Research Article A Survey of the DVB-T Spectrum: Opportunities for Cognitive Mobile …downloads.hindawi.com/journals/misy/2016/3234618.pdf · 2019. 7. 30. · devices like wireless

Research ArticleA Survey of the DVB-T Spectrum Opportunities forCognitive Mobile Users

Laacuteszloacute Csurgai-Horvaacuteth Istvaacuten Rieger and Joacutezsef Kerteacutesz

Department of Broadband Infocommunications and Electromagnetic Theory Budapest University of Technology and EconomicsEgry J Street 18 Budapest 1111 Hungary

Correspondence should be addressed to Laszlo Csurgai-Horvath csurgaihvtbmehu

Received 18 February 2016 Revised 30 May 2016 Accepted 5 July 2016

Academic Editor Janne Lehtomaki

Copyright copy 2016 Laszlo Csurgai-Horvath et alThis is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in anymedium provided the originalwork is properly cited

Cognitive radio (CR) systems are designed to utilize the available radio spectrum in an efficient and intelligent manner TerrestrialDigital Video Broadcasting (DVB-T) frequency bands are one of the future candidates for cognitive radio applications especiallybecause after digital television transition the TV white spaces (TVWS) became available for radio communication This paperdeals with the survey of the DVB-T spectrum wideband measurements were performed on mobile platform in order to studythe variation of the radio signal power in city area aboard a moving vehicle The measurement environment was a densely built-inregionwhere the properDVB-T receivingwas guaranteed by threeTV transmitters utilizing three central channel frequencies using610 746 and 770MHz In our paper the methods the applied antenna and measurement devices will be presented together withsimulated andmeasured fading statisticsThe final result is an estimation of the cognitive DVB-T spectrum utilization opportunityfurthermore a scenario is also proposed for secondary channel usage

1 Introduction

Cognitive radio is an emerging technology to utilize theradio spectrum with high efficiency The main owners ofthe spectrum the primary users (PUs) are not constrainedduring their operation while the secondary users (SUs)can operate in the same frequency band if the spectrumis free [1] It is very important to avoid the degrading ofPUrsquos quality of service (QoS) during the cognitive channelusage whereas an acceptable level of service should also beprovided for the secondary users Several technologies shouldbe applied to guarantee thesemdashsometimes contradictorymdashrequirements [2] Sensing of the spectrum and detectingthe available channels are some of the main tasks of a CRsystem The frequency range that can be utilized by theCR devices depends on the local frequency regulation andtherefore it may vary in different countries In the crowdedradio spectrum it is not a simple task to find the appropriateradio bands for cognitive terrestrial devices [3 4] This paperconcentrates on the terrestrial television bands and theirsecondary usage

In the literature numerous works are presented aboutspectrum measurements and on different technologies to

support cognitive users in better utilization of the availablebandwidth TV white space is also of a great interest due tothe digital TV transition that recently took place in severalcountries In the following an overview of this research fieldwill be given in order to put our research into context

In [5] despite the actual theory that the capacity of theradio spectrum is already achieved the underutilization ofthe spectrum is highlighted and the importance of cognitiveradio techniques is shown The paper is focusing on majortechnologies for opportunistic spectrum access through ahierarchical model approach that adopts the primary andsecondary user structure Spectrum sensing is the key tech-nology to estimating the availability of the licensed spectrumfor secondary usage In [6] the various spectrum occupancymodels used in different research campaigns worldwide werestudied and compared The authors evaluate the percentageof the whole spectrum occupied by different services Long-and short-term statistics are presented showing most of thecommercial terrestrial frequency bands (GSM TV broad-casting 3G etc) utilizing the available spectrum almostbelow 20ndash40 The experiments have been conducted invarious locations such as US Europe New Zealand South

Hindawi Publishing CorporationMobile Information SystemsVolume 2016 Article ID 3234618 11 pageshttpdxdoiorg10115520163234618

2 Mobile Information Systems

Africa China Singapore and Vietnam A similar study wasperformed in Chicago New York Washington DC and afew rural locations in 2005 between 30 and 3000MHz [7] Ina large business like Chicago low spectrum occupancy wasobserved indicating that a DSS (Dynamic Spectrum Sharing)radio system could access a huge amount of prime spec-trum as there are large unoccupied contiguous spectrumblocks The paper [8] collects previous research work carriedout worldwide and compares it with spectrum occupancymeasurements at the University of Hull UK The collectedhistorical measurements are covering also the 30ndash3000MHzband and they confirmed the generally low occupancy ofthe investigated spectrum The measurements in the UKwere performed with a similar hardware configuration towhat we also applied during our research work and willbe detailed later (spectrum analyser and computer) thefrequency range was 80ndash2700MHz For DVB-T spectrummeasurements in [9] several results can be found especiallyfor occupancy estimations serving as input for outdoor REM(Radio Environment Maps) The measurement setup wassimilar to the campaign performed in Budapest but the latterresearch is focusing also on fade duration statistics and itsconsequences as it will be later demonstrated The cellularand theUHFVHFTV bandwere studied in [10] forMalaysiaand actual spectrum utilization statistics are provided withstatic measurements The low duty cycle of the spectrumoccupancy was also proved by this study A comparativespectrum occupancy study was carried out in BarcelonaSpain andPoznan Poland [11]Themeasurement setupswereharmonized to obtain comparable results by concentratingon the problem of the efficient noise floor estimation Asa result differences have been obtained in the TETRAbands due to the different spectrum allocation regulations inthese countries This study highlights that efficient spectrumdetection is always required in order to avoid the congestionsdue to different local regulatory rules The change of theUHF TV band spectrum availability due to digital transitionin Greece is studied in [12] They proved that the spectrumavailability was significantly increased after the analogueswitch-off Furthermore the risk of LTE-4G interference toTV services and vice versa is also pointed out accordingto the spectrum measurements they carried out A generaland detailed discussion on different approaches to spectrumoccupancy measurements is provided in the relating ITUreport SM2256 [13] Unlicensed communication in the UHFband has also a great actuality Measurements in Italy Spainand Romania are presented in [14 15] in order to estimatepractical parameters to ensure the feasible and harmlessunlicensed communication in the UHF TV bands Specialdevices like wireless microphones may also utilize this bandunder strict regulatory control [16] that is also increasing theimportance of accurate spectrum sensing methods

In the present paper we demonstrate mobile measure-ments in the DVB-T spectrum by concentrating on theoccupancy statistics that can be inferred from the channelfading dynamicsWe significantly extended our former paper[17] with technical details and additional measurement routefurthermore results and conclusions are amended

SU route

Cognitive spectrum usage PU3

PU1

PU2

Figure 1 Fixed PUs and a moving SU for smart DVB-T spectrumutilization

DVB-T users are the primary owners of the televisionreceivers [18 19] In large cities like Budapest where weconducted our measurements the sufficient service requiresseveral multiplexed channels and usually more than onetransmit station DVB-T receivers are the primary users ofthis spectrum and the service provider takes care of thesufficient quality of service at the whole geographical region[20] Nevertheless in densely built-in areas and especiallyin case of hilly areas the received signal level could belocally insufficient to receive the DVB-T signal properly Inthis case by applying smart spectrum sensing technologies asecondarymobile user has an opportunity to utilize this spec-trum for different kind of short-distance communicationslike accessing locally transmitted traffic information and car-to-car communications or for general type of data transferA hypothetical scenario is depicted in Figure 1

Therefore our main goal during this survey was to inves-tigate the frequency band of the terrestrial digital televisionbroadcasting between 400 and 900MHz to have an overviewof the possibilities formobile CR applications [21] In order toachieve this goal the appropriate measurement devices hadto be selected and also designed if off-the-shelf equipmentwas not available The air interface was a custom designedwide band discone antenna For sensing the radio spectruma handheld spectrum analyser was applied As the mea-surement campaign was planned for mobile measurementsaboard a vehicle an appropriate and safe mechanical setupwas needed The route and the speed of movement wererecorded by a GPS-based navigation system

The main target of this research was twofold primarilyreceived power time series was recorded in a wide DVB-Tband while a vehicle was moving in city area Secondly byprocessing the measured data first- and second-order statis-tics were derived allowing inferring the CR opportunities inthis band

2 Measurement Location and Modelling

In the time of the measurements (122013 and 032014) inBudapest three DVB-T transmitters were operating Eachof them has multiplex channels with the standard 8MHzbandwidth providing the sufficient receiving conditions overthe whole city It is worthy of note that in the majority of the

Mobile Information Systems 3

Table 1 DVB-T transmitters in Budapest

UHF channels [MHz] Max ERP [kWdBm]CH Starting Centre Ending Szechenyi Hill 1 Harmashatar Hill 2 Szava Street 338 606 610 614 10080 95698 6267955 742 746 750 39876 9870 7168558 766 770 774 10080 74687 56675

Location LatLonASL 47∘29101584018∘581015840457m 47∘33101584019∘00443m 47∘28101584019∘071015840120m

1

2

3

Figure 2 DVB-T transmitters in Budapest (map source Google)

European countries the transition from analogue to digitalTV broadcasting technologies was finished (see for example[22]) and there are only a few countries where this is still anongoing process

In Table 1 the main transmitter parameters can be foundfor Budapest

The transmitter locations are depicted in the map shownin Figure 2 denoted with 1 2 and 3 signs It is worthmentioning that the left side of the city is hilly while the rightside is flat however transmitter 3 can be found on elevatedlocationThe arrangement of the transmitters and their powerradiated ensure the location-independent receiving despitethe geographical variability

For a first and rough estimation of the received signalpower at the different geographical positions the Okumura-Hata channel model [23] was selected to illustrate the capa-bilities and limitations of such calculations This model isvalid for 150ndash1500MHz frequency range therefore it is wellapplicable for DVB-T It is an empirical model suitable tocalculate the path loss 119871

119880for different urban areas The ℎ

119879

height of the transmit antenna and the ℎ119877receiver antenna

height are also input parameters of the model

119871119880= 6955 + 2616 log

10

119891[MHz]minus 1382 log

10

ℎ119879minus 119862119867

+ [449 minus 655 log10

ℎ119879] log10

119863[km]

(1)

119862119867is the antenna height coefficient and it is for small and

medium cities

119862119867= 08 + (11 log

10

119891[MHz]minus 07) ℎ

119877

minus 156 log10

119891[MHz]

(2)

and for big cities

119862119867

=

829 log10

(154ℎ119877)2

minus 11 150 le 119891[MHz]le 200

32 log10

(1175ℎ119877)2

minus 497 200 le 119891[MHz]le 1500

(3)

The model has limitations in range (1ndash20 km) and trans-mitter antenna height (30ndash200m) By taking into accountthat the sea level height of the city (river floor) is 90m themodel could be applied for a rough estimation of the receivedsignal level In the following this calculation is presentedwhere we considered big city model coefficients and providereceived signal power map for each transmitter frequency

To calculate with the Okumura-Hata model we posi-tioned three transmitters into a hypothetical square of 20 lowast20 km the origin of this area was N47∘251015840 and E18∘541015840The positions of the transmitters are representing their realgeographical places relatively to this origin The gain of thetransmitter antennas was selected uniformly 15 dB and thereceiver location was 3m respectively The result is depictedin Figure 3 where the transmitters are numbered accordingto Table 1

The modelled signal level in the rectangular area visu-alizes the received power at different locations produced bythe DVB-T transmitters Besides the Okumura-Hata modelthe Walfisch-Ikegami and the Lee models are compared andtested for different geographical areas in [24] In this paperthe goal of the modelling was to get a quantitative overviewof the received signal power field and therefore we selectedfor our calculations one of the best known models

Nevertheless the effect of the local variation of the envi-ronment for example shadowing of buildings reflectionsand local interferences is not visible in Figure 3 In order togenerate a more accurate power map a detailed geolocationmap would be required containing an exact database of theobject positions and dimensions across the city but such adatabase was not available for the authors

The lack of the fine structure and the variation of thesignal level on a specific route require a different approachThe description of this method and its conclusions is thefollowing subject of this paper


0 5 10 15 200

5

10

15

20

(dBm)

2

1

3

y(k

m)

x (km)

minus55 minus50 minus45 minus40 minus35 minus30 minus25

(a)

0

5

10

15

20

1

2

3

y(k

m)

0 5 10 15 20x (km)

(dBm)minus55 minus50 minus45 minus40 minus35 minus30 minus25

(b)

0 5 10 15 200

5

10

15

20

1

2

3

y(k

m)

x (km)


(c)

Figure 3 DVB-T signal power at 610MHz (a) 746MHz (b) and 770MHz (c) calculated with Okumura-Hata model

3 Receiver Antenna Design forSpectrum Sensing

Our goal was to build an all-purpose system that is capableof wide range spectral observations between 04 and 3GHzIn [25] for a similar measurement a commercially available25ndash1300MHz antennawas proposed but for our purposes weselected a customized antenna that has a broader bandwidthTherefore a special wideband antenna was designed [26] at

our department whose omnidirectional characteristic wasone of the most important requests (see Figure 4)

The requirements are well fulfilled by a discone antennathat consists of a flat disc on the top of a conical part Withinthis structure the wideband operation is mainly determinedby the conical structure The drawing and final dimensionsof the antenna can be found in Figure 4 Before antennafabrication computer simulations were done in order toprove the performance and check the main parameters


Main antenna dimensions

Cone max diameter 210mm

Cone angle 60∘

Disc diameter 150mm

Total height (wo connector) 180mm

Feed pinDisc

Copper cone Teflon holder

Cone

Coax cable

N connector

Figure 4 Antenna dimensions and simulated characteristics at 746MHz

05 1 15 2 25 3

0

2

Frequency (GHz)

Gai

n (d

Bi)

minus2

minus4

minus6

Figure 5 Simulated antenna gain and a two-channel measurement setup

The simulated antenna of a characteristic at 746MHzis depicted in Figure 4 while variation of the gain withfrequency is depicted in Figure 5 The latter figure alsoillustrates a two-antenna system assembled on the top of acar ready for mobile measurements The gain of the antennais slightly varying with the frequency and according tothe simulation it is nearly 2 dB in the investigated DVB-Tfrequency band

4 Mobile Sensing of the DVB-T Spectrum

Spectrum sensing is a secondary userrsquos task when his opera-tion is based on CR technology SUs should discover usually

a wide frequency band before they can utilize any spectraThis is an indispensable process because the main ownersof the spectrum the Pus cannot be disturbed or restrictedin their operation The air interface of this kind of sensing isusually a wideband and omnidirectional antenna Widebandsensing requires intelligent programmable received signaldetection that allows scanning the selected frequency rangeand performing fast energy detection at the single frequen-cies During our work we applied professional measurementdevices for similar purposes in order to explore the DVB-T spectrum in a larger geographical area The measurementcould be a base to qualify the DVB-T spectrum for mobilecognitive radio applications


GPS Spectrumanalyser

Figure 6 Mobile spectrum measurement setup

This section provides the detailed measurement setup forour experiments and then time series and different statisticswill be presented

In Section 2 we have seen that the modelled receivedsignal map especially in absence of a geolocation databaseof terrestrial objects cannot provide sufficient informationabout the local variability of the signal level In order toinvestigate the exact time series of the DVB-T signal poweraboard a moving vehicle a measurement with location-tagging was designed and conducted As spectrum sensingdevice a type of Agilent N9340B Handheld RF spectrumanalyser was utilized For our research purposes the flexibil-ity and precision of such ameasurement tool were an obvioussolutionThe investigated frequency band is supported by theapplied device [27] and its built-in memory was able to storethe measurement data through the whole route

Themeasurement setup for the mobile system is depictedin Figure 6 and it has the following main blocks

(i) A car equipped with a single discone antenna (seeSection 3)

(ii) A GPS device to record the route and the movingspeed (Mitac P560 PDA)

(iii) A portable spectrum analyser [27] with data storagecapability (Agilent N9340B)

(iv) A notebook to archive measurement files

To have a first look of the measured data a waterfalldiagram is a good opportunity (see Figure 8) depicting thereceived signal power in the complete frequency band for thetotal measurement period

In order to survey the DVB-T frequency band duringmovement two measurements were conducted in the cityarea of Budapest The routes are depicted in Figure 7 alsodenoting their length and duration

In order to cover the whole frequency band of the TVtransmitters the following spectrum analyser settings wereapplied

(i) Starting frequency 590MHz(ii) Stop frequency 800MHz(iii) Span 210MHz(iv) Span time 2 sec(v) Attenuation 10 dB

(vi) Bandwidth 100 kHz(vii) Reference noise power minus109 dBm

10 dB attenuation was required to keep the measuredsignal level within the analysermeasurement rangeThe 590ndash800MHz frequency band was sensed with 1022MHz stepsthus for example for a 8MHz DVB-T channel 176 sampleswere collected The spectrum analyser stores the measuredreceived power in floating point data type with two decimalplaces The antenna was connected with RG-58 type cable of3m length therefore the cable attenuation was 09 dB

TV transmitters 1 and 3 were closed by the routes(their places are marked on the maps) The speed of the carwas slightly varying but it was kept during the route as stableas possible

After processing the measurements the spectrogram andthe time series of the received power for three TV channelsare providing the first overview of the investigated spectrumIn the spectrogram and even more clearly in the receivedpower time series the strong variations of the signal levelsare well observable (Figures 8-9)

The results are indicating that the conditions of properDVB-T receiving do not always exist As the measurementwas performed in densely built-in city area and we con-sidered the movement of the car different type of channelimpairments may arise The shadowing interference andmultipath propagation could decrease the quality of serviceHowever the Okumura-Hata propagation model is a well-known tool to calculate the received signal level in built-inareas [28 29] this is a general model and cannot substitutethe real measurements like the present one allowing derivinga more accurate characterization of the mobile propagationchannel For proper DVB-T receiving primary users require50 dB120583V signal level or considering a 50Ω termination from(4) this level is minus57 dBm [30]

RPmindBm= RPmin

dB120583Vminus 90 minus 20 log (radic119885Ω)

= minus57 dBm(4)

More detailed discussion about the planning of DVB-Tservice area and the minimum field strength requirementscan be found in [31]

We will apply this threshold as an opportunity indicatorfor secondary channel usage On the other hand it shouldbe also considered that in order to minimise the harmfulinterference caused by the cognitive secondary user devicesthe TV signal sensing margin should be much lower thanthat of TV receivers required for high quality receiving [32]The hidden node problem when a primary user with goodreceiving conditions is interfered by a secondary transmittingdevice [33] is one of the reasons that cognitive devices areusually operating with lower sensing margin Neverthelessthis kind of problem is beyond the scope of this paperthe abovementioned minus57 dBm will be for us the measureof the local DVB-T signal quality As the goal of thispaper is a survey of the TVWS the investigation of somestatistical properties of the received signal time series willlead to the estimation of the secondary channel utilization


3

(a)

1

(b)

Figure 7 (a) Route 1 (229 km 58min 122013) (b) Route 2 (349 km 588min 032014) (map sources Google)

Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Figure 8 Spectrogram and received power time series at TV channel centre frequencies (Route 1)

opportunities We emphasize that for an operational cog-nitive radio application a lower sensing margin should berequired Furthermore especially to avoid the interferenceadditional techniques would be also desirable for examplepilot detection cyclostationary feature detection or cyclicprefix and autocorrelation detection [32]

To find the probability of the minimal received signallevel the Cumulative Distribution Function (CDF) of theattenuation could help To estimate a realistic receivingcondition an increased antenna gain should be appliedbecause the discone antenna is only an experimental deviceand it does not represent correctly the antenna of a standardDVB-T receiverThe applied discone antenna has sim2 dB gainnevertheless for real DVB-T receiving an antenna with 10ndash12 dB gain is recommended [34] and usually applied by PUs

The CDF of the received power indicates the probabilitythat the signal level is less than or equal to a certain value as itis depicted in Figure 10 for the two different routes If we take

into account that a standard PU has a receiving antenna withan additional 10 dB gain compared to the discone antenna inthe measurement according to (4) the probability values atminus57 minus 10 = minus67 dB are representing the thresholds of theimproper receiving conditions

One can see that the probability of insufficient DVB-T signal level is relatively high in Figure 10 these valuesare indicated for each channel Contrarily in case of thiscondition the spectrum could be utilized by the secondaryusers for their own purposes by applying CR technologies

Another aspect of the estimation of the channel impair-ment is the fade duration statistics [35]While the attenuationstatistics inform us about the probability that the fadingdepth exceeds a specified level the length of the individualfade events and thus the possible outage periods could bedetermined only from the fade duration distribution Theduration of fades can be calculated from the attenuation timeseries therefore the received power time series (see Figures 8


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1

Received power (dBm)

Prob

abili

ty

Route 1

Improper receiving conditions probabilities

minus20minus30minus40minus50minus60minus70minus80minus90

At 610MHz 008At 746MHz 022At 770MHz 015

610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2

Received power (dBm)minus40minus50minus60minus70minus80minus90

Improper receiving conditions probabilities At 610MHz 038At 746MHz 066At 770MHz 044

610MHz 746MHz770MHz

Figure 10 CDF of received power and probabilities of improper receiving conditions

and 9) should be converted For this conversion the highestmeasured received power value in the DVB-T channel wasconsidered as a reference (zero attenuation) level

Besides the fade duration in cognitive radio applicationsthe level crossing rate as another dynamics aspect of thechannel is studied in [36] for Rayleigh and Rician fastfading channels The effect of imperfections in the radioenvironment map (REM) information on the performance

of cognitive radio (CR) systems was investigated in [37] Inopportunistic channel allocation algorithms [38] the durationof fade event may play an important role Therefore inour paper we propose fade duration statistics as a tool foropportunity length estimation

Figure 11 indicates the probability of fade durations at15 dB and 20 dB attenuation levels for 10 and 60 secondsrespectively We proved with our measurements and with the


Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102

012 (D = 10 sec)002 (D = 60 sec)017 (D = 10 sec)003 (D = 60 sec)017 (D = 10 sec)003 (D = 60 sec)

610MHz

746MHz

770MHz



610MHz

746MHz

770MHz


Frequency FrequencyP (d gt D) | Th = 15dB P (d gt D) | Th = 20dB P (d gt D) | Th = 15dB P (d gt D) | Th = 20dB

Figure 11 Fade duration distribution of the 610MHz channel and probabilities of 10 and 60 sec fade events (all channels)

relating fade duration statistics that aboard a moving devicein city area the DVB-T spectrum can be used for secondarypurposes even for several seconds or for a minute durationCalculating with one-hour travelling the opportunity forsecondary channel usage during this journey is severalminutes in 10 s quanta and even some complete minutesThese are significant values that should be taken into accountif secondary channel utilization of the DVB-T spectra isplanned

For the calculations above we appliedminus57 dBm thresholdthat is according to the literature the signal level requiredfor the error-free DVB-T reception Our proposal is that thesecondary usage of the spectrum is a reality when the servicequality is insufficient for the primary users Contrarily forcognitive radio applications the protection of primary userrsquosservice quality is a key issue The appearance of secondaryusers may cause significant interference in the TVWS there-fore an advanced spectrum sensing technique is essential Astudy about this emerging technology [39] discusses that thesensing threshold is minus1128 dBm for 8MHz wide channelsshowing that high quality sensing technique is inevitable ina real CR application

5 Conclusions

In this paper we presented wideband mobile DVB-T spec-trum measurements to study the variation of the received

signal power in the TV channel frequencies Our suggestionis that for cognitive radio applications the same frequencyband is applicable if the service quality for the PUs is insuf-ficient It may happen in densely built-in city areas that dueto shadowing reflections or interference the DVB-T signalquality is improper for primary usage This fact has beenproved by the measurements In this case of short-distancecommunications for example for car-to-car data transfer oraccess local traffic information databases or even for self-driving vehicles the DVB-T spectrum could be utilized Inthe paper the antenna design for spectrum detection theapplied spectrum sensing hardware measurement methodsand their statistics were shown After the evaluation of theresults it was proven that for mobile CR users it is possible toutilize the DVB-T band with intelligent devices for secondarypurposes even without decreasing the QoS of the primaryusers

Competing Interests

The authors declare that they have no competing interests

References

[1] 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


[2] O Simeone J Gambini Y Bar-Ness and U SpagnolinildquoCooperation and cognitive radiordquo in Proceedings of the IEEEInternational Conference on Communications (ICC rsquo07) pp6511ndash6515 Glasgow UK June 2007

[3] E Axell G Leus and E G Larsson ldquoOverview of spectrumsensing for cognitive radiordquo in Proceedings of the 2nd Interna-tional Workshop on Cognitive Information Processing (CIP rsquo10)pp 322ndash327 Elba Italy June 2010

[4] A Garhwal and P P Bhattacharya ldquoA survey on spectrumsensing techniques in cognitive radiordquo International Journal ofComputer Science and Communication Networks vol 1 no 2pp 196ndash206 2011

[5] Q Zhao and B M Sadler ldquoA survey of dynamic spectrumaccessrdquo IEEE Signal Processing Magazine vol 24 no 3 pp 79ndash89 2007

[6] D Das and S Das ldquoA survey on spectrum occupancy measure-ment for cognitive radiordquo Wireless Personal Communicationsvol 85 no 4 pp 2581ndash2598 2015

[7] M A McHenry P A Tenhula D McCloskey D A Robersonand C S Hood ldquoChicago spectrum occupancy measurementsamp analysis and a long-term studies proposalrdquo in Proceedingsof the 1st International Workshop on Technology and Policy forAccessing Spectrum (TAPAS rsquo06) article 1 ACM Boston MassUSA 2006

[8] M Mehdawi N Riley M Ammar and M Zolfaghari ldquoCom-paring historical and current spectrum occupancy measure-ments in the context of cognitive radiordquo in Proceedings of the20th Telecommunications Forum (TELFOR rsquo12) pp 623ndash626Belgrade Serbia November 2012

[9] A Kliks P Kryszkiewicz K Cichon A Umbert J Perez-Romero and F Casadevall ldquoDVB-T channels measurementsfor the deployment of outdoor REM databasesrdquo Journal ofTelecommunications and Information Technology no 3 pp 42ndash52 2014

[10] S Jayavalan H Hafizal N M Aripin et al ldquoMeasurements andanalysis of spectrum occupancy in the cellular and TV bandsrdquoLecture Notes on Software Engineering vol 2 no 2 pp 133ndash1382014

[11] A Kliks P Kryszkiewicz J Perez-Romero A Umbert andF Casadevall ldquoSpectrum occupancy in big cities-comparativestudy Measurement campaigns in Barcelona and Poznanrdquo inProceedings of the 10th International Symposium on WirelessCommunication Systems (ISWCS rsquo13) pp 1ndash5 Ilmenau Ger-many August 2013

[12] P I Lazaridis S Kasampalis Z D Zaharis et al ldquoUHFTVbandspectrum and field-strength measurements before and afteranalogue switch-offrdquo in Proceedings of the 2014 4th InternationalConference on Wireless Communications Vehicular Technol-ogy Information Theory and Aerospace and Electronic Systems(VITAE rsquo14) pp 1ndash5 Aalborg Denmark May 2014

[13] ITU-R ldquoSpectrum occupancy measurements and evaluationrdquoReport ITU-R SM2256 2012

[14] P AngueiraM Fadda JMorgadeMMurroni andV PopesculdquoField measurements for practical unlicensed communicationin the UHF bandrdquo Telecommunication Systems vol 61 no 3 pp443ndash449 2016

[15] M Fadda V PopescuMMurroni P Angueira and JMorgadeldquoOn the feasibility of unlicensed communications in the TVwhite space field measurements in the UHF bandrdquo Interna-tional Journal of Digital Multimedia Broadcasting vol 2015Article ID 319387 8 pages 2015

[16] Federal Communications Commission ldquoSpectrum access forwireless microphone operationsrdquo FCC Record FCC-14-145Federal Communications Commission 2014

[17] L Csurgai-Horvath I Rieger and J Kertesz ldquoMobile accessof the DVB-T channel and the opportunity for cognitivespectrum utilizationrdquo in Proceedings of the 17th InternationalConference on Transparent Optical Networks (ICTON rsquo15) pp1ndash4 Budapest Hungary July 2015

[18] W Van den Broeck and J Pierson Digital Television in EuropeVUBpress Brussels Belgium 2008

[19] U Reimers DVB The Family of International Standards forDigital Video Broadcasting Springer Berlin Germany 2004

[20] D Noguet R Datta P H Lehne M Gautier and G FettweisldquoTVWS regulation and QoSMOS requirementsrdquo in Proceedingsof the 2nd International Conference onWireless CommunicationVehicular Technology Information Theory and Aerospace ampElectronic Systems Technology (Wireless VITAE rsquo11) pp 1ndash5Chennai India February 2011

[21] B Wild and K Ramchandran ldquoDetecting primary receiversfor cognitive radio applicationsrdquo in Proceedings of the 1stIEEE International Symposium on New Frontiers in DynamicSpectrum Access Networks (DySPAN rsquo05) pp 124ndash130 IEEEBaltimore Md USA November 2005

[22] R A Saeed and S J Shellhammer Eds TV White Space Spec-trum Technologies Regulations Standards and ApplicationsCRC Press New York NY USA 2012

[23] MHata ldquoEmpirical formula for propagation loss in landmobileradio servicesrdquo IEEE Transactions on Vehicular Technology vol29 no 3 pp 317ndash325 1980

[24] P M Ghosh Md A Hossain A F M Zainul Abadin and KK Karmakar ldquoComparison among different large scale pathloss models for high sites in urban suburban and rural areasrdquoInternational Journal of Soft Computing and Engineering vol 2no 2 2012

[25] A Martian C Vladeanu I Marcu and I Marghescu ldquoEval-uation of spectrum occupancy in an urban environment in acognitive radio contextrdquo International Journal on Advances inTelecommunications vol 3 no 3-4 2010

[26] K-H Kim J-U Kim and S-O Park ldquoAn ultrawide-banddouble discone antenna with the tapered cylindrical wiresrdquoIEEE Transactions on Antennas and Propagation vol 53 no 10pp 3403ndash3406 2005

[27] Agilent N9340B Handheld RF Spectrum Analyzer (HSA) 3GHz User Manual

[28] ITU ldquoPredictionmethods for the terrestrial landmobile servicein the VHF andUHF bandsrdquo ITU-R Recommendation P 529-2ITU Geneva Switzerland 1995

[29] A Medeisis and A Kajackas ldquoOn the use of the universalOkumura-Hata propagation prediction model in rural areasrdquoin Proceedings of the IEEE 51st Vehicular Technology ConferenceProceedings vol 3 pp 1815ndash1818 Tokyo Japan May 2000

[30] ROVER Laboratories SpA ldquoUnderstanding Digital TVrdquo 2013httpwwwroverinstrumentscom

[31] E P J Tozer Broadcast Engineerrsquos Reference Book Taylor ampFrancis London UK 2012

[32] M Nekovee ldquoA survey of cognitive radio access to TV whitespacesrdquo International Journal of Digital Multimedia Broadcast-ing vol 2010 Article ID 236568 11 pages 2010

[33] Ofcom ldquoStatement on Cognitive Access to Interleaved Spec-trumrdquo July 2009

[34] ITU ldquoDVB-T coverage measurements and verification of plan-ning criteriardquo ITU-R Recommendation SM1875-2 ITU 2014


[35] ITU-R Rec P1623-1 Prediction method of fade dynamics onEarth-space paths 2005

[36] M F Hanif and P J Smith ldquoLevel crossing rates of interferencein cognitive radio networksrdquo IEEE Transactions on WirelessCommunications vol 9 no 4 pp 1283ndash1287 2010

[37] M F Hanif P J Smith andM Shafi ldquoPerformance of cognitiveradio systems with imperfect radio environment map informa-tionrdquo in Proceedings of the Australian Communications TheoryWorkshop (AusCTW rsquo09) pp 61ndash66 IEEE Sydney AustraliaFebruary 2009

[38] H Shatila M Khedr and J H Reed ldquoOpportunistic channelallocation decision making in cognitive radio communica-tionsrdquo International Journal of Communication Systems vol 27no 2 pp 216ndash232 2014

[39] C Kocks A Viessmann P Jung L Chen Q Jing and R Q HuldquoOn spectrum sensing for TV white space in Chinardquo Journal ofComputer Networks and Communications vol 2012 Article ID837495 8 pages 2012

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Distributed Sensor Networks


Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014


ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014


Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Electrical and Computer Engineering

Journal of

Journal of

Computer Networks and Communications


Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia


Biomedical Imaging


ArtificialNeural Systems

Advances in


RoboticsJournal of



Computational Intelligence and Neuroscience

Industrial EngineeringJournal of


Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in



Africa China Singapore and Vietnam A similar study wasperformed in Chicago New York Washington DC and afew rural locations in 2005 between 30 and 3000MHz [7] Ina large business like Chicago low spectrum occupancy wasobserved indicating that a DSS (Dynamic Spectrum Sharing)radio system could access a huge amount of prime spec-trum as there are large unoccupied contiguous spectrumblocks The paper [8] collects previous research work carriedout worldwide and compares it with spectrum occupancymeasurements at the University of Hull UK The collectedhistorical measurements are covering also the 30ndash3000MHzband and they confirmed the generally low occupancy ofthe investigated spectrum The measurements in the UKwere performed with a similar hardware configuration towhat we also applied during our research work and willbe detailed later (spectrum analyser and computer) thefrequency range was 80ndash2700MHz For DVB-T spectrummeasurements in [9] several results can be found especiallyfor occupancy estimations serving as input for outdoor REM(Radio Environment Maps) The measurement setup wassimilar to the campaign performed in Budapest but the latterresearch is focusing also on fade duration statistics and itsconsequences as it will be later demonstrated The cellularand theUHFVHFTV bandwere studied in [10] forMalaysiaand actual spectrum utilization statistics are provided withstatic measurements The low duty cycle of the spectrumoccupancy was also proved by this study A comparativespectrum occupancy study was carried out in BarcelonaSpain andPoznan Poland [11]Themeasurement setupswereharmonized to obtain comparable results by concentratingon the problem of the efficient noise floor estimation Asa result differences have been obtained in the TETRAbands due to the different spectrum allocation regulations inthese countries This study highlights that efficient spectrumdetection is always required in order to avoid the congestionsdue to different local regulatory rules The change of theUHF TV band spectrum availability due to digital transitionin Greece is studied in [12] They proved that the spectrumavailability was significantly increased after the analogueswitch-off Furthermore the risk of LTE-4G interference toTV services and vice versa is also pointed out accordingto the spectrum measurements they carried out A generaland detailed discussion on different approaches to spectrumoccupancy measurements is provided in the relating ITUreport SM2256 [13] Unlicensed communication in the UHFband has also a great actuality Measurements in Italy Spainand Romania are presented in [14 15] in order to estimatepractical parameters to ensure the feasible and harmlessunlicensed communication in the UHF TV bands Specialdevices like wireless microphones may also utilize this bandunder strict regulatory control [16] that is also increasing theimportance of accurate spectrum sensing methods

In the present paper we demonstrate mobile measure-ments in the DVB-T spectrum by concentrating on theoccupancy statistics that can be inferred from the channelfading dynamicsWe significantly extended our former paper[17] with technical details and additional measurement routefurthermore results and conclusions are amended

SU route

Cognitive spectrum usage PU3

PU1

PU2

Figure 1 Fixed PUs and a moving SU for smart DVB-T spectrumutilization

DVB-T users are the primary owners of the televisionreceivers [18 19] In large cities like Budapest where weconducted our measurements the sufficient service requiresseveral multiplexed channels and usually more than onetransmit station DVB-T receivers are the primary users ofthis spectrum and the service provider takes care of thesufficient quality of service at the whole geographical region[20] Nevertheless in densely built-in areas and especiallyin case of hilly areas the received signal level could belocally insufficient to receive the DVB-T signal properly Inthis case by applying smart spectrum sensing technologies asecondarymobile user has an opportunity to utilize this spec-trum for different kind of short-distance communicationslike accessing locally transmitted traffic information and car-to-car communications or for general type of data transferA hypothetical scenario is depicted in Figure 1

Therefore our main goal during this survey was to inves-tigate the frequency band of the terrestrial digital televisionbroadcasting between 400 and 900MHz to have an overviewof the possibilities formobile CR applications [21] In order toachieve this goal the appropriate measurement devices hadto be selected and also designed if off-the-shelf equipmentwas not available The air interface was a custom designedwide band discone antenna For sensing the radio spectruma handheld spectrum analyser was applied As the mea-surement campaign was planned for mobile measurementsaboard a vehicle an appropriate and safe mechanical setupwas needed The route and the speed of movement wererecorded by a GPS-based navigation system

The main target of this research was twofold primarilyreceived power time series was recorded in a wide DVB-Tband while a vehicle was moving in city area Secondly byprocessing the measured data first- and second-order statis-tics were derived allowing inferring the CR opportunities inthis band

2 Measurement Location and Modelling

In the time of the measurements (122013 and 032014) inBudapest three DVB-T transmitters were operating Eachof them has multiplex channels with the standard 8MHzbandwidth providing the sufficient receiving conditions overthe whole city It is worthy of note that in the majority of the





1

2

3







119879



119871119880= 6955 + 2616 log

10


10

ℎ119879minus 119862119867

+ [449 minus 655 log10

ℎ119879] log10

119863[km]

(1)


medium cities

119862119867= 08 + (11 log

10


119877

minus 156 log10

119891[MHz]

(2)

and for big cities

119862119867

=

829 log10

(154ℎ119877)2

minus 11 150 le 119891[MHz]le 200

32 log10

(1175ℎ119877)2

minus 497 200 le 119891[MHz]le 1500

(3)







0 5 10 15 200

5

10

15

20

(dBm)

2

1

3

y(k

m)

x (km)


(a)

0

5

10

15

20

1

2

3

y(k

m)

0 5 10 15 20x (km)


(b)

0 5 10 15 200

5

10

15

20

1

2

3

y(k

m)

x (km)


(c)









Cone angle 60∘

Disc diameter 150mm


Feed pinDisc


Cone

Coax cable

N connector


05 1 15 2 25 3

0

2

Frequency (GHz)

Gai

n (d

Bi)

minus2

minus4

minus6

























RPmindBm= RPmin


= minus57 dBm(4)




3

(a)

1

(b)


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz









Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in







1

2

3







119879



119871119880= 6955 + 2616 log

10


10

ℎ119879minus 119862119867

+ [449 minus 655 log10

ℎ119879] log10

119863[km]

(1)


medium cities

119862119867= 08 + (11 log

10


119877

minus 156 log10

119891[MHz]

(2)

and for big cities

119862119867

=

829 log10

(154ℎ119877)2

minus 11 150 le 119891[MHz]le 200

32 log10

(1175ℎ119877)2

minus 497 200 le 119891[MHz]le 1500

(3)







0 5 10 15 200

5

10

15

20

(dBm)

2

1

3

y(k

m)

x (km)


(a)

0

5

10

15

20

1

2

3

y(k

m)

0 5 10 15 20x (km)


(b)

0 5 10 15 200

5

10

15

20

1

2

3

y(k

m)

x (km)


(c)









Cone angle 60∘

Disc diameter 150mm


Feed pinDisc


Cone

Coax cable

N connector


05 1 15 2 25 3

0

2

Frequency (GHz)

Gai

n (d

Bi)

minus2

minus4

minus6

























RPmindBm= RPmin


= minus57 dBm(4)




3

(a)

1

(b)


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz









Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




0 5 10 15 200

5

10

15

20

(dBm)

2

1

3

y(k

m)

x (km)


(a)

0

5

10

15

20

1

2

3

y(k

m)

0 5 10 15 20x (km)


(b)

0 5 10 15 200

5

10

15

20

1

2

3

y(k

m)

x (km)


(c)









Cone angle 60∘

Disc diameter 150mm


Feed pinDisc


Cone

Coax cable

N connector


05 1 15 2 25 3

0

2

Frequency (GHz)

Gai

n (d

Bi)

minus2

minus4

minus6

























RPmindBm= RPmin


= minus57 dBm(4)




3

(a)

1

(b)


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz









Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in






Cone angle 60∘

Disc diameter 150mm


Feed pinDisc


Cone

Coax cable

N connector


05 1 15 2 25 3

0

2

Frequency (GHz)

Gai

n (d

Bi)

minus2

minus4

minus6

























RPmindBm= RPmin


= minus57 dBm(4)




3

(a)

1

(b)


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz









Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in






















RPmindBm= RPmin


= minus57 dBm(4)




3

(a)

1

(b)


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz









Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




3

(a)

1

(b)


Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

010

0

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

0 10 20 30 40 50 60Time (min)minus10

minus20

minus30

minus40

minus50

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus60

minus70

minus80

minus90

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz









Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




Frequency (MHz)

Tim

e (m

in)

590 640 690 740 790

0

10

20

30

40

50

0

minus50

minus100

0

minus50

minus100

0

minus50

minus100

minus40

minus50

minus60

minus70

minus80

minus90

0 10 20 30 40 50 60Time (min)

610MHz

0 10 20 30 40 50 60Time (min)

746MHz

0 10 20 30 40 50 60Time (min)

770MHz

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)

Rece

ived

pow

er(d

Bm)


0

01

02

03

04

05

06

07

08

09

1


Prob

abili

ty

Route 1




610MHz 746MHz770MHz

0

01

02

03

04

05

06

07

08

09

1

Prob

abili

ty

Route 2



610MHz 746MHz770MHz







Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




Time (sec)

Prob

abili

tyRoute 1 Route 2

100

100

10minus1

10minus2

Prob

abili

ty

100

10minus1

10minus2

15dB20dB25dB

30dB35dB

15dB20dB25dB

30dB35dB

101 102

Time (sec)100 101 102


610MHz

746MHz

770MHz



610MHz

746MHz

770MHz






5 Conclusions



Competing Interests


References

















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in


















































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in
















Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in










Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in



Documents

Research Article A Survey of the DVB-T Spectrum: Opportunities for Cognitive Mobile …downloads.hindawi.com/journals/misy/2016/3234618.pdf · 2019. 7. 30. · devices like wireless