper focuses on large-scale MIMO technology. Firstly, the key technologies of large-scale MIMO system are introduced, including linear multiuser precoding, receiver signal detection algorithm and 3D beamforming using 2D antenna array. Then, the system capacity of large scale MIMO multi-user scenarios is analyzed, and the spatial degree of freedom (DOF) is introduced, and the analytical expression of the approximate system ergodic capacity under a certain degree of spatial freedom is derived. Then, on the basis of this, the problem of optimizing the number of users based on capacity maximization is studied, and a large scale MIMO user number optimization algorithm based on dichotomy is proposed, and the simulation analysis is carried out. Finally, a 3D beamforming method based on 2D antenna array is proposed to solve the problem that the large scale MIMO adopts linear array. The particle swarm optimization (PSO) algorithm is used to optimize the beam-inclination angle and the power distribution of the beam-beam. The system capacity is optimized on the premise of low complexity.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN919.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

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