The Flows VI. CONCLUSION This paper has studied

The packet loss
ratios (PLR) experienced by all flows are demonstrated in Figure 11-13. The PLR
of VoIP flows for RR algorithm is significantly lower than the video flows and
it is constant as the number of users increases as illustrated in figure 11.
The main reason behind this is that VoIP is delivering lower source bit rate as
compared to video flows. In the case of video service, as in figure 12, the
performance of the RR algorithm increases as the number of users increases and
relatively similar for both rural and urban areas. On the other hand, the FME
algorithm has the highest PLR for both rural and urban areas. This is probably due to higher network load. RR
algorithm has achieved the lowest PLR for video and VoIP by sacrificing the
available resources for BE flows as illustrated in figure 13 in both rural and
urban areas. Moreover, lower value of the target delay implies a higher value
of PLR due to a larger quota of packets violating the deadline, which is
observed for the video flows

 

Figure
11: PLR for VoIP Flows

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Figure
12: PLR for Video Flows

Figure
13: PLR for BE Flows

 

VI.  CONCLUSION

 

This
paper has studied the performance of two different scheduling algorithms and
the effect of different path loss for real-time and best effort services using the
LTE-SIM simulator. The study compares the performance of two scheduling
algorithms, namely the FME and RR for the performance metrics of throughput,
packet delay, PLR, and fairness. The best effort, video and VoIP traffic are
delivered by each UE in the urban and rural environments, which is moving at 3
km/h. For RT Traffic, FME has the highest packet loss ratio value and the
lowest throughput. Therefore, these algorithms may be a good solution for
non-real-time flows but are unsuitable to handle the RT multimedia services. RR
algorithm reaches the lowest PLR among all those strategies and is the most
suitable for VoIP flows and video flows. This study shows the importance of a
good scheduling strategy in a network base station for urban and rural areas.
The environment of high buildings and mountains landscape must be taken into
consideration when selecting the right schedulers. Future work will focus on
the development of the new algorithm, taking into account of the different
level of fairness among users as well as the quality of services policies that are
suitable for real-time and non real-time traffic for both urban and rural
environments.