Applying Distributed Constraint Optimization Approach to the User Association Problem in Heterogeneous Networks

Abstract

User association has emerged as a distributed resource allocation problem in the heterogeneous networks (HetNets). Although an approximate solution is obtainable using the approaches like combinatorial optimization and game theory-based schemes, these techniques can be easily trapped in local optima. Furthermore, the lack of exploring the relation between the quality of the solution and the parameters in the HetNet [e.g., the number of users and base stations (BSs)], at what levels, impairs the practicability of deploying these approaches in a real world environment. To address these issues, this paper investigates how to model the problem as a distributed constraint optimization problem (DCOP) from the point of the view of the multiagent system. More specifically, we develop two models named each connection as variable (ECAV) and each BS and user as variable (EBUAV). Hereinafter, we propose a DCOP solver which not only sets up the model in a distributed way but also enables us to efficiently obtain the solution by means of a complete DCOP algorithm based on distributed message-passing. Naturally, both theoretical analysis and simulation show that different qualitative solutions can be obtained in terms of an introduced parameter which has a close relation with the parameters in the HetNet. It is also apparent that there is 6% improvement on the throughput by the DCOP solver comparing with other counterparts when . Particularly, it demonstrates up to 18% increase in the ability to make BSs service more users when the number of users is above 200 while the available resource blocks (RBs) are limited. In addition, it appears that the distribution of RBs allocated to users by BSs is better with the variation of the volume of RBs at the macro BS.

Online Distributed User Association for Heterogeneous Radio Access Network

“…They theoretically found the circular boundaries between the devices selecting the macrocell and those selecting the picocells. However, in the game-theory-based schemes, the players (BSs or UEs) cannot act rationally all the time due to the fact that different players (e.g., BSs) always have different optimization objectives [44]. Although the user association problem for a static/offline environment has been thoroughly investigated, less attention has been given to the online user association.…”

RMB-DPOP: Refining MB-DPOP by Reducing Redundant Inferences

“…On the other hand, inference-based complete algorithms like DPOP [22] perform dynamic-programming on a pseudo-tree and only require a linear number of messages. However, the memory consumption in DPOP is exponential to the induced width [6], which makes it not applicable for the memory-limited scenarios where the optimal solution is desired [7,15]. Therefore, a number of algorithms [2,21,[23][24][25] were proposed to trade either solution quality or message number for smaller memory consumption.…”