{"title":"Optimal Resource Allocation in Two Tier Heterogeneous Network Through Network Slicing","authors":"S. Debnath, D. Sen, W. Arif","doi":"10.1109/ACTS53447.2021.9708385","DOIUrl":null,"url":null,"abstract":"Scare spectrum resources of the wireless networks have to be used efficiently for network utility maximization. The allocation of resources to different services based on the differentiated quality of service (QoS) can be done with dynamic resource slicing (DRS) paradigm. DRS is very efficient in providing adequate QoS to the associated user of the network. In the two-tier heterogeneous network, considering the DRS framework, optimal allocation of radio resources to each user and association of user to a cell is a challenging task to be performed. In this work, the allocation of resources among normal data services and machine-to-machine services under the differentiated QoS is quantified and analyzed while considering the load dynamics of the 5G communication network. Here we utilize efficient state-of-the-art optimization algorithms to analyze the network utility maximization property under the consideration of user association to the network based on geographical location and cell capacity. It is observed that the formulated PSO and SSA based algorithm is efficient in respect of network utility maximization as compare to the geographical SINR based connected user to the network.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACTS53447.2021.9708385","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
Scare spectrum resources of the wireless networks have to be used efficiently for network utility maximization. The allocation of resources to different services based on the differentiated quality of service (QoS) can be done with dynamic resource slicing (DRS) paradigm. DRS is very efficient in providing adequate QoS to the associated user of the network. In the two-tier heterogeneous network, considering the DRS framework, optimal allocation of radio resources to each user and association of user to a cell is a challenging task to be performed. In this work, the allocation of resources among normal data services and machine-to-machine services under the differentiated QoS is quantified and analyzed while considering the load dynamics of the 5G communication network. Here we utilize efficient state-of-the-art optimization algorithms to analyze the network utility maximization property under the consideration of user association to the network based on geographical location and cell capacity. It is observed that the formulated PSO and SSA based algorithm is efficient in respect of network utility maximization as compare to the geographical SINR based connected user to the network.