doc.: IEEE / n Submission September 2004 France TelecomSlide 1 Partial Proposal: Turbo Codes Marie-Helene Hamon, Olivier Seller, John Benko France Telecom Claude Berrou ENST Bretagne Jacky TouschTurboConcept Brian EdmonstoniCoding

doc.: IEEE / n Submission September 2004 France TelecomSlide 2 Outline Part I: Turbo Codes Part II: Turbo Codes for n Why TC for n? Flexibility Performance

doc.: IEEE / n Submission September 2004 France TelecomSlide 3 Outline Part I: Turbo Codes Part II: Turbo Codes for n Why TC for n? Flexibility Performance

doc.: IEEE / n Submission September 2004 France TelecomSlide 4 Known applications of convolutional turbo codes Applicationturbo codeterminationpolynomialsrates CCSDS (deep space) binary, 16-state tail bits23, 33, 25, 371/6, 1/4, 1/3, 1/2 UMTS, CDMA2000 (3G Mobile) binary, 8-state tail bits13, 15, 171/4, 1/3, 1/2 DVB-RCS (Return Channel over Satellite) duo-binary, 8-state circular15, 131/3 up to 6/7 DVB-RCT (Return Channel over Terrestrial) duo-binary, 8-state circular15, 131/2, 3/4 Inmarsat (M4) binary, 16-state no23, 351/2 Eutelsat (Skyplex) duo-binary, 8-state circular15, 134/5, 6/7 IEEE (WiMAX) duo-binary, 8-state circular15, 131/2 up to 7/8

doc.: IEEE / n Submission September 2004 France TelecomSlide 5 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 Performance and simplicity

doc.: IEEE / n Submission September 2004 France TelecomSlide 6 The TCs used in practice

doc.: IEEE / n Submission September 2004 France TelecomSlide 7 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 + P 1 ; -if j mod. 4 = 2, then P = P 2 ; -if j mod. 4 = 3, then P = N/2 + P 3. i = P 0 *j + P +1 mod. N No ROM Quasi-regular (no routing issue) Versatility Inherent parallelism

doc.: IEEE / n Submission September 2004 France TelecomSlide 8 Decoding Max-Log-MAP algorithm Sliding window + inherent parallelism, easy connectivity (quasi-regular permutation)

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

doc.: IEEE / n Submission September 2004 France TelecomSlide 10 Outline Part I: Turbo Codes Part II: Turbo Codes for n Why TC for n? Flexibility Performance

doc.: IEEE / n Submission September 2004 France TelecomSlide 11 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

doc.: IEEE / n Submission September 2004 France TelecomSlide 12 Duo-Binary Turbo Code

doc.: IEEE / n Submission September 2004 France TelecomSlide 13 Duo-Binary Turbo Code Duo-binary input: –Reduction of Latency & Complexity (compared to binary TCs) –Complexity per decoded bit is 35 % lower than binary 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

doc.: IEEE / n Submission September 2004 France TelecomSlide 14 Flexibility & Efficiency 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

doc.: IEEE / n Submission September 2004 France TelecomSlide 15 # of Iterations vs. Performance The number of iterations can be adjusted for better performance – complexity trade-off

doc.: IEEE / n Submission September 2004 France TelecomSlide 16 Simulation Environment Both Turbo Codes and a CCs simulated Simulation chain based on a PHY model –SISO configuration mainly –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

doc.: IEEE / n Submission September 2004 France TelecomSlide 17 Performance: AWGN dB gain over a CC

doc.: IEEE / n Submission September 2004 France TelecomSlide 18 Performance: model B ~ dB gain over a CC

doc.: IEEE / n Submission September 2004 France TelecomSlide 19 Performance: model D ~ dB gain over a CC

doc.: IEEE / n Submission September 2004 France TelecomSlide 20 Performance: model E ~ dB gain over a CC

doc.: IEEE / n Submission September 2004 France TelecomSlide 21 Performance in MIMO system Spatial multiplexing, 2x2, MMSE receiver

doc.: IEEE / n Submission September 2004 France TelecomSlide 22 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 binary TCs –Performance is slightly better than binary TCs Significant performance gain over.11a CC: – dB on AWGN channel – dB on n channel models

doc.: IEEE / n Submission September 2004 France TelecomSlide 23 References [1] IEEE /003, "Turbo Codes for n", France Telecom R&D, ENST Bretagne, iCoding Technology, TurboConcept, January [2] IEEE /243, "Turbo Codes for n", France Telecom R&D,iCoding Technology, May [3] IEEE /256, "PCCC Turbo Codes for IEEE n", IMEC, March [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 [8] EN : Digital Video Broadcasting (DVB) "Interaction channel or satellite distribution systems". December [9] EN : Digital Video Broadcasting (DVB) "Specification of interaction channel for digital terrestrial TV including multiple access OFDM". March 2002.