spectrum occupancy analysis based on radio

7/29/2019 Spectrum Occupancy Analysis Based on Radio

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Spectrum Occupancy Analysis Based on Radio

Monitoring Network

Dezhang Chen1, Jingjing Yang

2, Jida Wu

1, Hao Tang

1, Ming Huang

2*

1

Radio Monitoring Center of Yunnan province,Kunming, Yunnan, China

[email protected]

2

Wireless and innovation Lab, School of Information Science& Engineering, Yunnan University, Kunming, Yunnan, China

*[email protected]

AbstractAs the demand for wireless communication system

grows, the need for radio spectrum increases accordingly. In this

context, cognitive radio has emerged as a breakthrough for

effective utilization of radio spectrum. In order to realize

dynamic spectrum management in the future, it is imperative to

possess a thorough understanding about how wireless spectrum

behaves over time, frequency, and space, etc. In this paper, we

report the spectrum occupancy measurement campaign

conducted in the frequency range of 20-3000MHz based on the

radio monitoring network in Yunnan Province. Spectrum

occupancy with space and time dependent characteristic at sixtypical fixed stations are obtained. The measurement results

show relatively low spectrum occupancy with great potential for

dynamic usage of spectrum. Besides, the ambient noise has a

great influence on the measurement results, thus its calibration is

a key issue in radio monitoring which is based on energy

detection.

Keywords-Spectrum Monitoring; Dynamic spectrum access;

Energy detection

I. INTRODUCTIONRadio spectrum is a finite resource for wireless

communication. In order to share this resource the spectrumallocation policy which provides fixed allocation to licenseuser has been adopted since a hundred years ago. Althoughthis fixed spectrum allocation policy has been successful inavoiding the harmful interference that jeopardizes the qualityof delivered service, the efficiency of the radio spectrumutilization is rather low[1]. Due to the explosive growth ofwireless communications, the requirement for spectrum isexpanding rapidly, and radio spectrum becomes increasinglyscarce. Radio spectrum resources have become a bottleneckthat restrains the development of future wirelesscommunication systems [2, 3]. It is widely accepted that thefixed allocation scheme is inefficient for spectrum, and theFederal Communications Commission (FCC) is keenly

interested in new technologies which might mitigate this strain [4].Cognitive radio (CR) which is also known as dynamic

spectrum access, introduced by Mitola [5] has opened up anavenue for effective utilization of radio spectrum. CR is anintelligent radio system [6] that is capable of sensing itsenvironment, and adapting its physical operating parameterssuch as transmit power, carrier frequency and modulationaccordingly, for effective use of spectrum. This technologyenables the unlicensed users to identify an unoccupiedspectrum band to exploit temporarily, and then vacate whennecessary without harmful interference to the licensed users.

Recently, CR has attracted a great deal of attention [7-12]. Themeasurement of radio environment to understand the currentspectrum usage of the different wireless services in terms offrequency, time, and space is an important step towards thedynamic spectrum management in the future. Severalspectrum surveys, in different part of the world, have beenconducted. The spectrum occupancy measurements areperformed in Chicago a business of America [7]. Theobserved low spectrum occupancy indicates that a huge

amount of prime spectrum is available for dynamic spectrumaccess. An occupancy measurement campaign is conducted inthe frequency range between 806 MHz and 2750 MHz inurban Auckland, New Zealand [8] with the purpose ofidentifying the potential spectrum opportunities for CR. Theanalyses indicate that, on average, the actual spectral usage inthis band is only about 6.2%. Point-to-point links and somemobile uplink channels are identified as the most probablecandidates for future CR operations. A spectrum survey isconducted in the suburban of Mumbai, India [9] for thefrequency span of 700-2700MHz. The measurement results oftwo weekdays campaign shows the spectrum occupancy isconsiderably low and a substantial amount of spectrum couldbe considered for dynamic spectrum use. A 24-hour spectrum

usage pattern is studied in the frequency bands ranging from80MHz-5850MHz in Singapore [10]. The results suggest thatSingapore has a great potential for employing emerging CRtechnology to accommodate enormous demands for futurewireless services. Spectrum monitoring surveys are conductedin Johor Bahru, Malaysia[11], and Chengdu, China [12]. Theobtained results demonstrate significant amount of spectrum inTV band is available for deployment of cognitive radiosystems.

In this work, we conducted spectrum occupancymeasurement campaign based on the radio monitoringnetwork with 150 stations in Yunnan Province. Themeasurement results of six typical fixed stations that located in

Kunming, Qujing and Zhaotong Cities of Yunnan Province areanalyzed in detail. The goal of this campaign is to evaluate thespectrum occupancy in the frequency range of 20 to 3000

MHz. We report the occupancy statistics band by band. Thefrequency bands which could be considered for dynamic

spectrum access in the future are discussed.

II. MEASUREMENT SYSTEMA diagram of the spectrum monitoring network is shown in

Fig. 1. The Radio Monitoring Control Center (Longitude: 102o39 25 - East, Latitude: 24o 59 20- North) is located in

First IEEE International Conference on Communications in China: Wireless Networking and Applications (WNA)

978-1-4673-2815-9/12/$31.00 2012 IEEE 739


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Kunming, the capital city of Yunnan province. It is near theDianchi lake and in the residential zone not having anybusiness center or industrial zone. The center station isconnected to the fixed radio monitoring stations in Kunmingand in the other states of Yunnan Province via Ethernet. It isequipped with a fixed radio monitoring station of model TCI745 which is compliant with ITU recommendations. It has ahigh dynamic range and excellent co-channel frequency

resolution. Digital signal processing and multi-channel receiverare unsurpassed for dealing with crowded HF signalenvironments. The monitoring station is connected to an omnidirectional active antenna having frequency range of 20-3000MHz. The antenna is fixed on a 25m tower that is locatedon the roof of the office building of the Radio MonitoringControl Center. In what follows, the spectrum monitoringcampaign was performed at the center monitoring station, andcombined with the other 5 fixed stations which were connectedto the radio monitoring network, and the spectrum occupancyis analyzed in detail. Here, the other five fixed stations includeWuhua station (St1, Longitude: 102

o4222 - East, Latitude:

25o

3 3- North) in the center of Kunming, Mingzhai-Dongcheng Station (St2, Longitude: 102o 44 25 - East,

Latitude: 25o 0.846- North) that is near Kunming WujiabaInternational Airport, Chenggong Station (St3, Longitude: 102o4741 - East, Latitude: 24o 5351- North) in the suburbandistrict of Kunming, Wutai Mountains Station (St4, Longitude:103o 550.4 - East, Latitude: 25o 3142- North) which islocated in the suburban district of Qujing City in the east ofKunming, and the Qiaojia Station (St5, Longitude: 102

o55

52 - East, Latitude: 26o

5419- North) which is located atQiaojia County of Zhaotong City in the northeast of YunnanProvince. St1, St2 and St3 are equipped with ESMBMonitoring Receivers. St4 is equipped with a TCI monitoringsystem, while St5 is equipped with EB110 a small scalespectrum monitoring station.

Figure 1. Radio monitoring network in Yunnan Province.

III. MEASUREMENT RESULTS AND ANAYSISA. Ambinet noise and duty cycle

For each station, the spectrum monitoring is performed overtwo weekdays as suggested in [13].The scanning step size is200kHz thus given 14901 measurement point in the wholefrequency range of 20-3000MHz. For each measurement point,more than one hundred power levels can be received in an

hour. Therefore, for each measurement point we have receivedmore than two thousand data samples in one day from 1:00 to23:00. Taking the Center station as an example, the spectrummonitoring campaign is performed from Apr. 2 to Apr. 4,2012. The average received power as a function of frequencyobtained at about 14:00 in Apr. 2, 2012 is shown in Fig. 3(Solid blue line). The red line denotes the ambient noise of thedevice. This plot shows that in many bands, the averagereceived power level is below the ambient noise level. In thefollowing sections, the whole frequency range is divided into16 sub bands for spectrum occupancy analysis. Averageambient noise in each band for the center station and other fivefixed stations used in the spectrum monitoring campaign is

illustrated in Table I.Spectrum occupancy, also known as duty cycle, is animportant parameter in the assignment of frequency bands,and in further monitoring of their usage. It represents thedegree the frequency band that is occupied over theobservation period. Generally, the spectrum occupancy isdefined as the received signal strength during an observationthat is above the ambient noise. In this work, the amount ofthe effective power levels (Ne) that is above the ambient noiseand the total power levels (Nt) at each sub bands illustrated inTable I are estimated; the average spectrum occupancy at eachsub band is calculated by Ne/Nt. For the present spectrummonitoring stations which is based on energy detectionprinciple, the ambient noise is a threshold which has a great

impact on evaluation of spectrum occupancy. Selectingthreshold too low would result in a very conservativeoccupancy estimate that decides the channel is in use due tothe presence of ambient noise. On the other hand selection ofhigh decision threshold may lead to under estimation ofspectrum occupancy. Therefore, the calibration of ambientnoisy is a key issue in radio monitoring. In the context of thedevelopment of CR, the other detection methods [14, 15]including matched-filtering, cyclostationarity-based Sensing,waveform-based sensing, and radio identification basedsensing, become research hotspots.

Figure 2. Average received power versus frequency obtained at the Centerstation.

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Table I Sub frequency bands and ambient noise.

Average ambient Noise (dBm)Band Frequencyspan

(MHz)CenterStation

St1

St2 St3 St4 St5

1 20-87.5 -95 -106 -88 -98 -97 -105

2 87.8-108 -85 -106 -94 -97 -100 -94

3 108-223 -99 -105 -96 -98 -102 -106

4 223-400.05 -102 -104 -94 -97 -106 -107

5 400.05-470 -98 -104 -94 -97 -108 -1086 470-566 -91 -104 -94 -97 -108 -108

7 566-606 -102 -105 -94 -97 -110 -108

8 606-806 -102 -104 -94 -97 -109 -97

9 806-890 -102 -104 -94 -97 -109 -106

10 890-960 -91 -97 -85 -91 -105 -100

11 960-1215 -102 -105 -94 -97 -108 -106

12 1215-1710 -103 -105 -94 -97 -107 -108

13 1710-1880 -98 -104 -92 -97 -105 -110

14 1880-2170 -104 -105 -93 -97 -108 -110

15 2170-3000 -106 -105 -93 -96 -108 -109

B. Spectrum occupancy analysisIn this section, we present the spectrum occupancy details

of the frequency bands allocated for different wireless services.Taking the center station as an example, the spectrummonitoring campaign is performed for three days. The averageduty cycles for each sub band in every day are shown in TableII. From lower to higher frequency side, each sub band is

sorted from 1 to 15. Detailed wireless services for each bandare illustrated in column three of Table II. For the other fivefixed radio monitoring stations, the average occupancy circlesfor each band are also computed in the same way, and theaverage spectrum usages are 13.5%, 6.9%, 7.2%, 5% and 4%,respectively. To compare the spectrum occupancy of differentlocations, the duty circles obtain at each monitoring station areplotted in the form of histograms, as shown in Fig. 3.

From Fig. 3, we can clearly observe that the spectrumoccupancy is highly dependent on location. For example, subband 1 (20-87.5MHz) is assigned for Fixed/Mobile, MaritimeMobile Service, and Aeronautical radionavigation service. Atthe center station and the other two stations (St2 and St3)which are located in the suburban district of Kunming, thespectrum occupancy is larger than 20%. But at St1, St4 andSt5, the detected spectrum occupancy is lower than 7%.Especially for St1, which is located at the center of Kunming,the spectrum occupancy for this sub band is below 2%.

Sub band 2 (87.5-108MHz) is assigned for FM broadcastservice. At all the six monitoring stations, the detectedspectrum occupancy for this sub band is above 10%. Takingthe measurement results of the Center station as an example,the relation between spectrum occupancy and time at this subband is plotted in Fig. 4. It is seen that some FM channels,such as FM 99, FM 100.8, FM 101.7, and FM 95.4 are idlefrom 1:00 to 5:00 in the early morning.

Table II Spectrum occupancy of each sub band measured at the Center stat ion.

Band Frequencyspan(MHz)

services Averageduty cycle

day1

Average

duty cycle

day2

Average

duty cycle

day3

Average

of three

days

Occupied

spectrum

(MHz)

1 20-87.5 UHF TV, Fixed/Mobile, Maritime MobileService, Aeronautical radionavigation service

33.5% 37.2% 36.4% 35.7% 24.12 87.5-108 FM broadcast 64.3% 66.8% 65.1% 65.4% 13.43 108-223 Aeronautical radionavigation service,Radiodetermination service, Space research

service23.9% 26.3% 26.4% 25.5% 29.3

4 223-400.05 Fixed/Mobile, Aeronautical mobile-satelliteservice

12.6% 12.9% 12.7% 12.7% 22.55 400.05-470 UHF TV, Meteorological aids service, Earth

exploration-satellite service15.2% 15.2% 14.9% 15.1% 10.7

6 470-566 UHF TV, Space research service 61.6% 61.6% 61.5% 61.6% 59.17 566-606 Fixed/Mobile, Radiodetermination service 7.7% 8.4% 8.4% 8.2% 3.38 606-806 Fixed/Mobile, UHF TV 18.8% 19.2% 19.2% 19.1% 38.29 806-890 Fixed/Mobile, Radiodetermination service 22.2% 22.4% 22.3% 22.3% 18.710 890-960 GSM900 42.3% 43.3% 42.4% 42.7% 29.911 960-1215 Aeronautical radionavigation service 7.4% 8.2% 7.4% 7.7% 19.612

1215-1710 Radiodetermination service, Aeronautical

radionavigation service, Earth exploration-satellite service, Radio astronomy service,

Mobile-satellite service, Meteorological aids

service

0.6% 0.57% 0.5% 0.6% 3.0

13 1710-1880 GSM 1880 28.2% 29.3% 28.6% 28.7% 48.814 1880-2170 3G 9.8% 10% 10.3% 10% 29.015 2170-3000 SM, BWA 6.9% 7.1% 6.9% 7% 58.1

Total occupied bandwidth (MHz) 407.7

Total available bandwidth(MHz) 2980

Average spectrum usage (%) 13.7%

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Figure 3. Band by band spectrum occupancy. (a) Center Station. (b) WuhuaStation (St1). (c) Mingzhai-Dongcheng Station (St2). (d) Chenggong Station

(St3). (e) Wutai Mountains Station (St4). (f) Qiaojia Station (St5).

Figure 4. The relation between spectrum occupancy and time for the sub band

2 (87.5-108MHz) obtained at the Center Station (Apr. 2, 2012).

Sub band 3 (108-223MHz) and 4 (223-400.5MHz) areassigned for Aeronautical radionavigation service,

Radiodetermination service, Space research service Fixed/Mobile, and Aeronautical mobile-satellite service, etc. At thesesub bands, the spectrum occupancy varies distinctly withlocation. For example, at the Center Station which is in the


6 (470-566MHz) obtained at the Center Station (Apr. 2, 2012).

suburban district of Kunming, the detected spectrumoccupancy for these sub band is more than 15%; but at St1

which is located at the center of Kunming, the detect spectrumoccupancy indicates that these sub bands are almost idle. Sub

band 5 (400.5-470MHz) is assigned for meteorological aidsservice, earth exploration-satellite service, etc. From Fig. 3,we can observe that the spectrum occupancy is quit low forthis sub band at most locations, especially at St1, the detectedspectrum occupancy for this sub band is low than 1%.

Sub band 6 (470-566MHz) is assigned for UHF TV andSpace research service. The relation between spectrumoccupancy and time of this sub band detected at the CenterStation is plotted in Fig. 5. For a TV band, the span is 8MHz.

From Fig. 5, we can clearly observe that only five channels arein use in this sub band, that is, Channel 13 (470-478 MHz),Channel 15 (486-494 MHz), Channel 18 (510-518 MHz),Channel 21 (534-542 MHz) and Channel 23 (550-558 MHz).It means that a large portion of spectrum in this assigned subband is idle in a whole day. Besides, in Fig. 3, it is worth tonote that the spectrum occupancy of sub band 6 also shows ageographical dependent characteristic. The detected spectrumoccupancy at the Center station, St1, St2, St3 and St5 for thissub band varies from 10% to 60%. But at St4, the detectedspectrum occupancy is near zero. This is due to the factor thatSt4 is a highland radio monitoring station which is located atthe top of Wutai mountain with altitude of more than two

thousands meters. The deployment of the highland station haseffectively overcome the influence of surrounding buildingson the transmission of radio wave in urban environment. It ismuch more efficient in the monitoring and direction finding ofillegal access. Since Yunnan Province is situated in amountainous area, we have deployed many highlandmonitoring stations.

Sub bands 7 (566-606MHz), 11(960-1215MHz) and 12(1215-1710MHz) are assigned for Fixed/Mobile, Radio-determination service, Aeronautical radionavigation service,Radio astronomy service and Meteorological aids service, etc.The spectrum occupancy of these sub bands is dependent on

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geographical position. For example, at St1 which is located atthe center of Kunming, the detected spectrum occupancy forsub band 12 is above 10%, but the spectrum occupancy for thesame sub band detected by the other stations is nearly zero.Besides, from Fig.3 we can also observe that the spectrumoccupancy of sub band 15 (2170-3000MHz) measured bymost of these monitoring stations is quite low except St1. Thisis due to the factor that this sub band includes scientific &

medical service, broad band wireless access service. Thebroad band wireless services (WiFi) are employed in theindoor environment and wireless hotspots. The transmittingpower is relatively low, and then only St1 has detected thesesignals. This indicates that the occupancy or idle state of anassigned spectrum band cannot be simply revealed by themeasurement result of a single radio station. Therefore, theestablishing of the radio monitoring network is very important,and more stations will be added into the network in the future.

Sub band 8 (606-806MHz) is assigned for Fixed/Mobileservice and UHF TV. The relation between spectrumoccupancy and time in this sub band is shown in Fig. 6. It is





seen that the Only Channel 32 (662-670 MHz), Channel35(686-694 MHz) and Channel 47 (782-790 MHz) are in use.Most of the other spectrum is at the idle state in a whole day.Sub band 9 (806-890MHz) is assigned for Fix/Mobile serviceand Radiodetermination service. The spectrum occupancy ofthis sub band detected by the center station is 22.3%. At theother five stations, the detected spectrum occupancy for thissub band is about 10%. Taking the measurement results of the

Center Station as an example, the relation between spectrumoccupancy and time at this sub band is shown in Fig. 7. Wecan see that most of the spectrum is idle.

Sub bands 10 (890-960MHz) and 13 (1710-1880MHz) areassigned for GSM 900 and GSM 1800, respectively. Thespectrum occupancy of these two sub band detected by theCenter Station are 42.7% and 28.7%, respectively. Spectrumoccupancy versus time of these sub bands are plotted in Fig. 8and Fig. 9. It can be noted that the uplink and downlink sidesare not identical. This can be explained as follows. The controlchannels for GSM 900 and GSM 1800 are constantly beingbroadcasted by the base station on the downlink channel, thusit seems be fully occupied. On the other hand, the uplink

channel is randomly accessed by the mobile terminals. Besides,if there is no active communication there is still periodicalcontrol information that is transferred from a mobile terminalto the network through the uplink, but the power is relativelymuch lower, and it is not detected in this campaign.

Sub band 14 (1880-2170MHz) is assigned for 3G service.From Fig. 3 we can observe that the spectrum occupancy forthis band is relatively low. At St1, the detected spectrumoccupancy for this sub band is lower than 20%, at the otherstations which are located in the suburban district the detectedoccupancy is lower than 10%. The relation between spectrumoccupancy and time in this sub band is plotted in Fig. 10. Itdoesnt show any occupancy in the uplink. This is due to thefactor that the 3G service such as WCDMA is a spreadspectrum system where the signal is modulated over a largerbandwidth, and uplink signal has a very low transmissionpower. It is not detected in this campaign.



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Figure 9. The relation between spectrum occupancy and time for the sub band13 (1710-1880 MHz) obtained at the Center Station (Apr. 2, 2012).

Figure 10. The relation between spectrum occupancy and time for the sub

band 14 (1880-2170MHz) obtained at the Center Station (Apr. 2, 2012).

IV. CONCLUSIONIn this work, we have investigated the spectrum occupancy

for the frequency span of 20-3000MHz in Kunming and thenearby cities and counties based on the spectrum monitoringnetwork in Yunnan Province. The measurement results showthat the spectrum occupancy of the entire frequency band islower than 13.7%. The spectrum occupancy rates are highlydependent on space and time. In the TV band, a large amount

of spectrum is at the idle state in a whole day, and it can beconsidered for dynamic spectrum access. In the GSM bands,the downlink is fully occupied while the uplink is randomlyaccessed by mobile terminals. These results are obtained basedon energy detection principle, which is very sensitive toambient noise. Therefore, dynamic detection of noise and thedevelopment of noise independent monitoring method is thefuture work of our Lab.

ACKNOWLEDGMENT

This work was supported by the National Natural ScienceFoundation of China (Grant No. 61161007) and WirelessInnovation Laboratory jointly constructed by School ofInformation Science and Engineering of Yunnan University,and the Radio Monitoring Center of Yunnan province.

REFERENCES

[1] S. Pollin, M. Timmers and L. V. der Perre, Software defined radios:from smart(er) to cognitive, New York: Springer, 2011, pp. 1-8.

[2] D. Z. Chen, J. J. Yang, H. Tang, J. X. Lin, M. Huang, Researchprogress in radio monitoring techniques, The 2nd International

Conference on Aerospace Engineering and Information Technology,Nanchang, China, May 2012, vol.2, pp. 83-87.

[3] Qi Zhu Song, Frequency allocation mechanism for new generationwireless technology and its application, Beijing: Publishing House ofElectronics Industry, 2011.

[4] Federal Communications Commission, Spectrum Policy Task ForceReport, 2002.

[5] J. Mitola III, Cognitive Radio: an integrated agent architecture forsoftware defined radio, Ph.D. dissertation, KTH Royal Institute of

Technology, 2000.

[6] Definitions of Software Defined Radio (SDR) and Cognitive RadioSystem (CRS), International Telecommunication Union, Report ITU-RSM.2152, Sept. 2009.

[7] M. A. McHenry, P. A. Tenhula, D. McCloskey, D. A. Roberson and C. S.Hood, Chicago Spectrum Occupancy Measurements & Analysis and aLong-term Studies Proposal, in Proc. of Workshop on Technology and

Policy for Accessing Spectrum (TAPAS), Boston, USA, Aug. 2006.

[8] R. I. C. Chiang, G. B. Rowe and K. W. Sowerby, A QuantitativeAnalysis of Spectral Occupancy Measurements for Cognitive Radio,

in Proc. of IEEE Vehicular Technology Conference (VTC), Dublin,

Ireland, April 2007.

[9] K. Patil, K. Skouby, A. Chandra and R. Prasad, Spectrum OccupancyStatistics in the Context of Cognitive Radio, Wireless Personal

Multimedia Communications (WPMC), The 14th International

Symposium on, France, Brest, Oct. 2011.[10] M. Islam, G. L. Tan, F. Chin, B. E. Toh, Y.-C. Liang, C. Wang, Y. Y. Lai,

X. Qing, S. W. Oh, C. L. Koh and W. Toh, Spectrum Survey inSingapore: Occupancy Measurements and Analyses, in Proc. ofInternational Conference on Cognitive Radio Oriented Wireless

Networks and Communications (CROWNCOM), Singapore, May 2008,

pp. 1-7.[11] M. R. Dzulkifli, M. R. Kamarudin and T. A. Rahman, Spectrum

occupancy at UHF TV band for cognitive radio applications, 2011

IEEE International RF and Microwave Conference (RFM 2011),

Seremban, Malaysia, Dec. 2011, pp. 111-114.[12] Y. Han, Y. Wen, W. Tang and S. Li, Spectrum Occupancy

Measurement: Focus on the TV Frequency, The 2nd International

Conference on Signal Processing Systems (ICSPS), Dalian, China, July2010, pp. V2-490-494.

[13] M. Lpez-Bentez and F. Casadevall, Methodological aspects ofspectrum occupancy evaluation in the context of Cognitive Radio inProceedings of the 15th European Wireless Conference (EW 2009),

Aalborg, Denmark, May, 2009, pp. 199-204.

[14] T. Ycek and H. Arslan, A survey of spectrum sensing algorithms forcognitive radio applications, IEEE Communications Surveys and

Tutorials, vol. 11, pp. 116-130, 2009.[15] B. B. Wang and K. J. Ray Liu, Advances in cognitive radio networks:

a survey, IEEE Journal of Selected Topics in Signal Prodessing, vol. 5,

pp. 5-23, Feb. 2011.

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spectrum occupancy analysis based on radio

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