Clustering Approaches for Efficient Radio Resource Management in Heterogeneous Networks

Abstract

5G telecommunication industry promises to manage and accomplish the massive data traffic and growing network requirement complexities in heterogeneous networks (HetNets). HetNets are K-tier networks and are expected to be seamlessly connected networks with robust services for users anywhere at any time. In near future, the significance of 5G/B5G cellular networks; in both indoor and outdoor environments will be greater than before and it would add up to an exhaustive level. However, as a result of the increased density of networks, a rise in interference within these ultra-dense networks (UDN) will have an alarming impact on throughput, interference and latency. To ensure high throughput with reduced interference in UDNs a clustered architecture is required. A HetNet with clustered approach enables the network to mitigate interference effectively and achieve efficient radio resource management (RRM). In this paper, we analyzed different clustering classifications and existing clustering techniques that are used for proficient radio resource management. The centralized clustering techniques and decentralized clustering techniques are analyzed and as a result, it is assumed that improved performance can be achieved by emphasizing on hybrid clustering approaches. In addition to this, performed a thoughtful review of existing hybrid clustering techniques to achieve improved throughput and mitigate interference in dense heterogeneous networks. Our analysis shows that improved radio resource management and increased throughput in HetNets is achieved by applying hybrid clustering techniques with reduced inter and intra tier interference.