5,196 research outputs found
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
SPECTRUM SENSING AND COOPERATION IN COGNITIVE-OFDM BASED WIRELESS COMMUNICATIONS NETWORKS
The world has witnessed the development of many wireless systems and
applications. In addition to the large number of existing devices, such development of
new and advanced wireless systems increases rapidly the demand for more radio
spectrum. The radio spectrum is a limited natural resource; however, it has been
observed that it is not efficiently utilized. Consequently, different dynamic spectrum
access techniques have been proposed as solutions for such an inefficient use of the
spectrum. Cognitive Radio (CR) is a promising intelligent technology that can identify
the unoccupied portions of spectrum and opportunistically uses those portions with
satisfyingly high capacity and low interference to the primary users (i.e., licensed users).
The CR can be distinguished from the classical radio systems mainly by its awareness
about its surrounding radio frequency environment. The spectrum sensing task is the
main key for such awareness. Due to many advantages, Orthogonal Frequency Division
Multiplexing system (OFDM) has been proposed as a potential candidate for the CR‟s
physical layer. Additionally, the Fast Fourier Transform (FFT) in an OFDM receiver
supports the performance of a wide band spectrum analysis. Multitaper spectrum
estimation method (MTM) is a non-coherent promising spectrum sensing technique. It
tolerates problems related to bad biasing and large variance of power estimates.
This thesis focuses, generally, on the local, multi antenna based, and global
cooperative spectrum sensing techniques at physical layer in OFDM-based CR systems.
It starts with an investigation on the performance of using MTM and MTM with
singular value decomposition in CR networks using simulation. The Optimal MTM
parameters are then found. The optimal MTM based detector theoretical formulae are
derived. Different optimal and suboptimal multi antenna based spectrum sensing
techniques are proposed to improve the local spectrum sensing performance. Finally, a
new concept of cooperative spectrum sensing is introduced, and new strategies are
proposed to optimize the hard cooperative spectrum sensing in CR networks.
The MTM performance is controlled by the half time bandwidth product and
number of tapers. In this thesis, such parameters have been optimized using Monte
Carlo simulation. The binary hypothesis test, here, is developed to ensure that the effect
of choosing optimum MTM parameters is based upon performance evaluation. The
results show how these optimal parameters give the highest performance with minimum
complexity when MTM is used locally at CR.
The optimal MTM based detector has been derived using Neyman-Pearson
criterion. That includes probabilities of detection, false alarm and misses detection
approximate derivations in different wireless environments. The threshold and number
of sensed samples controlling is based on this theoretical work.
In order to improve the local spectrum sensing performance at each CR, in the CR
network, multi antenna spectrum sensing techniques are proposed using MTM and
MTM with singular value decomposition in this thesis. The statistical theoretical
formulae of the proposed techniques are derived including the different probabilities.
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The proposed techniques include optimal, that requires prior information about the
primary user signal, and two suboptimal multi antenna spectrum sensing techniques
having similar performances with different computation complexity; these do not need
prior information about the primary user signalling. The work here includes derivations
for the periodogram multi antenna case.
Finally, in hard cooperative spectrum sensing, the cooperation optimization is
necessary to improve the overall performance, and/or minimize the number of data to be
sent to the main CR-base station. In this thesis, a new optimization method based on
optimizing the number of locally sensed samples at each CR is proposed with two
different strategies. Furthermore, the different factors that affect the hard cooperative
spectrum sensing optimization are investigated and analysed and a new cooperation
scheme in spectrum sensing, the master node, is proposed.Ministry of Interior-Kingdom of Saudi Arabi
To analyze and compare the different spectrum sensing techniques over the primary channels from the study of CRN concept
The motive behind this paper is to utilize the RF Spectrum properly and to reduce the false alarm rate and to employ various techniques for cognitive radio network(CRN). In cognitive radio networks, to eliminate interference form other than primary users to the users who hold primary license of the spectrum, reliable spectrum sensing is needful. In endeavor, where the samples of noise are correlated, the spectrum sensing methods enhance considering impairment by the noise samples which are not dependent will not provide optimum performances. The probabilities of FA and detection of the designed detector in the low signal to noise ratio reign are visualized. The average probabilities are designed over distinct channel gains. Numerical and simulation results determine the better of the designed method over the known energy detection method and local optimum method with analogous convolution. Furthermore, we consider the endeavor where the calculated correlation is different from the ideal correlation and investigate the effect of this correlation mismatch on the probabilities of constant false alarm and detection of the purposed method. On comparing with the conventional techniques feature detection algorithm, cyclostationary approach is more accurate i.e. it can change the computational hazard according to current electromagnetic environment by motility its sampling times and the cyclic frequency step size
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