1,028 research outputs found
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
Green Base Station Placement for Microwave Backhaul Links
Wireless mobile backhaul networks have been proposed as a substitute in cases
in which wired alternatives are not available due to economical or geographical
reasons. In this work, we study the location problem of base stations in a
given region where mobile terminals are distributed according to a certain
probability density function and the base stations communicate through
microwave backhaul links. Using results of optimal transport theory, we provide
the optimal asymptotic distribution of base stations in the considered setting
by minimizing the total power over the whole network.Comment: Proceedings of the International Symposium on Ubiquitous Networking
(UNet'17), May 2017, Casablanca, Morocc
A Game Theoretic Analysis for Energy Efficient Heterogeneous Networks
Smooth and green future extension/scalability (e.g., from sparse to dense,
from small-area dense to large-area dense, or from normal-dense to super-dense)
is an important issue in heterogeneous networks. In this paper, we study energy
efficiency of heterogeneous networks for both sparse and dense two-tier small
cell deployments. We formulate the problem as a hierarchical (Stackelberg) game
in which the macro cell is the leader whereas the small cell is the follower.
Both players want to strategically decide on their power allocation policies in
order to maximize the energy efficiency of their registered users. A backward
induction method has been used to obtain a closed-form expression of the
Stackelberg equilibrium. It is shown that the energy efficiency is maximized
when only one sub-band is exploited for the players of the game depending on
their fading channel gains. Simulation results are presented to show the
effectiveness of the proposed scheme.Comment: 7 pages, 3 figures, in Wiopt 201
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