86,703 research outputs found
Wireless Network Stability in the SINR Model
We study the stability of wireless networks under stochastic arrival
processes of packets, and design efficient, distributed algorithms that achieve
stability in the SINR (Signal to Interference and Noise Ratio) interference
model.
Specifically, we make the following contributions. We give a distributed
algorithm that achieves -efficiency on all networks
(where is the number of links in the network), for all length monotone,
sub-linear power assignments. For the power control version of the problem, we
give a distributed algorithm with -efficiency (where is the length diversity of the link set).Comment: 10 pages, appeared in SIROCCO'1
Towards the Optimal Amplify-and-Forward Cooperative Diversity Scheme
In a slow fading channel, how to find a cooperative diversity scheme that
achieves the transmit diversity bound is still an open problem. In fact, all
previously proposed amplify-and-forward (AF) and decode-and-forward (DF)
schemes do not improve with the number of relays in terms of the diversity
multiplexing tradeoff (DMT) for multiplexing gains r higher than 0.5. In this
work, we study the class of slotted amplify-and-forward (SAF) schemes. We first
establish an upper bound on the DMT for any SAF scheme with an arbitrary number
of relays N and number of slots M. Then, we propose a sequential SAF scheme
that can exploit the potential diversity gain in the high multiplexing gain
regime. More precisely, in certain conditions, the sequential SAF scheme
achieves the proposed DMT upper bound which tends to the transmit diversity
bound when M goes to infinity. In particular, for the two-relay case, the
three-slot sequential SAF scheme achieves the proposed upper bound and
outperforms the two-relay non-orthorgonal amplify-and-forward (NAF) scheme of
Azarian et al. for multiplexing gains r < 2/3. Numerical results reveal a
significant gain of our scheme over the previously proposed AF schemes,
especially in high spectral efficiency and large network size regime.Comment: 30 pages, 11 figures, submitted to IEEE trans. IT, revised versio
Wireless Broadcast with Network Coding in Mobile Ad-Hoc Networks: DRAGONCAST
Network coding is a recently proposed method for transmitting data, which has
been shown to have potential to improve wireless network performance. We study
network coding for one specific case of multicast, broadcasting, from one
source to all nodes of the network. We use network coding as a loss tolerant,
energy-efficient, method for broadcast. Our emphasis is on mobile networks. Our
contribution is the proposal of DRAGONCAST, a protocol to perform network
coding in such a dynamically evolving environment. It is based on three
building blocks: a method to permit real-time decoding of network coding, a
method to adjust the network coding transmission rates, and a method for
ensuring the termination of the broadcast. The performance and behavior of the
method are explored experimentally by simulations; they illustrate the
excellent performance of the protocol
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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