Research On Radio Resource Management Based On Energy Efficiency For Single-Cell Multi-User Communication Systems

ABSTRACT:With the rapid development of wireless communications, we are having a strongly increased system capacity and widely expanding coverage area, along with a growing popularity and demand of wireless service. While we are pursuing higher data rate, wider bandwidth and denser deployment, however, the conflicts with the natural and social fields are also appearing. It mainly reflects in the electric waste and environmental pollution, resulting from the huge energy consumption. Besides, user devices for wire-less communications are usually energy-limited, the booming demand for the wireless applications and the relatively slow advancement of battery technology present a "battery bottleneck" for the users experience. Therefore, the requests of cutting cost of power consumption, diminishing environmental effects, and extending effective communication duration put a premium on achieving high energy-efficient link layer technology.Previous work on radio resource allocation, including power allocation, spectrum assignment, scheduling and access control, has mainly focused on optimizing spectrum efficiency. However, the energy efficiency and spectrum efficiency tradeoff makes the energy-efficient resource allocation with QoS (Quality of Service) requirements a chal-lenge. The ignorance of existing research on energy-efficient resource allocation includes: it ignores the specific characteristics of uplink systems, thus the system energy efficien-cy can be further increased by algorithm designs; it ignores the energy-efficient access control to confront the scenarios where the peak traffic exceeds the network carrying ca-pacity; it ignores the requests and the affects of energy efficiency resulted from the user satisfaction difference of various traffics. To investigate these issues, in this thesis, we focus on the OFDM (Orthogonal Frequency-Division Multiplexing) scenario, study the energy-efficient radio resource allocation, and aim at the tradeoff between energy effi-ciency and QoS requirements. The main contribution of this thesis includes:1) In the single-cell multi-user networks, we address the uplink power allocation and subcarrier assignment problem and develop energy-efficient schemes that maxi-mize the summation of energy efficiency of all users with minimum data rate con-straints taken into consideration. This optimization problem is built based on the independence among users in the uplink scenario, in other words, the powers of different users cannot be shared and neither can their throughput and energy effi- ciency. Since the optimization problem is a mixed integer nonlinear programming problem, the computation complexity is relatively high achieving the optimal solu-tion. Thus, we propose efficient suboptimal power allocation and subcarrier assign-ment algorithm. The proposed algorithms maximize the system energy efficiency in uplink multi-user network while guarantee the minimum data rate constraints. The simulation results show that the proposed algorithms increase the system energy efficiency as well as the system throughput, compared with existing algorithms.2) We consider the scenario in which the base station serves a subset of users when available resources cannot support all of the users’ QoS requirements. We intro-duce energy-efficient scheduling in the access control module to further increase energy efficiency. We proposed a scheduling metric to balance the tradeoff be-tween energy efficiency and fairness. Based on the scheduling metric, we propose a joint scheduling and resource allocation algorithm to address the system energy efficiency maximization problem with an acceptable complexity. Simulation results analyze the influences of parameters, such as QoS requirements, circuit power and user priority, on the system energy efficiency.3) In the single-cell multi-user networks with heterogeneous services, we consider the service characteristics differences. We propose energy-efficient utilities for various services describing the user satisfaction per energy consumption for transmission. The resource allocation problem is formulated to maximize the energy-efficient utility of the network while satisfying the QoS users’ requirements. Relying on the fractional programming and convex optimization tools, the corresponding near-optimal subcarrier and power allocation algorithm is developed afterwards. Sim-ulation results show that the proposed algorithm achieves higher energy-efficient utility as well as higher system energy efficiency, compared with existing algo-rithms.