TURBO EQUALIZATION - Adaptive Signal Processing: Next Generation Solutions - page 206

that the filtered noise power is lower bounded as

s 2
kHk

s 2
P k¼ 0 kh k k

E ( b 2
i

)

2 ¼ 2 :

Deduce the optimal coefficients ( p k ) to minimize the filtered noise power.

REFERENCES

1. C. Berrou and A. Glavieux, Near optimum error correction coding and decoding: Turbo
codes, IEEE Trans. Communications , 44, pp. 1262-1271, (1996).
2. S. Benedetto and G. Montorsi, Iterative decoding of serially concatenated convolutional
codes, Electronics Letters , 32, pp. 1186-1188, (1996).
3. S. Benedetto, D. Divsalar, G. Montorsi, and F. Pollara, Analysis, design, and iterative
decoding of double serial concatenated codes with interleaves, IEEE Selected Areas of
Communications , 16, pp. 231-244, (1998).
4. J. Haguenauer, E. Offer, and L. Papke, Iterative decoding of binary block and convolutional
codes, IEEE Trans. Information Theory , 42, pp. 429-445, (1996).
5. L. Hanzo, T. H. Liew, and B. L. Yeap, Turbo Coding, Turbo Equalisation and Space-Time
Coding . Chichester, UK: Wiley, 2002.
6. C. Heegard and S. B. Wicker, Turbo Coding . Boston, MA: Kluwer, 1999.
7. B. Vucetic and J. Yuan, Turbo Codes: Principles and Applications . Boston, MA: Kluwer,
2000.
8. C. E. Shannon, A mathematical theory of communication, Bell System Technical J. , 27,
pp. 379-423, 623-656, (1948).
9. J. G. Proakis, Digital Communications . Boston, MA: McGraw-Hill, 2001.
10. N. Blaustein and C. G. Christodoulou, Radio Propagation and Adaptive Antennas for
Wireless Communication Links . Hoboken, NJ: Wiley, 2007.
11. S. Haykin, Adaptive Filter Theory . Upper Saddle River, NJ: Prentice-Hall, 4th ed., 2001.
12. A. H. Sayed, Fundamentals of Adaptive Filtering . Hoboken, NJ: Wiley, 2003.
13. G. D. Forney, Jr., The Viterbi algorithm, Proc. IEEE , 61, pp. 268-278, (1973).
14. R. W. Chang and J. C. Hancock, On receiver structures for channels having memory, IEEE
Trans. Information Theory , 12, pp. 463-468, (1966).
15. L. E. Baum and T. Petrie, Statistical inference for probabilistic functions of finite state
Markov chains, Ann. Math. Statist. , 37, pp. 1554-1563, (1966).
16. G. Ungerboeck, Nonlinear equalization of binary signals in Gaussian noise, IEEE Trans.
Communication Technology , 19, pp. 1128-1137, (1971).
17. L. R. Bahl, J. Cocke, F. Jelinek, and J. Raviv, Optimal decoding of linear codes for mini-
mizing symbol error rate, IEEE Trans. Information Theoiy , 20, No. 3, pp. 284-287, (1974).
18. G. K. Kaleh and R. Vallet, Joint parameter estimation and symbol detection for linear or
nonlinear unknown channels, IEEE Trans. Communications , 42, pp. 2406-2413, (1994).
19. S. Chen, G. J. Gibson, C. F. N. Cowan, and P. M. Grant, Adaptive equalization of
finite nonlinear channels using multilayer perceptions, Signal Processing , 10,
pp. 107-119, (1990).