On the design of bit-interleaved turbo-coded modulation with low error floors

In this paper, we introduce an algorithm to optimize the performance in the error-floor region of bit-interleaved turbo-coded modulation (BITCM) on the additive white Gaussian noise channel. The key ingredient is an exact turbo code weight distribution algorithm producing a list of all codewords in the underlying turbo code of weight less than a given threshold. In BITCM, the information sequence is turbo-encoded, bit-interleaved, and mapped to signal points in a signal constellation. Using the union-bounding technique, we show that a well-designed bit interleaver is crucial to have a low error floor. Furthermore, the error-rate performance in the waterfall region depends on the bit interleaver, since the level of protection from channel noise on the bit level depends on the bit position and the neighboring bit values within the same symbol in the transmitted sequence. We observe a tradeoff between error-rate performance in the waterfall and error-floor regions, as illustrated by an extensive case study of a high-rate BITCM scheme. This tradeoff is typical in iterative decoding of turbo-like codes. The reported case study shows that it is possible to design bit interleavers with our proposed algorithm with equal or better performance in the waterfall region and superior performance in the error-floor region, compared with randomly generated bit interleavers. In particular, we were able to design BITCM schemes with maximum-likelihood decoding frame-error rates of 10-12 and 10 -17 at 2.6 and 3.8 dB away from unconstrained channel capacity, at spectral efficiencies of 3.10 and 6.20 b/s/Hz using square 16 and 256-quadrature amplitude modulation signal constellations, respectively

[1]  William E. Ryan,et al.  Bit-reliability mapping in LDPC-coded modulation systems , 2005, IEEE Communications Letters.

[2]  Øyvind Ytrehus,et al.  Improved algorithms for the determination of turbo-code weight distributions , 2005, IEEE Transactions on Communications.

[3]  Sven Riedel,et al.  MAP Decoding of Convolutional Codes Using Reciprocal Dual Codes , 1998, IEEE Trans. Inf. Theory.

[4]  John G. Proakis,et al.  Digital Communications , 1983 .

[5]  Giorgio Ausiello,et al.  Structure Preserving Reductions among Convex Optimization Problems , 1980, J. Comput. Syst. Sci..

[6]  Richard D. Wesel,et al.  Constellation labeling for linear encoders , 2001, IEEE Trans. Inf. Theory.

[7]  E. Rosnes,et al.  Improved algorithms for high rate turbo code weight distribution calculation , 2003, 10th International Conference on Telecommunications, 2003. ICT 2003..

[8]  C. Berrou,et al.  Non-binary convolutional codes for turbo coding , 1999 .

[9]  Amir H. Banihashemi,et al.  Reliability-based coded modulation with low-density parity-check codes , 2006, IEEE Transactions on Communications.

[10]  Henk D. L. Hollmann,et al.  Common coordinates in consecutive addresses , 2003, IEEE Trans. Inf. Theory.

[11]  C. Heegard,et al.  Interleaver design methods for turbo codes , 1998, Proceedings. 1998 IEEE International Symposium on Information Theory (Cat. No.98CH36252).

[12]  Dariush Divsalar,et al.  Iterative turbo decoder analysis based on density evolution , 2001, IEEE J. Sel. Areas Commun..

[13]  Roberto Garello,et al.  Computing the free distance of turbo codes and serially concatenated codes with interleavers: algorithms and applications , 2001, IEEE J. Sel. Areas Commun..

[14]  Hideki Imai,et al.  Decoding of high-rate turbo codes using a syndrome trellis , 2001, ICC 2001. IEEE International Conference on Communications. Conference Record (Cat. No.01CH37240).

[15]  A. Glavieux,et al.  Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[16]  Johannes B. Huber,et al.  Interleaver design using backtracking and spreading methods , 2000, 2000 IEEE International Symposium on Information Theory (Cat. No.00CH37060).

[17]  Daniel J. Costello,et al.  A distance spectrum interpretation of turbo codes , 1996, IEEE Trans. Inf. Theory.

[18]  Stéphane Y. Le Goff Signal constellations for bit-interleaved coded modulation , 2003, IEEE Trans. Inf. Theory.

[19]  Erik G. Ström,et al.  On the optimality of the binary reflected Gray code , 2004, IEEE Transactions on Information Theory.

[20]  Giuseppe Caire,et al.  Bit-Interleaved Coded Modulation , 2008, Found. Trends Commun. Inf. Theory.

[21]  Andres I. Vila Casado,et al.  The all-zero iterative decoding algorithm for turbo code minimum distance computation , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[22]  C. Berrou,et al.  Computing the minimum distances of linear codes by the error impulse method , 2002, Proceedings IEEE International Symposium on Information Theory,.

[23]  D.J.C. MacKay,et al.  Good error-correcting codes based on very sparse matrices , 1997, Proceedings of IEEE International Symposium on Information Theory.