15,256 research outputs found
Primary Channel Gain Estimation for Spectrum Sharing in Cognitive Radio Networks
In cognitive radio networks, the channel gain between primary transceivers,
namely, primary channel gain, is crucial for a cognitive transmitter (CT) to
control the transmit power and achieve spectrum sharing. Conventionally, the
primary channel gain is estimated in the primary system and thus unavailable at
the CT. To deal with this issue, two estimators are proposed by enabling the CT
to sense primary signals. In particular, by adopting the maximum likelihood
(ML) criterion to analyze the received primary signals, a ML estimator is first
developed. After demonstrating the high computational complexity of the ML
estimator, a median based (MB) estimator with proved low complexity is then
proposed. Furthermore, the estimation accuracy of the MB estimation is
theoretically characterized. By comparing the ML estimator and the MB estimator
from the aspects of the computational complexity as well as the estimation
accuracy, both advantages and disadvantages of two estimators are revealed.
Numerical results show that the estimation errors of the ML estimator and the
MB estimator can be as small as dB and dB, respectively.Comment: Submitted to IEEE Transactions on Communication
Phase resetting reveals network dynamics underlying a bacterial cell cycle
Genomic and proteomic methods yield networks of biological regulatory
interactions but do not provide direct insight into how those interactions are
organized into functional modules, or how information flows from one module to
another. In this work we introduce an approach that provides this complementary
information and apply it to the bacterium Caulobacter crescentus, a paradigm
for cell-cycle control. Operationally, we use an inducible promoter to express
the essential transcriptional regulatory gene ctrA in a periodic, pulsed
fashion. This chemical perturbation causes the population of cells to divide
synchronously, and we use the resulting advance or delay of the division times
of single cells to construct a phase resetting curve. We find that delay is
strongly favored over advance. This finding is surprising since it does not
follow from the temporal expression profile of CtrA and, in turn, simulations
of existing network models. We propose a phenomenological model that suggests
that the cell-cycle network comprises two distinct functional modules that
oscillate autonomously and couple in a highly asymmetric fashion. These
features collectively provide a new mechanism for tight temporal control of the
cell cycle in C. crescentus. We discuss how the procedure can serve as the
basis for a general approach for probing network dynamics, which we term
chemical perturbation spectroscopy (CPS)
H
This paper discusses Hβ control problems of continuous-time and discrete-time singular Markovian jump systems (SMJSs) with bounded transition probabilities. Improved sufficient conditions for continuous-time SMJSs to be regular, impulse free, and stochastically stable with Ξ³-disturbance attenuation are established via less conservative inequality to estimate the transition jump rates, so are the discrete-time SMJSs. With the obtained conditions, the design of a state feedback controller which ensures the resulting closed-loop system to be stochastically admissible and with Hβ performance is given in terms of linear matrix inequalities (LMIs). Finally, illustrative examples are presented to show the effectiveness and the benefits of the proposed approaches
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