DefinePK

DefinePK hosts the largest index of Pakistani journals, research articles, news headlines, and videos. It also offers chapter-level book search.

Comparison analysis of exponential rule and maximum throughput algorithms for uplink channel scheduling on long term evolution (LTE) network


Article Information

Title: Comparison analysis of exponential rule and maximum throughput algorithms for uplink channel scheduling on long term evolution (LTE) network

Authors: Endah Budi Purnomowati, Rudy Yuwono, Nadia Sinaga, Yola Yuliatri Mangera Putri, Aisah, Azizurrahman Rafli, Rusmi Ambarwati

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2020

Volume: 15

Issue: 5

Language: English

Categories

Abstract

Scheduling is a setting process on a system for better service. One of the system that uses scheduling is the Long Term Evolution (LTE) network. Scheduling on Long Term Evolution is used for allocating radio resource to serve users at a certain frequency and time. One of the methods that can be used is by using channel scheduling algorithm for uplink LTE direction. Exponential rule algorithm has the advantage of being able to support a fair system fairness index, but unable to maximize throughput user. On the other side, maximum throughput algorithm is able to maximize user throughput with the best channel condition, but has disadvantage on the fairness index side. This study will analyze the comparison between exponential rule and maximum throughput for LTE network uplink channel scheduling based on throughput user and system fairness index. This study uses 4 scenarios with variations in the distance of 1-4 km and variations in the number of users 4, 8, 12, and 16 in 2 track conditions, namely LOS (Line of Sight) and NLOS (Non-Line of Sight).


Paper summary is not available for this article yet.

Loading PDF...

Loading Statistics...