1. Partial Proposal: Turbo Codes
Month 2000
doc.: IEEE /xxx
September 2004
Partial Proposal: Turbo Codes
Marie-Helene Hamon, Olivier Seller, John Benko France Telecom
Claude Berrou ENST Bretagne
Jacky Tousch TurboConcept
Brian Edmonston iCoding
France Telecom
John Doe, His Company

2. Outline Part I: Turbo Codes Part II: Turbo Codes for 802.11n
Month 2000
doc.: IEEE /xxx
September 2004
Outline
Part I: Turbo Codes
Part II: Turbo Codes for n
Why TC for n?
Flexibility
Performance
France Telecom
John Doe, His Company

3. Outline Part I: Turbo Codes Part II: Turbo Codes for 802.11n
Month 2000
doc.: IEEE /xxx
September 2004
Outline
Part I: Turbo Codes
Part II: Turbo Codes for n
Why TC for n?
Flexibility
Performance
France Telecom
John Doe, His Company

4. Known applications of convolutional turbo codes
Month 2000
doc.: IEEE /xxx
September 2004
Application
turbo code
termination
polynomials
rates
CCSDS
(deep space)
binary,
16-state
tail bits
23, 33, 25, 37
1/6, 1/4, 1/3, 1/2
UMTS, CDMA2000
(3G Mobile)
8-state
13, 15, 17
1/4, 1/3, 1/2
DVB-RCS
(Return Channel over Satellite)
duo-binary,
circular
15, 13
1/3 up to 6/7
DVB-RCT
(Return Channel over Terrestrial)
1/2, 3/4
Inmarsat
(M4) no
23, 35
1/2
Eutelsat
(Skyplex)
4/5, 6/7
IEEE
(WiMAX)
1/2 up to 7/8
Known applications of convolutional turbo codes
France Telecom
John Doe, His Company

5. Main progress in turbo coding/decoding since 1993
September 2004
Main progress in turbo coding/decoding since 1993
Max-Log-MAP and Max*-Log-MAP algorithms
Sliding window
Duo-binary turbo codes
Circular (tail-biting) encoding
Permutations
Parallelism
Computation or estimation of Minimum Hamming distances (MHDs)
Stopping criterion
Bit-interleaved turbo coded modulation
Simplicity
Performance and simplicity
Performance
Throughput
Maturity
Power consumption
France Telecom

6. The TCs used in practice
September 2004
The TCs used in practice
France Telecom

7. The turbo code proposed for all sizes, all coding rates
September 2004
The turbo code proposed for all sizes, all coding rates
Very simple algorithmic permutation:
i = 0, …, N-1, j = 0, ...N-1
level 1: if j mod. 2 = 0, let (A,B) = (B,A) (invert the couple)
level 2:
- if j mod. 4 = 0, then P = 0;
- if j mod. 4 = 1, then P = N/2 + P1;
- if j mod. 4 = 2, then P = P2;
- if j mod. 4 = 3, then P = N/2 + P3.
i = P0*j + P +1 mod. N
No ROM
Quasi-regular (no routing issue)
Versatility
Inherent parallelism
France Telecom

8. Decoding Max-Log-MAP algorithm Sliding window
September 2004
Decoding
Max-Log-MAP algorithm
Sliding window
+ inherent parallelism, easy connectivity (quasi-regular permutation)
France Telecom

9. Decoding complexity Useful rate: 100 Mbps with 8 iterations
September 2004
Decoding complexity
Useful rate: 100 Mbps with 8 iterations
5-bit quantization (data and extrinsic)
Gates
Clock = 100 Mhz
82,000 @ Clock = 200 Mhz
54,000 @ Clock = 400 Mhz
RAM
Data input buffer +
8.5xk for extrinsic information
for sliding window
(example: 72,000 bits for 1000-byte block)
For 0.18m CMOS
No ROM
Duo-binary TC decoders are already available from several providers (iCoding Tech., TurboConcept, ECC, Xilinx, Altera, …)
France Telecom

10. Outline Part I: Turbo Codes Part II: Turbo Codes for 802.11n
Month 2000
doc.: IEEE /xxx
September 2004
Outline
Part I: Turbo Codes
Part II: Turbo Codes for n
Why TC for n?
Flexibility
Performance
France Telecom
John Doe, His Company

11. Introduction Purpose Properties of Turbo Codes (TCs)
September 2004
Introduction
Purpose
Show the multiple benefits of TCs for n standard
Overview of duo-binary TCs
Comparison between TC and .11a Convolutional Code
High Flexibility
Complexity
Properties of Turbo Codes (TCs)
Rely on soft iterative decoding to achieve high coding gains
Good performance, near channel capacity for long blocks
Easy adaptation in the standard frame
(easy block size adaptation to the MAC layer)
Well controlled hardware development and complexity
TC advantages led to recent adoption in standards
France Telecom

12. September 2004
Duo-Binary Turbo Code
France Telecom

13. Duo-Binary Turbo Code Duo-binary input:
September 2004
Duo-Binary Turbo Code
Duo-binary input:
Reduction of Latency & Complexity (compared to UMTS TCs)
Complexity per decoded bit is 35 % lower than binary UMTS TCs.
Better convergence in the iterative decoding process
Circular Recursive Systematic Codes
Constituent codes
No trellis termination overhead!
Original permuter scheme
Larger minimum distance
Better asymptotic performance
France Telecom

14. # of Iterations vs. Performance
September 2004
# of Iterations vs. Performance
The number of iterations can be adjusted for better performance – complexity trade-off
France Telecom

15. Simulation Environment
September 2004
Simulation Environment
Both Turbo Codes and a CCs simulated
Simulation chain based on a PHY model
SISO configuration
CC59 and CC67 followed
Simulated Channels: AWGN, models B, D, E
No PHY impairments
Packet size of 1000 bytes.
Minimum of 100 packet errors
Assume perfect channel estimation & synchronization
Turbo Code settings:
8-state Duo-Binary Convolutional Turbo Codes
Max-Log-MAP decoding
8 iterations
France Telecom

16. Performance: AWGN 3.5-4 dB gain over 802.11a CC September 2004
France Telecom

17. Performance: model B ~3 dB gain over 802.11a CC September 2004
France Telecom

18. Performance: model D ~3 dB gain over 802.11a CC September 2004
France Telecom

19. Performance: model E ~3 dB gain over 802.11a CC September 2004
France Telecom

20. Flexibility All Coding Rates possible (no limitations)
September 2004
Flexibility
All Coding Rates possible (no limitations)
Same encoder/decoder for:
any coding rate via simple puncturing adaptation
different block sizes via adjusting permutation parameters
4 parameters are used per block size to define an interleaver
Higher PHY data rates enabled with TCs:
High coding gains over a CC ( =>lower PER)
More efficient transmission modes enabled more often.
Combination with higher-order constellations
Better system efficiency
ARQ algorithm used less frequently
France Telecom

21. Conclusions Mature, stable, well established and implemented
September 2004
Conclusions
Mature, stable, well established and implemented
Multiple Patents, but well defined licensing
All other advanced FECs also have patents
Complexity:
Show 35% decrease in complexity per decoded bit over UMTS TCs
Performance is slightly better than UMTS TCs
Significant performance gain over .11a CC:
dB on AWGN channel
3 dB on n channel models
France Telecom

22. September 2004
References
[1] IEEE /003, "Turbo Codes for n", France Telecom R&D, ENST Bretagne, iCoding Technology, TurboConcept, January 2004.
[2] IEEE /243, "Turbo Codes for n", France Telecom R&D,iCoding Technology, May 2004.
[3] IEEE /256, "PCCC Turbo Codes for IEEE n", IMEC, March 2004.
[4] C. Berrou, A. Glavieux, P. Thitimajshima, "Near Shannon limit error-correcting coding and decoding: Turbo Codes", ICC93, vol. 2, pp , May 93.
[5] C. Berrou, "The ten-year-old turbo codes are entering into service", IEEE Communications Magazine, vol. 41, pp , August 03.
[6] C. Berrou, M. Jezequel, C. Douillard, S. Kerouedan, "The advantages of non-binary turbo codes", Proc IEEE ITW 2001, pp , Sept. 01.
[7] TS : 3rd Generation Partnership Project (3GPP) ; Technical Specification Group (TSG) ; Radio Access Network (RAN) ; Working Group 1 (WG1); "Multiplexing and channel coding (FDD)". October 1999.
[8] EN : Digital Video Broadcasting (DVB) "Interaction channel or satellite distribution systems". December 2000.
[9] EN : Digital Video Broadcasting (DVB) "Specification of interaction channel for digital terrestrial TV including multiple access OFDM". March 2002.
France Telecom