Hybrid radio resource allocation and interference coordination for type 1a-relayed long term evolution uplink

2014 ◽  
Vol 8 (11) ◽  
pp. 1928-1937 ◽  
Author(s):  
Irfan Ahmed ◽  
Amr Mohamed
Keyword(s):  
Resource Allocation ◽  
Long Term Evolution ◽  
Interference Coordination ◽  
Radio Resource Allocation ◽  
Radio Resource ◽  
Term Evolution

Survey on radio resource allocation in long‐term evolution‐vehicle

2021 ◽  
Author(s):  
Mariem Allouch ◽  
Sondes Kallel ◽  
Ahmed Soua ◽  
Oyunchimeg Shagdar ◽  
Samir Tohme
Keyword(s):  
Resource Allocation ◽  
Long Term Evolution ◽  
Radio Resource Allocation ◽  
Radio Resource ◽  
Term Evolution

scholarly journals COMPARATIVE ANALYSIS OF THE PERFORMANCE OF RESOURCE ALLOCATION ALGORITHMS IN LONG TERM EVOLUTION NETWORKS

2016 ◽  
Vol 36 (1) ◽  
pp. 163-171
Author(s):  
UN Nwawelu ◽  
CI Ani ◽  
MA Ahaneku
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Long Term Evolution ◽  
Proportional Fair ◽  
Term Evolution ◽  
Allocation Algorithms ◽  
Resource Allocation Schemes ◽  
Radio Resource Scheduling ◽  
Good Number

The growth in the good number of real-time and non-real-time applications has sparked a renewed interest in exploring resource allocation schemes that can be efficient and fair to all the applications in overloaded scenarios. In this paper, the performance of six scheduling algorithms for Long Term Evolution (LTE) downlink networks were analyzed and compared. These algorithms are Proportional Fair (PF), Exponential/Proportional Fair (EXP/PF), Maximum Largest Weighted Delay First (MLWDF), Frame Level Scheduler (FLS), Exponential (EXP) rule and Logarithmic (LOG) rule.  The performances of these algorithms were evaluated using an open source simulator (LTE simulator) and compared based on network parameters which include: throughput, delay, Packet Loss Ratio (PLR), and fairness. This work aims at giving insight on the gains made on radio resource scheduling for LTE network and to x-ray the issues that require improvement in order to provide better performance to the users. The results of this work show that FLS algorithm outperforms other algorithms in terms of delay, PLR, throughput, and fairness for VoIP and video flow. It was also observed that for Best Effort (BE) flows, FLS outperforms other algorithms in terms of delay and PLR but performed least in terms of throughput and fairness. http://dx.doi.org/10.4314/njt.v36i1.21

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