Joint Optimization on Resource Allocation with Reinforcement Learning based Intercell Interference Coordination Cancellation in Heterogeneous Networks


Authors : P. Madhu; V. Sujatha

Volume/Issue : Volume 5 - 2020, Issue 12 - December

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/2KMZDtY

The most difficult challenge in femtocells networks is the alleviation of Inter-Cell Interference (ICI) that occurs between macro and femtocells during robust video transfer. Due to this issue, bandwidth utilization and system efficiency are reduced. To avoid this issue, a Joint dynamic Layer, Channel and Power assignment with Further enhanced ICI Coordination and Coordinated Multipoint Transmission (JLCP-FeICICCMT) method has been suggested for two-tier HetNets that allocates both resources and User Equipments (UEs) in each eNodeBs (eNBs) for increasing the network performance. However, it partitions the bandwidth among UEs within each cell which dissipates the bandwidth while Resource Blocks (RBs) are utilized only by few UEs. Therefore, in this article, a Reinforcementbased Interference Coordination Cancellation method is proposed with the JLCP-FeICIC-CMT method, known as JLCP-RICC-CMT. In this proposed method, the bandwidth partition is not required. The total bandwidth is distributed among UEs who are independent of their locations related to the eNB within serving cell formulates the Resource Allocation (RA) as an optimization problem. Initially, JLCP is performed by using Genetic Algorithm (GA) as a Policy Search-based Reinforcement (PSR). Then, RICC scheme is performed to allow UEs in neighbor cells to be assigned the same RBs and increase the system efficiency. Finally, the experimental results exhibit that the efficiency of the JLCP-RICC-CMT method compared to the JLCP-FeICIC-CMT method.

Keywords : Femtocells Network; Hetnets, JLCP-FeicicCMT; Resource Allocation; Genetic Algorithm; Policy Space Search Reinforcement

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