TY - GEN
T1 - Experimental Analysis of Handover Process in Cell-Free Networks
AU - Jeong, Bomi
AU - Lee, Sungwon
AU - Siddiqa, Ayesha
AU - Ajmal, Mahnoor
AU - Seo, Junho
AU - Kim, Dongkyun
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/8/6
Y1 - 2023/8/6
N2 - With the emergence of services that require a high level of data usage, wireless networks are required to support higher data rates and greater capacity. To satisfy these requests, 5G architecture supports a high-frequency band. However, a high frequency occurs small range resulting in a need for numerous base stations (BSs). Deploying numerous BSs can be considered practically impossible due to high costs. To address the cost issue, instead of BSs, access points (APs) are used in Cell-free networks. That is, Cell-free networks that offer promising coverage gain and enhanced data rates consist of multiple APs and a single central process unit (CPU). This coverage of multiple APs' is much smaller than BS's. As a result, this small coverage can lead to frequent handovers. To overcome this frequent handover, an optimized handover scheme for the Cell-free network is required. Despite this optimization requirement, many studies in the Cell-free network field remain at the physical layer stage. No basic handover process is optimized for Cell-free networks, and no protocol for upper layers is defined. We consider that existing technologies will continue to be used in Cell-free networks, even if the protocols optimized for Cellfree networks are developed and used. For these reasons, we construct a Cell-free network architecture similar to the 5G structure for the handover process. In this paper, we investigate the handover process in 5G architecture and extend it to a Cellfree network environment. In our simulations, APs initiate and perform the handover process based on measurement reports from users. We analyzed and discussed the performance matrices of the handover in a Cell-free network environment, such as handover delay and throughput.
AB - With the emergence of services that require a high level of data usage, wireless networks are required to support higher data rates and greater capacity. To satisfy these requests, 5G architecture supports a high-frequency band. However, a high frequency occurs small range resulting in a need for numerous base stations (BSs). Deploying numerous BSs can be considered practically impossible due to high costs. To address the cost issue, instead of BSs, access points (APs) are used in Cell-free networks. That is, Cell-free networks that offer promising coverage gain and enhanced data rates consist of multiple APs and a single central process unit (CPU). This coverage of multiple APs' is much smaller than BS's. As a result, this small coverage can lead to frequent handovers. To overcome this frequent handover, an optimized handover scheme for the Cell-free network is required. Despite this optimization requirement, many studies in the Cell-free network field remain at the physical layer stage. No basic handover process is optimized for Cell-free networks, and no protocol for upper layers is defined. We consider that existing technologies will continue to be used in Cell-free networks, even if the protocols optimized for Cellfree networks are developed and used. For these reasons, we construct a Cell-free network architecture similar to the 5G structure for the handover process. In this paper, we investigate the handover process in 5G architecture and extend it to a Cellfree network environment. In our simulations, APs initiate and perform the handover process based on measurement reports from users. We analyzed and discussed the performance matrices of the handover in a Cell-free network environment, such as handover delay and throughput.
KW - 5G networks
KW - Cell-free networks
KW - Handover
UR - https://www.scopus.com/pages/publications/85174227874
U2 - 10.1145/3599957.3606221
DO - 10.1145/3599957.3606221
M3 - Conference contribution
AN - SCOPUS:85174227874
T3 - 2023 Research in Adaptive and Convergent Systems RACS 2023
BT - 2023 Research in Adaptive and Convergent Systems RACS 2023
PB - Association for Computing Machinery, Inc
T2 - 2023 Research in Adaptive and Convergent Systems, RACS 2023
Y2 - 6 August 2023 through 10 August 2023
ER -