5,737 research outputs found
Distributive Power Control Algorithm for Multicarrier Interference Network over Time-Varying Fading Channels - Tracking Performance Analysis and Optimization
Distributed power control over interference limited network has received an
increasing intensity of interest over the past few years. Distributed solutions
(like the iterative water-filling, gradient projection, etc.) have been
intensively investigated under \emph{quasi-static} channels. However, as such
distributed solutions involve iterative updating and explicit message passing,
it is unrealistic to assume that the wireless channel remains unchanged during
the iterations. Unfortunately, the behavior of those distributed solutions
under \emph{time-varying} channels is in general unknown. In this paper, we
shall investigate the distributed scaled gradient projection algorithm (DSGPA)
in a pairs multicarrier interference network under a finite-state Markov
channel (FSMC) model. We shall analyze the \emph{convergence property} as well
as \emph{tracking performance} of the proposed DSGPA. Our analysis shows that
the proposed DSGPA converges to a limit region rather than a single point under
the FSMC model. We also show that the order of growth of the tracking errors is
given by \mathcal{O}\(1 \big/ \bar{N}\), where is the \emph{average
sojourn time} of the FSMC. Based on the analysis, we shall derive the
\emph{tracking error optimal scaling matrices} via Markov decision process
modeling. We shall show that the tracking error optimal scaling matrices can be
implemented distributively at each transmitter. The numerical results show the
superior performance of the proposed DSGPA over three baseline schemes, such as
the gradient projection algorithm with a constant stepsize.Comment: To Appear on the IEEE Transaction on Signal Processin
Multiuser Switched Diversity Scheduling Schemes
Multiuser switched-diversity scheduling schemes were recently proposed in
order to overcome the heavy feedback requirements of conventional opportunistic
scheduling schemes by applying a threshold-based, distributed, and ordered
scheduling mechanism. The main idea behind these schemes is that slight
reduction in the prospected multiuser diversity gains is an acceptable
trade-off for great savings in terms of required channel-state-information
feedback messages. In this work, we characterize the achievable rate region of
multiuser switched diversity systems and compare it with the rate region of
full feedback multiuser diversity systems. We propose also a novel proportional
fair multiuser switched-based scheduling scheme and we demonstrate that it can
be optimized using a practical and distributed method to obtain the feedback
thresholds. We finally demonstrate by numerical examples that
switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the
ultimate network capacity of full feedback systems in Rayleigh fading
conditions.Comment: Accepted at IEEE Transactions on Communications, to appear 2012,
funded by NPRP grant 08-577-2-241 from QNR
Distributive Network Utility Maximization (NUM) over Time-Varying Fading Channels
Distributed network utility maximization (NUM) has received an increasing
intensity of interest over the past few years. Distributed solutions (e.g., the
primal-dual gradient method) have been intensively investigated under fading
channels. As such distributed solutions involve iterative updating and explicit
message passing, it is unrealistic to assume that the wireless channel remains
unchanged during the iterations. Unfortunately, the behavior of those
distributed solutions under time-varying channels is in general unknown. In
this paper, we shall investigate the convergence behavior and tracking errors
of the iterative primal-dual scaled gradient algorithm (PDSGA) with dynamic
scaling matrices (DSC) for solving distributive NUM problems under time-varying
fading channels. We shall also study a specific application example, namely the
multi-commodity flow control and multi-carrier power allocation problem in
multi-hop ad hoc networks. Our analysis shows that the PDSGA converges to a
limit region rather than a single point under the finite state Markov chain
(FSMC) fading channels. We also show that the order of growth of the tracking
errors is given by O(T/N), where T and N are the update interval and the
average sojourn time of the FSMC, respectively. Based on this analysis, we
derive a low complexity distributive adaptation algorithm for determining the
adaptive scaling matrices, which can be implemented distributively at each
transmitter. The numerical results show the superior performance of the
proposed dynamic scaling matrix algorithm over several baseline schemes, such
as the regular primal-dual gradient algorithm
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