本文選題：基于部分干擾消除的廣義干擾對(duì)齊方法 + 可行性條件�。� 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：近年來(lái),人們?cè)谘芯總鹘y(tǒng)干擾對(duì)齊技術(shù)時(shí)發(fā)現(xiàn)了一個(gè)重要的問(wèn)題,即這種方法需要足夠的維度空間來(lái)實(shí)行對(duì)齊和消除干擾,這一問(wèn)題導(dǎo)致傳統(tǒng)的干擾對(duì)齊技術(shù)難以被用于規(guī)模較大的系統(tǒng)。因而,人們將研究的重點(diǎn)轉(zhuǎn)向了廣義干擾對(duì)齊技術(shù),這種技術(shù)的核心思想是利用信道衰落的差異,只對(duì)其中影響較強(qiáng)的干擾進(jìn)行對(duì)齊,從而使系統(tǒng)需對(duì)齊的干擾數(shù)目能夠控制在一定的范圍內(nèi),因而干擾對(duì)齊能夠?qū)嵭小Ｒ罁?jù)這一思想衍生出多種方法,其中較為流行的是基于L-interfering模型的干擾對(duì)齊方法,但這一方法在適用范圍上也有很大局限。針對(duì)這一局限,本文提出了基于部分干擾消除的廣義干擾對(duì)齊方法,即每個(gè)用戶根據(jù)自身的配置情況和需求及各干擾的影響情況,確定系統(tǒng)可行性條件,并根據(jù)該條件對(duì)其進(jìn)行選擇,將其中被選出的一部分干擾進(jìn)行對(duì)齊和消除。相比于已有的基于L-interfering模型的方法,這一方法的優(yōu)勢(shì)在于:首先,在適用條件上,不必要求每個(gè)用戶的發(fā)送流數(shù)完全相同,因而每個(gè)用戶可對(duì)齊的干擾數(shù)也不必相同;其次,在空間資源的利用上,由于這種方法在設(shè)計(jì)之時(shí),充分考慮到系統(tǒng)配置和發(fā)送流數(shù)等方面的差異性,因而它可以根據(jù)用戶所擁有的空間資源進(jìn)行靈活地調(diào)整,使資源的利用更加充分,因而無(wú)論從系統(tǒng)總體還是單個(gè)用戶來(lái)說(shuō),都可以達(dá)到更優(yōu)的性能;同時(shí),由于該方法在資源調(diào)度方面的靈活性,該方法在實(shí)施過(guò)程中還可以與其他優(yōu)化目標(biāo)相結(jié)合,從而滿足某些特殊性能的優(yōu)化需要。在該方法中,可行性條件是基礎(chǔ),依據(jù)該條件實(shí)行的干擾選擇策略是核心步驟。根據(jù)這兩點(diǎn),本文主要做了以下幾項(xiàng)工作:(1)分析了現(xiàn)有的L-interfering模型在適用性方面的局限性,提出了基于部分干擾消除的廣義干擾對(duì)齊方法,并從理論方面分析其在擴(kuò)展適用范圍和節(jié)省空間資源方面的作用。(2)利用圖論的知識(shí),以單流和多流兩個(gè)場(chǎng)景為背景,推導(dǎo)了該方法實(shí)行的可行性條件,并通過(guò)仿真驗(yàn)證和與基于L-interfering模型的方法對(duì)比說(shuō)明,以此可行性條件為基礎(chǔ)的PIC-GIA方法在擴(kuò)大適用范圍和利用空間資源提升性能方面的重要作用。(3)以可行性條件為約束條件,以最優(yōu)化系統(tǒng)傳輸速率為目標(biāo),利用整數(shù)規(guī)劃的相關(guān)知識(shí)提出相應(yīng)的干擾選擇和優(yōu)化策略。由于系統(tǒng)速率直接取決于接收機(jī)處理之后的信干噪比(Signal to Interference and Noise Ratio,SINR),因而,這里通過(guò)最大化處理后的SINR來(lái)確定選擇策略,并近似推導(dǎo)出在以可行性條件為約束條件的情況下,通過(guò)選擇部分干擾對(duì)齊和消除能夠達(dá)到的最優(yōu)系統(tǒng)速率。同時(shí),本文還提出了兩種簡(jiǎn)化選擇策略,使其能夠在逼近基于最大化SINR的性能的同時(shí),降低復(fù)雜度。
[Abstract]:In recent years, people have found an important problem when studying the traditional interference alignment technology, that is, this method needs enough dimension space to align and eliminate interference. This problem makes it difficult for traditional interference alignment techniques to be used in large scale systems. Therefore, the focus of the research has been shifted to the generalized interference alignment technique. The core idea of this technique is to make use of the difference of channel fading and to align only the more influential interference. So that the number of interference needed to be aligned can be controlled within a certain range, so interference alignment can be carried out. According to this idea, many methods are derived, among which the more popular one is the interference alignment method based on L-interfering model, but this method is also limited in its application scope. Aiming at this limitation, this paper proposes a generalized interference alignment method based on partial interference cancellation, that is, each user determines the feasibility condition of the system according to the configuration and requirements of the user and the influence of each interference. According to the condition, the selected part of the interference is aligned and eliminated. Compared with the existing methods based on L-interfering model, the advantages of this method are: first, it is not necessary to require every user to have exactly the same number of streams sent by each user, so that the number of interference that can be aligned by each user does not need to be the same, and second, the number of interference that can be aligned by each user does not have to be the same. In the use of space resources, this method can be flexibly adjusted according to the space resources owned by the user, because it fully takes into account the differences in system configuration and the number of sending streams when it is designed. Make full use of resources, so that better performance can be achieved both from the system as a whole and from a single user; at the same time, because of the flexibility of the method in resource scheduling, The method can also be combined with other optimization objectives in the process of implementation, so as to meet the needs of some special performance optimization. In this method, the feasibility condition is the basis, and the interference selection strategy based on the condition is the core step. According to these two points, this paper mainly does the following work: 1) analyzes the limitations of the existing L-interfering model in applicability, and proposes a generalized interference alignment method based on partial interference cancellation. The paper also analyzes its function in expanding the scope of application and saving space resources theoretically. (2) using the knowledge of graph theory and taking two scenarios of single flow and multi-flow as the background, the feasibility conditions of this method are deduced. The simulation and comparison with the method based on L-interfering model show that the PIC-GIA method based on this feasibility condition plays an important role in expanding the scope of application and using space resources to improve its performance. Aiming at optimizing the transmission rate of the system, the corresponding interference selection and optimization strategy are proposed by using the relevant knowledge of integer programming. Since the system rate is directly dependent on the signal-to-noise ratio (signal-to-noise ratio) after processing by the receiver, the selection strategy is determined by maximizing the processed SINR, and the selection strategy is approximately deduced under the condition that the feasibility condition is taken as the constraint condition. By selecting partial interference alignment and eliminating the optimal system rate that can be achieved. At the same time, two simplified selection strategies are proposed to reduce the complexity while approximating the performance based on maximization of SINR.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN972

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 李玲香;蜂窩系統(tǒng)中廣義干擾對(duì)齊技術(shù)研究[D];電子科技大學(xué);2013年

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本文編號(hào)：1979493