TY - JOUR
T1 - User Association and Small Base Station Configuration for Energy-Efficiency Maximization in Hybrid-Energy Heterogeneous Cellular Networks
AU - Ni, Weiyi
AU - Xiao, Hailin
AU - Zhou, Meng
AU - Theodore Chronopoulos, Anthony
AU - Zhang, Zhongshan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2025
Y1 - 2025
N2 - Dense deployment of small base stations (SBSs) within the coverage of macro base station (MBS) has been spotlighted as a promising solution to conserve grid energy in hybrid-energy heterogeneous cellular networks (HCNs), which caters to the rapidly increasing demand of mobile user (MU). However, MUs in the ultradense cellular network experience handover events more frequently than in conventional networks, which results in increased service interruption time and performance degradation due to blockages. In addition, blindly increasing the number of SBSs not only results in an increased cost for network operators but also brings serious system energy consumption and interference. In this article, we propose a joint user association and SBSs configuration scheme for maximizing energy efficiency (EE) in hybrid-energy HCNs. Specially, an association model with dual connectivity for MUs where they are connected simultaneously with SBSs and MBSs is first proposed to reduce frequent handover, which is also presented to preferentially select SBSs that can provide data transmission for MUs under the user association constraints according to the maximum system EE. And then the ratio between the number of SBSs and the number of MUs for SBSs configuration is analyzed to reduce interference and energy consumption under the tidal effect of HCNs. Furthermore, the EE utility function of joint user association and SBSs configuration is extended, and the Dinkelbach and Lagrangian algorithms are jointly optimized to solve the EE utility function. Finally, numerical simulation results are provided to demonstrate the feasibility of the proposed scheme. It is shown that the proposed scheme outperforms other schemes and can also maximize the EE in hybrid-energy HCNs.
AB - Dense deployment of small base stations (SBSs) within the coverage of macro base station (MBS) has been spotlighted as a promising solution to conserve grid energy in hybrid-energy heterogeneous cellular networks (HCNs), which caters to the rapidly increasing demand of mobile user (MU). However, MUs in the ultradense cellular network experience handover events more frequently than in conventional networks, which results in increased service interruption time and performance degradation due to blockages. In addition, blindly increasing the number of SBSs not only results in an increased cost for network operators but also brings serious system energy consumption and interference. In this article, we propose a joint user association and SBSs configuration scheme for maximizing energy efficiency (EE) in hybrid-energy HCNs. Specially, an association model with dual connectivity for MUs where they are connected simultaneously with SBSs and MBSs is first proposed to reduce frequent handover, which is also presented to preferentially select SBSs that can provide data transmission for MUs under the user association constraints according to the maximum system EE. And then the ratio between the number of SBSs and the number of MUs for SBSs configuration is analyzed to reduce interference and energy consumption under the tidal effect of HCNs. Furthermore, the EE utility function of joint user association and SBSs configuration is extended, and the Dinkelbach and Lagrangian algorithms are jointly optimized to solve the EE utility function. Finally, numerical simulation results are provided to demonstrate the feasibility of the proposed scheme. It is shown that the proposed scheme outperforms other schemes and can also maximize the EE in hybrid-energy HCNs.
KW - Energy efficiency (EE)
KW - heterogeneous cellular networks (HCNs)
KW - hybrid energy
KW - user association
UR - http://www.scopus.com/inward/record.url?scp=105002580284&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2024.3510785
DO - 10.1109/JIOT.2024.3510785
M3 - Article
AN - SCOPUS:105002580284
SN - 2327-4662
VL - 12
SP - 9858
EP - 9871
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 8
ER -