Abstract
With the increasing amounts of terminal equipment with higher requirements of communication quality in the emerging fifth generation mobile communication network (5G), the energy consumption of 5G base stations (BSs) is increasing significantly, which not only raises the operating expenses of telecom operators but also imposes a burden on the environment. To solve this problem, a two-step energy management method that coordinates 5G macro BSs for 5G networks with user clustering is proposed. The coordination among the communication equipment and the standard equipment in 5G macro BSs is developed to reduce both the energy consumption and the electricity costs. A novel user clustering method is proposed together with Benders decomposition to accelerate the solving process. Simulation results show that the proposed method is computationally efficient and can ensure near-optimal performance, effectively reducing the energy consumption and electricity costs compared with the conventional dispatching scheme.
Highlights
Fifth generation mobile communications technology (5G) is meant to deliver higher peak data speeds, ultra-low latency, increased reliability, massive network capacity, increased availability, and a more uniform experience to an increased number of users
The increase in the power consumption of 5G macro base stations (BSs) networks will directly lead to an increase in the operating expense (OPEX) of telecom operators
To tackle the aforementioned challenges, this study proposes a dispatching scheme for a 5G macro BS network incorporating the optimal scheduling of standard equipment in the BSs
Summary
Fifth generation mobile communications technology (5G) is meant to deliver higher peak data speeds, ultra-low latency, increased reliability, massive network capacity, increased availability, and a more uniform experience to an increased number of users. HEST is proposed to improve the energy efficiency of 5G BSs with hardware designs, power source modification, and network architecture upgrades. SEST is dedicated to the improvement of the operation strategy of communication equipment, optimizing the resource allocation and shutting down redundant hardware by taking advantage of the distribution characteristics of traffic loads to realize the energy reduction of the 5G network [2]. Simulation results show that the proposed algorithm significantly increases energy savings [18] Power allocation is another promising SEST used to reduce the energy consumption of 5G networks by allocating power resources to different users while meeting the users’ quality of service (QoS) [19]. (1) A two-step energy management model for both communication equipment and standard equipment in the 5G macro BS network is proposed to reduce further the energy consumption and electricity costs.
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