本文選題：能量效率 + 節(jié)能��； 參考：《中國科學(xué)技術(shù)大學(xué)》2014年博士論文

【摘要】：隨著移動互聯(lián)網(wǎng)的發(fā)展,無線業(yè)務(wù)出現(xiàn)爆炸性增長。這種增長不僅體現(xiàn)在數(shù)據(jù)量的增加,也體現(xiàn)在業(yè)務(wù)種類和QOS需求的多樣性變化。為了滿足業(yè)務(wù)需求、提升網(wǎng)絡(luò)容量,需要從傳輸技術(shù)和網(wǎng)絡(luò)架構(gòu)兩個方面進(jìn)行下一代無線網(wǎng)絡(luò)設(shè)計。先進(jìn)的物理層技術(shù),如OFDM、MIMO,在增大頻譜效率的同時,帶來了更大的能量開銷。未來網(wǎng)絡(luò)站點(diǎn)密集化、異構(gòu)化不僅增加站點(diǎn)數(shù)目、增加耗能,還提升網(wǎng)絡(luò)干擾強(qiáng)度,降低了整網(wǎng)的能量效率。為了降低能量開銷,減少碳排放,需要在保證業(yè)務(wù)需求的前提下對基站進(jìn)行節(jié)能設(shè)計。 本文先從業(yè)務(wù)QOS的表征參數(shù)出發(fā),將時延作為最重要的QOS影響因素,并按照業(yè)務(wù)的時延要求,將業(yè)務(wù)分為嚴(yán)格時延約束和時延容忍兩大類。針對這兩類業(yè)務(wù),分別從鏈路級角度設(shè)計時延保障的節(jié)能調(diào)度器,并考慮實際多小區(qū)系統(tǒng),設(shè)計分層調(diào)度器,在保證時延要求的前提下最小化基站耗能,并協(xié)調(diào)相鄰小區(qū)間休眠子幀,以降低網(wǎng)絡(luò)間干擾。所有的這些研究都是基于實際的功耗模型進(jìn)行的。由于基站功耗模型非連續(xù),調(diào)度問題在多數(shù)場景下沒有最優(yōu)解。 本文研究了嚴(yán)格時延約束業(yè)務(wù)的高能效調(diào)度策略。首先針對AWGN信道,研究如何在給定時間內(nèi)傳輸不同時延要求的數(shù)據(jù)包使得系統(tǒng)所需的能量最小的問題,利用擬凸優(yōu)化提出了低復(fù)雜度最優(yōu)傳輸速率和休眠控制策略,在此基礎(chǔ)上,提出因果系統(tǒng)的高能效傳輸調(diào)度器設(shè)計；進(jìn)一步需要考慮衰落信道下存在信道估計耗能時的數(shù)據(jù)包級能效最優(yōu)傳輸控制和調(diào)度策略,通過聯(lián)合考慮信道的統(tǒng)計特性、導(dǎo)頻耗能和數(shù)據(jù)包長度,提出包含剩余時間項、信道相關(guān)項和能量相關(guān)項的次優(yōu)調(diào)度算法進(jìn)行能效資源調(diào)度。 本文針對時延容忍業(yè)務(wù)進(jìn)行能效傳輸設(shè)計,提出兩種休眠策略并利用排隊論中帶休假的M/G/1模型,計算出不同休眠控制策略下的能耗和業(yè)務(wù)平均時延的閉式表達(dá),利用凸優(yōu)化理論和拉格朗日乘子法對問題進(jìn)行迭代求解,并提出給定拉格朗日乘子下的迭代凸搜索的最優(yōu)功率分配和休眠控制算法；在多用戶場景下,分析ARQ對時延影響,依據(jù)業(yè)務(wù)的統(tǒng)計特性建立優(yōu)化問題,利用組合優(yōu)化理論進(jìn)行能效資源分配,在保證業(yè)務(wù)平均時延要求下最大化系統(tǒng)能效。 本文最后研究實際多小區(qū)中滿足用戶QoS需求的子幀級協(xié)調(diào)休眠調(diào)度策略,提出兩層調(diào)度器模型,利用線性控制理論設(shè)計上層調(diào)度器的等效濾波器,為每幀分配數(shù)據(jù)以保證QoS,底層進(jìn)行高能效資源分配；先針對單用戶,將活躍子幀連續(xù)化,利用擬凸優(yōu)化證明問題存在最優(yōu)解,通過迭代搜索求得最優(yōu)功率和休眠子幀數(shù)目；然后考慮多用戶系統(tǒng),利用時間共享條件和擬凸優(yōu)化可以獲得休眠子幀數(shù)目,利用邊緣自適應(yīng)算法分配子信道、功率；最后對于多小區(qū),依據(jù)單小區(qū)的資源分配結(jié)果確定各小區(qū)在每幀內(nèi)所需傳輸數(shù)據(jù)量,依據(jù)上一時隙信道狀態(tài)和干擾強(qiáng)度分布結(jié)果,動態(tài)協(xié)調(diào)休眠子幀,使得強(qiáng)干擾鄰小區(qū)休眠子幀正交,進(jìn)而提升網(wǎng)絡(luò)能量效率。
[Abstract]:With the development of mobile Internet, wireless services have exploded. This growth is not only reflected in the increase in the amount of data, but also in the variety of business types and QOS requirements. In order to meet business needs and improve the network capacity, the next generation of wireless networks should be designed from two aspects of transmission technology and network architecture. The physical layer technology, such as OFDM, MIMO, increases the energy cost while increasing the spectrum efficiency. In the future, the network site intensive, isomerization not only increases the number of sites, increases energy consumption, but also improves the network interference intensity and reduces the energy efficiency of the whole network. In order to reduce the energy cost and reduce the carbon emissions, it is necessary to ensure the business needs. Under the premise, the energy saving design of the base station is carried out.
In this paper, starting from the characterization parameters of the service QOS, the time delay is considered as the most important QOS influence factor, and the service is divided into two categories, strict delay constraint and delay tolerance according to the time delay requirements of the business. The layer scheduler minimizes the energy consumption of the base station and coordinates intercell dormant subframes between adjacent cells to reduce internetwork interference. All these studies are based on the actual power model. The scheduling problem has no optimal solution in multiple scenes because of the discontinuous power model of the base station.
In this paper, the high-energy efficient scheduling strategy of strict time delay constrained service is studied. Firstly, the problem of how to transmit the required data in a given time in a given time is studied for the AWGN channel to minimize the energy required for the system. By using quasi convex optimization, a low complexity optimal transmission speed rate and a dormancy control strategy are proposed. The high energy efficiency transmission scheduler design of the causality system; further need to consider the packet level energy efficiency optimal transmission control and scheduling strategy in the channel estimation energy dissipation under the fading channel. By considering the statistical characteristics of the channel, the pilot energy consumption and the packet length, the residual time term, the channel correlation and the energy correlation term are proposed. The suboptimal scheduling algorithm is used for energy efficient resource scheduling.
In this paper, two kinds of sleep strategies are designed for time delay tolerance service. Two kinds of dormancy strategies are proposed and the closed expression of energy consumption and service average delay under different sleep control strategies is calculated by using the M/G/1 model with vacation in queuing theory. The convex optimization theory and Lagrange multiplier method are used to solve the problem iteratively, and the given pull is given. The optimal power allocation and dormancy control algorithm for iterative convex search under the Grange multiplier is used. Under multi user scenarios, the effect of ARQ on time delay is analyzed, and the optimization problem is established according to the statistical characteristics of the service. The energy efficiency resource allocation is carried out by combined optimization theory, and the energy efficiency of the system is maximized under the guarantee of the service average time delay.
At the end of this paper, a sub frame coordinated dormancy scheduling strategy which satisfies the user's QoS needs is studied. A two layer scheduler model is proposed and the equivalent filter of the upper level scheduler is designed by using linear control theory. The allocation of high energy efficiency resources at the bottom of each frame is guaranteed by QoS, and the active subframe is continuous for the single user. By using pseudo convex optimization, the optimal solution is proved, the optimal power and the number of dormant subframes are obtained by iterative search, and then the number of dormant subframes can be obtained by using the time sharing condition and pseudo convex optimization, and the sub channel and power are allocated by the edge adaptive algorithm. Finally, the multiple cell, based on the single cell, is based on the single cell. The result of resource allocation determines the amount of data that each cell needs to transmit in each frame. According to the results of the state of the slots channel and the distribution of the interference intensity, the dormant subframe is dynamically coordinated so that the strong interference neighbour subframe is orthogonal, and then the energy efficiency of the network is improved.
【學(xué)位授予單位】：中國科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN929.5

【共引文獻(xiàn)】

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