本文選題：能量效率　切入點(diǎn)：鏈路自適應(yīng)　出處：《中國科學(xué)技術(shù)大學(xué)》2014年博士論文

【摘要】：隨著無線通信技術(shù)的高速發(fā)展,用戶對于無線業(yè)務(wù)的需求也越來越高,這一切都集中反映出了日益增長的無線數(shù)據(jù)速率要求。這使得現(xiàn)有的無線通信系統(tǒng)受到頻譜資源緊缺和能耗嚴(yán)重的雙重挑戰(zhàn)。隨著3G甚至是4G通信網(wǎng)絡(luò)的廣泛架設(shè),可以預(yù)見無線通信的能耗將會迅猛增長。作為無線通信系統(tǒng)中能耗的重要組成部分,提高發(fā)送端的能效對于降低通信系統(tǒng)的能耗有著重要的現(xiàn)實(shí)意義。同時由于移動終端便攜性和移動性要求所帶來的體積和重量限制,以及電池材料發(fā)展的相對緩慢,造成了現(xiàn)有移動通信終端的“電池瓶頸”。因此除了節(jié)能環(huán)保的意義,提高終端發(fā)送能效同樣可以延長有效通信時間。因此如何通過終端發(fā)送技術(shù),提高終端發(fā)送能效是一個亟待解決的問題。本文研究兩個終端發(fā)送場景：點(diǎn)對點(diǎn)單用戶鏈路和多點(diǎn)對點(diǎn)多用戶發(fā)送。并分別提出了基于能效的鏈路自適應(yīng)發(fā)送技術(shù)和多用戶自適應(yīng)發(fā)送策略,來根據(jù)系統(tǒng)的CSIT,干擾狀態(tài)和目標(biāo)頻譜效率等自適應(yīng)調(diào)整發(fā)送速率,發(fā)射功率,多天線模式,協(xié)作方式等來提高終端發(fā)送能效。 首先,本文研究在非完美的發(fā)送端信道狀態(tài)信息下,OSTBC-MIMO系統(tǒng)的能效鏈路自適應(yīng)問題。之前基于完美信道狀態(tài)信息的研究和基于統(tǒng)計(jì)信道狀態(tài)信息的研究都可以歸為本章研究問題的極限情況。同時,我們不僅僅考慮常值的放大器效率,還考慮MQAM調(diào)制時,由于非恒包絡(luò)調(diào)制而造成的與調(diào)制階數(shù)相關(guān)的放大器效率。盡管建模的問題是非凸的,通過廣義凸優(yōu)化的理論,我們推導(dǎo)出在即時BER約束下,能效最優(yōu)的發(fā)送速率和發(fā)射功率的閉式表達(dá)結(jié)果。根據(jù)這個表達(dá)結(jié)果,我們進(jìn)一步給出完美信道狀態(tài)信息和統(tǒng)計(jì)信道狀態(tài)信息下的極限結(jié)果。 然后我們分別討論了通過自適應(yīng)的多天線選擇和訓(xùn)練序列優(yōu)化機(jī)制來提高點(diǎn)對點(diǎn)鏈路的能效。針對能效優(yōu)化的多天線自適應(yīng)選擇,我們提出了一種基于能效優(yōu)化的一般性天線選擇合并機(jī)制,即EE-GSC機(jī)制。通過該機(jī)制,我們實(shí)現(xiàn)了發(fā)送端多天線分集增益和電路功耗的最優(yōu)折中,來最大化鏈路的能效�；陧樞蚪y(tǒng)計(jì)理論,我們推導(dǎo)出了在目標(biāo)頻譜效率下,平均發(fā)射天線數(shù)和平均發(fā)送能效。并基于推導(dǎo)出的理論結(jié)果,給出了一些特殊情況的分析。針對能效優(yōu)化的訓(xùn)練序列自適應(yīng)功率分配,我們分別分析了基于訓(xùn)練序列的有反饋MIMO系統(tǒng)和無反饋MIMO系統(tǒng)。首先,我們考慮了無反饋MIMO系統(tǒng)中,發(fā)送端發(fā)送功率在各個天線上平均分配的情況。當(dāng)訓(xùn)練序列功率固定時,我們給出了能效最優(yōu)的數(shù)據(jù)序列功率,同時證明了它的存在唯一性。當(dāng)數(shù)據(jù)序列功率和訓(xùn)練序列功率都可變時,我們提出了一種收斂的交替優(yōu)化算法,獲得能效優(yōu)化的數(shù)據(jù)序列功率和訓(xùn)練序列功率。接著,我們分析了有反饋的MIMO系統(tǒng),發(fā)送功率在各個天線上注水分配的情況。當(dāng)訓(xùn)練序列功率固定時,我們給出了最優(yōu)的數(shù)據(jù)序列功率和其對應(yīng)的有效發(fā)送天線數(shù)。盡管有效發(fā)送天線數(shù)目是離散的,我們?nèi)宰C明了它們的存在唯一性。當(dāng)數(shù)據(jù)序列功率和訓(xùn)練序列功率都可變時,我們提出了一種類似的收斂的交替優(yōu)化算法,獲得能效優(yōu)化的數(shù)據(jù)序列功率和訓(xùn)練序列功率。通過這些算法的數(shù)值結(jié)果,我們討論了多天線配置,電路功耗和塊衰落長度對于發(fā)送端能效的影響。 接著我們研究了多用戶無用戶間協(xié)作系統(tǒng)中,用戶通過分布式功率控制,在實(shí)現(xiàn)目標(biāo)SINR的約束下,最小化總的發(fā)射功耗,以提高用戶能效的問題。對于系統(tǒng)中發(fā)射用戶較少,每個用戶都可以達(dá)到目標(biāo)SINR,即系統(tǒng)可行時,我們證明了采用ZF和MMSE接收機(jī),多用戶采用標(biāo)準(zhǔn)功控算法時,可以收斂到最優(yōu)的發(fā)射功率。當(dāng)系統(tǒng)中發(fā)射用戶較多,或者用戶目標(biāo)SINR較大時,不能保證每個用戶都可以達(dá)到目標(biāo)SINR,即系統(tǒng)不可行時,我們提出了具有用戶軟移除的分布式功控算法。通過廣義標(biāo)準(zhǔn)的理論,我們證明了該算法的收斂性。通過數(shù)值結(jié)果,我們證明了該算法通過軟移除不可行用戶,不僅僅提高了用戶的能效,而且降低了系統(tǒng)中用戶的掉線概率。 最后我們提出在有用戶間協(xié)作的MU-SIMO系統(tǒng)中,目標(biāo)頻譜效率下,一種分布式的能效優(yōu)化體制。我們將該體制分為兩個部分。在第一個部分,我們回答這樣一個問題,即：“在MU-SIMO協(xié)作集合內(nèi),用戶間如何協(xié)作?”。我們給出目標(biāo)頻譜效率下,在MU-SIMO協(xié)作集合內(nèi),每個用戶在各個RB上最優(yōu)發(fā)送能效功率分配的閉式表達(dá)式。在第二個部分,我們回答“用戶與誰協(xié)作,形成MU-SIMO協(xié)作集合?”。根據(jù)第一部分得到的閉式結(jié)果,我們提出了一種基于聯(lián)盟形成的合作博弈算法,在用戶間形成協(xié)作的MU-SIMO集合。該算法根據(jù)用戶能效的Pareto特性,采用了一種融合分裂的收斂迭代操作。
[Abstract]:With the rapid development of wireless communication technology, users are more and more demand for wireless services, all of which reflects the growing demand for wireless data rate. This makes the existing wireless communication systems by the shortage of spectrum resources and energy challenges seriously. Even with the 3G 4G communication network is widely set up, energy consumption can foresee the rapid growth of wireless communication. As an important part of energy consumption in wireless communication system, improve energy efficiency and reduce the energy consumption of the transmitter for communication system has important practical significance. At the same time from the mobile terminal portability and mobility requirements of the size and weight limit, and the battery materials development is relatively slow, resulting in the existing mobile communication terminal "battery bottleneck". So in addition to the significance of energy saving and environmental protection, improving energy efficiency can also extend the terminal to send Effective communication time. So how to improve the terminal technology, terminal transmission efficiency is an urgent problem to be solved. This paper studies two terminal transmission scene: point-to-point single user and multi link point-to-point multiuser transmission. And then proposed link adaptive efficiency transmission technology and multi-user adaptive transmission strategy based on according to the system, CSIT, interference state and target spectral efficiency of adaptive adjust the transmission rate, transmission power, multi antenna mode, cooperative mode to improve the terminal energy efficiency.
First, this paper studies in the transmitter channel state information non perfect, efficient link adaptive OSTBC-MIMO system. Based on the research before the perfect channel state information and statistical research based on channel state information can be classified as the limit of this chapter studies the problem. At the same time, we not only consider the amplifier efficiency values, but also consider the MQAM modulation, the amplifier efficiency caused by the non constant envelope modulation and modulation order. Although the related modeling problem is non convex, the generalized convex optimization theory, we derive the instant BER constraints, transmission rate and power transmission efficiency optimal closed form results. According to this the expression of results, we further give the perfect channel state information and the statistical channel state information under the ultimate results.
And then we discuss the adaptive multi antenna selection and training sequence optimization mechanism to improve the efficiency of a point-to-point link. For multi antenna adaptive optimization of energy efficiency, we propose a general antenna selection combining mechanism based on energy efficiency optimization, namely EE-GSC mechanism. Through this mechanism, we achieve the best compromise more the antenna diversity gain and power consumption of the circuit of the sending end, to maximize the link efficiency. Based on order statistics theory, we derive the spectral efficiency in the target, the average number of transmit antennas and the average transmission efficiency. Based on the theoretical results derived from the analysis is given in some special circumstances. For the training of adaptive power allocation efficiency sequence optimization, we analyzed based on training sequence feedback MIMO system and feedback MIMO system. Firstly, we consider the MIMO system without feedback,. The sending end transmission power in each antenna on the average distribution. When the training sequence power is fixed, we give the optimal energy efficiency of the power sequence data, and proved the existence and uniqueness of the data sequence. When the power and power variable training sequence, we propose an alternate optimization algorithm convergence, access to energy efficiency optimization of data sequence power and the training sequence power. Then, we analyzed the MIMO feedback system, distribution of water transmission power in each antenna case. When the training sequence power is fixed, we give the optimal number of transmit antennas according to the effective power sequence and its corresponding number. Although the number of transmit antennas is discrete and effective the US still proves their existence and uniqueness. When the data sequence power and power variable training sequence, we propose an alternating optimization algorithm with a similar convergence, by We get the data sequence power and training sequence power optimized by energy efficiency. Through the numerical results of these algorithms, we discuss the influence of multi antenna configuration, circuit power and block fading length on the energy efficiency of transmitter.
Then we studied the multi user cooperative system useless between households, the user through the control of distributed power, achieve the goal in the SINR under the constraint of minimizing the total transmit power, in order to improve the efficiency of user problems. For the launch of a few users in the system, each user can achieve the goal of SINR, the system is feasible, we prove that the use of ZF and MMSE receiver, multiuser using standard power control algorithm, can converge to the optimal transmit power. When transmitting more users in the system, or the user SINR is large, can not guarantee that each user can reach the goal of SINR, the system is not feasible, we propose a distributed power control software with user removed by using the generalized algorithm. The standard theory, we prove the convergence of the algorithm. The numerical results, we prove that the algorithm by soft remove infeasible users, not only enhance the user The energy efficiency of the system and the drop probability of the user in the system are reduced.
Finally, we put forward the MU-SIMO system has the collaboration between users in the target spectrum efficiency, energy efficiency optimization of a distributed system. The system is divided into two parts. In the first part, we answer such a question, namely: "in the MU-SIMO collaboration in the collection, the user how to work?" we give the target spectral efficiency, the MU-SIMO collaboration within each user in each RB optimal closed form sending energy-efficient power allocation. In the second part, we answer the user who form cooperation, MU-SIMO cooperation set? ". according to the first part of the closed form results, we propose a the algorithm of coalition formation based on cooperative game, formed in the collaboration between users of MU-SIMO set. The algorithm according to the characteristics of Pareto user efficiency, using a fusion fission iteration operation.

【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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本文編號：1660375