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Research On Cross-Layer Design And Energy Efficiency Optimization Resource Allocation Scheme For Broadband Wireless Communication Systems

Posted on:2016-06-26Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y HuFull Text:PDF
GTID:1108330503977349Subject:Information and Communication Engineering
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With the attention of environment, people are paying more and more attention to Green Communi-cations. While maximizing energy efficiency is one of the important objectives of Green Communications. Moreover, Orthogonal Frequency Division Multiple Access (OFDMA) technique can enhance the spectrum efficiency of the system and combat the inter-symbol interference causing by the multi-path effect. Mean-while, OFMDA technique may according to the Channel State Information (CSI) of users to dynamic assign sub-channel for users to realize multi-user diversity gain. Multiple-Input Multiple-Output (MIMO)technique not only can enhance data rate, but also can improve link reliability. So, OFDMA and MIMO are the key technologies of broadband wireless communication systems. Therefore, it is very important to research OFD-MA/MIMO system and energy efficiency resource allocation. In this dissertation, we mainly focus on the topic of cross-layer design for FDD-OFDM systems, energy efficiency optimization resource allocation for multiuser OFDMA systems, multiuser Massive MIMO systems, multiuser Massive MIMO-OFDMA systems, multi-cell cooperation Massive MIMO systems and massive MIMO heterogeneous networks, and proposed optimal or suboptimal schemes respectively. The main contributions of this dissertation are listed as follows.1. A resource scheduling cross-layer design scheme in FDD-OFDMA mobile communication down-link system about the issue of limited interference is proposed. A mathematical formulation of optimization issue is provided with the objective of maximizing system goodput under target Packet Error Rate (PER) constraint, meanwhile, we consider the interference of base station of neighbor. The proposed method can use ACK/NAK feedback information to transform the process of optimizing the objective function to Markov Decision Process(MDP), then we proposed the closed solution to implement user selection and rate alloca-tion without Channel State Information (CSI) at the base station. Compared with the traditional schemes, the system goodput of proposed algorithm is close to the condition of with perfect channel state information at the base station, it also has low complexity.2. An algorithm is proposed for energy-efficient user scheduling and resource allocation scheme in multiuser OFDMA mobile communication downlink system. A mathematical formulation of optimization issue is provided with the objective of maximizing system energy-efficient under QoS constraint. With per-fect Channel State Information (CSI) at the base station, in which the power consumption accounts for both transmit power and circuit power. We proposed two steps realize user scheduling and rate allocation scheme. Firstly, we selected the user according to the minimum rate requirement of user and the objective function of maximum energy efficiency. Secondly, we used Binary Search Assisted Ascent (BSAA) algorithm to realize rate allocation, when the user who does not satisfy the QoS requirement, we should user Lagrange method to do rate allocation. The proposed scheme can use the system diversity, it also enhanced the usage of energy effectively under QoS constraint.3. We consider energy-efficient resource allocation scheme in uplink multi-user Massive MIMO mobile communication systems. When the BS uses a zero-forcing(ZF) receiver.Using the energy efficiency lower bound as the optimization criterion, two resource allocation algorithms were investigated. Specifically, in our problem formulation the number of antenna arrays at BS and the transmit data rate vector at the user are jointly optimized to maximize the energy efficiency. We first demonstrated the existence of a unique globally optimal solution by exploiting the properties of objective function, then we developed an iterative algorithm to solve the resource allocation problem. While the convergence rate and the performance are sensitive to initialization point and the value of step length. Herein, we further adopt convex optimization to propose a more efficient iterative algorithm by transforming the considered non-convex optimization in fractional form into an equivalent optimization problem in subtractive form. Its convergence property is also proved. The numerical results show that the proposed algorithms converge to a near optimal point with a small number of iterations. When the BS uses a maximum-ratio combining(MRC) receiver, we first derived the lower bound of the capacity. Then a mathematical formulation of optimization issue is provided with the objective of maximizing system energy efficiency lower bound under the data rate of user and tolerable interference level constraints. By transforming the originally fractional optimization problem into an equivalent subtractive form using the properties of fractional programming, then we adopt convex optimization to maximize the energy efficiency. Specifically, both the number of antenna arrays at the BS and the transmit power at the user are adjusted. Simulation results show that the performance of proposed algorithm is close to the optimal algorithm with a small number of iterations.4. We consider downlink energy-efficient resource allocation scheme in multiuser massive MIMO OFD-MA systems. We first derived the capacity lower bound by using Zero Forcing (ZF) precoding with perfect CSI at base station. Then a mathematical formulation of optimization issue is provided with the objective of maximizing system energy efficiency lower bound under the minimum data rate requirement of users. Herein, we proposed a low complexity suboptimal algorithm because we should use exhaustive algorithm to get the globally optimal solution. We first developed a bandwidth allocation algorithm according for the minimum rate requirement of user and the objective function of maximum energy efficiency. Then the number of an-tenna arrays at BS and the transmit data rate vector at the user are jointly optimized to maximize the energy efficiency under bandwidth allocation algorithm. The numerical results show that the performance of energy efficiency and system throughput of proposed algorithm are well.5.We consider energy-efficient resource allocation scheme scheme in cooperation multi-cell massive MI-MO systems. A mathematical formulation of optimization issue is provided with the objective of maximizing system energy efficiency with the BSs fully cooperate, meanwhile the BS uses a zero-forcing(ZF) precoding. Using the properties of fractional programming, we proposed a power allocation algorithm. The numerical results show that the performance of energy efficiency and spectral efficiency of proposed algorithm are well, it also has low complexity.6.We consider energy-efficient resource allocation scheme for massive MIMO heterogeneous networks. We first derived the capacity lower bound by using Zero Forcing (ZF) precoding. Then a mathematical for-mulation of optimization issue is provided with the objective of maximizing system energy efficiency lower bound under the tolerable interference level constraints. Specifically, both the number of antenna arrays at the BS and the transmit power of the Bast Station and small-cell access points are adjusted. Simulation results show that the performance of proposed algorithm is good.
Keywords/Search Tags:Orthogonal Frequency Division Multiplexing, Orthogonal Frequency Division Multiple Access, Multiple-Input Multiple Output, multiuser diversity, user scheduling, dynamic resource allocation, Green, Communications, energy efficiency, Massive MIMO
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