5,116 research outputs found
Stability and Distributed Power Control in MANETs with Outages and Retransmissions
In the current work the effects of hop-by-hop packet loss and retransmissions
via ARQ protocols are investigated within a Mobile Ad-hoc NET-work (MANET).
Errors occur due to outages and a success probability function is related to
each link, which can be controlled by power and rate allocation. We first
derive the expression for the network's capacity region, where the success
function plays a critical role. Properties of the latter as well as the related
maximum goodput function are presented and proved. A Network Utility
Maximization problem (NUM) with stability constraints is further formulated
which decomposes into (a) the input rate control problem and (b) the scheduling
problem. Under certain assumptions problem (b) is relaxed to a weighted sum
maximization problem with number of summants equal to the number of nodes. This
further allows the formulation of a non-cooperative game where each node
decides independently over its transmitting power through a chosen link. Use of
supermodular game theory suggests a price based algorithm that converges to a
power allocation satisfying the necessary optimality conditions of (b).
Implementation issues are considered so that minimum information exchange
between interfering nodes is required. Simulations illustrate that the
suggested algorithm brings near optimal results.Comment: 25 pages, 6 figures, 1 table, submitted to the IEEE Trans. on
Communication
Utility Optimal Scheduling and Admission Control for Adaptive Video Streaming in Small Cell Networks
We consider the jointly optimal design of a transmission scheduling and
admission control policy for adaptive video streaming over small cell networks.
We formulate the problem as a dynamic network utility maximization and observe
that it naturally decomposes into two subproblems: admission control and
transmission scheduling. The resulting algorithms are simple and suitable for
distributed implementation. The admission control decisions involve each user
choosing the quality of the video chunk asked for download, based on the
network congestion in its neighborhood. This form of admission control is
compatible with the current video streaming technology based on the DASH
protocol over TCP connections. Through simulations, we evaluate the performance
of the proposed algorithm under realistic assumptions for a small-cell network.Comment: 5 pages, 4 figures. Accepted and will be presented at IEEE
International Symposium on Information Theory (ISIT) 201
Energy-Efficient Resource Management in Ultra Dense Small Cell Networks: A Mean-Field Approach
In this paper, a novel approach for joint power control and user scheduling
is proposed for optimizing energy efficiency (EE), in terms of bits per unit
power, in ultra dense small cell networks (UDNs). To address this problem, a
dynamic stochastic game (DSG) is formulated between small cell base stations
(SBSs). This game enables to capture the dynamics of both queues and channel
states of the system. To solve this game, assuming a large homogeneous UDN
deployment, the problem is cast as a mean field game (MFG) in which the MFG
equilibrium is analyzed with the aid of two low-complexity tractable partial
differential equations. User scheduling is formulated as a stochastic
optimization problem and solved using the drift plus penalty (DPP) approach in
the framework of Lyapunov optimization. Remarkably, it is shown that by weaving
notions from Lyapunov optimization and mean field theory, the proposed solution
yields an equilibrium control policy per SBS which maximizes the network
utility while ensuring users' quality-of-service. Simulation results show that
the proposed approach achieves up to 18:1% gains in EE and 98.2% reductions in
the network's outage probability compared to a baseline model.Comment: 6 pages, 7 figures, GLOBECOM 2015 (published
Ultra Dense Small Cell Networks: Turning Density into Energy Efficiency
In this paper, a novel approach for joint power control and user scheduling
is proposed for optimizing energy efficiency (EE), in terms of bits per unit
energy, in ultra dense small cell networks (UDNs). Due to severe coupling in
interference, this problem is formulated as a dynamic stochastic game (DSG)
between small cell base stations (SBSs). This game enables to capture the
dynamics of both the queues and channel states of the system. To solve this
game, assuming a large homogeneous UDN deployment, the problem is cast as a
mean-field game (MFG) in which the MFG equilibrium is analyzed with the aid of
low-complexity tractable partial differential equations. Exploiting the
stochastic nature of the problem, user scheduling is formulated as a stochastic
optimization problem and solved using the drift plus penalty (DPP) approach in
the framework of Lyapunov optimization. Remarkably, it is shown that by weaving
notions from Lyapunov optimization and mean-field theory, the proposed solution
yields an equilibrium control policy per SBS which maximizes the network
utility while ensuring users' quality-of-service. Simulation results show that
the proposed approach achieves up to 70.7% gains in EE and 99.5% reductions in
the network's outage probabilities compared to a baseline model which focuses
on improving EE while attempting to satisfy the users' instantaneous
quality-of-service requirements.Comment: 15 pages, 21 figures (sub-figures are counted separately), IEEE
Journal on Selected Areas in Communications - Series on Green Communications
and Networking (Issue 2
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