SDR Based Energy Detection Spectrum Sensing in Cognitive...

Research ArticleSDR Based Energy Detection Spectrum Sensing inCognitive Radio for Real Time Video Transmission

Rupali B Patil K D Kulat and A S Gandhi

Department of Electronics and Communication Visvesvaraya National Institute of Technology Maharashtra India

Correspondence should be addressed to Rupali B Patil rupali1210gmailcom

Received 10 December 2017 Revised 10 March 2018 Accepted 20 March 2018 Published 29 April 2018

Academic Editor Aiguo Song

Copyright copy 2018 Rupali B Patil et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Cognitive radio is a budding approach which helps to address the imminent spectrum crisis by dynamic spectrum allocationand support the increased data traffic with an intelligent mechanism of Software Defined Radio (SDR) SDR avoid the frequentmodifications in the hardware structure with the use of software defined protocols The main novelty of the paper is an effectiveimplementation of CR using energy based spectrum sensing method which is done on GNU radio for real time transmission ofvideo as a primary user From evaluation results one can see that the proposed system can indicate the frequency band occupancyby setting the detection output Detection output changes to one with start of video transmission Motivation behind this workis design of a spectrum sensing method which is best suited for detection of white spaces during the transmission of video as aprimary user on SDR platform

1 Introduction

According to spectrum survey conducted by the FederalCommunication Commission (FCC) has indicated that theactual licensed spectrum is not utilized properly for varioustime frequency and geographical locations [1] Also thedemand of allocating and using the radio frequency spectra israpidly growing due to increasing number of wireless applica-tions [2] An unlicensed user or secondary user may utilizethis band when licensed user is absent To encourage the pro-ficient use of spectrum concept of cognitive radio (CR) hasbeen proposed in [3] CR fundamentals and the challengesinvolved in dynamic spectrum allocation and sharing inCR are discussed in [4] CR allows opportunistic usage offrequency bands that are not used by licensed users ThusCR relies on efficient spectrum sensing to detect vacantspectrum bands Also deployment of new wireless devicesand applications has increased more expensive hardwarestructure to be dealt with these types of signal processingSo this requires reconfigurable hardware platforms A bestsolution to these problems is SDR platforms GNU radioalong with SDR provides the cost effective and flexible plat-form A major challenge for SDR is to equal the proficienciesof purely hardware solutions while providing intelligence

that software can offer The employment of GNU radio andUniversal Software Radio Peripheral (USRP) for developingsoftware based wireless transmission system that is SDR isdiscussed in [5] CR is having the capability to optimally adapttheir operating parameters according to the trades of thesurrounding radio environment CR can detect the spectrumwhite space that is a portion of frequency band that is notbeing used by the primary users (licensed users) and utilizethe same for secondary user (SU) transmission But whenlicensed users start using the spectrum again CR can detecttheir activity through spectrum sensing and hold the trans-mission generated due to secondary userrsquos transmissionMoreover the ability of CR to identify and exploit the unusedspectrum band allows them to coexist with inheritance radiosystems improving spectrum utilization without impairingthe primary users (PU) So mainly CR comprises two typesof users First one is PU who has the license to use the givenfrequency band and second one is SU who is not a licenseduser of the given frequency band but can use band wheneverit is vacant As soon as the PU or licensed user returns to thefrequency band SU has to vacate it and find another vacantfrequency band To detect whether a frequency band is unoc-cupied or not SU needs to perform spectrum sensing Sosensing is identified as the key aspects of a CR which means

HindawiModelling and Simulation in EngineeringVolume 2018 Article ID 2424305 10 pageshttpsdoiorg10115520182424305

2 Modelling and Simulation in Engineering

a CR must be able to identify the unused spectrum bandCompetencies of CR are combined with SDR SDR enhancesthe functionality of CR through smart mechanism usingGNU radio that would automatically reconfigure the radioparameters and senses the spectrumThere are various detec-tion techniques available for spectrum sensing The momen-tous amount of study is performed on spectrum sensingfor CR based system in [6] Energy detection constitutesa favored approach for spectrum sensing in CR due to itssimplicity and applicability The traditional energy detectiontechnique [7] which is based upon fixed threshold is sen-sitive to noise uncertainty which is unavoidable in practicalcases So in this paper an efficient energy detector is proposedfor optimum CR performance In the proposed schemeunder a practical scenario some parameters are measuredand these parameters are used to calculate the threshold ofenergy based sensing methodThe purpose of thresholds cal-culation is to maximize the probability of detection (119875119863) andminimize the probability of false alarm (119875FA) Theoreticalanalysis and simulation results show the efficiency of the pro-posed scheme in comparison to the traditional energy detec-tion method with less increase in complexity

Also data traffic in air has increased beyond limit whichdevelops the growing demand for the transfer of data imagesand video using the same medium which is used for voicetransmission So for testing instead of random data real timevideo signal is transmitted and at the receiver CR based en-ergy detection of this video signal is done This video signalis acting as a primary user and energy detector is able todetect the availability of this video signal on given frequencyby setting parameter detection output

Most research currently emphasizes on spectrum sensingin CR but theoretical detection algorithms are not enoughAs discussed in [8] SDR is an important convenient basetechnology for the future context-sensitive adaptive andlearning radio units referred to as CRs SDR requires theblending of software-based signal processing and the ena-bling hardware components The overview of the criteria forsuch platforms and the current state of development andupcoming trends in this area are presented in [9]

A hardware test platform is required to test and checkthe performances of the CR This problem can be resolvedusing emergent technology of SDR which gives easiness inthe implementation process by replacing the hardware by software in addition to cost effectiveness Several benefits likefaster execution time and extensibility to meet new require-ments are given by SDR

A large number of experimental SDR platforms are avail-able to support individual research projects [10] GNU radio[11] is one of the most popular and an interesting softwareplatform for radio network which is introduced by BlossomIt is a free software toolkit for building software radio and iscompatible with SDR kits [12] The whole GNU radio projectis available under GNU license which does not limit free useof GNU radio components in research projects This GNUradio project contains a large library of functions written inC++python language for the SDR system and the library ofseveral basic components for implementing basic functionsof a digital radio receiver Moreover GNU radio is designedto work with an inexpensive hardware device

For testing of the above project SDR-Lab kits havingtransmit and receive frequency range of 04ndash4GHz are usedThe SDR-LAB is a powerful software programmable hard-ware transceiver

To support high date rate and good spectral efficiency arethe requirements in the case of transmittingmultimedia dataGaussian Minimum Shift Keying (GMSK) is a modulationscheme which proves to be effective in wireless scenarioGMSK is derived fromMinimum Shift Keying (MSK) whichreplaces the rectangular pulse with a sinusoidal pulse Thismethod will apply Gaussian filter for pulse-shaping A Gaus-sian-shaped impulse response filter has an advantage that itgenerates a signal with low side lobes and narrowermain lobethan the rectangular pulse As it uses Gaussian filter for pulse-shaping this modulation is called GMSK modulation Therelationship between the premodulation filter bandwidth119882 and the bit period 119879119887 defines the bandwidth of thesystem Global System for Mobile Communications (GSM)designers used a119882119879119887 = 03 This compromises between a biterror rate and an out-of-band interference since the narrowfilter increases Intersymbol Interference (ISI) and reduces thesignal power [13] The GMSKmodulation has been preferredfor video transmission in wireless communication becauseit compromises between spectrum efficiency complexityand low spurious radiations which lessen the possibilities ofadjacent channel interference

The paper is organized as follows Section 2 contains sys-tem outline Section 3 considers theoretical aspects of energybased spectrum sensing In Section 4 we investigate energybased spectrum sensing method on SDR for detection of pri-mary userrsquos presence and its implementation issues Section 5is dedicated to theoretical analysis and numerical calculationof threshold Section 6 presents the results from energy detec-tor sensing method Finally conclusions and future scopeare presented in Section 7

2 System Outline

A block diagram of the CR-GMSK system considered in thisarticle is shown in Figure 1 The cognitive engine is respon-sible for making intellectual decisions and configuring theradio and physical layer (PHY) parametersThe transmissionprospects are identified by the decision unit based on theinformation from the policy engine as well as local and net-work spectrum sensing data As far as the PHY layer is con-cerned CR can communicate with various radio-access tech-nologies in the environment or it can improve the qualityof communication depending on the environmental charac-teristics by simply changing the configuration parameters ofthe GMSK system and the SDR interface Note that spectrumsensing and detection is done on single carrier frequency

The overall block diagram of transmitter and receiverfor energy based spectrum sensing is shown in Figure 2The input to the system is a real time video captured bywebcamandmodulated byGMSK It is processed through thecode written in python language using GNU radio softwareAfter this processing it is transmitted wirelessly on 1234GHzfrequency using a SDR-LAB device The receiver is tunedto transmitted frequency Transmitted signal is received by

Modelling and Simulation in Engineering 3

Upper

LayersPHY SDR

GMSK MODULATOR

COGNITIVE RADIO

Decision Unit

Local SpectrumSensing

PolicyEngine

Subcarrier assignment

GMSK DEMODULATOR

Synchronization

SpectrumSensing

Radio configuration

DigitalRF

DigitalRF

DAC

ADC

PA

LNA

Figure 1 Overall system block diagram

Video file Source(Webcam or video

file)

GNU Radio(GMSK

Modulator)

SDRTransmitter

SDRReceiver

GNU Radio(GMSK

Demodulator)

File Sink (videoPlayback

eg VLC Player)

Energy baseddetector

Detection Outputwith SNRcalculator

Figure 2 Overall block diagram transmitter and receiver for energy based spectrum sensing

another SDR-LAB Trans receiver which hands over theincoming information to the GNU radio software which hastwo parts one is GMSK demodulation used for detection ofvideo signal and another is energy based spectrum sensingwhich gives detection output along with signal to noise ratio(SNR) calculations We are trying to display the received

video and simultaneously trying to detect the white spaces atthis frequency using energy based spectrum sensing Testingis done by switching the video transmission on and off

Project setup with SDR-Lab with Laptop is shown inFigure 3 One SDR connected to laptop is acting as transmit-ter and the other is acting as receiver


Figure 3 Project setup for transmitter and receiver of energy basedspectrum sensing

3 Theoretical Aspects ofEnergy Based Spectrum

Energy detection is the simple spectrum sensing methodbecause it is easy to implement and requires no prior knowl-edge about the primary signal Let us assume the hypothesismodel of the received signal given by the following

1198670 119911 (119905) = 119899 (119905) 1198671 119911 (119905) = ℎ119909 (119905) + 119899 (119905) (1)

Here 119909(119905) is the primary userrsquos signal to be detected at thelocal receiver of a secondary user 119899(119905) is the additive whiteGaussian noise and ℎ is the channel gain from the primaryuserrsquos transmitter to the secondary userrsquos receiver1198670 is a nullhypothesis which means there is no primary user present inthe band while 1198671 means the primary userrsquos presence Thedetection statistics of the energy detector can be defined asthe average energy of 119873 observed samples 119911(119905) and is givenby

119879 = 1119873119873sum119905=1

|119911 (119905)|2 (2)

The decision regarding the occupancy of the spectrum isgiven by comparing the detection statistics with a predeter-mined threshold (120582) 119875FA the probability of false alarm and119875119863 the probability of detection are two probabilities whichare used to characterize the performance of the detector 119875FAdenotes the probability that the test decides 1198671 while it isactually1198670 given by

119875FA = 119875119903 (119879 gt 120582 | 1198670) (3)

119875119863 denotes the probability that the test correctly decides 1198671given by

119875119863 = 119875119903 (119879 gt 120582 | 1198671) (4)

A good detector should ensure a high detection probability119875119863 and a low false alarm 119875FA or it should optimize thespectrum usage efficiency The efficiency of energy detectorbased spectrum sensing can be improved by the developmentof various approaches

An efficient energy detector is proposed in which undera practical scenario some parameters are measured and theseparameters are used to calculate the threshold for this system

Design of this energy detection uses a squaring device fol-lowed by an integrator the output of which gives the decisionvariable This variable is then compared with a threshold andif it is above the predefined threshold then the result of thedetector specifies that a PU is present An energy detectorsets a threshold according to the noise floor and comparesit with the energy of the data stream in input The inputsignal selects the required bandwidth by a band pass filterthen it is sampledThe digital implementation of this methoduses the Fast Fourier Transform (FFT) so the absolute valueof the samples is squared and integrated over the observationband Finally according to a comparison between the outputof the integrator and threshold the presence or absence ofthe primary user can be detected The block diagram of thismethod is given in Figure 4

4 Energy Based Spectrum Sensing on SDR

The GNU radio based transmitter flow graph shown inFigure 5 is designed to transmit a real time video signal whichis acting as a PU The modulation used for the transmissionfor this video signal is GMSK This wirelessly transmittedsignal is received by the GNU radio based receiver shown inFigure 6 The design of the receiver flow graph is done as perthe block diagram shown in Figure 4 To measure the signalenergy selected band data is sampled with stream to vectorcomplex to mag blocks which perform the task of squaringand averaging Further it is compared with a predefinedthreshold The sensing method gives the output of PU signaldetection by setting output flag named detection output andcalculation of SNR with an assumption that no user otherthan PU is present on the channel SU transmission is decidedbased on the detection output flag status of the PU

41 Transmitter Side Implementation The flow graph oftransmitter is shown in Figure 5 The process which is fol-lowed for the implementation and execution firstly opens theterminal window using keyboards ctrl + alt + T Type GNUradio companion (GRC) in opened window In untitled GRCwindow double click on the option block Set the parametersfor the flow graph And open the other block named variablein flow graph and set the sample rate value Generate a flowgraph as per shown in Figure 5 of Tx video by simply puttingalready generated GNU blocks in GNU radio companionwindow To transmit a live video from webcam input to theGMSK modulator block is fed through File Sink To specifythe rate at which the frames are to be transmitted and theirsize create a new shell file Video txsh in home folder Thisfile when executed will create a queue of First In First Out(FIFO) type to transmit data Execute this file later on Openthe file operators category and double click on file source

Set the address and arrange the overall flow-graph tocomplete video transmitting section of GMSK modulatorNow execute the Shell File Video txsh and then execute thisflow graph by pressing F6

42 Receiver Side Implementation The flow graph of receiveris shown in Figure 6 The process which is followed for the


ThresholdDefinition

Filterand ADC FFT

Comparisonwith

Threshold

MeanValue| |

2

Figure 4 Block diagram of energy based spectrum sensing

Figure 5 Transmitter flow graph for video transmission designed using GNU radio

Figure 6 Receiver side flow graph for video reception and detection of signal designed using GNU radio


implementation and execution on receiver side is creating afile called Video rxsh in the home folder with instructionsto generate queue to receive the data in FIFO manner andstore the received videowith extension filenametsThenopena terminal window using Ctrl + alt + T At the receiverside terminal type gnuradio-companion Then double clickon options block set the parameters and close the propertieswindow Open the other block named variable in flow graphand set the sample rate value as 11198906 Arrange all the blocksand logically connect them as per the flow graph as shown inFigure 6

Then open another command prompt and type thefollowing command after the $ signVideo rxsh

Execute the flow graph by pressing F6 Receiver side flowgraphs have added blocks required for demodulation as wellas the implementation of energy sensing based spectrumsensing as per the block diagram shown in Figure 4

5 Theoretical Analysis and NumericalCalculations of Threshold

To decide the threshold value for energy based spectrumsensing for flow graph shown in Figure 6 is another challeng-ing task So there is a necessity to carry out the theoreticalanalysis and numerical calculations based on the practicalconditions The essence of energy based spectrum sensing isa binary hypothesis testing problem Theoretical analysis isdone for the same as follows

119910 (119899) = 119908 (119899) under 1198670119909 (119899) + 119908 (119899) under 1198671 (5)

where 119910(119899) 119909(119899) and 119908(119899) are the received signals at CRnodes transmitted signals at primary nodes and white noisesamples respectively The above two hypotheses are taken todecide the signal is present or notThe119908(119899) noise is assumedto be additive white Gaussian noise (AWGN) with zero meanand is a random process The signal to noise ratio is

SNR = 119878power119873power (6)

where 119878power is signal power and119873power is noise powerThe energy detection algorithm is semiblind detection

under the assumption of absolutely no deterministic knowl-edge about the signal 119909(119899) Let us assume that we know onlythe average power of the signal The optimal detector is thecorrelation detector [14] The decision model is

119863(119910) =

1119873119899minus1sum119899=0

119910 (119899) 119909 (119899) gt 120574 under 11986711119873119899minus1sum119899=0

119910 (119899) 119909 (119899) lt 120574 under 1198670 (7)

where 119863(119910) is decision variable and 120574 is the threshold If thenoise variance is completely known then from Central LimitTheorem the following approximation can be made

119863( 1199101198670) = N(1205902119899 21205904119899119873 )

119863( 1199101198671) = N(119875 + 1205902119899 2 (119875 + 1205902

119899)2119873 )

(8)

where 119875 is the average signal power 119873 are the number ofsamples and 1205902

119899is the noise varianceN() symbol is used for

approximation The energy detector decides1198671 if119879 (119909) = 119873minus1sum

119899=0

1199092 (119899) gt 120574 (9)

If 119873 is large then 119879(119909) can be approximated by a Gaussianrandom variable since it is the sum of 119873 independentalthough not identically distributed random variables Thuswe need only to find out first two movements to characterizethe detection performance To do so

1198791015840 (x) = 119879 (119909)1205902 = 1199092 (119899) under 11986701199092 (120582) under 1198671 (10)

where 120582 = sum119873minus1119899=0

1199042(119899)1205902 = 1205981205902This is because under1198671

1198791015840 (119909) = 119873minus1sum119899=0

((119904 (119899) + 119908 (119899))1205902) (11)

And hence mean of 119909(119899)120590 is 119904(119899)120590 Using the properties ofchi-squared random variables we have

119864 (1198791015840 (119909) 1198670) = 119873119864 (1198791015840 (119909) 1198671) = 120582 + 119873

var (1198791015840 (119909) 1198670) = 2119873var (1198791015840 (119909) 1198671) = 4120582 + 2119873

(12)

119875FA the probability of false alarm and 119875119863 the probability ofdetection are given by

119875FA = 119876(12057410158401205902 minus 119873radic2119873 ) (13)

119875119863 = 119876(12057410158401205902 minus (120582 + 119873)radic4120582 + 2119873 ) (14)

where 119876(sdot) is the standard Gaussian complementary Cumu-lative Distribution Function (CDF) and 1205741015840 is the thresholdwhich is 120574119873


Rearranging 119875119863119875119863 = 119876(12057410158401205902 minus 120582 minus 119873radic4120582 + 2119873 ) (15)

Rearranging and multiplying and dividing by radic2119873119875119863 = 119876((12057410158401205902 minus 119873)radic2119873radic2119873 minus 120582radic4120582 + 2119873 ) (16)

Taking 119876minus1 of 119875FA in (13)

119876minus1 (119875FA) = 119876minus1 (119876(12057410158401205902 minus 119873radic2119873 )) (17)

119876minus1 (119875FA) = (12057410158401205902 minus 119873radic2119873 ) (18)

Putting (18) in (16) modified equation of 119875119863 is119875119863 = 119876(radic2119873119876minus1 (119875FA) minus 120582radic4120582 + 2119873 ) 119875119863 = 119876(119876minus1 (119875FA) minus radic1198732 (120582119873)radic1 + 2 (120582119873) )

(19)

where 119876minus1(sdot) is the inverse standard Gaussian complemen-tary CDF The last approximation is valid for large119873 Finallywe have

119875119863 = 119876(119876minus1 (119875FA) minus radic1198732 120582119873) 119875119863 = 119876(119876minus1 (119875FA) minus radic 12058222119873)

(20)

This equation will be recognized as the performance of theNeyman-Pearson detector Thus threshold formula for theenergy detector based on the probability of the false alarm119875FA is derived as given in

1205741015840 = [(119876minus1 (119875FA) times radic2119873) + 119873] times 1205902 (21)

Under the practical condition some parameters aremeasuredand these parameters are used to calculate the threshold ofthe projectThe gain of the RF signal and energy of the signalare selected as 10 and 00364 respectively Also number ofsamples are taken as 150000The variance is calculated as per(22)

1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)

Put 1205902 in1205741015840 = (119876minus1 (119875FA) times radic2119873 + 119873) times 12059021205741015840 = (00889 times radic2 times 150000 + 150000) times 24267

times 10minus9(24)

1205741015840 = 00336 (25)

The threshold calculated in (25) is set in flow graph of receiverside energy based spectrum sensing for detection of videosignal

6 Results of Energy Detection Method

The energy detection spectrum sensing in cognitive radio isimplemented efficiently with GNU Radio and SDR-LAB kitfor the real time video signal acting as a primary user

The input real time video captured by webcam is modu-lated byGMSKThis processing is done on transmitter side inGNU radioThe detection algorithm is implemented in GNUradio on receiver side as per the the block diagram shown inFigure 4 Initially transmitted frequency is set at 12345GHzbut we can also adaptively change the frequency of trans-mission This transmitted video signal is received by anotherSDR-LAB transreceiver which is tuned to transmitter pro-cessed using GNU radio and GMSK demodulated It is alsoplayed using VLC media player simultaneously The samereceived video signal is also given to energy based spectrumsensing blockset designed using GNU radio software Thecode is written in python The threshold calculated in (25) ofSection 5 is used in the threshold block of GNU radio receiverside flow graph for the detection of the real time video signal

Energy based spectrum sensing block gives the output ofvideo signal detection in the form of flag named detectionoutput The SNR and energy of signal are also measuredon receiver side for the transmitted video signal with thehelp of energy detector spectrum sensing method If videois present energy of the signal becomes higher than thethreshold and detected output becomes one But if the signaltransmission stops then the energy of the signal becomesless than threshold and detected output becomes zero Herevideo signal is acting as primary user This shows successfulimplementation of energy based detector which detects theprimary userrsquos presence on given frequency by setting thedetection output Fast Fourier Transforms (FFT) and scopeplots are used to observe the signals at each point Initiallythe working of only energy detector is also tested under noisecondition with no signal results clearly show that noise isdetected as no signal present by the detection output flag inFigure 7 Figure 8 shows the results when video transmissionstops with status of detection output and energy of the signalThe detection output and the energy of the signal becomeszero as transmission of video stops while Figure 9 shows theresult of energy detectorwhen the video transmission is goingon The detector output is one and energy of received signalis measured at the output when the video transmission isgoing on Figure 10 shows the FFT plot specifying amplitude


Figure 7 Energy based detector output is zero under only noise no signal condition

Figure 8 Energy based detector output is zero as the transmission stops

in decibel (dB) versus frequency (KHz) at 123GHz The re-ceived signal is represented with FFT plot in GUI of GNUradio companionThe results of the energy detector are testedand verified by varying the distance between transmitter andreceiver from one to ten meters

7 Conclusion and Future Scope

GNU radio based innovative approach has been designedfor detection of transmitted live video using energy basedspectrum sensing of CR and implemented on SDR platformTransmitted signal is modulated with GMSK and energydetector is implemented successfully with averaging blocksIn conclusion this work has produced a significant amount

of theoretical and algorithmic results for energy detectormoreover the SDR implementation along with GNU radiooffers a set of tools that allow the creation of a realistic CR sys-tem with real time spectrum sensing capabilities So we havesuccessfully designed and implemented CR based communi-cation system for real time video transmission

Future work focuses on experimentation of same spec-trum sensing techniques for improving the performance incognitive radio and also finding out the one which is moresuitable to work in wireless environment Further this can beextended for simultaneous transmission of multiple signalsand use of multiple frequency bands Also this work will bequite helpful for implementation of real time projects such astraffic control which can use this spectrum sensing method


Figure 9 Energy based detector output is one as the transmission starts

Figure 10 Spectrum of received signal (FFT plot)

for wireless transmission and detection of traffic video signalsdata from multiple signal posts to one master check postThis can be further transferred to control unit which will usethis information for controlling the traffic So decisive aim ofthis system is design and implementation of CR based trafficcontrol system for real time video transmission

Conflicts of Interest

The authors declare that they have no conflicts of interest

References[1] Federal Communications Commission ldquoSpectrum policy task

forcerdquo Report ET Docket no 02-135 2002[2] S-S Byun K Kansanen I Balasingham and J-MGil ldquoAchiev-

ing fair spectrum allocation and reduced spectrum handoff inwireless sensor networks modeling via biobjective optimiza-tionrdquoModelling and Simulation in Engineering vol 2014 ArticleID 406462 12 pages 2014

[3] J Mitola and G Q Maguire ldquoCognitive radio making softwareradios more personalrdquo IEEE Personal Communications vol 6no 4 pp 13ndash18 1999


[4] BWang and K J R Liu ldquoAdvances in cognitive radio networksa surveyrdquo IEEE Journal of Selected Topics in Signal Processingvol 5 no 1 pp 5ndash23 2011

[5] Z Tong M S Arifianto and C F Liau ldquoWireless transmissionusing universal software radio peripheralrdquo in Proceedings of theInternational Conference on Space Science and Communication(IconSpace rsquo09) pp 19ndash23 Negeri Sembilan Malaysia October2009

[6] I F Akyildiz W-Y Lee M C Vuran and S Mohanty ldquoNeXtgenerationdynamic spectrum accesscognitive radio wirelessnetworks a surveyrdquo Computer Networks vol 50 no 13 pp2127ndash2159 2006

[7] H Urkowitz ldquoEnergy detection of unknown deterministic sig-nalsrdquo Proceedings of the IEEE vol 55 no 4 pp 523ndash531 1967

[8] T Ulversoy ldquoSoftware defined radio Challenges and opportu-nitiesrdquo IEEE Communications Surveys amp Tutorials vol 12 no 4pp 531ndash550 2010

[9] R Farrell M Sanchez and G Corley ldquoSoftware-defined radiodemonstrators an example and future trendsrdquo InternationalJournal of DigitalMultimedia Broadcasting vol 2009 Article ID547650 12 pages 2009

[10] E Blossom ldquoGNUradio tools for exploring the radio frequencyspectrumrdquo Linux Journal no 122 2004

[11] GNU Radio 2017 httpgnuradioorg[12] SDR Kit 2017 httpsdr-labcom[13] S Haykin Communication Systems John Wiley amp Sons New

York NY USA 4th edition 2001[14] R Tandra and A Sahai ldquoSNR walls for signal detectionrdquo IEEE

Journal of Selected Topics in Signal Processing vol 2 no 1 pp4ndash17 2008

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a CR must be able to identify the unused spectrum bandCompetencies of CR are combined with SDR SDR enhancesthe functionality of CR through smart mechanism usingGNU radio that would automatically reconfigure the radioparameters and senses the spectrumThere are various detec-tion techniques available for spectrum sensing The momen-tous amount of study is performed on spectrum sensingfor CR based system in [6] Energy detection constitutesa favored approach for spectrum sensing in CR due to itssimplicity and applicability The traditional energy detectiontechnique [7] which is based upon fixed threshold is sen-sitive to noise uncertainty which is unavoidable in practicalcases So in this paper an efficient energy detector is proposedfor optimum CR performance In the proposed schemeunder a practical scenario some parameters are measuredand these parameters are used to calculate the threshold ofenergy based sensing methodThe purpose of thresholds cal-culation is to maximize the probability of detection (119875119863) andminimize the probability of false alarm (119875FA) Theoreticalanalysis and simulation results show the efficiency of the pro-posed scheme in comparison to the traditional energy detec-tion method with less increase in complexity

Also data traffic in air has increased beyond limit whichdevelops the growing demand for the transfer of data imagesand video using the same medium which is used for voicetransmission So for testing instead of random data real timevideo signal is transmitted and at the receiver CR based en-ergy detection of this video signal is done This video signalis acting as a primary user and energy detector is able todetect the availability of this video signal on given frequencyby setting parameter detection output

Most research currently emphasizes on spectrum sensingin CR but theoretical detection algorithms are not enoughAs discussed in [8] SDR is an important convenient basetechnology for the future context-sensitive adaptive andlearning radio units referred to as CRs SDR requires theblending of software-based signal processing and the ena-bling hardware components The overview of the criteria forsuch platforms and the current state of development andupcoming trends in this area are presented in [9]

A hardware test platform is required to test and checkthe performances of the CR This problem can be resolvedusing emergent technology of SDR which gives easiness inthe implementation process by replacing the hardware by software in addition to cost effectiveness Several benefits likefaster execution time and extensibility to meet new require-ments are given by SDR

A large number of experimental SDR platforms are avail-able to support individual research projects [10] GNU radio[11] is one of the most popular and an interesting softwareplatform for radio network which is introduced by BlossomIt is a free software toolkit for building software radio and iscompatible with SDR kits [12] The whole GNU radio projectis available under GNU license which does not limit free useof GNU radio components in research projects This GNUradio project contains a large library of functions written inC++python language for the SDR system and the library ofseveral basic components for implementing basic functionsof a digital radio receiver Moreover GNU radio is designedto work with an inexpensive hardware device

For testing of the above project SDR-Lab kits havingtransmit and receive frequency range of 04ndash4GHz are usedThe SDR-LAB is a powerful software programmable hard-ware transceiver

To support high date rate and good spectral efficiency arethe requirements in the case of transmittingmultimedia dataGaussian Minimum Shift Keying (GMSK) is a modulationscheme which proves to be effective in wireless scenarioGMSK is derived fromMinimum Shift Keying (MSK) whichreplaces the rectangular pulse with a sinusoidal pulse Thismethod will apply Gaussian filter for pulse-shaping A Gaus-sian-shaped impulse response filter has an advantage that itgenerates a signal with low side lobes and narrowermain lobethan the rectangular pulse As it uses Gaussian filter for pulse-shaping this modulation is called GMSK modulation Therelationship between the premodulation filter bandwidth119882 and the bit period 119879119887 defines the bandwidth of thesystem Global System for Mobile Communications (GSM)designers used a119882119879119887 = 03 This compromises between a biterror rate and an out-of-band interference since the narrowfilter increases Intersymbol Interference (ISI) and reduces thesignal power [13] The GMSKmodulation has been preferredfor video transmission in wireless communication becauseit compromises between spectrum efficiency complexityand low spurious radiations which lessen the possibilities ofadjacent channel interference

The paper is organized as follows Section 2 contains sys-tem outline Section 3 considers theoretical aspects of energybased spectrum sensing In Section 4 we investigate energybased spectrum sensing method on SDR for detection of pri-mary userrsquos presence and its implementation issues Section 5is dedicated to theoretical analysis and numerical calculationof threshold Section 6 presents the results from energy detec-tor sensing method Finally conclusions and future scopeare presented in Section 7

2 System Outline

A block diagram of the CR-GMSK system considered in thisarticle is shown in Figure 1 The cognitive engine is respon-sible for making intellectual decisions and configuring theradio and physical layer (PHY) parametersThe transmissionprospects are identified by the decision unit based on theinformation from the policy engine as well as local and net-work spectrum sensing data As far as the PHY layer is con-cerned CR can communicate with various radio-access tech-nologies in the environment or it can improve the qualityof communication depending on the environmental charac-teristics by simply changing the configuration parameters ofthe GMSK system and the SDR interface Note that spectrumsensing and detection is done on single carrier frequency

The overall block diagram of transmitter and receiverfor energy based spectrum sensing is shown in Figure 2The input to the system is a real time video captured bywebcamandmodulated byGMSK It is processed through thecode written in python language using GNU radio softwareAfter this processing it is transmitted wirelessly on 1234GHzfrequency using a SDR-LAB device The receiver is tunedto transmitted frequency Transmitted signal is received by


Upper

LayersPHY SDR

GMSK MODULATOR

COGNITIVE RADIO

Decision Unit


PolicyEngine


GMSK DEMODULATOR

Synchronization

SpectrumSensing

Radio configuration

DigitalRF

DigitalRF

DAC

ADC

PA

LNA



file)

GNU Radio(GMSK

Modulator)

SDRTransmitter

SDRReceiver

GNU Radio(GMSK

Demodulator)


eg VLC Player)











1198670 119911 (119905) = 119899 (119905) 1198671 119911 (119905) = ℎ119909 (119905) + 119899 (119905) (1)


119879 = 1119873119873sum119905=1

|119911 (119905)|2 (2)


119875FA = 119875119903 (119879 gt 120582 | 1198670) (3)


119875119863 = 119875119903 (119879 gt 120582 | 1198671) (4)










ThresholdDefinition

Filterand ADC FFT

Comparisonwith

Threshold

MeanValue| |

2










119910 (119899) = 119908 (119899) under 1198670119909 (119899) + 119908 (119899) under 1198671 (5)





119863(119910) =

1119873119899minus1sum119899=0


119910 (119899) 119909 (119899) lt 120574 under 1198670 (7)


119863( 1199101198670) = N(1205902119899 21205904119899119873 )

119863( 1199101198671) = N(119875 + 1205902119899 2 (119875 + 1205902

119899)2119873 )

(8)




119899=0

1199092 (119899) gt 120574 (9)


1198791015840 (x) = 119879 (119909)1205902 = 1199092 (119899) under 11986701199092 (120582) under 1198671 (10)

where 120582 = sum119873minus1119899=0


1198791015840 (119909) = 119873minus1sum119899=0

((119904 (119899) + 119908 (119899))1205902) (11)


119864 (1198791015840 (119909) 1198670) = 119873119864 (1198791015840 (119909) 1198671) = 120582 + 119873

var (1198791015840 (119909) 1198670) = 2119873var (1198791015840 (119909) 1198671) = 4120582 + 2119873

(12)


119875FA = 119876(12057410158401205902 minus 119873radic2119873 ) (13)

119875119863 = 119876(12057410158401205902 minus (120582 + 119873)radic4120582 + 2119873 ) (14)









(19)



(20)




1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)


times 10minus9(24)

1205741015840 = 00336 (25)





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Upper

LayersPHY SDR

GMSK MODULATOR

COGNITIVE RADIO

Decision Unit


PolicyEngine


GMSK DEMODULATOR

Synchronization

SpectrumSensing

Radio configuration

DigitalRF

DigitalRF

DAC

ADC

PA

LNA



file)

GNU Radio(GMSK

Modulator)

SDRTransmitter

SDRReceiver

GNU Radio(GMSK

Demodulator)


eg VLC Player)











1198670 119911 (119905) = 119899 (119905) 1198671 119911 (119905) = ℎ119909 (119905) + 119899 (119905) (1)


119879 = 1119873119873sum119905=1

|119911 (119905)|2 (2)


119875FA = 119875119903 (119879 gt 120582 | 1198670) (3)


119875119863 = 119875119903 (119879 gt 120582 | 1198671) (4)










ThresholdDefinition

Filterand ADC FFT

Comparisonwith

Threshold

MeanValue| |

2










119910 (119899) = 119908 (119899) under 1198670119909 (119899) + 119908 (119899) under 1198671 (5)





119863(119910) =

1119873119899minus1sum119899=0


119910 (119899) 119909 (119899) lt 120574 under 1198670 (7)


119863( 1199101198670) = N(1205902119899 21205904119899119873 )

119863( 1199101198671) = N(119875 + 1205902119899 2 (119875 + 1205902

119899)2119873 )

(8)




119899=0

1199092 (119899) gt 120574 (9)


1198791015840 (x) = 119879 (119909)1205902 = 1199092 (119899) under 11986701199092 (120582) under 1198671 (10)

where 120582 = sum119873minus1119899=0


1198791015840 (119909) = 119873minus1sum119899=0

((119904 (119899) + 119908 (119899))1205902) (11)


119864 (1198791015840 (119909) 1198670) = 119873119864 (1198791015840 (119909) 1198671) = 120582 + 119873

var (1198791015840 (119909) 1198670) = 2119873var (1198791015840 (119909) 1198671) = 4120582 + 2119873

(12)


119875FA = 119876(12057410158401205902 minus 119873radic2119873 ) (13)

119875119863 = 119876(12057410158401205902 minus (120582 + 119873)radic4120582 + 2119873 ) (14)









(19)



(20)




1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)


times 10minus9(24)

1205741015840 = 00336 (25)





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






1198670 119911 (119905) = 119899 (119905) 1198671 119911 (119905) = ℎ119909 (119905) + 119899 (119905) (1)


119879 = 1119873119873sum119905=1

|119911 (119905)|2 (2)


119875FA = 119875119903 (119879 gt 120582 | 1198670) (3)


119875119863 = 119875119903 (119879 gt 120582 | 1198671) (4)










ThresholdDefinition

Filterand ADC FFT

Comparisonwith

Threshold

MeanValue| |

2










119910 (119899) = 119908 (119899) under 1198670119909 (119899) + 119908 (119899) under 1198671 (5)





119863(119910) =

1119873119899minus1sum119899=0


119910 (119899) 119909 (119899) lt 120574 under 1198670 (7)


119863( 1199101198670) = N(1205902119899 21205904119899119873 )

119863( 1199101198671) = N(119875 + 1205902119899 2 (119875 + 1205902

119899)2119873 )

(8)




119899=0

1199092 (119899) gt 120574 (9)


1198791015840 (x) = 119879 (119909)1205902 = 1199092 (119899) under 11986701199092 (120582) under 1198671 (10)

where 120582 = sum119873minus1119899=0


1198791015840 (119909) = 119873minus1sum119899=0

((119904 (119899) + 119908 (119899))1205902) (11)


119864 (1198791015840 (119909) 1198670) = 119873119864 (1198791015840 (119909) 1198671) = 120582 + 119873

var (1198791015840 (119909) 1198670) = 2119873var (1198791015840 (119909) 1198671) = 4120582 + 2119873

(12)


119875FA = 119876(12057410158401205902 minus 119873radic2119873 ) (13)

119875119863 = 119876(12057410158401205902 minus (120582 + 119873)radic4120582 + 2119873 ) (14)









(19)



(20)




1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)


times 10minus9(24)

1205741015840 = 00336 (25)





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



ThresholdDefinition

Filterand ADC FFT

Comparisonwith

Threshold

MeanValue| |

2










119910 (119899) = 119908 (119899) under 1198670119909 (119899) + 119908 (119899) under 1198671 (5)





119863(119910) =

1119873119899minus1sum119899=0


119910 (119899) 119909 (119899) lt 120574 under 1198670 (7)


119863( 1199101198670) = N(1205902119899 21205904119899119873 )

119863( 1199101198671) = N(119875 + 1205902119899 2 (119875 + 1205902

119899)2119873 )

(8)




119899=0

1199092 (119899) gt 120574 (9)


1198791015840 (x) = 119879 (119909)1205902 = 1199092 (119899) under 11986701199092 (120582) under 1198671 (10)

where 120582 = sum119873minus1119899=0


1198791015840 (119909) = 119873minus1sum119899=0

((119904 (119899) + 119908 (119899))1205902) (11)


119864 (1198791015840 (119909) 1198670) = 119873119864 (1198791015840 (119909) 1198671) = 120582 + 119873

var (1198791015840 (119909) 1198670) = 2119873var (1198791015840 (119909) 1198671) = 4120582 + 2119873

(12)


119875FA = 119876(12057410158401205902 minus 119873radic2119873 ) (13)

119875119863 = 119876(12057410158401205902 minus (120582 + 119873)radic4120582 + 2119873 ) (14)









(19)



(20)




1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)


times 10minus9(24)

1205741015840 = 00336 (25)





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia








119910 (119899) = 119908 (119899) under 1198670119909 (119899) + 119908 (119899) under 1198671 (5)





119863(119910) =

1119873119899minus1sum119899=0


119910 (119899) 119909 (119899) lt 120574 under 1198670 (7)


119863( 1199101198670) = N(1205902119899 21205904119899119873 )

119863( 1199101198671) = N(119875 + 1205902119899 2 (119875 + 1205902

119899)2119873 )

(8)




119899=0

1199092 (119899) gt 120574 (9)


1198791015840 (x) = 119879 (119909)1205902 = 1199092 (119899) under 11986701199092 (120582) under 1198671 (10)

where 120582 = sum119873minus1119899=0


1198791015840 (119909) = 119873minus1sum119899=0

((119904 (119899) + 119908 (119899))1205902) (11)


119864 (1198791015840 (119909) 1198670) = 119873119864 (1198791015840 (119909) 1198671) = 120582 + 119873

var (1198791015840 (119909) 1198670) = 2119873var (1198791015840 (119909) 1198671) = 4120582 + 2119873

(12)


119875FA = 119876(12057410158401205902 minus 119873radic2119873 ) (13)

119875119863 = 119876(12057410158401205902 minus (120582 + 119873)radic4120582 + 2119873 ) (14)









(19)



(20)




1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)


times 10minus9(24)

1205741015840 = 00336 (25)





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia









(19)



(20)




1205902 = 1119873119873minus1sum119899=0

1199092 (119899) (22)

1205902 = 00364150000 = 24267 times 10minus9 (23)


times 10minus9(24)

1205741015840 = 00336 (25)





































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia

































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


SDR Based Energy Detection Spectrum Sensing in Cognitive...

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