Advances in opportunistic radio technologies for TVWS
© Noguet et al; licensee Springer. 2011
Received: 20 May 2011
Accepted: 15 November 2011
Published: 15 November 2011
Cognitive radio has been an active research area in wireless communications over the past 10 years. TV Digital Switch Over resulted in new regulatory regimes, which offer the first large-scale opportunity for cognitive radio and networks. This article considers the most recent regulatory rules for TV White Space opportunistic usage, and proposes technologies to operate in these bands. It addresses techniques to assess channel vacancy by the cognitive radio, focusing on the two incumbent systems of the TV bands, namely TV stations and wireless microphones. Spectrum-sensing performance is discussed under TV White Space regulation parameters. Then, modulation schemes for the opportunistic radio are discussed, showing the limitations of classical multi-carrier techniques and the advantages of filter bank modulations. In particular, the low adjacent band leakage of filter bank is addressed, and its benefit for spectrum pooling is stressed as a means to offer broadband access through channel aggregation.
Cognitive radio (CR) has been a major research topic in the radio communication community since it was introduced by Mitola in the early 2000s . Cognitive Radio capitalizes on the flexible radio concept by setting the configuration of a flexible radio according to sensing and decision-making capabilities. Unfortunately, large-scale deployment of CR in civil telecommunication systems was somewhat limited. This is mainly because its full benefits would require disruptive regulation rules, where spectrum resources would be allocated according to actual needs at a specific location in space and time, rather than ruled by fixed frequency assignments . Therefore, first experimental over-the-air testbeds were restricted to the ISM bands [3–5] and/or to the research community [6, 7].
In some countries, the so-called digital switch over (DSO) in TV bands has recently resulted in relaxed regulatory regimes, where unlicensed spectrum use is allowed, provided that non-harmful interference to incumbent systems is guaranteed. This move was first initiated in the USA, where the first proposed rules for the "Unlicensed Operation in the TV Broadcast Bands" were published as early as 2004 , with the final set of rules in 2009  and an additional notice in 2011 . A similar trend is currently under way in other countries: for example, in the UK , Europe , and Australia . As a consequence, the unused TV spectrum, referred to as TV White Space (TVWS), has become one of the very first portions of the spectrum where the concepts of CR meet regulatory and actual deployment-driven requirement figures.
Standardization actions to exploit the TVWS have been carried out within IEEE802 groups, first in IEEE802.22 , and more recently in IEEE802.11af . Both standards further develop previous technologies (respectively, IEEE802.16 and IEEE802.11a) to make them fit the specific requirements of the TVWS to enable rapid availability of white space devices (WSD) on the market. Similarly, the study of the CogNea consortium to deliver the ECMA392 standard can also be mentioned [16, 17].
This article aims at highlighting the challenges to improve TVWS resource usage, suggesting new physical layer (PHY) options compared to those developed in these standards. Section 2 summarizes the regulation regimes for TV spectrum in the USA, the UK, and other countries to identify the key technical requirements for the rest of the article. Section 3 describes techniques to assess the vacancy of TV channels and ensure non-interference with incumbents. The detection of both digital terrestrial television (DTT) and wireless microphones is discussed, considering sensing and geo-location based approaches. Section 4 analyzes the specific nature of the fragmented TVWS and the stringent requirements on adjacent band leakage to suggest a new approach for the PHY in the TVWS, using filter bank modulation (FBMC) and spectrum pooling techniques.
2 Context of the TVWS and key requirements
It is envisaged that cleared spectrum be allocated to specific and potentially licensed services. This is already the case of the 800 MHz band (ch61-ch68), where a continuous portion of 72 MHz has been harmonized across Europe, Middle East, and Africa  and in the UK  for potential cellular extensions, and further harmonization of the digital dividend is still to be expected . Thus, CR technology is foreseen to occur in the interleaved spectrum where opportunistic usage is expected, as non-interference with incumbents is requested in these channels. Owing to the good propagation properties of UHF signals, various scenarios are foreseen .
Although cognitive access is being considered by many regulators around the world, few of them have agreed on parameter figures. As far as spectrum sensing is concerned, the UK communications regulator (OFCOM) recommends a sensing sensitivity of -120 dBm, assuming DTT receiver sensitivity of -78 dBm . In its first set of rules, the US federal communications commission (FCC) recommended a DTT signal sensing sensitivity of -114 dBm . It shall be noted that the OFCOM and the FCC consider channels of 8 and 6 MHz, respectively. An opportunistic system is also requested to detect potential apparition of an incumbent signal and to evacuate the band whenever this situation occurs. The FCC  requires that in-service monitoring is performed at least every 60 s, and that the channel is released within an evacuation time of no more than 2 s. The OFCOM considers more conservative figures, since time between sensing is limited to 1 s .
Key FCC and OFCOM requirements
Sensing sensitivity for DTT
Sensing sensitivity for wireless microphones
In 200 kHz bandwidth
Power for FD in adjacent band
Power for FD in non-adjacent band with geo-location capability
FCC: 36 dBm EIRP with a gain antenna
Power for PPD in adjacent band
Gain antenna not allowed
Power for PPD in non-adjacent band with geo-location capability
Gain antenna not allowed
Power for PPD in non-adjacent band without geo-location capability
Relative to in-band power in the case of the FCC
In-service monitoring period
3 Spectrum vacancy detection
The main purpose of vacant channel detection is to protect TV bands incumbents: DTT and program making and special events (PMSE) services. Different approaches have been envisaged by regulators to determine whether spectrum is free: spectrum sensing, geo-location, and beaconing, although the latter has not been identified as a suitable option [11, 25].
WSD is based on sensing assess spectrum vacancy without any support from the infrastructure. The hidden device problem may result in some residual probability of interference . This has pushed regulators to consider very conservative scenarios and to impose very high sensitivity requirements (see Table 1). Moreover, signals in adjacent channels and fluctuating signal levels may lead to even more demanding detection contexts. Several blind and signal-specific feature-based techniques have been proposed to perform sensing: spectral correlation, time-domain cyclostationarity, eigenvalue decomposition, pilot detection, higher order statistics analysis .
In the UHF TV bands (typically 470-862 MHz), the primary system is the DTT broadcast. Thus, the detector can exploit a priori knowledge of the waveform to improve its sensitivity at low signal-to-noise ratio (SNR) . In this article, DTT systems comply with the DVB-T standard. DVB-T is used in many countries including Europe, India, Australia, Russia, and some Asian, African and American countries. The DVB-T signal is built on the orthogonal frequency division multiplexing (OFDM) modulation. OFDM has strong cyclostationary features stemming from the presence of the cyclic prefix (CP). For this reason, cyclostationarity detector has been proposed as one of the most promising technique for DVB-T signal sensing . Theoretical aspects of cyclostationary detection have been thoroughly addressed in the literature [29–32], and more recently in the specific context of CR [28, 33–36]. Implementation of cyclostationary spectrum density (CSD) detectors has been proposed in [37, 38] in a general CR context where the cyclic frequencies of the signal to detect are unknown. In , we proposed a hardware architecture for specific OFDM waveforms (i.e., WiFi and DVB-T) based on the cyclostationarity algorithm presented in . It performs like CSD where the analyzed cyclic frequencies are restricted to the ones of the a-priori-known waveform. As  is tailored to these specific cyclic tones, the implementation complexity could be reduced compared with CSD. It was also highlighted in  that the DVB-T detector can benefit from long integration time thanks to the broadcast nature of the DTT signal.
Consequently, measurement results show that at least 2 seconds are needed to reach the sensing sensitivity required by OFCOM's recommendation. Thus, the proposed architecture fits the relaxed requirements of the FCC but needs to be improved to reach the OFCOM ones (see Section 2). Moreover, it is expected that integration time will be larger than channel coherence time (Tc), even for the simulated case (e.g., Tc = 65 ms, at 700 MHz and for mobile scenario of 10 km/h according to ). Therefore, additional channel variation compensation would be required, leading to a more complex implementation.
Furthermore, performance results of Figure 4 only consider one set of DVB-T parameters, which is a favorable scenario. In some countries, DVB-T broadcast may use several parameter sets and the sensor must be able to detect each of these configurations. Scanning several parameter sets would increase the complexity of the detector or would result in longer sensing time.
The main PMSE services to be detected are wireless microphones. Most of the literature references suggest the use of blind detection . They are based on eigenvalue decomposition, spectral correlation, or energy detection . Wireless microphone FM signal occupies a 200 kHz band in a 8 MHz channel. In , we propose a semi-blind detector based on the Teager-Kaiser energy operator . It is based on the nonlinear model of the FM signal energy to estimate the energy accurately. An alternative promising solution performs energy calculation in the frequency domain on the microphone actual bandwidth . It uses an FFT to compute the frequency response of the signal. Once the FFT is performed, the 8 MHz band can be decomposed into sub-bands, and the energy can be estimated on each sub-band. This algorithm is called the "frequency domain energy detector."
The Teager-Kaiser energy detector allows a 2 dB detection gain compared to the energy detection, while the frequency domain energy detector allows a 5.5 dB detection gain and outperforms the autocorrelation detection as discussed in .
Complexity evaluation of the wireless microphone detectors for Ns samples
Complexity in number of complex multiplication
Frequency domain energy detector
Ns*log2(Ns) + Ns
From these results, it can be understood that sensing is not foreseen as a short term large market option considering current requirements. The issue is made even more complex in the case of PMSE services which are more dynamic than DTT transmitters. One option is to have a harbor channel for PMSE transmission and to prohibit the opportunistic use of this channel. This solution has been adopted in the UK where channel 38 is already dedicated to PMSE transmission (see Section 2). However, in many countries, PMSE services are allowed to use any of the UHF bands, and this solution will induce deep modifications for the PMSE manufacturers, making it hard to generalize to all countries.
Geo-location-based approach is an alternative to sensing. The FFC and the OFCOM recommend location accuracies of 50 m  and 100 m , respectively. The accuracy of commercially available global positioning system (GPS) receivers meets these requirements  where the signal is available. Hybrid geo-location technologies have emerged to extend GPS coverage [46, 47] (e.g., for indoor applications). Therefore, providing geo-location information is not a major challenge for a WSD. Channel vacancy assessment requires a global infrastructure where the location information is an entry to a database. This centralized approach enables a more flexible management, since the protection margins may be globally modified by updating the database. The main challenges are on the database management, maintenance, and information exchange. They have been identified by the OFCOM . For instance, how frequently should the database be updated is an open issue to consider non-permanent incumbents, such as PMSE devices. Another issue is the propagation model to be considered to determine white space areas. Accurate models need to be developed, as conservative ones would lead to a dramatic reduction of available white space.
4 Modulation schemes for opportunistic radio
Multicarrier modulation techniques in general, and OFDM in particular, have developed as the most adapted techniques for broadband wireless communications. These waveforms have proven their worth in various applications and standards, and are commonly deployed in broadcast applications (DAB, DVB-T) as well as mobile wireless communications (WLAN, LTE). A relatively simple equalization and high bandwidth efficiency have been so far the main motivations for using OFDM when data are to be transmitted over a wireless multipath channel. Owing to the narrowband subcarriers, the CP in combination with channel coding, OFDM modulation techniques have led to very robust and reliable systems. The modulation technique is therefore a natural choice for CR in the TVWS.
The results highlight the necessity for a transmit filter cascaded after the modulator to limit the leakage of out-of-band signal power and meet the rejection level requirements of 55 dB introduced in Section 2. In order to understand the requirements on the transmit filter, we derive the rejection requirement on the transmit filter and then extrapolate the number of taps required for a finite impulse response implementation of the filter. The filter length is estimated using an equiripple low-pass implementation and should be applied to both real and imaginary components of the baseband signal. In order to keep the distortion of the OFDM signal to a reasonable level at the output of the transmitter, the ripple in the band is set to 0.5 dB, while the end of the passband is set to the limit of the occupied bandwidth.
Complexity of transmit filter as a function of occupied bandwidth
Occupied bandwidth (MHz)
Number of active carriers
Guard bandwidth (MHz)
Requirement on Tx filter rejection to meet 55 dB rejection
Length of baseband Tx filter
The length and the complexity of the transmit filter increase dramatically as the guard band is reduced. A compromise between spectral efficiency and complexity has to be found.
The main shortcoming of the OFDM waveform identified here originates from the large side-lobes because of the rectangular shaping of the temporal signal. Severe out-of-band leakage constraints have been set to guarantee non-interference to adjacent incumbent transmission. Therefore, OFDM-based opportunistic radio transmitters require either very complex transmit filters, or large frequency guard. A solution introduced by Chang  and Saltzberg  in the mid-1960s suggests combining filtering and multicarrier modulation techniques. This solution is becoming a strong contender to replace OFDM for CR applications , whenever drastic adjacent incumbent protection is required, as in the case of TVWS communication. This alternative solution is known as filter bank multicarrier communication techniques or FBMC.
FBMC allows the control of the frequency response of each carrier by introducing a filter bank, g k , centered on every active carrier and based on the same prototype response. The orthogonality of overlapping carriers is not preserved as for OFDM techniques, and the symbol spans over more than one symbol duration. Instead, an offset-QAM (OQAM) transmitted at twice the symbol rate enables mitigation of the impact of intersymbol and intercarrier interference, while keeping the same overall bandwidth . This technique is usually referred to as OFDM/OQAM in the literature.
The FBMC waveform does not require any external transmit filter to meet the spectral constraints imposed on the adjacent channel spectrum leakage, while as already underlined earlier CP-OFDM requires a transmit lowpass filter of around 52 taps applied on both real and imaginary parts of the signal assuming an occupied bandwidth of 7.2 MHz.
Complexity comparison in number of real multiplications per symbol (N = 1024, K = 4)
Occupied bandwidth (MHz)
Complexity of Tx filter for CP-OFDM
Total complexity CP-OFDM
Total complexity FBMC
As FBMC does not require any transmit filter, as its in-built filter matches adjacent channel requirement; its complexity does not change with the occupied bandwidth. For CP-OFDM, complexities of modulation and demodulation are heavily dependent on the length of the transmit filter. Values in Table 4 do not take complexity of the equalizer into account. When considered, complexity figures are mitigated, and CP-OFDM and FBMC are expected to be comparable.
Its ability to perform spectrum aggregation is another challenge a waveform adapted to the TVWS must face. Opportunistic users may get access to a spectrum that is already heavily fragmented. If the spectral needs are not met in a contiguous space of spectrum, then some form of aggregation should be realized. An efficient form of spectrum aggregation is the OFDM-based spectrum pooling as presented in . The idea is to match the bandwidth of one sub-band with an integer multiple of the carrier spacing, Δ, used by the opportunist transmitter.
In this article, TVWS was discussed as a new and promising opportunity for CR. In these bands, some countries have assessed technical requirements for incumbent detection and opportunistic communication. Considering these requirements, technical options were reviewed and discussed. The access to interleaved spectrum requires spectrum vacancy assessment to insure that no harmful interference with incumbents is guaranteed. Significant study has been carried out in the field of spectrum sensing. This article showed that the regulator's requirements are difficult to achieve, specifically when sensing allowed time is limited. TV broadcast signals have features that can be exploited and the US regulation requirements can be met, when measurements can be performed over several seconds. This implies low mobility of the sensor. As far as wireless microphones are concerned, it was shown that detection is even more difficult because of the evanescence of the signal. Geo-location techniques translate the detection issue into a more complex global system architecture, which requires an up-to-date maintained, and reliable database, as well as means to insure that opportunistic radios can query the database. This requires another radio or a wired access to the database. Communication schemes for TVWS were also discussed. It was shown that despite its prominence in modern broadband radios, CP-OFDM has some drawbacks for TVWS operation. Indeed, CP-OFDM sidelobes make it inappropriate in adjacent channels, unless expensive rejection filters are used. Furthermore, new services claim for broadband access, which may be difficult to achieve in on TV channels of 6-8 MHz. Spectrum pooling is an appealing approach to virtually elaborate wider channels, but again CP-OFDM is not applicable because of unaffordable out-of-band leakage. FBMC was presented as a valid alternative to CP-OFDM, as it achieves both adjacent coexistence and spectrum pooling.
The research support leading to these results was derived from the European community's seventh framework program (FP7) under Grant Agreement number 248454 (QoSMOS).
- Mitola J: Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio. Ph.D. thesis, Royal Institute of Technology, Sweden; 2000.Google Scholar
- Noguet D: How to Reorganise Radio Spectrum Resources. eStrategies--Projects. British Publishers No 7; 2008.Google Scholar
- Raychaudhuri D, Seskar I, Ott M, Ganu S, Ramachandran K, Kremo H, Siracusa R, Liu H, Singh M: Overview of the ORBIT radio grid testbed for evaluation of next-generation wireless network protocols. IEEE Wireless Communications and Networking Conference (WCNC) 2005.Google Scholar
- Mishra SM, Cabric D, Chang C, Willkomm D, van Schewick B, Wolisz A, Brodersen RW: A real time cognitive radio testbed for physical and network level experiments. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DYSPAN) 2005.Google Scholar
- Biard L, Noguet D, Gernandt T, Marques P, Gameiro AA: Hardware demonstrator of an opportunistic radio system using temporal opportunities. In Cognitive Radio Oriented Wireless Networks and Communications (Crowncom). Hanover, Germany; 2009.Google Scholar
- Newman TR, Depoy D, Bose T, Reed JH: Designing and deploying a building-wide cognitive radio network testbed. IEEE Commun Mag 2010, 48(9):106-112.View ArticleGoogle Scholar
- WARP:Wireless open-Access Research Platform. Rice University; [http://warp.rice.edu/]
- FCC Proposed Rule: Unlicensed Operation in the TV Broadcast Bands. Volume 69. US Federal Register; 2004:34103-34111.Google Scholar
- FCC Final Rule: Unlicensed Operation in the TV Broadcast Bands. Volume 74. US Federal Register; 2009:7314-7332.Google Scholar
- FCC Notice: Unlicensed Operation in the TV Broadcast Bands. Volume 76. US Federal Register; 2011:6789-6792.Google Scholar
- Digital Dividend: Cognitive Access, Statement on Licence-Exempting Cognitive Devices Using Interleaved Spectrum. OFCOM; 2009.Google Scholar
- CEPT:Report from CEPT to the European Commission in response to the Mandate on the identification of Common and Minimal (Least Restrictive) Technical Conditions for 790-862 MHz for the Digital Dividend in the European Union, CEPT Report 30. 2009. [http://www.erodocdb.dk/Docs/doc98/official/pdf/CEPTREP030.PDF]Google Scholar
- Freyens BP, Loney M: Opportunities for white space usage in Australia. In 2nd International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace in Electronic Systems Technology (Wireless VITAE). Chennai, India; 2011.Google Scholar
- IEEE 80222:Wireless Regional Area Networks (WRANs). [http://www.ieee802.org/22/]
- IEEE 80211af:TV White Space Study Group AF, Wireless Local Area Network (WLAN). [http://www.ieee802.org/11/]
- ECMA392 Standard:MAC and PHY for Operation in TV White Space. [http://www.ecma-international.org/publications/standards/Ecma-392.htm]
- Wang J, Song MS, Santhiveeran S, Lim K, Ko G, Kim K, Hwang SH, Ghosh M, Gaddam V, Challapali K: First cognitive radio networking standard for personal/portable devices in TV white spaces. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DYSPAN) 2010.Google Scholar
- Nekovee M: Quantifying the availability of TV white spaces for cognitive access in the UK. In IEEE ICC. Dresden, Germany; 2009.Google Scholar
- ITU:World Radio Conference 07. [http://www.itu.int/ITU-R/indexasp?category=conferences&link=wrc&lang=en]
- Digital Dividend: Clearing the 800 MHz band, Statement, OFCOM. 2009.Google Scholar
- World Radiocommunication Conference Set for Early2012. [http://www.itu.int/net/itunews/issues/2009/08/36aspx]
- Mueck M, Noguet D: TV white space standardization and regulation in Europe. In 2nd International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace in Electronic Systems Technology (Wireless VITAE). Chennai, India; 2011.Google Scholar
- Noguet D, Datta R, Lehne PH, Gautier M, Fettweis G: TVWS regulation and QoSMOS requirements. In 2nd International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace in Electronic Systems Technology (Wireless VITAE). Chennai, India; 2011.Google Scholar
- Mishra M, Sahai A: How Much White Space is there? In Technical Report. Electrical Engineering and Computer Sciences, University of California at Berkeley; 2009.Google Scholar
- ECC REPORT 159: Technical and Operational Requirements for the Possible Operation of Cognitive Radio Systems in the 'White Spaces' of the Frequency Band 470-790 MHz. CEPT, Cardiff; 2011.Google Scholar
- Cabric D, Tkachenko A, Brodersen R: Spectrum sensing measurements of pilot, energy, and collaborative detection. IEEE Military Communication Conference 2006, 1-7.Google Scholar
- Noguet D, Demessie YA, Biard L, Bouzegzi A, Debbah M, Haghighi K, Jallon P, Laugeois M, Marques P, Muroni M, Palicot J, Sun C, Thilakawardana S, Yamaguchi A:Sensing Techniques for Cognitive Radio--State of the art and trends. 2009. [http://dyspan-sc.org]Google Scholar
- Jallon P: An algorithm for detection of DVB-T signals based on their second-order statistics. EURASIP J Wireless Commun Netw 2008, 1-9.Google Scholar
- Gardner WA: Statistical Spectral Analysis: A Nonprobabilistic Theory. Prentice-Hall, Englewood Cliffs, New Jersey; 1988.Google Scholar
- Gardner WA, Zivanovic G: Degrees of cyclostationary and their application to signal detection and estimation. Sig Process 1991., 22(3):
- Gardner WA, Spooner M: Signal interception: performance advantages of cyclic-feature detectors. IEEE Trans Commun 1992, 40(1):149-159. 10.1109/26.126716View ArticleGoogle Scholar
- Gardner W, William A: Cyclostationarity in Communications and Signal Processing. IEEE Press, New York; 1994.Google Scholar
- Lunden J, Koivunen V, Huttunen A, Poor H Vincent:Spectrum Sensing in Cognitive Radios Based on Multiple Cyclic Frequencies. 2007. [http://arxiv.org/abs/07070909]View ArticleGoogle Scholar
- Ye Z, Grosspietsch J, Memik G: Spectrum Sensing Using Cyclostationary Spectrum Density for Cognitive Radios. In IEEE Workshop on Signal Processing Systems. Shanghai, China; 2007.Google Scholar
- Ghozzi M, Dohler M, Marx F, Palicot J: Cognitive radio: methods for detection of free bands. Elsevier Sci J Special Issue on Cognitive Radio 2006, 794-805.Google Scholar
- Bouzegzi A, Jallon P, Ciblat P: A second order statistics based algorithm for blind recognition of OFDM based systems. GLOBECOM 2008.Google Scholar
- Turunen V, Kosunen M, Huttunen A, Kallioinen S, Ikonen P, Pärssinen A, Ryynänen J: Implementation of cyclostationary feature detector for cognitive radios. In Proceedings of the 4th international conference cognitive radio oriented wireless networks and communications (CROWNCOM). Hannover, Germany; 2009.Google Scholar
- Turunen V, Kosunen M, Kallioinen S, Pärssinen A, Ryynänen J: Spectrum estimator and cyclostationary detector for cognitive radio. In European Conference on Circuit Theory and Design (ECCTD 2009). Antalya, Turkey; 2009.Google Scholar
- Noguet D, Biard L, Laugeois M: Cyclostationarity detectors for cognitive radio: architectural tradeoffs. EURASIP J Wirel Commun Netw 2010.Google Scholar
- Gautier M, Laugeois M, Hostiou Ph: Cyclostationarity detection of DVB-T Signal: testbed and measurement. In The First International Conference on Advances in Cognitive Radio (COCORA). Budapest, Hungary; 2011.Google Scholar
- Rappaport Th S: Wireless Communications: Principles and Practice. Prentice Hall, London; 1996.Google Scholar
- Chen H-S, Gao W, Daut D: Spectrum sensing for wireless microphone signals. IEEE Sensor, Mesh and Ad Hoc Communications and Networks Workshops (SECON08) 2008.Google Scholar
- Gautier M, Laugeois M, Noguet D: Teager-kaiser energy detector for narrowband wireless microphone spectrum sensing. In Proceedings of the 5th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM). Cannes, France; 2010.Google Scholar
- Kaiser JF: On simple algorithm to calculate the energy of signal. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP90) 1990.Google Scholar
- Neihart NM, Roy S, Allstot DJ: A parallel multi-resolution sensing technique for multiple antenna cognitive radios. IEEE International Symposium on Circuits and Systems 2007.Google Scholar
- Wang S, Ming J, Yi BK, Kwon S: Location based services for mobiles: technologies and standards. In IEEE International Conference on Communications (ICC). Beijin, China; 2008.Google Scholar
- Liu H, Darabi H, Banerjee P, Liu J: Survey of wireless indoor positioning techniques and systems, systems, man, and cybernetics, part c: applications and reviews. IEEE Trans 2007, 37(6):1067-1080.Google Scholar
- Digital Dividend: Geolocation for Cognitive Access, OFCOM. 2009.Google Scholar
- van Waterschoot T, Le Nir V, Duplicy J, Moonen M: Analytical expressions for the power spectral density of CP-OFDM and ZP-OFDM signals. IEEE Sig Process Lett 2010, 17(4):371-374.View ArticleGoogle Scholar
- Chang RW: Synthesis of band-limited orthogonal signals for multichannel data transmission. Bell Syst Technol J 1966, 45: 1175-1796.View ArticleGoogle Scholar
- Saltzberg BR: Performance of an efficient parallel data transmission system. IEEE Trans Commun Technol 1967, COM-15: 805-813.View ArticleGoogle Scholar
- Datta R, Gautier M, Berg V, Futatsugi Y, Ariyoshi M, Schühler M, Kollár Zs, Horváth P, Noguet D, Fettweis G: Flexible Multicarrier PHY design for cognitive radio in white space. In Proceedings of the 6th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM). Osaka, Japan; 2011.Google Scholar
- Siohan P, Siclet C, Lacaille N: Analysis and design of OFDM/OQAM systems based on filterbank theory. IEEE Trans Sig Process 2002, 50(5):1170-1183. 10.1109/78.995073View ArticleGoogle Scholar
- Bellanger MG: Specification and design of a prototype filter for filter bank based multicarrier transmission. Proceedings of International Conference on Acoustics, Speech and Signal Processing (ICASSP '01) 2001, 4: 2417-2420.Google Scholar
- Hirosaki B: An orthogonally multiplexed QAM sytem using the discret fourier transform. IEEE Trans Commun 1981, 29(7):982-989. 10.1109/TCOM.1981.1095093View ArticleGoogle Scholar
- Ihalainen T, Viholainen A, Stitz TH, Renfors M: Generation of filter bank-based multicarrier waveform using partial synthesis and time domain interpolation, circuits and systems i: regular papers. IEEE Trans 2010, 57(7):1767-1778.MathSciNetGoogle Scholar
- Weiss TA, Jondral FK: Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency. IEEE Commun Mag 2004, 42(3):S8-S14.View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.