Cluster Based Resource Allocation for CoMP MU-MIMO 5G Network

Abstract

Massive MIMO (multiple-input multiple considered as an heir of the multi technology and it has recently gained lots of attention from both academia and industry. In 5G environment, more users using the network at the same tim is used for MU-MIMO beamforming environment to provide network from BS. The transmit power, pilot training, and spatial transmission resources need to be allocated properly to the users to achieve the highest possible performance. This is called re allocation and can be formulated as design utility optimization problems. Identifying non clusters is an important issue in clustering referred to as Overlapping Clustering. While traditional clustering methods ignore the possibility that a observation can be assigned to several groups and lead to k exhaustive and exclusive clusters representing the data, Overlapping Clustering methods offer a richer model for fitting existing structures in several applications requiring a non disjoint partitioning. In this Thesis Develop Proper Clustering algorithm for CoMP network based on location and traffic load using Similarity Clustering and Model-based Overlapping Clustering. The Simulation results analysis the performance of K Means and Hierarchical Clustering.