Optimising LTE Network Performance: An ANN Model Based on Normalised Throughput Data
Keywords:
LTE network, ANN, resource allocation, normalisedAbstract
An effective design that schedules a proper resource allocation and allows
efficient use of the available radio resources is an important step in
improving the Long-Term Evolution (LTE) system performance to fulfill all
user requirements according to the Quality of Services (QoS) criteria.
However, some persisting issues affect the resource allocation in the LTE
networks, caused by poor network performance that degrades the network
fairness index, increases the average delay, and decreases data throughput,
particularly during the video flow. In this study, the researcher proposed a
novel technique using the Artificial Neural Network (ANN) model that was
based on the normalized data techniques to accurate and more reliable data
output for the LTE downlink scheduling algorithms, intending to satisfy the
LTE network specification, proposed by 3GPP. Thereafter, the researcher
compared the performance of the various proposed methods based on their
throughput. the throughput was regarded as an important factor that helped in
assessing the algorithm‟s efficiency. The simulation results indicated that the
proposed algorithm could significantly improve the scheduling throughput of
the real-time streaming compared to the popular LTE-DL algorithms.
