Modified Proportional Fair Scheduling Algorithm for Heterogeneous LTE-A Networks

Modified Proportional Fair Scheduling Algorithm for Heterogeneous LTE-A Networks

Long Term Evolution Advanced (LTE-A)

Heterogeneous network (HetNet)

QoS Scheduling Algorithms

Proportional Fair (PF)

root mean square (RMS).

Growing of time-sensitive applications such as streaming multimedia, voice over IP and online gaming required strongly support from mobile communication technology. So, the persistent need for wireless broadband technologies such as LTE-A is essential. LTE-A can achieve QoS in an efficient manner by using a reliable packet scheduling algorithm. It also supports good cell coverage by using heterogeneous capability. In this paper, modifications of proportional fair (PF) algorithm are proposed with different methods to compute the average throughput, which is the main and important parameter in the PF cost function. These methods are geometric mean, root mean square and arithmetic mean. Vienna simulator is used to study the performance of the proposed algorithms. A comparison between PF modifications and the most famous algorithms (the original PF and Best CQI algorithms) with various UE velocities is introduced. Average UE throughput, spectral efficiency, energy per bit, cell throughput and fairness are used as performance indicators. The results expose that QPF has best improved values for spectral efficiency, energy per bit and fairness by 8.4%, 14%, and 9.3%, respectively than original PF. However, Best CQI has a better value of average UE and cell throughput than all algorithms of 2% and 1.8% in low and medium UE velocity, respectively, but the best value of all types of throughput at high speed is gained by QPF. QPF and GMPF has the same performance in fairness with all UEs speeds.

Elshennawy, Nada M.

International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 10 (2020); pp. 22-34

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2020-06-30

Copyright (c) 2020 Dina M. Ibrahim

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Peer-reviewed Article