TY - GEN
T1 - Traffic-Aware UAV Placement Strategies for Load Balancing in 5G Cellular Hotspots
AU - Mahapatra, Byomakesh
AU - Verma, Anuradha
AU - Gupta, Deepika
AU - Sharma, Pankaj K.
AU - Turuk, Ashok K.
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In the fifth-generation (5G) network, dependency on the cellular platforms increases due to an increase in the number of cellular and wireless devices. In such network, a hotspot situation arises when the user density goes beyond the threshold capacity. To reduce the load of this hotspot we have proposed a traffic-aware proactive load balancing (TPLBA) strategy. This strategy used a feedback approach to monitor and control the traffic load at the cellular base station or gNodeB. When the traffic load goes beyond a certain value, the main control unit (MCU) present at the base band unit (BBU) takes preventive actions by putting one or more number of F-RRHs at the probable hotspot. These F-RRH share the traffic load of the gNB to maintain the quality-of-service (QoS) of the cellular network. To implement the proposed strategy, we have used Tu-Vienna LTE simulator. Further, the simulation results show that the proposed TPLBA algorithm significantly improves the QoS by improving UE throughput, UE spectral efficiency, and blocking probability.
AB - In the fifth-generation (5G) network, dependency on the cellular platforms increases due to an increase in the number of cellular and wireless devices. In such network, a hotspot situation arises when the user density goes beyond the threshold capacity. To reduce the load of this hotspot we have proposed a traffic-aware proactive load balancing (TPLBA) strategy. This strategy used a feedback approach to monitor and control the traffic load at the cellular base station or gNodeB. When the traffic load goes beyond a certain value, the main control unit (MCU) present at the base band unit (BBU) takes preventive actions by putting one or more number of F-RRHs at the probable hotspot. These F-RRH share the traffic load of the gNB to maintain the quality-of-service (QoS) of the cellular network. To implement the proposed strategy, we have used Tu-Vienna LTE simulator. Further, the simulation results show that the proposed TPLBA algorithm significantly improves the QoS by improving UE throughput, UE spectral efficiency, and blocking probability.
UR - https://www.scopus.com/pages/publications/85126663250
UR - https://www.scopus.com/inward/citedby.url?scp=85126663250&partnerID=8YFLogxK
U2 - 10.1109/ACTS53447.2021.9708242
DO - 10.1109/ACTS53447.2021.9708242
M3 - Conference contribution
AN - SCOPUS:85126663250
T3 - 2021 Advanced Communication Technologies and Signal Processing, ACTS 2021
BT - 2021 Advanced Communication Technologies and Signal Processing, ACTS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 Advanced Communication Technologies and Signal Processing, ACTS 2021
Y2 - 15 December 2021 through 17 December 2021
ER -