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Energy-efficient resource allocation in mobile network is of great importance in reducing the total energy consumption of the network and its operational cost to realize green communication.
Recently, we, researchers of High-Technology Institute at
In the study, the resource block allocation problem considering energy balance between downlink and uplink was solved by decomposing it into an optimization problem for allocation of bandwidth and power and a resource block allocation problem according to the allocated bandwidth and power. A mathematical model and some transformations concerning these aspects have been presented and evaluated by simulation using iteration method.
The proposed method is as follows.
Firstly, the network energy efficiency was defined as a weighted sum of uplink energy efficiency and downlink energy efficiency. The weight factors can reflect the QoS Class and the power consumption level. Moreover, we mathematically formulated the power and the bandwidth upper limit condition, the throughput lower bound condition, the unique allocation of resource block, constraint for allocation of CA, CQI index and MCS. As a result, the optimization problem to maximize the total energy efficiency of network was formulated.
In order to solve the NP-HARD optimization problem, we decomposed it into a nonlinear sum-of-ratios problem in which bandwidth and power were taken as arguments and the set of equations for resource block allocation. The obtained nonlinear sum-of-ratios problem was solved by using the new proposed transformation and the linear programming based on Laglange multipliers. The resource block allocation problem over the obtained solution was solved using a quadratic programming. It resulted in the allocation of power and bandwidth for maximizing overall energy efficiency of the network.
The results of the simulation showed that the proposed method guarantees the higher energy efficiency than that of the previous methods.
The results were published in the SCI journal "Wireless Personal Communications" under the title of " A Study on the Resource Block Allocation Method to Enhance the Total Energy Efficiency for LTE A Networks "(https://doi.org/10.1007/s11277-021-09260-y).