Abstract
Heterogeneous cloud radio access network (H-CRAN) needs more elegant design to achieve higher energy efficiency and spectral efficiency than traditional cloud radio access networks. In this paper, we propose an energy-efficient resource allocation algorithm by taking into account the impact of arrival rates of various user traffic. Firstly, based on the power consumption model of the H-CRAN, the average energy-efficiency of the whole network is adopted as the optimization objective with multiple constraints of maximum transmit power, average power, and minimum data rate of each users, etc. In order to solve the non-convex and non-deterministic polynomial time- hardness (NP-hard) problem, we transform the objective function into analyzable multiple sub-problems by using fractional programming and norm approximation. Secondly, by the Lyapunov optimization method, we turn the original problem into a problem of system stability. Thirdly, we derive the closed expression of the optimal power allocation matrix and the optimal user association matrix with the Lagrangian dual decomposition. We propose a two-layer iterative algorithm to balance the power consumption and energy efficiency with a designed control factor. Both theoretical bound of average energy efficiency and length of data queuing are derived. Finally, the comprehensive numerical results demonstrate of convergence of the proposed algorithm and verify the performance gain by proposed energy-efficient resource allocation scheme.
Highlights
It is a trend that millions more base stations (BSs) and billions more smart devices will be connected in the fifth generation (5G) wireless network [1]
SYSTEM MODEL AND PROBLEM FORMULATION Different from the traditional network architecture, the power consumption of the Heterogeneous cloud radio access network (H-CRAN) is mainly composed of three parts: high power nodes (HPNs)/remote radio heads (RRHs) consumption, fronthaul link consumption, and baseband units (BBUs) pool consumption
A resource allocation algorithm has been proposed based on arrival rate
Summary
It is a trend that millions more base stations (BSs) and billions more smart devices will be connected in the fifth generation (5G) wireless network [1]. Y. Zhang et al.: Arrival Rate-Based Average Energy-Efficient Resource Allocation for 5G H-CRAN be handled and even eliminated by cooperation in BBU pool. The centralized BBU pool facilitates the interaction of different cells and regions, enabling efficient cooperation between HPNs (e.g., macro or micro base stations) and low-power RRH nodes. An average energy efficiency optimization problem under the traditional network architecture is studied in [17]. The authors in [22] propose an energy efficient radio resource management algorithm in H-CRAN. We propose an efficient resource allocation algorithm called Arrival Rate based Average Energyefficient (ARAE) dynamic resource allocation which introduces the arrival rate of users under H-CRAN architecture. The optimization problem is modeled under the constraints of average power, maximum power, minimum data rate, etc.
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