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Algorithm Design DocumentDocument no.: CRAW_???_001 draft v0.1

Spectrum Sensing AlgorithmDesign Document

Abstract: This document illustrates the algorithm design

for CRAWs spectrum sensing proect. This document

includes introduction! o"er"ie# of the sensing algorithms!

the co"ariance $ased sensing algorithm and the spectrum

$ased h%$rid detection algorithm for signal em$edded in

spurious and noise. Detailed descriptions on

implementation of the algorithms are included. Channel

selection filters are also attached in the appendi&.

Role Name Designation Signature

Owner 'eng (onghong Research )cientist

Reviewer 'hang Wei*iang

+e Tran ,huoc Cuong

)%ed -a"een AltafAhmed

Research anager

Research /fficer

)enior Research /fficer

Approver /h )er Wah ,roect anager! CRAW

Revision 1.0 Date of Issue 1 Dec 00

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COPYRIGH NOIC!Cop%right 2 00 $% 3nstitute for 3nfocomm Research 43R5! )ingapore. All rights reser"ed.

-o part of this pu$lication ma% $e reproduced! transmitted! transcri$ed! stored in aretrie"al s%stem! or translated into an% language #ithout the #ritten permission of 3 R.

"ARNING

Chec6 document control s%stem for the latest "ersion $efore using or cop%ing.

R!#ISION HISORY

Revision Date Authors Comments Reasons for

Change0.1 0 /CT 00 (. 7.

'eng1.0 1 D8C 00 (. 7.

'eng

CONRI$%ORS

/h )er Wah

9ruce +e

'hang Wei*iang

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D!(INIIONS) ACRONY*S + A$$R!#IAIONS

AA A"erage Amplitude

ADC Analog to Digital Con"erter

CA Co"ariance A$solute alue

CRAW ,roect Code -ame! Research ,roect on W;RA-

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A$-! O( CON!N

COPYRIGHT NOTICE.....................................................................................................................................................2

WARNING..........................................................................................................................................................................2

REVISION HISTORY.......................................................................................................................................................2

CONTRIBUTORS..............................................................................................................................................................2

DEFINITIONS, ACRONYMS & ABBREVIATIONS....................................................................................................3

TABLE OF CONTENT......................................................................................................................................................4

1. INTRODUCTION.........................................................................................................................................................5

1.1. PURPOSE....................................................................................................................................................................51.2. SCOPE........................................................................................................................................................................51.3. REFERENCEDOCUMENTS..........................................................................................................................................5

2. OVERVIEW OF SENSING ALGORITHMS.................................................................................................... .........7

3. COVARIANCE BASED SENSING ALGORITHM.................................................................................................. .

4. IMPLEMENTATION OF THE CAV ALGORITHM...............................................................................................11

5. SPECTRUM BASED HYBRID DETECTION.........................................................................................................12

!. IMPLEMENTATION OF THE SHD ALGORITHM......................................................................................... .....15

7. APPENDI" 1# DIGITAL FILTERS...........................................................................................................................1!

. APPENDI" 2# MATLAB CODES.............................................................................................................................1$

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/0 Intro1uction

This document descri$es the algorithm design for the CRAW spectrum sensing proect.

The main purpose for this proect is to detect the presence of R< signals in the 77 ! signal e&istsL other#ise! signal not e&ists

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/: he choice of channel selection filter

To ha"e a good adacent channel signal reection! the channel selection filter should

ha"e stop;$and attenuation as high as possi$le! prefera$l% higher than G0d9.

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1( )

faIP =

20 Spectrum 5ase1 h>5ri1 1etection)ometimes the recei"ed signal ma% not onl% contain the desired signal and #hite noise!

$ut also some spurious signal and interference. The spurious signal ma% $e generated $%

Analog;to;Digital Con"erters 4ADC5 due to its non;linearit%. 3f the sensing antenna is near

some electronic de"ices! the spurious signal generated $% the de"ices can $e strong in

the recei"ed signal. We need signal processing techni*ues to handle the

spurious=interference.

There are t#o h%pothesises: 0H : signal not e&istsL and 1H : signal e&ists. 3f there is

possi$le spurious signal! the recei"ed signal samples under the t#o h%pothesises are

therefore respecti"el% as follo#s:

0

1

: ( ) ( ) ( )K

i

i

H x n n n =

= +

1

1

: ( ) ( ) ( ) ( )K

i

i

H x n s n n n

=

= + + !

#here )(ns is the transmitted signal passed through a #ireless channel 4including fading

and multipath effect5! ( )i n is a possi$le spurious signal and )(n is the #hite noise

samples. -ote that )(ns can $e the superposition of multiple signals. The spurious signal

( )i n is normall% an e&tremel% narro#$and signal. an% detection algorithms cannot

differentiate the transmitted signal )(ns and spurious signal ( )i n . Therefore! these

algorithms #ill produce false alarm #hen spurious signal presents! that is! e"en ifinterested signal does not presents! the algorithms #ill #rongl% report signal presentB due

to the interference of the spurious signals. To sol"e this pro$lem! #e propose a detection

algorithm $ased on po#er spectrum densit% or

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The flo#;chart of the algorithm is gi"en in

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/ 12

0

( ) ( ) , 0,1,..., 1N M

T m

m

n X n n M

=

= =

Alternati"el%! #e can also use the AA at terminating case defined as

/ 1

0

( ) ( ) , 0,1,..., 1N M

T m

m

n X n n M

=

= =

The pre;#hitening "ector ( )nW is simpl% chosen as ( )T n or A ( )T n . The "ector can $e

computed offline once for all and stored.

,: hreshol1 setting

The threshold 1 is set $ased on the re*uired pro$a$ilit% of false alarm at terminating

case. +et faP $e the re*uired pro$a$ilit% of false alarm. At terminating case! the

spurious detection method is used for I tests. To guarantee high relia$ilit%! the num$er

of tests I should $e large. +et the ratio ( ) /x meann of test i $e ( )i . Reorder ( )i into

1( )i #ith descending order. Then the threshold 1 is chosen as

1 1( )

faIP =

The threshold 2 is set $ased on the re*uired pro$a$ilit% of false alarm #hen $oth

spurious signal and noise present. +et faP $e the re*uired pro$a$ilit% of false alarm.

The threshold 2 should $e chosen such that the pro$a$ilit% of decision signal presentB

is less than faP .

40 Appen1i< /8 1igital filters

The coefficients of the filter #ith $and#idth G7K are as follo#s 4centered at fre*uenc%

E.E 7K! after truncation to 10 $its5:

1 1 0 ;1 ; ; ;1 0 0 ;1 ;1 0 0 0

;1 ; ; 0 1 1 0 0 0 1 0 ;1 ;1 0 0

0 ; ; ; 0 1 1 0 ;1 0 H 1 ;1 ;1 1

1 ;1 ;H ;E ;H ;1 1 1 ;1 ; 1 E E 1 ;1 0

;1 ; ;M ;G ;1 1 ;1 ;E ;H M 11 1 ;1

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G ; ;11 ;1 ; ;1 0 ;G ;11 ; 1H 1E 1

11 1 11 ;H ;1 ;1 ; 0 ;E ;1 ;E ;1E E 1 0

;1 M G 1 ; ;G ; ;H ;1G ;HG ;EG ;1 10 H

; ;G H MM EH ;1 ;E ;H 1M ;MH ;E ;E ;0 1

E11 1 ;0 ;E ;E ;MH 1M ;H ;E ;1 EH MM H ;G

; H 10 ;1 ;EG ;HG ;1G ;H ; ;G ; 1 G M

;1 0 1 E ;1E ;E ;1 ;E 0 ; ;1 ;1 ;H 11 1 11

1 1E 1H ; ;11 ;G 0 ;1 ; ;1 ;11 ; G

;1 1 11 M ;H ;E ;1 1 ;1 ;G ;M ; ;1

0 ;1 1 E E 1 ; ;1 1 1 ;1 ;H ;E ;H ;1

1 1 ;1 ;1 1 H 0 ;1 0 1 1 0 ; ; ; 0 0 0 ;1 ;1 0 1 0 0 0 1 1 0 ; ;

;1 0 0 0 ;1 ;1 0 0 ;1 ; ; ;1 0 1

1

The coefficients of the filter #ith $and#idth 10I7K 4centered at fre*uenc% .GM0G

7K! after truncation to 10 $its5 are as follo#s:

G 1E ;10 ;M ;H ;M ; ;HM ;GG ;1E0 ;1H 1H H H ME

MM EH GH 1H 1 ;1H1 ;G ;G0 ;H0M ;H0 ;E ;G1 ;1 1H 1EM E

H H1 EM E 1 ;M ;1 ;0H ;MH ;HG ;HH ;G0 ;E1 ;110 HE

1ME H10 HH H0 EM HH M ;G1 ;1 ;H0 ;HE ;HE ;HE ;E ;G

;H E HM HG H EH G 0 ;MG ;E0 ;H ;HE ;HE ;HM

;HM ;1G ;EE 11 G M0 HGH H HH0 H 0H M ;11 ;E ;H0E ;HE

;H ;H ;G ;1M1 ; 1HM 0 H1M HE HM0 HG 1 G ;1G ;1M

;H ;HM ;HM ;H1 ;1 ;1G 11 1H E HHE E00 HM HG 0G 1H ;M;0 ;E0 ;HEG ;E0E ;HM ;H1M ;M ;1 HG 1M GH HGE E0M HM0 H10 0

11E ;GH ;E ; ;HH ;E11 ;HG ;H01 ;GG ;M 1 E1 M0 H0 E11 H0

M0 E1 1 ;M ;GG ;H01 ;HG ;E11 ;HH ; ;E ;GH 11E 0 H10 HM0

E0M HGE GH 1M HG ;1 ;M ;H1M ;HM ;E0E ;HEG ;E0 ;0 ;M 1H 0G

HG HM E00 HHE E 1H 11 ;1G ;1 ;H1 ;HM ;HM ;H ;1M ;1G G

1 HG HM0 HE H1M 0 1HM ; ;1M1 ;G ;H ;H ;HE ;H0E ;E

;11 M 0H H HH0 H HGH M0 G 11 ;EE ;1G ;HM ;HM ;HE ;HE

;H ;E0 ;MG 0 G EH H HG HM E ;H ;G ;E ;HE

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;HE ;HE ;H0 ;1 ;G1 M HH EM H0 HH H10 1ME HE ;110 ;E1

;G0 ;HH ;HG ;MH ;0H ;1 ;M 1 E EM H1 H E 1EM 1H

;1 ;G1 ;E ;H0 ;H0M ;G0 ;G ;1H1 1 1H GH EH MM ME H H

1H ;1H ;1E0 ;GG ;HM ; ;M ;H ;M ;10 1E G

60 Appen1i< &8 *atla5 co1es

The atla$ code for the CA algorithm is included in the follo#ing as an illustration to

the method.

OO atla$ codes for the CA algorithm

-)P000L OO the num$er of s%m$ols generated

threPL OO input the threshold here

hfPL OO input filter here

+P10L OO the smooth factor

-TP1L OO the num$er of filter taps

OO The pre;#hitening matri& generation $ased on filterR-1PKeros4+!-TQ+;15L

for nP1:+

R-14n!n:nQ-T;15PhfL

end

OO The pre;#hitening matri&

R-PR-1R-1SL

RR-Ps*rtm4R-5L

RR-Pin"4RR-5L

OO 3nput the signal samples here

&1PL

OO

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End of Document

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