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Author:Kokkinen, Kari
Title:Implementation of Autocorrelation-based Feature Detector for Cognitive Radio
Publication type:Master's thesis
Publication year:2010
Pages:viii + 49      Language:   eng
Department/School:Mikro- ja nanotekniikan laitos
Main subject:Piiritekniikka   (S-87)
Supervisor:Ryynänen, Jussi
Instructor:Kosunen, Marko
Electronic version URL: http://urn.fi/URN:NBN:fi:aalto-201203131513
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto  890   | Archive
Keywords:cognitive radio
spectrum sensing
autocorrelation
kognitiivinen radio
spektrin havainnointi
autokorrelaatio
Abstract (eng): Emerging wireless systems demandmore frequency bands in order to provide high data rate services.
Most of the licensed frequency bands are underutilized, because of the rigid spectrum allocation.
Cognitive radios aim to relieve the situation by identifying and exploiting the underutilized radio spectrum.
A key task of the cognitive radio is spectrum sensing, which is intended to detect unoccupied frequency slots and licensed spectrum user transmissions.

This thesis presents an implementation of an autocorrelation-based feature detector for orthogonal frequency-division multiplexing (OFDM) based primary user signals.
The autocorrelation-based detection algorithm is optimized in order to achieve power and area efficient hardware realization.
The VHDL implementation is presented in detail and verified by simulations.
After verification, the algorithm is implemented in a field-programmable gate array (FPGA) evaluation environment, and the performance is verified with measurements.
An application-specific integrated circuit (ASIC) implementation is also realized in order to obtain comparable data of power consumption and area.

The algorithm implementation with DC offset compensation performed as predicted by simulations.
The FPGA implementation requires 987 LUT flip-flop units, and the dynamic power consumption is 3.69 mW.
The ASIC circuit implemented with 65 nm CMOS process occupies an area of 0.26 mm2, and has power consumption of 1.02 mW.
Abstract (fin): Nykyiset ja tulevat langattomat järjestelmät tarvitsevat yhä enemmän taajuuskaistoja uusille palveluille.
Lähes koko käytettävissä oleva radiospektri on lisensoitu, mutta suurinta osaa lisensoiduista taajuuskaistoista ei hyödynnetä tehokkaasti tiukkojen käyttöehtojen vuoksi.
Kognitiiviset radiot voivat helpottaa tätä ongelmaa, tunnistamalla vajaasti käytetyn kaistan ja ottamalla sen käyttöön häiritsemättä kaistan lisensoinutta käyttäjää.
Kognitiivisten radioiden tärkein ominaisuus on löytää vapaat spektrin alueet sekä tunnistaa lisensoitujen käyttäjien lähetykset.

Tässä diplomityössä esitetään autokorrelaatioon perustuvan spektrinhavainnointialgoritmin suunnittelu ja toteutus.
Algoritmi tunnistaa OFDM-signaaleihin perustuvia järjestelmiä.
Toteutuksessa algoritmia on muokattu, ja laskentaa yksinkertaistettu tarvittavan pinta-alan ja tehonkulutuksen pienentämiseksi.

Implementaatio ja VHDL kuvaukset verifioidaan simulaatioilla.
Algoritmi on toteutettu FPGA kehitysalustalle, ja sen toiminta on varmennettu mittauksilla.
Algoritmi toteutettiin myös ASIC-piirinä tehonkulutus- ja pinta-alatietojen saamiseksi.

FPGA-toteutus tarvitsee 987 LUT flip-flop paria, ja sen tehonkulutus oli 3.69 mW.
ASIC:na piiri toteutettiin 65 nm CMOS prosessilla pinta-alan ollessa 0.26 mm2 ja tehonkulutuksen 1.02 mW.
ED:2010-08-20
INSSI record number: 40201
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