{"title":"Heuristic Energy Efficiency Optimization Scheme for Multi-hop mMTC Networks","authors":"Huan Gao, Xiaodong Xu","doi":"10.1109/PIMRC.2019.8904269","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate a heuristic energy efficiency optimization scheme for the multi-hop massive machine-type communication (mMTC) networks to maximize the network energy efficiency. First, we present a power selection approach based on maximum energy efficiency for one-hop communication between the devices. Second, we obtain the energy efficiency objective function for all the devices with respect to the resource allocation and the path of multi-hop relay. Considering the complexity of the objective function, we propose a resource allocation scheme based on the genetic algorithm to solve the optimization problem. To evaluate the performance of our algorithm, simulations are conducted to compare its performance with the random resource allocation scheme. Results show that the proposed algorithm effectively improves the network energy efficiency.","PeriodicalId":412182,"journal":{"name":"2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIMRC.2019.8904269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we investigate a heuristic energy efficiency optimization scheme for the multi-hop massive machine-type communication (mMTC) networks to maximize the network energy efficiency. First, we present a power selection approach based on maximum energy efficiency for one-hop communication between the devices. Second, we obtain the energy efficiency objective function for all the devices with respect to the resource allocation and the path of multi-hop relay. Considering the complexity of the objective function, we propose a resource allocation scheme based on the genetic algorithm to solve the optimization problem. To evaluate the performance of our algorithm, simulations are conducted to compare its performance with the random resource allocation scheme. Results show that the proposed algorithm effectively improves the network energy efficiency.