# An Energy-Efficient Coverage Algorithm for Macrocell--Small Cell Network Systems
## 1 Introduction  
In recent years, the flow rate indices for wireless transmission in mobile networks have exhibited continuous growth. In fact, it is expected that mobile data throughput will have increased by seven-fold from 2016 to 2021, according to a forecast published by Cisco [1]. The increased utilization of mobile devices, including devices supporting data services (smartphones in particular), is primarily responsible for this ongoing growth in mobile data throughput. In this context of rapid throughput growth, one effective means of ensuring that sufficient resources are provided and that service quality is maintained on a local level is the deployment of small cell base stations (SBSs) inside the coverage area of a macrocell base station (MBS). By allowing for the efficient utilization of spectrum resources, which in turn allows for increased network capacity and is thus key to enhancing the energy efficiency of networks, the use of SBSs makes it easier for network operators to meet the requirements of network users. In other words, for operators seeking to ensure efficient transmission in the context of modern wireless network environments, it is generally understood that the utilization of a two-layer cellular network architecture (that is, small cell areas incorporated into a larger macrocell area) is key [2; 3]. The Small Cell Forum [4] predicted that the SBS market will substantially grow in the next few years, providing services to more and more mobile users. Hence, the spread of SBSs and related devices,along with associated technological growth, are expected to be ongoing. With data transmission projected to grow notably by the year 2021, and in order to achieve the vision of \"seamless connection\", \"incessantness\", and \"connection without connections\", the 3 rd Generation Partnership Project (3 GPP) organization suggested the widespread and high-density deployment of SBSs. High-density SBS deployment is considered to be a highly promising strategy to address the demand for high capacity in next-generation networks, and is also expected to be a subject of considerable interest in future research studies. Relatedly, it is essential that current research into the improvement of data transmission efficiency in such network environments via the more efficient allocation of resources be continued. One problem that research thus far has failed to effectively address, however, is that of the coverage holes that may occur in a two-layer cellular network. Coverage holes consist of specific locations or areas in which a user is not able to get an adequate signal from the wireless network. For example, in a metropolis with many irregularly distributed high buildings, signals may be obstructed by buildings, negatively affecting the quality of wireless reception. For related reasons of physical obstruction, there is typically no signal available in mountain caves, basements, or elevators. At the same time, the internet has become and will continue to be an integral element of people's lives, such that people expect ubiquitous network coverage. Indeed, whether or not a person absolutely needs to have network service at any given moment, its mere availability provides a sense of security. Thus, more in-depth investigations and discussion is required to address this ongoing problem. The present study offers a potential means of addressing the problem of coverage holes in two-layer cellular networks, via its proposal of an energy-efficient coverage algorithm for use in such systems. The goal of the proposed algorithm is minimizing the combined power consumed by the transceivers of all the BSs (that is, the SBSs and the MBS) in a system, while simultaneously guaranteeing the provision of comprehensive wireless signal coverage to users under various scenarios. The simulation results for various test scenarios indicated that the algorithm yields substantially better system performance than two conventional methods in terms of coverage, power usage, and average transmission rate.