Modulation, Demodulation and Coding Course

Download Report

Transcript Modulation, Demodulation and Coding Course

EE 3220: Digital Communication

Lec-8: Error performance of bandpass modulation Dr. Hassan Yousif Ahmed Department of Electrical Engineering College of Engineering at Wadi Aldwasser Slman bin Abdulaziz University 1 Dr Hassan Yousif

Last time we talked about:

• Some bandpass modulation schemes – M-PAM, M-PSK, M-FSK, M-QAM • How to perform coherent and non-coherent detection Dr Hassan Yousif 2

Example of two dim. modulation

16QAM 8PSK s

3  2 (

t

)

“011”

 2 (

t

)

“0000” “0001” “0011” “0010” s

1

s

2 3

s

3

s

4

“010” s

4

E s

“001” s

2

“110” s

5

s “000”

1  1 (

t

)

“1000” “1001” “1011” “1010” s

5

s

6

s

7

s

1 8 -3 -1 1 3

s

9

s

10 -1

s

11

s “1100” “1101” “1111” “1110”

12

s

13

s

14 -3

s

15

s “0100” “0101” “0111” “0110”

16  1 (

t

)

QPSK “111” s

6

s

2

“01”

2 (

t

)

s

7

E s

s

8

“100” “00” s

1  1 (

t

) Dr Hassan Yousif

s

3

“11” “10” s

4 3

Today, we are going to talk about:

• How to calculate the average probability of symbol error for different modulation schemes that we studied?

• How to compare different modulation schemes based on their error performances?

Dr Hassan Yousif 4

Error probability of bandpass modulation • Before evaluating the error probability, it is important to remember that: – The type of modulation and detection ( coherent or non coherent) determines the structure of the decision circuits and hence the decision variable, denoted by

z

.

– The decision variable,

z

, is compared with M-1 thresholds, corresponding to M decision regions for detection purposes.

r

(

t

)  1 (

t

) 

N

(

t

) 

T

0 

T

0

r

1

r N

    

r r N

1       

r r Decision Circuits

Compare z with threshold. Dr Hassan Yousif 5

Error probability …

– – The matched filters output (observation vector= ) is the detector input and the decision variable is a function of , i.e. •

r

For MPAM, MQAM and MFSK with coherent detection

z

r

• For MPSK with coherent detection

z

 

r

(

r

) • For non-coherent detection (M-FSK and DPSK),

z

 |

r

| We know that for calculating the average probability of symbol error, we need to determine • inside i

i

| sent) i

i Hence, we need to know the statistics of z, which depends on the modulation scheme and the detection type.

Dr Hassan Yousif 6

Error probability …

• AWGN channel model: – –

r

s

i

n s

i

a a i

2

a

)

iN

The elements of the noise vector are i.i.d 1 ,

n

2

N

) Gaussian random variables with zero-mean and variance – (

n

) 1  0  

n

0  

r

r r

independent Gaussian random variables. Its pdf is

p

r

|

i

1  0  

s

i

0  

r N

) Dr Hassan Yousif 7

Error probability …

• BPSK and BFSK with coherent detection:

BPSK s

1

“0”

E b

 2 (

t

)

“1”

B

 

s s

N

0 / 2 2  1 (

t

)

E b

s

2  1 (

t

)

BFSK “0” s

1

E b

s s

2 

P B

s s

b N

0  

P

N

0  

s

2

“1”

E b

 2 (

t

) Dr Hassan Yousif 8

Error probability …

Non-coherent detection of BFSK /

T

 ) /

T

 ) 

T

0

r

11   2 Decision variable: Difference of envelopes

z

z

1 

z

2

z

1 

r

2  11 2

r

12 

T

0

r

12 +

r

(

t

)

T

 2

t

)   2

z

Decision rule:

( )  ( ) 

m m

T

0

r

21   2 -

T

 2

t

) 

T

0

r

22   2

z

2  2  2 Dr Hassan Yousif 9

Error probability – cont’d

Non-coherent detection of BFSK …

B

1 2  1 2

z

) 2 1 2

z

2 | ) 1 1 ) 2 

z z

s

2 2    0

z

| ,

p

2 2 2

s

2 2   | 1 2   | 2 ) 2 2

P B

1

E

exp 2

b N

0 Rayleigh pdf Rician pdf • Similarly, non-coherent detection of DBPSK

P B

2

E b N

0 Dr Hassan Yousif 10

Error probability ….

Coherent detection of M-PAM – Decision variable:

4-PAM “00” s

1  3

E g

“01” s

2 

E g

0

z

r

1

“11” s

3

E g

“10” s

4  1 (

t

) 3

E g

 1 (

t

)

r

(

t

) 

T

0

r

1

ML detector

(Compare with M-1 thresholds) Dr Hassan Yousif 11

Error probability ….

• • Coherent detection of M-PAM ….

n

1 1 

s

m

the distance between adjacent symbols. For symbols on the border, error can happen only in one direction. Hence:

P

 

r E m g

g

  

g

( )

M

M

M s

M

M

2 

b

 3

E g

 (

E

 

Q M

log 2 

b

0   M   M  

g

(  2  0 Gaussian pdf with zero mean and variance

N

0 / 2 Dr Hassan Yousif 12

r

(

t

)

Error probability …

Coherent detection of M-QAM

s

1

s

2  2 (

t

)

s

3  1 (

t

) 

T

0

r

1

16-QAM ML detector s

4

s

5

s

6

s

7

s

8

s

9  1 (

t

)

s

10

s

11

s

12

“1100” “1101” “1111” “1110” s

13

s

14

s

15

s

16

“0100” “0101” “0111” “0110”

Parallel-to-serial converter  2 (

t

) 

T

0

r

2

ML detector

Dr Hassan Yousif 13

Error probability …

• • • • Coherent detection of M-QAM … M-QAM can be viewed as the combination of two

M

 PAM modulations on I and Q branches, respectively. No error occurs if no error is detected on either the I or the Q branch. Considering the symmetry of the signal space and the orthogonality of the I and Q branches: ( 1  Q and I)Pr(no    (

E

)   1 log

Q M

2 

b

0 Dr Hassan Yousif Average probability of

M

 14

Error probability …

r

(

t

) Coherent detection of MPSK  1 (

t

)  2 (

t

)  0

T

8-PSK

r

1

r

arctan

r

1 2  ˆ

“110” s

5

s

4 6

s

3  2 (

t

)

“011” s “001”

2

E s

s “000”

1  1 (

t

)

s

8

“100” “101” s

7 | Compute 

i

  ˆ | Choose smallest 

T

0

r

2 Decision variable

z

   

r

Dr Hassan Yousif 15

Error probability …

• • • • Coherent detection of MPSK … The detector compares the phase of observation vector to M-1 thresholds.

Due to the circular symmetry of the signal space, we have:

P E P C

M

  where 

s

N

0  0    2 It can be shown that (

E

) 2 2

s

 sin

N

0

M

or (

E

) 2  2 0 

b N

 sin  Dr Hassan Yousif 16

Error probability …

Coherent detection of M-FSK

r

(

t

)  1 (

t

) 

M

(

t

) 

T

0 

T

0

r

1

r M

    

r M r

1       

r r ML detector:

Choose the largest element in the observed vector Dr Hassan Yousif 17

Error probability …

• • Coherent detection of M-FSK … The dimension of the signal space is M. An upper bound for the average symbol error probability can be obtained by using the union bound. Hence:   or, equivalently (

E

)    2 

b N

0 Dr Hassan Yousif 18

• • Bit error probability versus symbol error probability Number of bits per symbol

k

 log 2

M

For orthogonal M-ary signaling (M-FSK)

P B P E

 2 2

k k

 1  1 

M

/ 2

M

 1

k

lim

P B P E

 1 2 • For M-PSK, M-PAM and M-QAM

P

P k P

Dr Hassan Yousif 19

P E

Probability of symbol error for binary modulation

Note!

“The same average symbol energy for different sizes of signal space”

E b

/

N

0 dB Dr Hassan Yousif 20

P E

Probability of symbol error for M-PSK

Note!

“The same average symbol energy for different sizes of signal space”

E b

/

N

0 dB Dr Hassan Yousif 21

Probability of symbol error for M-FSK

P E

Note!

“The same average symbol energy for different sizes of signal space”

E b

/

N

0 dB Dr Hassan Yousif 22

P E

Probability of symbol error for M-PAM

Note!

“The same average symbol energy for different sizes of signal space”

E b

/

N

0 dB Dr Hassan Yousif 23

P E

Probability of symbol error for M-QAM

Note!

“The same average symbol energy for different sizes of signal space”

E b

/

N

0 dB Dr Hassan Yousif 24

Example of samples of matched filter output for some bandpass modulation schemes Dr Hassan Yousif 25