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Dimension Boundary Between Finite and Infinite Random Matrices in Cognitive Radio Networks
2017
IEEE Communications Letters
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The dimension boundary between finite random matrices and infinite random matrices is originally defined in this paper. ...
Index Terms-Finite random matrix theory, infinite random matrix theory, dimension boundary, cognitive radio networks. ...
According to the size of the dimension, random matrices can be generally divided into two categories: finite random matrices with finite dimension and infinite random matrices with infinite dimension. ...
doi:10.1109/lcomm.2017.2698474
fatcat:gsgbvo6yrjdbxhx5qxu7v5w6u4
Exact Distributions of Finite Random Matrices and Their Applications to Spectrum Sensing
2016
Sensors
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The dimension boundary provides a theoretical way to divide random matrices into infinite random matrices and finite random matrices. ...
The exact and simple distributions of finite random matrix theory (FRMT) are critically important for cognitive radio networks (CRNs). ...
Introduction Cognitive radio networks (CRNs), working as a sharp tool to deal with the spectrum scarcity problem, have been recognized as one of the most promising communication technologies in recent ...
doi:10.3390/s16081183
pmid:27483273
pmcid:PMC5017349
fatcat:6jsi3ulst5f55lh4ztdw63ar5a
Discrete-Time Analysis of Cognitive Radio Networks with Nonsaturated Source of Secondary Users
2019
Wireless Communications and Mobile Computing
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Sensing is a fundamental aspect in cognitive radio networks and one of the most complex issues. ...
A comprehensive analysis of the proposed models is carried out to derive several key performance indicators in cognitive radio networks. ...
Alfa was partially supported by the NRF SARChI Chair in ASN cohosted by UP and CSIR. ...
doi:10.1155/2019/7367028
fatcat:ue7mtxg7fzdmti4hl55zrzlwhu
Dynamic Spectrum Access for Internet of Things Service in Cognitive Radio-Enabled LPWANs
2017
Sensors
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In this paper, we focus on a dynamic spectrum access strategy for Internet of Things (IoT) applications in two types of radio systems: cellular networks and cognitive radio-enabled low power wide area ...
The spectrum channel contention between the licensed cellular networks and the unlicensed CR-LPWANs, which work with them, only takes place within the cellular radio spectrum range. ...
If r and c 1 are large, the dimension of the matrix T for the boundary probabilities also becomes large. ...
doi:10.3390/s17122818
pmid:29206215
pmcid:PMC5750700
fatcat:bmhftk64rbf35ngod6rkppkfiy
A Survey on Compressive Spectrum Sensing for Cognitive Radio Networks
2019
2019 IEEE International Smart Cities Conference (ISC2)
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In order to improve the efficiency of spectrum sensing in wideband cognitive radio networks, compressive sensing framework has been recommended and studied in many papers since it helps the system to get ...
radio networks. ...
INTRODUCTION Cognitive radio network (CRN) have been proposed as an attractive field of research and effective solution to improve the spectrum utilization in the next-generation of wireless networks. ...
doi:10.1109/isc246665.2019.9071710
dblp:conf/isc2/BenazzouzaRSH19
fatcat:e6oemvwmwzem7kkq7dni62hz6u
Limits on Sparse Data Acquisition: RIC Analysis of Finite Gaussian Matrices
2018
IEEE Transactions on Information Theory
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In this paper we provide a new approach for the analysis of the restricted isometry constant (RIC) of finite dimensional Gaussian measurement matrices. ...
Then, we analyze the recovery of compressible signals in noise through the statistical characterization of stability and robustness. ...
Note that, while previously known approaches refer to infinite dimensional matrices, our analysis accounts for the (always finite) true dimensions of the problem.
V. ...
doi:10.1109/tit.2018.2859327
fatcat:ii3oasoqara6xn5siftvmecgcm
Structured Compressed Sensing: From Theory to Applications
2011
IEEE Transactions on Signal Processing
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Previous review articles in CS limit their scope to standard discrete-to-discrete measurement architectures using matrices of randomized nature and signal models based on standard sparsity. ...
In our overview, the theme is exploiting signal and measurement structure in compressive sensing. ...
ACKNOWLEDGMENT The authors would like to thank their colleagues for many useful comments and for their collaboration on many topics related to this review. In particular, they are grateful to M. ...
doi:10.1109/tsp.2011.2161982
fatcat:mlbtksjmqvbmfmi6gpxwtunbti
Green Small-Cell Networks
2011
IEEE Vehicular Technology Magazine
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A promising solution to this problem is the concept of small-cell networks (SCNs), which is founded by the idea of a very dense deployment of self-organizing, low-cost, low-power, ...
he exponentially increasing demand for wireless data services requires a massive network densification that is neither economically nor ecologically viable with the current cellular system architectures ...
Acknowledgments Feedback from Vinod Kumar (Alcatel-Lucent Bell Labs, France) has been very helpful in the preparation of this article. ...
doi:10.1109/mvt.2010.939904
fatcat:btirdaxywrgz3h7n5lcky3ztpe
Robust set-theoretic distributed detection in diffusion networks
2012
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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radio networks. ...
In the proposed method, nodes in a network detect the presence of a signal of interest by means of an inner product between the current term of a series and a known reference vector. ...
We consider a network with N nodes (cognitive radio networks as a particular case), which are represented by a graph G := (N , E ), where N := {1, . . . , N} is the node set, and E ⊂ N × N is the edge ...
doi:10.1109/icassp.2012.6288734
dblp:conf/icassp/CavalcanteS12
fatcat:gmzauhsapjac7oi2ndho6mshee
Improved Throughput Performance in Wideband Cognitive Radios via Compressive Sensing
2013
2013 8th EUROSIM Congress on Modelling and Simulation
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radio (CR) receivers. ...
Compressive sensing (CS) is a new paradigm in signal processing, chosen for sparse wideband spectrum estimation with compressive measurements, thus provides relief of high-speed DSP requirements of cognitive ...
As , the dimension of in (2) is much lower than that of , so there are theoretically infinite solutions to the equation. ...
doi:10.1109/eurosim.2013.102
fatcat:l3onodynuffmxbsg5jcdyc5rw4
Interference Reduction by Beamforming in Cognitive Networks
2008
IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference
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We consider beamforming in a cognitive network with multiple primary users and secondary users sharing the same spectrum. ...
Using mathematical tools from random matrix theory, we derive both lower and upper bounds on the average interference at the primary receivers and the average SIR of the cognitive user. ...
ACKNOWLEDGMENT This research is supported in part by ARO MURI grant number W911NF-07-1-0376 and a NSERC PDF. The views expressed in this paper are those of the authors alone and not of the sponsors. ...
doi:10.1109/glocom.2008.ecp.845
dblp:conf/globecom/YiuVT08
fatcat:kfgx7f7gd5bg5iqtp2xkczwxe4
Interference and noise reduction by beamforming in cognitive networks
2009
IEEE Transactions on Communications
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Index Terms-Cognitive network, beamforming, fading channels, interference, random matrix theory. ...
We consider beamforming in a cognitive network with multiple primary users and a secondary user sharing the same spectrum. Each primary and secondary user consists of a transmitter and a receiver. ...
NETWORK AND CHANNEL MODELS A. Network Model Consider a cognitive network with primary users and a single cognitive (secondary) user. ...
doi:10.1109/tcomm.2009.10.080501
fatcat:vgfsd2yeojdubcvkxfedwqskk4
A Survey of Wideband Spectrum Sensing Algorithms for Cognitive Radio Networks and Sub-Nyquist Approaches
[article]
2020
arXiv
pre-print
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Cognitive Radio (CR) networks presents a paradigm shift aiming to alleviate the spectrum scarcity problem exasperated by the increasing demand on this limited resource. ...
Spectrum sensing is a key cognitive radio functionality, which entails scanning the RF spectrum to unveil underutilised spectral bands for opportunistic use. ...
In this article, we present a survey of key wideband spectrum sensing algorithms for cognitive radio networks. ...
arXiv:2001.02574v1
fatcat:y5ooiavl7nbcxcx5l7744jeezi
A Journey from Improper Gaussian Signaling to Asymmetric Signaling
2020
IEEE Communications Surveys and Tutorials
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2020 pre-print arXiv:2005.00058v1 fatcat:mxsuueh3vjeizmmd75n5z7byku
between a random entity and its complex conjugate), respectively, introduces new design freedom and various potential merits. ...
Such asymmetric shaping bridges the gap between theoretically and practically achievable limits with sophisticated transceiver and detection schemes in both coded/uncoded wireless/optical communication ...
Radio
Interweave
Cognitive Radio
Underlay
Cognitive Radio
Eavesdroppers
Sensing
and Detection
Communication
Network
Illegitimate links
Interference links
Self-Interference
Two-Way link ...
doi:10.1109/comst.2020.2989626
fatcat:zyno7ku6n5eqnp6rrcopczb4qu
Intelligent Reflecting Surface-Assisted Cognitive Radio System
[article]
2019
arXiv
pre-print
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To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple primary ...
Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users. ...
CN (µ, σ 2 ) denotes the distribution of a circularly symmetric complex Gaussian random variable with mean µ and variance σ 2 . 0 N and I N denote the N -dimensional zero and identity matrices, respectively ...
arXiv:1912.10678v1
fatcat:tnnpditrkva2dgxyp62zlkmsdq
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