Energy efficient deployment solutions in high density heterogeneous networks

TL;DR

This paper addresses energy-efficient transmit power optimization in high density heterogeneous networks, proposing iterative algorithms to reduce power consumption while maintaining user quality of service.

Contribution

The paper introduces new iterative algorithms for non-convex power optimization in heterogeneous networks and evaluates their convergence and complexity.

Findings

Algorithms converge effectively in simulations

Proposed methods outperform current technologies

Energy efficiency is significantly improved

Abstract

This study deals with the problem of optimizing transmit power in high density heterogeneous networks. In the communication network, effective methods of allocating transmit power, in order to reduce the total transmit power, but still ensure the quality of service of the user equipment, is a big challenge. number of power consumption optimization problems in core station links, with the goal of maximizing network energy efficiency while ensuring user experience. To solve this non-convex optimization problem, the authors first propose some iterative algorithms to find the convergence point such as the "descent" method, the "Lagrange" method. Then, the authors evaluate the convergence point of each method as well as consider the complexity of each algorithm when put into application. Finally, the simulation results will show the convergence value and compare the performance with the technologies being used today to confirm the effectiveness of the proposed algorithm.