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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 2 / 41
Outline
1 Satellite Television Standards
2 DVB-S2 Modulation
3 LDPC Coding
4 Tricks for Improving Performance
5 Conclusion
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 3 / 41
Satellite Television Standards
Outline
1 Satellite Television Standards
2 DVB-S2 Modulation
3 LDPC Coding
4 Tricks for Improving Performance
5 Conclusion
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 4 / 41
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.
$14.7 billion market cap.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 5 / 41
Satellite Television Standards Providers
The DVB Family
DVB is a family of open standards for digital video broadcasting.
Maintained by 270-member industry consortium.
Published by ETSI.
Modes of transmission
Satellite: DVB-S, DVB-S2, and DVB-SH
Cable: DVB-C, DVB-C2
Terrestrial: DVB-T, DVB-T2, DVB-H
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 6 / 41
Satellite Television Standards Providers
DVB-S
!!"#$%&'()$("*+),-".$"/01234"
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B'@-"V"$="4M!!
Modulation: QPSK with α = 0.35 rolloff.
Channel coding: Concatenated Reed Solomon and convolutional.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 7 / 41
Satellite Television Standards Providers
DVB-S2
DVB-S2 was introduced in 2003 with the following goals:
Improve spectral efficiency by 30% through better modulation andcoding.
Modulation: QPSK, 8PSK, 16/32 APSK.Channel coding: LDPC with outer BCH code.
Offer a more diverse range of services.
HDTV broadcast television.Backhaul applications, e.g., electronic news gathering.Internet downlink access.Large-scale data content distribution, e.g., electronic newspapers.
Ratified 2005.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 8 / 41
Satellite Television Standards Providers
Adaptive Internet Downlink!
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O'8-"4P"$:"4Q!!
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 9 / 41
DVB-S2 Modulation
Outline
1 Satellite Television Standards
2 DVB-S2 Modulation
3 LDPC Coding
4 Tricks for Improving Performance
5 Conclusion
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 10 / 41
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 !
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 11 / 41
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 12 / 41
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 13 / 41
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 14 / 41
LDPC Coding
Outline
1 Satellite Television Standards
2 DVB-S2 Modulation
3 LDPC Coding
4 Tricks for Improving Performance
5 Conclusion
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 15 / 41
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).
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 16 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 17 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 18 / 41
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 19 / 41
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 21 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 22 / 41
LDPC Coding
DVB-S2 vs. Shannon
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 23 / 41
Tricks for Improving Performance
Outline
1 Satellite Television Standards
2 DVB-S2 Modulation
3 LDPC Coding
4 Tricks for Improving Performance
5 Conclusion
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 24 / 41
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 25 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 26 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 27 / 41
Tricks for Improving Performance Constellation Shaping
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
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 28 / 41
Tricks for Improving Performance Constellation Shaping
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 29 / 41
Tricks for Improving Performance Constellation Shaping
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 30 / 41
Tricks for Improving Performance Constellation Shaping
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 31 / 41
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).
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 32 / 41
Tricks for Improving Performance Degree Optimization
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:
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 33 / 41
Tricks for Improving Performance Degree Optimization
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 34 / 41
Tricks for Improving Performance Degree Optimization
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 35 / 41
Tricks for Improving Performance Degree Optimization
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 36 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 37 / 41
Conclusion
Outline
1 Satellite Television Standards
2 DVB-S2 Modulation
3 LDPC Coding
4 Tricks for Improving Performance
5 Conclusion
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 38 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 39 / 41
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.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 40 / 41
Conclusion
Thank You.
M.C. Valenti ( Lane Department of Computer Science and Electrical Engineering West Virginia University U.S.A. )LDPC Codes Apr. 2, 2012 41 / 41