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To reduce the energy consumption in heterogeneous 5G access networks, we propose a cooperative energy-saving mechanism based on user association (UA-CESM). Joint processing (JP) and centralized resource scheduling are introduced into the mechanism to solve inadequate coverage problem caused by base-station (BS) dormancy by means of cooperative BS selection and BS state control. First, the number of...
Energy efficiency in future green cellular wireless networks poses a challenge to operators and researchers. An effective method of providing energy savings (ES) in base stations (BSs) is to switch off idle BSs or put them into sleep mode and subsequently migrate the traffic loads to active BSs in their neighborhood. The intrinsic issue related to such methods applied to heterogeneous networks (HetNets)...
Power models are crucial to assess the power consumption of base stations (BSs) without quantitive description. Currently available models seldom consider the dynamic factors such as indoor and outdoor temperature. As power model will affect the energy-saving gains of different green resolutions, in this paper we provide such power models for mobile communication BSs relying on practical data collected...
Reducing the energy consumption (EC) of base station (BS) is one of the major concerns in wireless cellular networks. Additionally, turning off some underutilized BSs during off-peak period and performing effective compensation without delay are the most efficient way to save energy. However, large-scale energy conservation yet remains to be investigated at macro level. In this paper, to solve the...
Energy issue of cellular access network has drawn much attention in the recent years. In this paper, we propose a Novel Energy-Saving Cell Selection Mechanism (ESCSM) including the energy-saving triggering conditions determination and a regional cell selection algorithm based on traffic. ESCSM selects the BSes which can be switched off without any negative effects to the radio coverage and service...
The requirement of QoE is gradually increasing currently. Simultaneously, as the intermedium between the users and network, devices support collecting several QoS parameters which could predict expected QoE for users. However, a large quantity of mobile devices will become the obstacle for the QoS collection due to the costs of collection traffic. To solve it, this paper proposes a framework for collecting...
Cell classification in traffic analysis and modeling is an important task which is required by planning and optimization of mobile networks. Because traffic is always nonlinear, nonstationary and influenced by immeasureable factors, accurate analytical traffic model can be hardly obtained. Therefore a new classification method using reservoir computing to cell types is proposed. Analysis of field...
The accurate traffic model and prediction of mobile network plays an important role in network planning. It is particularly important for the performance analysis of mobile networks. The study in this paper concerns predicting the traffic of mobile network, which is essentially nonlinear, dynamic and affected by immeasurable parameters and variables. The accurate analytical model of the traffic of...
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