6 research outputs found
Matching Theory for Backhaul Management in Small Cell Networks with mmWave Capabilities
Designing cost-effective and scalable backhaul solutions is one of the main
challenges for emerging wireless small cell networks (SCNs). In this regard,
millimeter wave (mmW) communication technologies have recently emerged as an
attractive solution to realize the vision of a high-speed and reliable wireless
small cell backhaul network (SCBN). In this paper, a novel approach is proposed
for managing the spectral resources of a heterogeneous SCBN that can exploit
simultaneously mmW and conventional frequency bands via carrier aggregation. In
particular, a new SCBN model is proposed in which small cell base stations
(SCBSs) equipped with broadband fiber backhaul allocate their frequency
resources to SCBSs with wireless backhaul, by using aggregated bands. One
unique feature of the studied model is that it jointly accounts for both
wireless channel characteristics and economic factors during resource
allocation. The problem is then formulated as a one-to-many matching game and a
distributed algorithm is proposed to find a stable outcome of the game. The
convergence of the algorithm is proven and the properties of the resulting
matching are studied. Simulation results show that under the constraints of
wireless backhauling, the proposed approach achieves substantial performance
gains, reaching up to compared to a conventional best-effort approach.Comment: In Proc. of the IEEE International Conference on Communications
(ICC), Mobile and Wireless Networks Symposium, London, UK, June 201
The 5G Cellular Backhaul Management Dilemma: To Cache or to Serve
With the introduction of caching capabilities into small cell networks
(SCNs), new backaul management mechanisms need to be developed to prevent the
predicted files that are downloaded by the at the small base stations (SBSs) to
be cached from jeopardizing the urgent requests that need to be served via the
backhaul. Moreover, these mechanisms must account for the heterogeneity of the
backhaul that will be encompassing both wireless backhaul links at various
frequency bands and a wired backhaul component. In this paper, the
heterogeneous backhaul management problem is formulated as a minority game in
which each SBS has to define the number of predicted files to download, without
affecting the required transmission rate of the current requests. For the
formulated game, it is shown that a unique fair proper mixed Nash equilibrium
(PMNE) exists. Self-organizing reinforcement learning algorithm is proposed and
proved to converge to a unique Boltzmann-Gibbs equilibrium which approximates
the desired PMNE. Simulation results show that the performance of the proposed
approach can be close to that of the ideal optimal algorithm while it
outperforms a centralized greedy approach in terms of the amount of data that
is cached without jeopardizing the quality-of-service of current requests.Comment: Accepted for publication at Transactions on Wireless Communication