Digital Video Broadcasting By Satellitecommunity.wvu.edu/~mcvalenti/documents/WVU2012.pdf · 2017. 1. 6. · Digital Video Broadcasting By Satellite Matthew C. Valenti Lane Department

Digital Video Broadcasting By Satellite

Matthew C. Valenti

Lane Department of Computer Science and Electrical EngineeringWest Virginia University

U.S.A.

Apr. 2, 2012

M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 1 / 41

Acknowledgements

I would like to thank:

Xingyu Xiang.

National Science Foundation.

Army Research Lab.

Hughes Network Systems.

DirecTV.


Outline

1 Satellite Television Standards

2 DVB-S2 Modulation

3 LDPC Coding

4 Tricks for Improving Performance

5 Conclusion


Satellite Television Standards

Outline


2 DVB-S2 Modulation

3 LDPC Coding


5 Conclusion


Satellite Television Standards Providers

Digital Satellite Television in the United States

DirecTV

Spinoff of Hughes Network Systems.

Began operations in 1994.

12 geosynchronous satellites.

20 million U.S. subscribers at end of 2011.

23,000 employees in U.S. and Latin America.

$33.4 billion market cap.

Dish Network.

Spinoff of EchoStar.

Began operations in 1996.

14 million U.S. subscribers in at end of 2011.

22,000 employees.

$14.7 billion market cap.



The DVB Family

DVB is a family of open standards for digital video broadcasting.

Maintained by 270-member industry consortium.

Published by ETSI.

Modes of transmission

Satellite: DVB-S, DVB-S2, and DVB-SH

Cable: DVB-C, DVB-C2

Terrestrial: DVB-T, DVB-T2, DVB-H



DVB-S

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:

:

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:

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B'@-"V"$="4M!!

Modulation: QPSK with α = 0.35 rolloff.

Channel coding: Concatenated Reed Solomon and convolutional.



DVB-S2

DVB-S2 was introduced in 2003 with the following goals:

Improve spectral efficiency by 30% through better modulation andcoding.

Modulation: QPSK, 8PSK, 16/32 APSK.Channel coding: LDPC with outer BCH code.

Offer a more diverse range of services.

HDTV broadcast television.Backhaul applications, e.g., electronic news gathering.Internet downlink access.Large-scale data content distribution, e.g., electronic newspapers.

Ratified 2005.



Adaptive Internet Downlink!

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O'8-"4P"$:"4Q!!


DVB-S2 Modulation

Outline


2 DVB-S2 Modulation

3 LDPC Coding


5 Conclusion


DVB-S2 Modulation

Why Not Use QAM?

A constellation with M = 2m conveys m bits per channel use.

Higher spectral-efficiencies require larger signal constellations.

Nonlinear satellite channels are not well suited to square QAM.

Nonlinear !TWTA !


DVB-S2 Modulation

The DVB-S2 Signal Constellations

A Companion Guide to DVB-S2

4 DVB-S2 in Detail

4.1 The Modulation Scheme The primary objective of DVB-S2 was to bring 8PSK within reach of consumer-sized satellite dishes and the increase in spectrum efficiency that 8PSK brings. With this work came the acceptance that real world transmission factors should be taken into account for the new system design. Rather than considering only the standard linear channel as with the previous DVB-S and DVB-DSNG specifications, the DVB-S2 specification recognises the following effects:

Phase noise

Non-linear magnitude and phase characteristics of a saturated transponder

The fact that the transponder is power limited

Group delay effects

This work led to the defined constellations to be optimised for the above conditions. The constellations that were chosen are shown below:

I

I

I

I

Q

Q

Q

QQPSK 8PSK

16APSK 32APSK

Figure 1: DVB-S2 Constellations

16APSK and 32APSK were chosen over the more familiar QAM constellations because their round shape makes them more power efficient in the power-limited channel that is a saturated satellite transponder. It is interesting to note that the ratio of the radii of the concentric circles for 16- and 32APSK changes slightly depending upon the FEC that is used in order to achieve maximum performance.

Page 7 of 21


DVB-S2 Modulation

Raised-Cosine Rolloff Filtering

DVB-S2 uses a tighter root RC-rolloff filter.

B = Rs(1 + α)

Assuming a 6 MHztransponder channel...

DVB-S Example:

α = 0.35.QPSK: Rb = 2Rs

2(6)/(1.35) = 8.9 Mbps

DVB-S2 Example:

α = 0.20.32-APSK: Rb = 5Rs

5(6)/(1.2) = 25 Mbps 0.75 0.5 0.25 0 0.25 0.5 0.750.750

0.25

0.5

0.75

1

1.25

2f/Rs

H(f)

= 0.20 = 0.25 = 0.35


DVB-S2 Modulation

Uncoded BER in AWGN

0 5 10 15 20 2510 6

10 5

10 4

10 3

10 2

10 1

100

Es/No in dB

BER

32APSK16APSK8PSKQPSK


LDPC Coding

Outline


2 DVB-S2 Modulation

3 LDPC Coding


5 Conclusion


LDPC Coding

Maximum Information Rate

Performance can beimproved by using errorcontrol coding.

Gains are limited by themodulation-constrainedcapacity.

LDPC codes are capableof approaching capacity. 10 5 0 5 10 15 20 25

0

1

2

3

4

5

6

Es/No in dB

Cap

acity

(bits

per

cha

nnel

use

)

32APSK16APSK8PSKQPSK

Symmetric information rate(assumes uniform input).


LDPC Coding

Available Code Rates

The encoder mapslength-k messages tolength-n codewords.

The code rate isR = k/n.

Useful bit rate isRu = R log2(M).

Two codeword lengths:

16, 200.64, 800.


LDPC Coding

Coding by Example: Single Parity-Check Codes

Consider the following rate R = 5/6 single parity-check code:

c = [1 0 1 0 1︸︷︷︸u

1︸︷︷︸parity bit

]

One error in any position may be detected:

c =[1 0 X 0 1 1

]Problem with using an SPC is that it can only detect a single error.


LDPC Coding

Product Codes

Place data into a k by k rectangular array.Encode each row with a SPC.Encode each column with a SPC.Result is a rate R = k2/(k + 1)2 code.

Example k = 2.

c1 = u1 c2 = u2 c3 = c1 ⊕ c2c4 = u3 c5 = u4 c6 = c4 ⊕ c5

c7 = c1 ⊕ c4 c8 = c2 ⊕ c5 c9 = c3 ⊕ c6=

1 0 1

1 1 0

0 1 1

A single error can be corrected by detecting its row and columnlocation

1 0 1

0 1 0

0 1 1

⇒1 0 1

1 1 0

0 1 1


LDPC Coding

Linear Codes

c1 = u1 c2 = u2 c3 = c1 ⊕ c2c4 = u3 c5 = u4 c6 = c4 ⊕ c5

c7 = c1 ⊕ c4 c8 = c2 ⊕ c5 c9 = c3 ⊕ c6

The example product code is characterized by the set of fivelinearly-independent equations:

c3 = c1 ⊕ c2 ⇒ c1 ⊕ c2 ⊕ c3 = 0

c6 = c4 ⊕ c5 ⇒ c4 ⊕ c5 ⊕ c6 = 0

c7 = c1 ⊕ c4 ⇒ c1 ⊕ c4 ⊕ c7 = 0

c8 = c2 ⊕ c5 ⇒ c2 ⊕ c4 ⊕ c8 = 0

c9 = c3 ⊕ c6 ⇒ c3 ⊕ c6 ⊕ c9 = 0

In general, it takes (n− k) linearly-independent equations to specify alinear code.M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 20 / 41

LDPC Coding

What is a Parity-Check Matrix?

The system of equations may be expressed in matrix form as:

cHT = 0

where H is a parity-check matrix.

Example:

c1 ⊕ c2 ⊕ c3 = 0c4 ⊕ c5 ⊕ c6 = 0c1 ⊕ c4 ⊕ c7 = 0c2 ⊕ c4 ⊕ c8 = 0c3 ⊕ c6 ⊕ c9 = 0System of equations

⇔ H =

1 1 1 0 0 0 0 0 00 0 0 1 1 1 0 0 01 0 0 1 0 0 1 0 00 1 0 1 0 0 0 1 00 0 1 0 0 1 0 0 1

Parity-check matrix


LDPC Coding

LDPC Codes

An LDPC code is a code with a large, sparse H matrix.

A code from MacKay and Neal (1996):

H =

1 1 1 11 1 1 1

1 1 1 11 1 1 11 1 1 1

1 1 1 11 1 1 1

1 1 1 11 1 1 1

The code called a (3, 4) regular code because:

Each column has exactly 3 ones.Each row has exactly 4 ones.

The DVB-S2 LDPC codes are irregular. More about this later.


LDPC Coding

DVB-S2 vs. Shannon


Tricks for Improving Performance

Outline


2 DVB-S2 Modulation

3 LDPC Coding


5 Conclusion


Tricks for Improving Performance BICM-ID

Iterative Demodulation and Decoding

Conventional receivers firstdemodulation, then decode.

Performance is improved byiterating between thedemodulator and decoder.

BICM-ID: bit-interleavedmodulation with iterativedecoding.

APSK demodulator

VND

CND

Hard decision

_

Π3

Π1-1

Π3-1

La(z) Π1

y

LDPC Decoder

Feedback LLRs


Tricks for Improving Performance BICM-ID

BICM vs. BICM-ID

9.8 10.1 10.4 10.7 11 11.3 11.6 11.9 12.2 12.5 12.8 13.1 13.4 13.710-6

10-5

10-4

10-3

10-2

10-1

100

Es/N0 in dB

BE

R

Rate 4 BICM (4by5 LDPC)Rate 4 BICM-ID (4by5 LDPC)Rate 3.75 BICM (3by4 LDPC)Rate 3.75 BICM-ID (3by4 LDPC)Rate 3 BICM (3by5 LDPC)Rate 3 BICM-ID (3by5 LDPC)

Curves show performance of 32APSK in AWGN.


Tricks for Improving Performance Constellation Shaping

Constellation Shaping

The symmetric information rate curves assume equiprobable signaling.It is possible to reduce the energy required to achieve a certaininformation rate by transmitting higher-energy signals less frequentlythan lower-energy signals.

-2 -1 0 1 2-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

Figure: Uniform 32APSK o vs. shaped32APSK o. Both constellations have thesame energy.

-10 0 10 20 300

1

2

3

4

5

Es/No (dB)

mut

ual i

nfor

mat

ion

11.211.411.611.8 12

3.8

3.9

4

uniformshaping g=1

Figure: The capacity of shaped 32APSK isabout 0.3 dB better than uniform 32APSK.



Sub-constellations

The 32APSK is partitioned into two equal-sized sub-constellations.

A shaping bit selects the sub-constellation, while the remaining bitsselect a symbol from the chosen sub-constellation.

The lower-energy sub-constellation is selected more frequently.

Figure: 32APSK w/ 2 sub-constellations

10100

01100

11101 01000

1100011100

10000

01101

01111 01001

1100110101

00101 00001

10001

0000000100

1111101011

00111

1011110011

0001100110 00010

0 1

01110

11110 01010

11011

1011110110 10010

1101011010

Figure: 32APSK symbol-labeling map



Shaping Encoder

The shaping encoder should produce more zeros than ones.

Example: (ns, ks) = (5, 3)

3 input data bits 5 output codeword bits0 0 0 0 0 0 0 00 0 1 0 0 0 0 10 1 0 0 0 0 1 00 1 1 0 0 1 0 01 0 0 0 1 0 0 01 0 1 1 0 0 0 01 1 0 0 0 0 1 11 1 1 1 0 1 0 0

p0 = 31/40: fraction of zeros.p1 = 9/40: fraction of ones.



Receiver Implementation

Demodulator + Shaping Decoder

S/PAPSK P/Sydemodulator

shapingdecoder

2-1

decoder

2S/PP/S

La(z)

FeedFeed

Hard d i i

LDPC Decoder

SCND

decision

1-1

-1

VND

CND_1 3

P3

1

dback LLRsdback LLRs

Additional complexity relative to BICM-ID due to shaping decoder.

MAP shaping decoder compares against all 2ks shaping codewords.



BER of Shaping in AWGN

4.4 4.5 4.6 4.7 4.8 4.9 5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 610-6

10-5

10-4

10-3

10-2

10-1

100

Eb/N

0 in dB

BE

R

BICM UniformBICM-ID Uniform Shaping (4,2)Shaping (6,3)Shaping (12,6)

BER of 32-APSK in AWGN at rate R=3 bits/symbol.

Code rates: Rc = 3/5 for uniform and Rc = 2/3 for shaped.


Tricks for Improving Performance Degree Optimization

Irregular vs. Regular Codes

An irregular LDPC code has columns with different weights.

The Hamming weight of a column is the number of 1’s.

An irregular code can outperform a regular code.

The main design consideration is the degree distribution, whichquantifies how many columns there are of a particular weight.

The optimal degree distribution can be found through linearprogramming.

The optimization takes into account the APSK modulation andshaping (if used).



Tanner Graphs

The parity-check matrix may be represented by a Tanner graph.Bipartite graph:

Check nodes: Represent the n− k parity-check equations.Variable nodes: Represent the n code bits.

If Hi,j = 1, then ith check node is connected to jth variable node.Example: For the parity-check matrix:

H =

1 1 1 0 0 0 0 0 00 0 0 1 1 1 0 0 01 0 0 1 0 0 1 0 00 1 0 1 0 0 0 1 00 0 1 0 0 1 0 0 1

The Tanner Graph is:



Degree Distribution

Edge-perspective degree distributions:

ρi is the fraction of edges touching degree i check nodes.λi is the fraction of edges touching degree i variable nodes.

For example, consider the Tanner graph:

15 edges.All are connected to degree-3 check nodes, so ρ3 = 15/15 = 1.Four are connected to degree-1 variable nodes, so λ1 = 4/15.Eight are connected to degree-2 variable nodes, so λ2 = 8/15.Three are connected to the degree-3 variable node, so λ3 = 3/15.



Optimal Degree Distributions

First, let’s optimize for uniform 32-APSK.

The DVB-S2 standard rate Rc = 3/5 LDPC code has degreedistributions:

ρ11 = 1

λ2 = 0.182

λ3 = 0.273

λ12 = 0.545

The optimized degree distributions are:

ρ11 = 1

λ2 = 0.182

λ4 = 0.473

λ19 = 0.345

A similar optimization can be performed for shaped 32-APSK.



BER with Optimized Degree Distributions

4.4 4.6 4.8 5 5.2 5.4 5.6 5.8 610-6

10-5

10-4

10-3

10-2

10-1

Eb/N

0 in dB

BE

RBICM-ID UniformBICM-ID Uniform withoptimized 3/5 LDPC codeDVB-S2 2/3 LDPC and(4,2) shaping codeoptimized 9/14 LDPC and(3,2) shaping code

BER of 32-APSK in AWGN at rate R=3 bits/symbol.Comparison of standard vs. optimized LDPC codes.


Tricks for Improving Performance Cumulative Gains

Summary of Performance Gains

4.6 4.8 5 5.2 5.4 5.6 5.8 6 6.210-6

10-5

10-4

10-3

10-2

10-1

Eb/N

0 in dB

BE

R

BICM UniformBICM-ID UniformBICM-ID Uniform withoptimized 3/5 LDPC codeDVB-S2 2/3 LDPC and(4,2) shaping codeoptimized 2/3 LDPC and(4, 2) shaping codeoptimized 9/14 LDPC and(3,2) shaping code

0.33 dB gain from using BICM-ID.0.46 dB gain from using shaping.0.34 dB gain from optimizing LDPC code.Cumulative gain of 1.13 dB.


Conclusion

Outline


2 DVB-S2 Modulation

3 LDPC Coding


5 Conclusion


Conclusion

Conclusion

DVB-S2 is a highly efficient system, thanks to

APSK modulation.Tight RC-rolloff filtering.Capacity-approaching irregular LDPC codes.

The performance of DVB-S2 can be improved by

BICM-ID.Constellation shaping.Optimization of LDPC degree-distribution.

The cumulative gain is 1 dB with all of these.

Future work:

Application to 64APSK and other modulations.Joint design of shaped modulation and code.


Conclusion

References

1 M.C. Valenti and X. Xiang, “Constellation shaping for bit-interleavedcoded APSK,” in Proc. IEEE Int. Conf. on Commun. (ICC), (Kyoto,Japan), June 2011.

2 C. Nannapaneni, M.C. Valenti, and X. Xiang, “Constellation shapingfor communication channels with quantized outputs,” in Proc. Conf.on Info. Sci. and Sys. (CISS), (Baltimore, MD), Mar. 2011.

3 X. Xiang and M.C. Valenti, “Improving DVB-S2 performance throughconstellation shaping and iterative demapping,” in Proc. IEEEMilitary Commun. Conf. (MILCOM), (Baltimore, MD), Nov. 2011.

4 X. Xiang and M.C. Valenti, “LDPC-coded APSK with constellationshaping and optimized degree distributions, ” submitted to IEEEGlobecom, (Anaheim, CA), Dec. 2012. In review.

5 M.C. Valenti and X. Xiang, “Constellation shaping for bit-interleavedLDPC coded APSK,” submitted to IEEE Trans. Commun., revisionunder review.


Conclusion

Thank You.


Documents

Digital Video Broadcasting By Satellitecommunity.wvu.edu/~mcvalenti/documents/WVU2012.pdf · 2017. 1. 6. · Digital Video Broadcasting By Satellite Matthew C. Valenti Lane Department