The Source-Channel Separation Theorem Revisited

IEEE Transactions on Information Theory

Volumn 41, Issue 1, 1995, Pages 44-54

  Vembu, Sridhar ^a   Verdú, Sergio ^b   Steinberg, Yossef ^c  

^a QUALCOMM INC   (United States)

^b PRINCETON UNIVERSITY   (United States)

^c BEN GURION UNIVERSITY OF THE NEGEV   (Israel)

Author keywords

channel capacity, source coding; joint source channel coding; separation theorem; Shannon Theory

Indexed keywords

BLOCK CODES; CHANNEL CAPACITY; CODES (SYMBOLS); CODING ERRORS; DECODING; INFORMATION THEORY; PROBABILITY;

JOINT SOURCE-CHANNEL CODING; SEPARATION THEOREM; SHANNON THEORY; SOURCE CODING; SOURCE-CHANNEL SEPARATION;

COMMUNICATION CHANNELS (INFORMATION THEORY);

EID: 0029231349     PISSN: 00189448     EISSN: 15579654     Source Type: Journal    
DOI: 10.1109/18.370119     Document Type: Article

References (17)

1. C. E. Shannon, “A mathematical theory of communication,” Bell Syst. Tech. J., vol. 27, pp. 379–423, July 1948.
2. R. L. Dobrushin, “General formulation of Shannon's basic theorems of information theory,” AMS Transl., vol. 33, pp. 323–438, AMS, Providence, RI, 1963.
3. M. S. Pinsker, Information and Information Stability of Random Variables and Processes. Oakland, CA: Holden-Day, 1964.
4. G. D. Hu, “On Shannon theorem and its converse for sequence of communication schemes in the case of abstract random variables,” in Trans. 3rd Prague Conf. on Information Theory, Statistical Decision Functions, Random Processes (Czechoslovak Academy of Sciences, Prague, 1964), pp. 285–333.
5. S. Vembu, “Information theory without ergodicity assumptions: Some new results,” Ph.D. dissertation, Princeton University, Princeton, NJ, June 1994.
6. A. N. Kolmogorov, “On the Shannon theory of information in the case of continuous signals,” IEEE Trans. Inform. Theory, vol. IT-2, pp. 102–108, Sept. 1956.
7. C. E. Shannon, “Coding theorems for a discrete source with a fidelity criterion,” in IRE Nat. Conv. Rec., pt. 4, pp. 142–163, Mar. 1959.
8. T. M. Cover, A. El Gamal, and M. Salehi, “Multiple access channels with arbitrary correlated sources,” IEEE Trans. Inform. Theory, vol. IT-26, no. 6, pp. 648–657, Nov. 1980.
9. R. M. Gray and L. D. Davisson, Eds., Ergodic and Information Theory (Benchmark Papers in Electrical Engineering and Computer Science), Dowden, Hutchinson and Ross, Inc. 1977.
10. I. Csiszár, “Information theory and ergodic theory,” Probl. Contr. Inform. Theory, vol. 16, no. 1, pp. 3–27, 1978.
11. J. C. Kieffer, “Block coding for weakly continuous channels,” IEEE Trans. Inform. Theory, vol. IT-27, pp. 721–727, 1981.
12. K. Winkelbauer, “On the asymptotic rate of non-ergodic information sources,” Kybernetika, vol. 6, pp. 127–148, 1970.
13. T. S. Han and S. Verdú, “Approximation theory of output statistics,” IEEE Trans. Inform. Theory, vol. 39, no. 3, pp. 752–772, May 1993.
14. S. Verdú and T. S. Han, “A general formula for channel capacity,” IEEE Trans. Inform. Theory, vol. 40, no. 4, pp. 1147–1157, July 1994.
15. I. Csiszár and J. Körner, Information Theory: Coding Theorems for Discrete Memoryless Systems. New York: Academic Press, 1981.
16. T. M. Cover and J. A. Thomas, Elements of Information Theory. New York: Wiley, 1991.
17. R. B. Ash, Information Theory. New York: Interscience, 1965; Dover, 1990.