本文選題：異構(gòu)網(wǎng)絡(luò)　切入點：資源分配　出處：《東南大學(xué)》2016年碩士論文

【摘要】：無線網(wǎng)絡(luò)異構(gòu)化是無線通信技術(shù)的發(fā)展趨勢,設(shè)計合理的資源優(yōu)化算法以最大化無線資源利用率,最大程度保證用戶的服務(wù)質(zhì)量(QoS, Quality of Service)需求是異構(gòu)網(wǎng)絡(luò)研究中必須解決的問題。本學(xué)位論文圍繞異構(gòu)網(wǎng)絡(luò)場景下時延與功率最小化問題展開研究,提出了協(xié)作多點傳輸(CoMP, Coordinated Multi-Point)系統(tǒng)中基于Lyapunov優(yōu)化的功率分配算法,以及蜂窩與設(shè)備到設(shè)備(D2D, Device-to-Device)通信共存系統(tǒng)中基于強化學(xué)習(xí)的子信道共享與功率分配算法。本學(xué)位論文的主要工作如下：(1)介紹了異構(gòu)網(wǎng)絡(luò)的研究背景,回顧了異構(gòu)網(wǎng)絡(luò)資源分配方面已取得的研究成果,總結(jié)了異構(gòu)網(wǎng)絡(luò)時延與功率最小化問題研究中必備的數(shù)學(xué)方法。(2)針對時延敏感異構(gòu)CoMP系統(tǒng)中時延與功率最小化這一動態(tài)多目標(biāo)問題,首先使用主要目標(biāo)法將其轉(zhuǎn)化為時延約束下功率最小化問題,然后基于Lyapunov優(yōu)化理論,通過在每一時隙求解Lyapunov偏移與懲罰項之和的上界最小化進(jìn)行功率分配,并使用拉格朗日對偶分解法求解上述問題。仿真結(jié)果驗證了該算法在時延性能和功率消耗上均優(yōu)于貪婪算法和比例公平性算法,并分析了懲罰因子的選擇對時延和功率性能的影響。(3)針對蜂窩網(wǎng)絡(luò)與D2D通信共存系統(tǒng),提出了一種基于時延與功率最小化的子信道共享與功率控制算法,首先使用線性加權(quán)法將動態(tài)多目標(biāo)問題轉(zhuǎn)化為時延與功率加權(quán)和最小化問題,進(jìn)而使用Markov決策模型進(jìn)行建模。然后引入決策后狀態(tài)變量且基于線性模型逼近其值函數(shù),通過TD(0)算法進(jìn)行值函數(shù)估計,并通過策略迭代方法進(jìn)行策略更新,使之逐漸收斂于最優(yōu)策略。仿真結(jié)果表明,該算法經(jīng)過有限次迭代即可收斂,且能獲得較好的時延和功率性能。
[Abstract]:Isomerization of wireless network is the development trend of wireless communication technology. Reasonable resource optimization algorithm is designed to maximize the utilization ratio of wireless resources.To ensure the QoS (Quality of Service) requirement of users to the maximum extent is a problem that must be solved in the research of heterogeneous networks.This dissertation focuses on the problem of delay and power minimization in heterogeneous network scenarios, and proposes a power allocation algorithm based on Lyapunov optimization in cooperative multi-point transmission (Coordinated) systems.And the sub-channel sharing and power allocation algorithm based on reinforcement learning in D2D, Device-to-device) communication coexistence systems based on reinforcement learning.The main work of this dissertation is as follows: (1) the research background of heterogeneous network is introduced, and the research results in resource allocation of heterogeneous network are reviewed.This paper summarizes the necessary mathematical method in the study of delay and power minimization in heterogeneous networks. It aims at the dynamic multi-objective problem of delay and power minimization in delay-sensitive heterogeneous CoMP systems.Firstly, the main objective method is used to transform it into a time-delay constrained power minimization problem, and then based on the Lyapunov optimization theory, the power allocation is performed by solving the upper bound minimization of the sum of Lyapunov offsets and penalty terms in each time slot.The Lagrange dual decomposition method is used to solve the above problems.Simulation results show that the proposed algorithm is superior to greedy algorithm and proportional fairness algorithm in terms of delay performance and power consumption. The influence of penalty factor selection on delay and power performance is analyzed.A subchannel sharing and power control algorithm based on delay and power minimization is proposed. Firstly, the dynamic multi-objective problem is transformed into the time-delay and power-weighted minimization problem by linear weighting method, and then the Markov decision model is used to model the problem.Then the state variable after decision is introduced and the value function is approximated based on the linear model, and the value function is estimated by TD0) algorithm, and the policy is updated by the policy iteration method to make it converge to the optimal strategy gradually.The simulation results show that the algorithm can converge after finite iteration and can obtain better delay and power performance.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TN92

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