發(fā)布時(shí)間：2018-06-15 00:16

  本文選題：家庭基站 + 能量效率��； 參考：《北京郵電大學(xué)》2014年博士論文

【摘要】：為了應(yīng)對(duì)無(wú)線數(shù)據(jù)業(yè)務(wù)的爆發(fā)式增長(zhǎng),無(wú)線基礎(chǔ)設(shè)施的規(guī)模變得日益龐大,由此也產(chǎn)生了大量的能源消耗。歐盟的最新報(bào)告指出,信息通信技術(shù)(ICT)產(chǎn)業(yè)已經(jīng)成為全球第5大耗能產(chǎn)業(yè),其中移動(dòng)通信網(wǎng)絡(luò)的能耗占ICT產(chǎn)業(yè)總能耗的15%～20%。另外,作為移動(dòng)通信網(wǎng)絡(luò)的重要組成部分,Femtocell的數(shù)量也在逐年遞增。據(jù)Informa TelecomsMedia公司的市場(chǎng)調(diào)研報(bào)告顯示,截止到2013年底Femtocell基站的出貨量將近1700萬(wàn)臺(tái),預(yù)計(jì)到2016年底Femtocell基站的數(shù)量將超過(guò)8500萬(wàn)臺(tái),部署如此大規(guī)模的Femtocell必將導(dǎo)致巨大的能源消耗。因此,研究Femtocell網(wǎng)絡(luò)的節(jié)能通信技術(shù)對(duì)提高無(wú)線網(wǎng)絡(luò)的能源利用率具有非常重要的意義。 本文在總結(jié)Femtocell網(wǎng)絡(luò)節(jié)能通信現(xiàn)有成果的基礎(chǔ)上,針對(duì)Femtocell網(wǎng)絡(luò)節(jié)能通信技術(shù)在干擾管理,資源分配策略的復(fù)雜性和QoS保障等方面存在的問(wèn)題,提出了三種能量效率模型：基于干擾凸定價(jià)的瞬時(shí)能效模型、基于指數(shù)級(jí)低通濾波器的能效模型和基于時(shí)延保障的能效模型。同時(shí),根據(jù)以上三種能效模型分別提出了三種具體的節(jié)能策略。本文的主要工作和創(chuàng)新成果如下： 1)為了提高Femtocell雙層網(wǎng)絡(luò)中家庭用戶的能量效率并且抑制其對(duì)鄰小區(qū)的同頻干擾,提出一種基于干擾凸定價(jià)的分布式節(jié)能資源分配策略。首先,建立基于干擾凸定價(jià)的瞬時(shí)能效模型,并據(jù)此模型研究了Femtocell雙層網(wǎng)絡(luò)中聯(lián)合子信道分配和功率控制問(wèn)題。其次,由于此資源優(yōu)化問(wèn)題為NP-難問(wèn)題,為降低計(jì)算復(fù)雜度,將原問(wèn)題分解為兩個(gè)子問(wèn)題：子信道分配和功率控制。在假設(shè)功率平均分配的前提下,提出能效優(yōu)先的子信道分配準(zhǔn)則,在此基礎(chǔ)上,將功率控制建模為超模博弈,并得到發(fā)射功率的帕累托最優(yōu)解。最后,提出一種基于干擾凸定價(jià)的節(jié)能資源分配算法。仿真結(jié)果表明,與一種聯(lián)合輪詢信道調(diào)度和基于能效的功率注水算法相比,本算法不但能有效地提高用戶的信干噪比和能量效率,并且通過(guò)干擾凸定價(jià)機(jī)制降低了對(duì)相鄰小區(qū)的同頻干擾。 2)針對(duì)基于瞬時(shí)能效模型的資源分配策略無(wú)法獲得發(fā)射功率的閉式解,導(dǎo)致計(jì)算復(fù)雜度高的問(wèn)題,提出一種兼顧公平的低復(fù)雜度的節(jié)能資源分配策略。首先,采用統(tǒng)計(jì)預(yù)測(cè)的思想,建立基于指數(shù)級(jí)低通濾波器的能效模型,并據(jù)此能效模型研究了Femtocell網(wǎng)絡(luò)的節(jié)能資源優(yōu)化問(wèn)題。其次,針對(duì)此資源分配問(wèn)題,采用近似替代的方法,分別獲得Femtocell稀疏部署場(chǎng)景下發(fā)射功率的閉式解和Femtocell密集部署場(chǎng)景下的近最優(yōu)閉式解,降低了運(yùn)算的復(fù)雜度。為保證家庭用戶的公平性,通過(guò)最大化用戶能效幾何平均數(shù)的方法,得到一種公平的子信道分配策略。最后,提出一種公平的低復(fù)雜度的節(jié)能資源分配算法。仿真結(jié)果表明,與一種聯(lián)合輪詢信道調(diào)度和基于非合作博弈的節(jié)能功率控制算法相比,本文所提算法在能效方面略有損失,但是極大地降低了算法的復(fù)雜度,并且保證了用戶的公平性。 3)針對(duì)現(xiàn)有的Femtocell網(wǎng)絡(luò)綠色資源分配中極少考慮業(yè)務(wù)時(shí)延的問(wèn)題,提出一種基于時(shí)延保障的節(jié)能功率控制策略。首先,為滿足實(shí)時(shí)業(yè)務(wù)的時(shí)延需求,采用有效容量理論,建立基于時(shí)延保障的能效模型,并據(jù)此模型研究了Femtocell自組織網(wǎng)絡(luò)時(shí)延保障的功率優(yōu)化問(wèn)題。其次,在給定時(shí)延要求的前提下,將此功率優(yōu)化問(wèn)題建模為斯坦伯格博弈。此博弈中,宏用戶定義為領(lǐng)導(dǎo)者,家庭用戶定義為跟隨者,領(lǐng)導(dǎo)者知道跟隨者的所有策略信息,并首先選擇功率策略；跟隨者根據(jù)領(lǐng)導(dǎo)者的策略選擇最佳策略,直至穩(wěn)定狀態(tài)。最后,在證明斯坦伯格博弈均衡點(diǎn)的存在性與唯一性的基礎(chǔ)上,采用Q學(xué)習(xí)理論,提出一種基于時(shí)延保障的節(jié)能功率控制算法。仿真結(jié)果表明,本文所提出的算法在實(shí)現(xiàn)節(jié)能并且保障用戶時(shí)延的同時(shí),與一種基于推測(cè)的多智能體Q學(xué)習(xí)算法相比,收斂速度提高了將近一倍。
[Abstract]:In order to cope with the explosive growth of wireless data services, the scale of wireless infrastructure has become increasingly large and thus produces a large amount of energy consumption. The latest EU report indicates that the ICT industry has become the fifth largest energy consuming industry in the world, in which the energy consumption of mobile communication networks accounts for 15% to 20%. of the total energy consumption of the ICT industry. In addition, as an important part of the mobile communication network, the number of Femtocell is increasing year by year. According to the Market Research Report of Informa TelecomsMedia, the shipments of Femtocell base station are nearly 17 million by the end of 2013, and the number of Femtocell base stations is expected to exceed 85 million by the end of 2016, deploying such a large scale of F Emtocell will inevitably lead to great energy consumption. Therefore, it is of great significance to study the energy saving communication technology of the Femtocell network to improve the energy utilization of the wireless network.
On the basis of summarizing the existing results of Femtocell network energy saving communication, this paper proposes three energy efficiency models for Femtocell network energy saving communication technology in the aspects of interference management, the complexity of resource allocation strategy and the QoS guarantee, and the instantaneous energy efficiency model based on the interference convex pricing, based on the exponential low pass filter The energy efficiency model and the energy efficiency model based on time delay guarantee. At the same time, three specific energy saving strategies are put forward according to the above three energy efficiency models. The main work and innovation results of this paper are as follows:
1) in order to improve the energy efficiency of the family users in the Femtocell double layer network and to suppress the same frequency interference to neighbouring communities, a distributed energy saving resource allocation strategy based on interference convex pricing is proposed. First, a transient energy efficiency model based on interference convex pricing is established, and the joint subchannel in the Femtocell double layer network is studied based on the model type. Secondly, because the problem of resource optimization is NP- difficult, in order to reduce the computational complexity, the original problem is decomposed into two sub problems: subchannel allocation and power control. Based on the assumption of average power allocation, the energy efficiency priority subchannel partition criterion is proposed. On this basis, the power control is modeled as super. In the end, an energy-efficient resource allocation algorithm based on interference convex pricing is proposed. The simulation results show that, compared with a joint polling channel scheduling and energy efficiency based power injection algorithm, this algorithm can not only effectively improve the signal to noise ratio and energy efficiency of the high user, but also pass through the energy efficiency and the energy efficiency of the high user. The interference convex pricing mechanism reduces the same frequency interference to adjacent cells.
2) for the resource allocation strategy based on the instantaneous energy efficiency model, the closed solution of the transmission power can not be obtained, which leads to the problem of high computational complexity. A kind of energy-saving resource allocation strategy with fair and low complexity is proposed. Firstly, the energy efficiency model based on the exponential low pass filter is established by using the thought of statistical prediction, and the energy efficiency model based on this model is established. The optimization of energy saving resources in Femtocell network is studied. Secondly, an approximate replacement method is used to obtain the close solution of the transmission power in the Femtocell sparse deployment scene and the near optimal closed solution under the Femtocell intensive deployment scenario with an approximate alternative method. A fair subchannel allocation strategy is obtained by maximizing the user's energy efficiency geometric mean. Finally, a fair and low complexity energy saving resource allocation algorithm is proposed. The simulation results show that the proposed algorithm can be compared with an energy-saving power control algorithm based on a joint polling channel scheduling and an uncooperative game. There is a slight loss in efficiency, but it greatly reduces the complexity of the algorithm and ensures the fairness of users.
3) in order to solve the problem of time delay in the distribution of green resources in Femtocell network, an energy-saving power control strategy based on time delay guarantee is proposed. First, in order to meet the time delay requirement of real time service, an effective capacity model based on time delay guarantee is established by using effective capacity theory, and the Femtocell self organizing network is studied. The power optimization problem of collateral delay guaranteed. Secondly, under the premise of timing delay, the power optimization problem is modeled as a Steinberg game. In this game, the macro user is defined as the leader, the family user is defined as the follower, the leader knows all the policy information of the followers, and the power strategy is selected first; the follower is based on the leader. In the end, on the basis of proving the existence and uniqueness of Steinberg's game equilibrium point, the Q learning theory is used to propose an energy-saving power control algorithm based on time delay guarantee. The simulation results show that the proposed algorithm can save energy and ensure the time delay of users. Compared with a speculative multi-agent Q learning algorithm, the convergence speed is nearly doubled.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5

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本文編號(hào)：2019634