PCCC Turbo Codes for IEEE 802.11n

1. PCCC Turbo Codes for IEEE 802.11n B. Bougard; B. Van Poucke; L. Van der Perre {bougardb, vanpouck, vdperre}@imec.be Presented by Bert Gyselinckx IMEC/Wireless Research March 2004

2. Outline • Advanced FEC for WLAN • Myths about Turbo-Codes • Turbo Codes: preferred choice for WLAN

3. Outline • Advanced FEC for WLAN • Myths about Turbo-Codes • Turbo Codes: preferred choice for WLAN

4. 8 4 Spectral Efficiency [bit/s/Hz] Add points ( Benedetto ) 2 1 1/2 Eb /No [dB] Advanced FECs get close to Shannon’s Limit 8 8 Shannon Limit Shannon Limit 4 4 Uncoded Uncoded Spectral Efficiency [bit/s/Hz] Spectral Efficiency [bit/s/Hz] QPSK QPSK Add points ( Add points ( Benedetto Benedetto ) ) 2 2 SCBC SCBC Regular Regular Irregular Viterbi+RS Viterbi+RS LDPC LDPC LDPC 1 1 PCCC PCCC 1/2 1/2 Eb Eb /No [dB] /No [dB]

5. PCCC and LDPC are close competitors Performance

6. PCCC and LDPC are close competitors Complexity > < Turbo: N: block size; v: constraint length LDPC: N: block size; M: code dimension; Nc: #ones per column of H; #ones per row of H

7. Outline • Advanced FEC for WLAN • Myths about Turbo-Codes • Turbo Codes: preferred choice for WLAN

8. Myth 1: PCCCs have poor performance with small blocksize

9. Myth 2: PCCCs require code termination that reduces code rate Double termination Virtual termination

10. Myth 3: PCCCs are power hungry Look at the average TX+RX DC power with adaptive modulation over a representative set of channel instances -5%

11. Outline • Advanced FEC for WLAN • Myths about Turbo-Codes • Turbo Codes: preferred choice for WLAN

12. PCCC assets • PCCC already recognized in several standards • Potential for low latency • Potential for low power • Flexibility • Unconstrained in blocksize (numerous interleaver sizes possible) • Any code rate achievable by puncturing • Code rate ‘compatible’ with CC scheme • Energy-Scalable architecture possible

13. Parallel PCCC codec prototype Nominal clock frequency (max) 160 MHz (170.9 MHz) Nominal throughput (max) 75.6 Mb/s (80.7 Mb/s) Number of gates <400 K Total RAM area 36 Kbit Decoding Latency 5s Energy consumption <1.45 nJ/bit This holds for UMC .18 m technology. If mapped in .13 m, the architecture achieves easily 100Mbps with still less latency and energy consumption

14. Flexibility makes integration in 802.11n easy • Interleaver size leading to an integer number of coded OFDM symbols without bit stuffing • Interleaver sizes = {128, 144, 192, 256, 288, 384, 432} • Code rate = {1/3, 1/2, 2/3, 3/4} • Virtual termination Interleaver size

15. Energy-scalability improves the data rate versus energy consumption trade-off Total Rx energy per bit vs. net goodput

16. Backup

17. LDPC in a nutshell Parity check matrix c.HT=0 Tanner graph

18. LDPC in a nutshell: decoding Sum-product algorithm

19. s SISO 1 - c1 D D D DILV ILV ILV c2 ILV SISO 2 D D D - PCCC in a nutshell

20. PCCC in a nutshell: decoding BCJR algorithm

21. Key References [1] S. B. Wicker, S. Kim, Fundamentals of codes, graphs and iterative decoding, Kluwer Academic Publishers, 2003 [2] A. Giulietti, B. Bougard, L. Van der Perre, Turbo Codes, Desirable and Designable, Kluwer Academic Publisher, 2003 [3] R. G. Gallager, Low Density Parity-Check Codes, Cambridge, MA: MIT Press, 1963 [4] G. Berrou, A. Glavieux, P. Thitimajshima, “Near Shannon limit error-correcting coding and decoding: Turbo Codes”, in Proc. Int. Conf. Commun., Geneva, Switzerland, May 1993 pp. 1064-1070. [5] C. Schurgers et al., "Memory Optimization of MAP Turbo Decoder Algorithms,“, IEEE Transactions on VLSI Systems, Vol.9, No.2, pp. 305-312, April 2001. [6] A. Giulietti et al., "Parallel turbo code interleavers : avoiding collisions in accesses to storage elements", Electronics Letters, Vol. 38 No. 5, Feb. 2002 [7] Thul, M.J.; Gilbert, F.; Wehn, N, "Concurrent interleaving architectures for high-throughput channel coding”, in Proc. IEEE ICASSP 2003, Vol. 2 , pp.  6-10 April 2003 [8] B. Bougard et al., “A Scalable 837nJ/bit 75Mb/s Parallel Concatenated Convolutional (Turbo-) CODEC”, IEEE International Solid-State Circuits Conference, Digest of Technical Papers, Vol. 1., pp.152 - 484, San Francisco, CA, Feb. 2003 [9] D. J. C. Mac Kay, “Good error correcting codes based on very sparse matrices”, IEEE Trans. Inform. Theory, vol. 45, pp. 399-431, Mar. 1999 [10] T. Richardson and R. Urbanke, “Efficient encoding of Low-density parity-check codes”, IEEE Trans. Inform. Theory, vol. 47, pp. 638-656, Feb. 2001