Distributed Cloud Association in Downlink Multicloud Radio Access Networks

TL;DR

This paper addresses user-to-cloud assignment in multicloud radio access networks, proposing distributed and centralized algorithms that improve network utility while respecting connectivity constraints.

Contribution

It introduces an auction-based distributed algorithm and a low-complexity heuristic for user-cloud assignment in M-CRANs, enhancing performance over traditional methods.

Findings

Distributed algorithm achieves near-optimal utility.

Heuristic algorithm reduces computational complexity.

Significant performance gains over conventional solutions.

Abstract

This paper considers a multicloud radio access network (M-CRAN), wherein each cloud serves a cluster of base-stations (BS's) which are connected to the clouds through high capacity digital links. The network comprises several remote users, where each user can be connected to one (and only one) cloud. This paper studies the user-to-cloud-assignment problem by maximizing a network-wide utility subject to practical cloud connectivity constraints. The paper solves the problem by using an auction-based iterative algorithm, which can be implemented in a distributed fashion through a reasonable exchange of information between the clouds. The paper further proposes a centralized heuristic algorithm, with low computational complexity. Simulations results show that the proposed algorithms provide appreciable performance improvements as compared to the conventional cloud-less assignment solutions.