本文關(guān)鍵詞：大規(guī)模MIMO通信系統(tǒng)中信號(hào)干擾抑制及系統(tǒng)性能研究　出處：《北京交通大學(xué)》2017年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 5G移動(dòng)通信 大規(guī)模MIMO系統(tǒng) 導(dǎo)頻污染減輕 系統(tǒng)整體性能

【摘要】：無(wú)線通信數(shù)據(jù)量的爆炸式增長(zhǎng)和無(wú)線連接數(shù)量的極度增加,使得頻譜資源的有限性和人們對(duì)無(wú)線通信服務(wù)需求之間的矛盾越發(fā)突出。在此背景下,大規(guī)模MIMO技術(shù)在2010年被Thomas.L.Marzetta等人提出后受到廣泛關(guān)注。前期研究證實(shí)該技術(shù)通過(guò)充分挖掘空間自由度能夠極大地提升頻譜資源的利用效率,與此同時(shí)在能量效率方面和當(dāng)前無(wú)線通信系統(tǒng)相比也存在幾個(gè)量級(jí)的提升空間。因此,大規(guī)模MIMO技術(shù)成為第五代(5G,the Fifth Generation)移動(dòng)通信系統(tǒng)中具有潛力的備選技術(shù)之一。但是,大規(guī)模MIMO多小區(qū)系統(tǒng)中小區(qū)間導(dǎo)頻信號(hào)的干擾成為系統(tǒng)性能提升的瓶頸。因此,本文主要研究大規(guī)模MIMO多小區(qū)系統(tǒng)中導(dǎo)頻信號(hào)干擾減輕問(wèn)題,并提出幾種抑制導(dǎo)頻污染的方案,以期提升大規(guī)模MIMO系統(tǒng)的性能。本文主要的研究工作從以下方面展開(kāi):1.基于"注水算法"原理的導(dǎo)頻智能分配方案大規(guī)模MIMO系統(tǒng)中用于信道估計(jì)的正交導(dǎo)頻的數(shù)量受限于信道的相干時(shí)長(zhǎng)。同一組正交導(dǎo)頻在所有小區(qū)間的復(fù)用造成復(fù)用導(dǎo)頻之間的信號(hào)干擾,即導(dǎo)頻污染。該問(wèn)題成為大規(guī)模MIMO多小區(qū)系統(tǒng)性能提升的瓶頸。然而,不同終端對(duì)應(yīng)信道的通信質(zhì)量是不同的,不同的導(dǎo)頻受相鄰小區(qū)中復(fù)用導(dǎo)頻的干擾程度也存在差異。因此,本文提出一種基于"注水算法"思想的導(dǎo)頻智能分配方案。根據(jù)終端信道質(zhì)量和導(dǎo)頻受干擾的程度將導(dǎo)頻和終端按"注水算法"思想進(jìn)行智能配對(duì),達(dá)到減輕整個(gè)系統(tǒng)導(dǎo)頻污染、優(yōu)化導(dǎo)頻資源利用率的目的。實(shí)驗(yàn)證明,此方案在犧牲少數(shù)信道質(zhì)量極差終端性能的情況下,極大提升了系統(tǒng)整體的數(shù)據(jù)容量。2.基于粒子群優(yōu)化算法的導(dǎo)頻智能快速分配方案大規(guī)模MIMO多小區(qū)系統(tǒng)中導(dǎo)頻智能分配方案能夠有效的抑制系統(tǒng)整體的導(dǎo)頻污染。但是,導(dǎo)頻智能分配的運(yùn)算復(fù)雜度與終端數(shù)量正相關(guān)。例如,10個(gè)終端10個(gè)正交導(dǎo)頻的情況下,終端和導(dǎo)頻的配對(duì)方案多達(dá)10!=3 628 800種。為了降低導(dǎo)頻智能分配方案的運(yùn)算復(fù)雜度,本文提出一種基于粒子群優(yōu)化算法的智能導(dǎo)頻快速分配方案。利用粒子群優(yōu)化算法進(jìn)行導(dǎo)頻智能尋優(yōu)分配過(guò)程中所有粒子之間信息即時(shí)共享的特性,有助于快速尋找到終端和導(dǎo)頻之間最佳的配對(duì)方案,在降低導(dǎo)頻智能分配過(guò)程運(yùn)算復(fù)雜度的同時(shí)減輕系統(tǒng)的導(dǎo)頻污染。實(shí)驗(yàn)結(jié)果證明此方案在抑制導(dǎo)頻污染和降低導(dǎo)頻智能分配過(guò)程中運(yùn)算復(fù)雜度方面的有效性。3.基于終端分層及層間導(dǎo)頻異步發(fā)送的方案相鄰小區(qū)間復(fù)用導(dǎo)頻導(dǎo)致的導(dǎo)頻污染對(duì)小區(qū)中心處終端和邊緣處終端的影響是不同的�；诖吮疚奶岢鲆环N終端分層小區(qū)間邊緣終端簇導(dǎo)頻異步發(fā)送的方案。在此方案中將終端分層,各小區(qū)內(nèi)受干擾程度小的中心終端簇同時(shí)發(fā)送上行導(dǎo)頻,而不同小區(qū)內(nèi)受導(dǎo)頻污染嚴(yán)重的邊緣終端簇在互不重疊的時(shí)隙內(nèi)發(fā)送上行導(dǎo)頻。實(shí)驗(yàn)證明,該方案可以有效的減輕導(dǎo)頻污染對(duì)整個(gè)系統(tǒng)的影響。但是此方案中存在一個(gè)小區(qū)內(nèi)的邊緣終端與相鄰小區(qū)內(nèi)中心終端復(fù)用導(dǎo)頻的情況,因此不同小區(qū)內(nèi)邊緣終端簇和中心終端簇之間仍然存在導(dǎo)頻干擾。為了減輕此部分導(dǎo)頻污染,本文又提出一種改進(jìn)的終端分層及不同終端簇上行導(dǎo)頻、下行數(shù)據(jù)對(duì)齊發(fā)送的方案。利用上行導(dǎo)頻與下行數(shù)據(jù)之間不相關(guān)的特性,通過(guò)不同終端簇間上行導(dǎo)頻、下行數(shù)據(jù)交叉發(fā)送的方式,導(dǎo)頻污染可以得到進(jìn)一步減輕。實(shí)驗(yàn)證實(shí)改進(jìn)的方案比前一種方案在減輕導(dǎo)頻污染提高系統(tǒng)性能方面更有優(yōu)勢(shì)。4.基于小區(qū)分簇導(dǎo)頻異步發(fā)送及導(dǎo)頻功率控制的方案對(duì)大規(guī)模MIMO多小區(qū)系統(tǒng)的小區(qū)進(jìn)行分簇,不同小區(qū)分簇內(nèi)終端以異步的方式輪流發(fā)送上行導(dǎo)頻。此方案通過(guò)將導(dǎo)頻污染壓縮到同分簇內(nèi)部小區(qū)之間達(dá)到減輕整個(gè)系統(tǒng)導(dǎo)頻污染的目的。顯然,小區(qū)分簇?cái)?shù)量越多導(dǎo)頻污染的影響就越小,但是分簇越多一個(gè)相干時(shí)長(zhǎng)內(nèi)上行數(shù)據(jù)的發(fā)送時(shí)間就越被壓縮,所以并非小區(qū)分簇?cái)?shù)量越多系統(tǒng)的整體性能就越好。合理的小區(qū)分簇策略對(duì)于此方案性能的發(fā)揮是至關(guān)重要的。本文從上行和下行綜合角度考慮有效數(shù)據(jù)的發(fā)送并得到合適的小區(qū)分簇策略,從而在減輕導(dǎo)頻污染和提升系統(tǒng)整體性能兩個(gè)方面找到平衡點(diǎn)。實(shí)驗(yàn)證實(shí)了理論得出的最佳小區(qū)分簇因子的有效性。另外,由于此方案中同分簇內(nèi)部小區(qū)之間仍然存在導(dǎo)頻污染問(wèn)題,本文將導(dǎo)頻發(fā)送功率控制引入到小區(qū)分簇導(dǎo)頻異步發(fā)送方案中,通過(guò)控制導(dǎo)頻發(fā)送功率從而減輕小區(qū)分簇內(nèi)部各小區(qū)之間的導(dǎo)頻污染,實(shí)驗(yàn)仿真證明了該方案在減輕導(dǎo)頻污染方面的優(yōu)勢(shì)。
[Abstract]:The explosive growth of wireless communication data and wireless connection number increasing, the limited spectrum resources and people become more and more prominent contradictions between the demand of wireless communication services. Under this background, large-scale MIMO technology was proposed by Thomas.L.Marzetta received extensive attention in 2010. Previous studies demonstrated that the technique by exploiting the spatial degrees of freedom can greatly improve the utilization efficiency of spectrum resources, at the same time there are several orders of magnitude compared to improve the energy efficiency of the wireless communication system. Therefore, the large-scale MIMO technology to become the fifth generation (5G the, Fifth Generation) is one of the alternative technology has the potential of mobile communication system. However, large scale MIMO system in small and medium sized multi cell interference the interval of the pilot signal has become the bottleneck of system performance improvement. Therefore, this paper mainly studies the small scale MIMO To alleviate the problem of pilot frequency signal interference system, and puts forward several pilot pollution plan, in order to improve the performance of large scale MIMO system. The main work of this paper from the following aspects: 1. based on the "pilot scheme of intelligent allocation of water filling algorithm" principle in the large scale MIMO system for a limited number of orthogonal pilot channel estimation the channel coherence length. The same set of orthogonal pilot frequency multiplexing in all the inter cell interference between signals caused by complex pilot, pilot pollution. This problem has become a large-scale multi cell MIMO to enhance the system performance bottleneck. However, the quality of different communication terminal corresponding channel is different, different pilot the degree of interference with neighboring cells in the pilot are also different. Therefore, this paper puts forward a based on the "water filling algorithm" thinking of the pilot program. According to the intelligent distribution terminal channel quality and pilot subject The degree of disturbance and pilot terminal according to the "water filling algorithm" thought of intelligent matching, to reduce the whole system pilot pollution, optimize the pilot resource utilization. Experiments show that this scheme at the expense of minority and poor quality of channel terminal performance situation, greatly enhance the data capacity of the overall.2. system fast allocation scheme pilot Intelligent Particle Swarm Optimization Algorithm for large scale MIMO in multi cell system intelligent frequency allocation scheme can effectively suppress the system pilot pollution based on the whole. However, the pilot intelligent allocation of computational complexity and the number of terminals are related. For example, the 10 terminal 10 orthogonal pilot case, and terminal matching program the pilot as many as 10! 628800 =3. In order to reduce the pilot intelligent allocation scheme of computational complexity, this paper proposes an intelligent particle swarm optimization algorithm based on pilot fast allocation scheme. Using particle The characteristics of information sharing between the instant all particle swarm optimization algorithm for pilot intelligent optimization in the distribution process, helps to quickly find the best match for terminal and guide in the pilot frequency between, reduce the computational complexity of the intelligent distribution process and pilot pollution reduce the dye. The experimental results show the effectiveness of.3. scheme in suppressing the pilot pollution and to reduce the computational intelligence pilot allocation process complexity of the pilot scheme of pollution layer stratification and the adjacent cell terminal pilot sent asynchronously between the multiplexed pilot LED based on the impact on the terminal area at the center and the edge of the terminal is different. This paper proposes a hierarchical terminal the inter cell edge terminal cluster pilot scheme based on asynchronous transmission. In this scheme, the terminal layer, each district center and terminal cluster interference degree small transmit uplink pilot, and different In the area by the guide edge of the terminal cluster frequency pollution serious frequency sends the uplink slots in non overlapping. Experiments show that this scheme can effectively reduce the influence of the pilot pollution of the entire system. But the existing edge terminal and the adjacent cell within a cell in the center terminal multiplexing pilot of this scheme therefore, between different areas within the cluster and the cluster center edge terminal terminal still exists pilot interference. In order to reduce the pilot pollution, this paper proposed an improved hierarchical terminal and different terminal cluster uplink pilot downlink data transmission alignment in the case. No related characteristics between using uplink pilot and downlink the data, through different terminal clusters uplink pilot downlink data transmission cross way, pilot pollution can be further reduced. Experiments prove that the improved scheme is a scheme to reduce pilot pollution and improve the system The system performance is more advantageous.4. cell clustering and asynchronous transmission pilot pilot power control scheme for large scale MIMO system based on multi cell cell cluster, different cell cluster terminal asynchronously turns to transmit uplink pilot. This scheme through the pilot pollution pressure reduced to between cluster area to reduce the whole system of pilot pollution. Obviously, affecting cell cluster number of pilot pollution is smaller, but more time to send a coherent cluster within the time length of uplink data is compressed, so the overall performance is not the small number of clusters more system play a reasonable better. Cell clustering strategy for this scheme is essential. This paper from the upstream and downstream comprehensive consideration to send effective data and obtain the suitable cell clustering strategy, in order to reduce pilot pollution and Two aspects to enhance the overall performance of the system to find a balance point. Experiment proves the effectiveness of the best cell theory to find the clustering factor. In addition, the pilot pollution problem still exists between this scheme in the same cluster area, the pilot transmission power control is introduced into the cell cluster pilot asynchronous transmission scheme. Through the pilot pollution control pilot transmission power so as to reduce the area between each cell cluster, simulation experiments show that the scheme to reduce pilot pollution advantages.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN919.3

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2 伏曉慧;導(dǎo)頻污染下Massive MIMO系統(tǒng)的信道估計(jì)與導(dǎo)頻調(diào)度研究[D];西南交通大學(xué);2015年

3 程卿卿;Massive MIMO系統(tǒng)中減小導(dǎo)頻污染影響問(wèn)題研究[D];哈爾濱工業(yè)大學(xué);2015年

4 徐政;基于大規(guī)模MIMO系統(tǒng)預(yù)編碼算法研究[D];西安郵電大學(xué);2015年

5 王丹;大規(guī)模MIMO系統(tǒng)預(yù)編碼算法和導(dǎo)頻污染問(wèn)題研究[D];南京郵電大學(xué);2015年

6 馬琦;聯(lián)通小區(qū)覆蓋系統(tǒng)建設(shè)項(xiàng)目的風(fēng)險(xiǎn)分析與控制策略[D];南京郵電大學(xué);2014年

7 唐文銳;大規(guī)模MIMO無(wú)線通信系統(tǒng)的容量分析[D];東南大學(xué);2015年

8 黃禹淇;大規(guī)模無(wú)線MIMO系統(tǒng)的上行鏈路傳輸技術(shù)研究[D];東南大學(xué);2015年

9 鄭心如;大規(guī)模MIMO系統(tǒng)導(dǎo)頻設(shè)計(jì)和信道估計(jì)技術(shù)研究[D];東南大學(xué);2015年

10 姚天騏;大規(guī)模MIMO TDD無(wú)線系統(tǒng)中的導(dǎo)頻污染問(wèn)題研究[D];武漢郵電科學(xué)研究院;2015年

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