TY - JOUR
T1 - Joint user association and resource allocation in HetNets based on user mobility prediction
AU - Cheng, Zhipeng
AU - Chen, Ning
AU - Liu, Bang
AU - Gao, Zhibin
AU - Huang, Lianfen
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/8/4
Y1 - 2020/8/4
N2 - Virtual small cell (VSC) formed by directional beams is seen as an alternative for the small base station (SBS) within the coverage of macro base station (MBS), to increase system capacity and reduce site cost. However, the flexibility of development for VSC poses challenges to user association and resource allocation in heterogeneous networks. In this paper, we consider the joint problem of user association and resource allocation in VSC aided multi-tier heterogeneous networks. To better analyze the formation of VSC and the impact of user mobility on the system, a user mobility prediction model is firstly constructed based on the Markov model. Then the joint user association and resource allocation problem is formulated to maximize the system capacity. Since the aforementioned problem is a coupling problem, two different solutions, namely, a decoupling solution and a coupling solution, are proposed based on the multi-agent Q-learning (MAQL) method, to find the optimal user association and resource allocation strategy. Moreover, to overcome the state and action space explosion in MAQL and accelerate convergence, the deep Q-network (DQN) is applied. Simulation results reveal that the deployment of VSC can increase the system capacity and spectrum efficiency. The coupling solution achieves better performance than the decoupling solution under a large number of users.
AB - Virtual small cell (VSC) formed by directional beams is seen as an alternative for the small base station (SBS) within the coverage of macro base station (MBS), to increase system capacity and reduce site cost. However, the flexibility of development for VSC poses challenges to user association and resource allocation in heterogeneous networks. In this paper, we consider the joint problem of user association and resource allocation in VSC aided multi-tier heterogeneous networks. To better analyze the formation of VSC and the impact of user mobility on the system, a user mobility prediction model is firstly constructed based on the Markov model. Then the joint user association and resource allocation problem is formulated to maximize the system capacity. Since the aforementioned problem is a coupling problem, two different solutions, namely, a decoupling solution and a coupling solution, are proposed based on the multi-agent Q-learning (MAQL) method, to find the optimal user association and resource allocation strategy. Moreover, to overcome the state and action space explosion in MAQL and accelerate convergence, the deep Q-network (DQN) is applied. Simulation results reveal that the deployment of VSC can increase the system capacity and spectrum efficiency. The coupling solution achieves better performance than the decoupling solution under a large number of users.
KW - Deep Q-network
KW - Heterogeneous networks
KW - Multi-agent Q-learning
KW - Resource allocation
KW - User association
KW - User mobility prediction
KW - Virtual small cell
UR - http://www.scopus.com/inward/record.url?scp=85085547223&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85085547223&partnerID=8YFLogxK
U2 - 10.1016/j.comnet.2020.107312
DO - 10.1016/j.comnet.2020.107312
M3 - Article
AN - SCOPUS:85085547223
SN - 1389-1286
VL - 177
JO - Computer Networks
JF - Computer Networks
M1 - 107312
ER -