4,390 research outputs found
Averaged Iterative Water-Filling Algorithm: Robustness and Convergence
The convergence properties of the Iterative water-filling (IWF) based
algorithms have been derived in the ideal situation where the transmitters in
the network are able to obtain the exact value of the interference plus noise
(IPN) experienced at the corresponding receivers in each iteration of the
algorithm. However, these algorithms are not robust because they diverge when
there is it time-varying estimation error of the IPN, a situation that arises
in real communication system. In this correspondence, we propose an algorithm
that possesses convergence guarantees in the presence of various forms of such
time-varying error. Moreover, we also show by simulation that in scenarios
where the interference is strong, the conventional IWF diverges while our
proposed algorithm still converges
Joint Distributed Access Point Selection and Power Allocation in Cognitive Radio Networks
Spectrum management has been identified as a crucial step towards enabling
the technology of the cognitive radio network (CRN). Most of the current works
dealing with spectrum management in the CRN focus on a single task of the
problem, e.g., spectrum sensing, spectrum decision, spectrum sharing or
spectrum mobility. In this work, we argue that for certain network
configurations, jointly performing several tasks of the spectrum management
improves the spectrum efficiency. Specifically, we study the uplink resource
management problem in a CRN where there exist multiple cognitive users (CUs)
and access points (APs), with each AP operates on a set of non-overlapping
channels. The CUs, in order to maximize their uplink transmission rates, have
to associate to a suitable AP (spectrum decision), and to share the channels
belong to this AP with other CUs (spectrum sharing). These tasks are clearly
interdependent, and the problem of how they should be carried out efficiently
and distributedly is still open in the literature.
In this work we formulate this joint spectrum decision and spectrum sharing
problem into a non-cooperative game, in which the feasible strategy of a player
contains a discrete variable and a continuous vector. The structure of the game
is hence very different from most non-cooperative spectrum management game
proposed in the literature. We provide characterization of the Nash Equilibrium
(NE) of this game, and present a set of novel algorithms that allow the CUs to
distributively and efficiently select the suitable AP and share the channels
with other CUs. Finally, we study the properties of the proposed algorithms as
well as their performance via extensive simulations.Comment: Accepted by Infocom 2011; Infocom 2011, The 30th IEEE International
Conference on Computer Communication
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