40 research outputs found
Spectrum Occupancy Measurement: An Autocorrelation based Scanning Technique using USRP
This paper presents a technique for scanning and evaluating the radio
spectrum use. This technique determines the average occupancy of a channel over
a specific duration. The technique was implemented using Software Defined Radio
units and GNU Radio software. The survey was conducted in Grand Forks, North
Dakota, over a frequency range of 824 MHz to 5.8 GHz. The results of this
technique were compared to those of two existing techniques, energy detection
and autocorrelation, that were also implemented. The results show that the
proposed technique is more efficient at scanning the radio spectrum than the
other two techniques.Comment: 5 pages, IEEE Wireless and Microwave Technology Conference (WAMICON),
201
A Bayesian Network Model of the Bit Error Rate for Cognitive Radio Networks
In addition to serve as platforms for dynamic spectrum access, cognitive
radios can also serve as a method for improving the performance of wireless
communication systems by smartly adjusting their operating parameters according
to the environment and requirements. The uncertainty always present in the
environment makes the practical implementation of the latter application
difficult. In this paper, we propose a probabilistic graphical model, Bayesian
network that captures the causal relationships among the variables bit energy
to noise spectral density ratio (EbN0), carrier to interference ratio (C/I),
modulation scheme (MOD), Doppler phase shift (Dop_Phi), and bit error rate
(BER). BER indicates how the communication link is performing. The goal of our
proposed Bayesian network is to use the BER as evidence in order to infer the
behavior of the other variables, so the cognitive radio can learn how the
conditions of the environment are, and based on that knowledge make better
informed decisions. This model along with the method used to build it are
described in this paper.Comment: 4 pages, IEEE Wireless and Microwave Technology Conference (WAMICON),
201
Noise Cancellation in Cognitive Radio Systems: A Performance Comparison of Evolutionary Algorithms
Noise cancellation is one of the important signal processing functions of any
communication system, as noise affects data integrity. In existing systems,
traditional filters are used to cancel the noise from the received signals.
These filters use fixed hardware which is capable of filtering specific
frequency or a range of frequencies. However, next generation communication
technologies, such as cognitive radio, will require the use of adaptive filters
that can dynamically reconfigure their filtering parameters for any frequency.
To this end, a few noise cancellation techniques have been proposed, including
least mean squares (LMS) and its variants. However, these algorithms are
susceptible to non-linear noise and fail to locate the global optimum solution
for de-noising. In this paper, we investigate the efficiency of two global
search optimization based algorithms, genetic algorithm and particle swarm
optimization in performing noise cancellation in cognitive radio systems. These
algorithms are implemented and their performances are compared to that of LMS
using bit error rate and mean square error as performance evaluation metrics.
Simulations are performed with additive white Gaussian noise and random
nonlinear noise. Results indicate that GA and PSO perform better than LMS for
the case of AWGN corrupted signal but for non-linear random noise PSO
outperforms the other two algorithms
Primary User Emulation Attacks: A Detection Technique Based on Kalman Filter
Cognitive radio technology addresses the problem of spectrum scarcity by
allowing secondary users to use the vacant spectrum bands without causing
interference to the primary users. However, several attacks could disturb the
normal functioning of the cognitive radio network. Primary user emulation
attacks are one of the most severe attacks in which a malicious user emulates
the primary user signal characteristics to either prevent other legitimate
secondary users from accessing the idle channels or causing harmful
interference to the primary users. There are several proposed approaches to
detect the primary user emulation attackers. However, most of these techniques
assume that the primary user location is fixed, which does not make them valid
when the primary user is mobile. In this paper, we propose a new approach based
on the Kalman filter framework for detecting the primary user emulation attacks
with a non-stationary primary user. Several experiments have been conducted and
the advantages of the proposed approach are demonstrated through the simulation
results.Comment: 14 pages, 9 figure