1,690 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
Aggregate Interference Modeling in Cognitive Radio Networks with Power and Contention Control
In this paper, we present an interference model for cognitive radio (CR)
networks employing power control, contention control or hybrid power/contention
control schemes. For the first case, a power control scheme is proposed to
govern the transmission power of a CR node. For the second one, a contention
control scheme at the media access control (MAC) layer, based on carrier sense
multiple access with collision avoidance (CSMA/CA), is proposed to coordinate
the operation of CR nodes with transmission requests. The probability density
functions of the interference received at a primary receiver from a CR network
are first derived numerically for these two cases. For the hybrid case, where
power and contention controls are jointly adopted by a CR node to govern its
transmission, the interference is analyzed and compared with that of the first
two schemes by simulations. Then, the interference distributions under the
first two control schemes are fitted by log-normal distributions with greatly
reduced complexity. Moreover, the effect of a hidden primary receiver on the
interference experienced at the receiver is investigated. It is demonstrated
that both power and contention controls are effective approaches to alleviate
the interference caused by CR networks. Some in-depth analysis of the impact of
key parameters on the interference of CR networks is given via numerical
studies as well.Comment: 24 pages, 8 figures, submitted to IEEE Trans. Communications in July
201
Cramer-Rao Bounds for Joint RSS/DoA-Based Primary-User Localization in Cognitive Radio Networks
Knowledge about the location of licensed primary-users (PU) could enable
several key features in cognitive radio (CR) networks including improved
spatio-temporal sensing, intelligent location-aware routing, as well as aiding
spectrum policy enforcement. In this paper we consider the achievable accuracy
of PU localization algorithms that jointly utilize received-signal-strength
(RSS) and direction-of-arrival (DoA) measurements by evaluating the Cramer-Rao
Bound (CRB). Previous works evaluate the CRB for RSS-only and DoA-only
localization algorithms separately and assume DoA estimation error variance is
a fixed constant or rather independent of RSS. We derive the CRB for joint
RSS/DoA-based PU localization algorithms based on the mathematical model of DoA
estimation error variance as a function of RSS, for a given CR placement. The
bound is compared with practical localization algorithms and the impact of
several key parameters, such as number of nodes, number of antennas and
samples, channel shadowing variance and correlation distance, on the achievable
accuracy are thoroughly analyzed and discussed. We also derive the closed-form
asymptotic CRB for uniform random CR placement, and perform theoretical and
numerical studies on the required number of CRs such that the asymptotic CRB
tightly approximates the numerical integration of the CRB for a given
placement.Comment: 20 pages, 11 figures, 1 table, submitted to IEEE Transactions on
Wireless Communication
Eigen-Inference for Energy Estimation of Multiple Sources
In this paper, a new method is introduced to blindly estimate the transmit
power of multiple signal sources in multi-antenna fading channels, when the
number of sensing devices and the number of available samples are sufficiently
large compared to the number of sources. Recent advances in the field of large
dimensional random matrix theory are used that result in a simple and
computationally efficient consistent estimator of the power of each source. A
criterion to determine the minimum number of sensors and the minimum number of
samples required to achieve source separation is then introduced. Simulations
are performed that corroborate the theoretical claims and show that the
proposed power estimator largely outperforms alternative power inference
techniques.Comment: to appear in IEEE Trans. on Information Theory, 17 pages, 13 figure
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