An Energy-Aware Protocol for Self-Organizing Heterogeneous LTE Systems

TL;DR

This paper introduces an energy-aware, distributed protocol for self-organizing heterogeneous LTE networks that enhances spectrum efficiency and reduces energy costs by considering interference, different base station capabilities, and energy consumption.

Contribution

It presents a novel distributed protocol that jointly optimizes spectrum efficiency and energy consumption in heterogeneous LTE systems, considering multiple system characteristics.

Findings

Achieves better spectrum efficiency than existing methods.

Reduces energy costs through optimized base station operation.

Requires low computational and communication overheads.

Abstract

This paper studies the problem of self-organizing heterogeneous LTE systems. We propose a model that jointly considers several important characteristics of heterogeneous LTE system, including the usage of orthogonal frequency division multiple access (OFDMA), the frequency-selective fading for each link, the interference among different links, and the different transmission capabilities of different types of base stations. We also consider the cost of energy by taking into account the power consumption, including that for wireless transmission and that for operation, of base stations and the price of energy. Based on this model, we aim to propose a distributed protocol that improves the spectrum efficiency of the system, which is measured in terms of the weighted proportional fairness among the throughputs of clients, and reduces the cost of energy. We identify that there are several important components involved in this problem. We propose distributed strategies for each of these components. Each of the proposed strategies requires small computational and communicational overheads. Moreover, the interactions between components are also considered in the proposed strategies. Hence, these strategies result in a solution that jointly considers all factors of heterogeneous LTE systems. Simulation results also show that our proposed strategies achieve much better performance than existing ones.