本文選題：能效 + 分布式MIMO　； 參考：《南通大學》2015年碩士論文

【摘要】：隨著移動互聯(lián)網(wǎng)的快速發(fā)展,以寬帶多媒體業(yè)務為代表的數(shù)據(jù)業(yè)務成為主流,無線接入速率越來越高,而可用的頻譜資源卻日益緊張。以MIMO及MIMO-OFDM技術(shù)為代表的新一代無線傳輸技術(shù)極大提高了無線鏈路性能,成為下一代移動通信系統(tǒng)中的關(guān)鍵技術(shù)。然而,通信產(chǎn)業(yè)的迅猛發(fā)展加劇了全球的能源消耗與環(huán)境污染。因此,綠色通信成為通信領域新的研究熱點。研究分布式MIMO及分布式MIMO-OFDM系統(tǒng)的能效優(yōu)化問題。在深入分析分布式MIMO及分布式MIMO-OFDM系統(tǒng)架構(gòu)基礎上,以提高系統(tǒng)能效為目的,圍繞一維資源分配技術(shù)中的天線選擇技術(shù)以及聯(lián)合資源分配技術(shù)中的聯(lián)合天線選擇與功率分配技術(shù)展開研究。主要工作如下:(1)根據(jù)分布式MIMO系統(tǒng)的結(jié)構(gòu)特點,提出一種基于大尺度衰落信息的分簇選擇算法。該算法通過采用分簇選擇的策略有效縮小待選天線范圍,并且用迭代算法更新參數(shù)。仿真結(jié)果表明,該算法在有效降低計算復雜度的同時,明顯改善系統(tǒng)能效。(2)在基于大尺度衰落信息的分簇選擇算法基礎上,進一步提出能效逐增算法。該算法采用多個局部最優(yōu)解逼近全局最優(yōu)解的方式改進系統(tǒng)能效。仿真分析表明,系統(tǒng)能效逼近最優(yōu)。(3)針對分布式MIMO-OFDM系統(tǒng),采用多維資源聯(lián)合優(yōu)化思想,在子梯度功率分配算法與快速天線選擇算法基礎上,提出聯(lián)合快速天線選擇與子梯度功率分配的次優(yōu)能效優(yōu)化算法。仿真結(jié)果表明,該聯(lián)合算法使系統(tǒng)能效趨近最優(yōu)。
[Abstract]:With the rapid development of mobile Internet, the data services represented by broadband multimedia services become the mainstream. The wireless access rate is getting higher and higher, but the available spectrum resources are increasingly scarce. The new generation wireless transmission technology, represented by MIMO and MIMO-OFDM technology, has greatly improved the wireless link performance and become the key technology in the next generation mobile communication system. However, the rapid development of the communications industry has increased global energy consumption and environmental pollution. Therefore, green communication has become a new research hotspot in the field of communication. The energy efficiency optimization of distributed MIMO and distributed MIMO-OFDM systems is studied. Based on the deep analysis of distributed MIMO and distributed MIMO-OFDM system architecture, the purpose of this paper is to improve system energy efficiency. The antenna selection technology in one-dimensional resource allocation technology and the joint antenna selection and power allocation technology in joint resource allocation technology are studied. The main work is as follows: (1) according to the structural characteristics of distributed MIMO system, a clustering algorithm based on large-scale fading information is proposed. The algorithm effectively reduces the range of the antenna to be selected by adopting the strategy of clustering selection, and updates the parameters with iterative algorithm. The simulation results show that the proposed algorithm not only reduces the computational complexity but also improves the energy efficiency of the system obviously. On the basis of the clustering selection algorithm based on large-scale fading information, the algorithm of increasing energy efficiency is further proposed. In this algorithm, the energy efficiency of the system is improved by using multiple local optimal solutions to approximate the global optimal solutions. Simulation results show that the energy efficiency approach to the optimal. 3) for distributed MIMO-OFDM systems, the idea of multi-dimensional resource joint optimization is adopted, based on sub-gradient power allocation algorithm and fast antenna selection algorithm. A sub-optimal energy efficiency optimization algorithm combining fast antenna selection and sub-gradient power allocation is proposed. The simulation results show that the joint algorithm approaches the optimal energy efficiency.
【學位授予單位】：南通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TN919.3
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本文編號：1816819