Title: Applying DCOP to User Association Problem in Heterogeneous Networks with Markov Chain Based Algorithm,
Abstract: Multi-agent systems (MAS) is able to characterize the behavior of individual
agent and the interaction between agents. Thus, it motivates us to leverage the
distributed constraint optimization problem (DCOP), a framework of modeling
MAS, to solve the user association problem in heterogeneous networks (HetNets).
Two issues we have to consider when we take DCOP into the application of HetNet
including: (i) How to set up an effective model by DCOP taking account of the
negtive impact of the increment of users on the modeling process (ii) Which
kind of algorithms is more suitable to balance the time consumption and the
quality of soltuion. Aiming to overcome these issues, we firstly come up with
an ECAV-$\eta$ (Each Connection As Variable) model in which a parameter $\eta$
with an adequate assignment ($\eta=3$ in this paper) is able to control the
scale of the model. After that, a Markov chain (MC) based algorithm is proposed
on the basis of log-sum-exp function. Experimental results show that the
solution obtained by DCOP framework is better than the one obtained by the
Max-SINR algorithm. Comparing with the Lagrange dual decomposition based method
(LDD), the solution performance has been improved since there is no need to
transform original problem into a satisfied one. In addition, it is also
apparent that the DCOP based method has better robustness than LDD when the
number of users increases but the available resource at base stations are
limited.