Development of a Hybrid Algorithm for User Association and Resource Allocation to Improve Load Balancing and Energy Efficiency in 5G HetNet
Keywords:Optimization, User association, Bandwidth allocation, Power control, HetNet, mmWave, Massive MIMO, Hybrid beamforming.
This paper presents the development and integration of a power control algorithm into the User Association Algorithm with Optimal Bandwidth Allocation (UAAOBA) to form a Hybrid Algorithm for User Association and Resource Allocation (HAUARA). The power control algorithm updates the transmit power of the Base Stations (BSs) towards a minimum transmit power that satisfies the minimum data rate requirement (1 Gbps) of the User Equipment UEs. The power update is achieved using the Newton Rhapsonâ€™s method and it adapts the transmit powers of the BSs to the number of their connected UEs. The developed HAUARA provides an optimal solution for user associations, bandwidth allocation, and transmit powers to UEs concurrently. This maximizes the network energy efficiency by coordinating the load fairness of the network while guaranteeing the quality of service requirement of the UEs. The network energy efficiency performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network energy efficiency improvement of 12.36%, 10.58%, and 13.44% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. Also, the network load balancing performance of the developed HAUARA is compared with that of the UAAOBA. The results show that the developed algorithm has network load balancing improvement of 12.62%, 10.04%, and 10.34% with respect to UAAOBA for increase number of macro BS antennas, pico BSs, and femto BSs, respectively. This implies that the developed algorithm outperforms the UAAOBA in terms of network energy efficiency and load balancing.
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