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  • Research Article
  • Open Access

Combined Source-Channel Coding of Images under Power and Bandwidth Constraints

EURASIP Journal on Advances in Signal Processing20062007:049172

  • Received: 8 June 2006
  • Accepted: 14 October 2006
  • Published:


This paper proposes a framework for combined source-channel coding for a power and bandwidth constrained noisy channel. The framework is applied to progressive image transmission using constant envelope -ary phase shift key ( -PSK) signaling over an additive white Gaussian noise channel. First, the framework is developed for uncoded -PSK signaling (with ). Then, it is extended to include coded -PSK modulation using trellis coded modulation (TCM). An adaptive TCM system is also presented. Simulation results show that, depending on the constellation size, coded -PSK signaling performs 3.1 to 5.2 dB better than uncoded -PSK signaling. Finally, the performance of our combined source-channel coding scheme is investigated from the channel capacity point of view. Our framework is further extended to include powerful channel codes like turbo and low-density parity-check (LDPC) codes. With these powerful codes, our proposed scheme performs about one dB away from the capacity-achieving SNR value of the QPSK channel.


  • Additive White Gaussian Noise
  • Channel Code
  • Noisy Channel
  • Additive White Gaussian Noise Channel
  • Powerful Channel


Authors’ Affiliations

Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA
Department of Electrical Engineering, University of Hawaii, Honolulu, HI 96822, USA


  1. Shannon C: A mathematical theory of communication. The Bell System Technical Journal 1948, 27: 379-423.MathSciNetView ArticleMATHGoogle Scholar
  2. Hochwald B, Zeger K: Tradeoff between source and channel coding. IEEE Transactions on Information Theory 1997,43(5):1412-1424. 10.1109/18.623141MathSciNetView ArticleMATHGoogle Scholar
  3. Sherwood G, Zeger K: Progressive image coding for noisy channels. IEEE Signal Processing Letters 1997,4(7):189-191. 10.1109/97.596882View ArticleGoogle Scholar
  4. Said A, Pearlman W: A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits and Systems for Video Technology 1996,3(3):243-250.View ArticleGoogle Scholar
  5. Ramabadran T, Gaitonde S: A tutorial on CRC computations. IEEE Micro 1988,8(4):62-75. 10.1109/40.7773View ArticleGoogle Scholar
  6. Hamzaoui R, Stankovic V, Xiong Z: Optimized error protection of scalable image bitstreams. IEEE Signal Processing Magazine 2005,22(6):91-107.View ArticleGoogle Scholar
  7. Fossorier M, Xiong Z, Zeger K: Progressive source coding for a power constrained Gaussian channel. IEEE Transactions on Communications 2001,49(8):1301-1306. 10.1109/26.939838View ArticleMATHGoogle Scholar
  8. Chande V, Farvardin N: Progressive transmission of images over memoryless noisy channels. IEEE Journal on Selected Areas in Communications 2000,18(6):850-860. 10.1109/49.848239View ArticleGoogle Scholar
  9. Farshchian M, Cho S, Pearlman W: Optimal error protection for real-time image and video transmission. IEEE Signal Processing Letters 2004,11(10):780-783. 10.1109/LSP.2004.835470View ArticleGoogle Scholar
  10. Ungerboeck G: Channel coding with multilevel/phase signals. IEEE Transactions on Information Theory 1982,28(1):55-67. 10.1109/TIT.1982.1056454MathSciNetView ArticleMATHGoogle Scholar
  11. Biglieri E, Divsalar D, McLane P, Simon M: Introduction to Trellis-Coded Modulation with Applications. Macmillan, New York, NY, USA; 1991.MATHGoogle Scholar
  12. Viterbi A, Wolf J, Zehavi E, Padovani R: A pragmatic approach to trellis-coded modulation. IEEE Communications Magazine 1989,27(7):11-99. 10.1109/35.31452View ArticleGoogle Scholar
  13. Wolf J, Zehavi E: codes: pragmatic trellis codes utilizing punctured convolutional codes. IEEE Communications Magazine 1995,33(2):94-99. 10.1109/35.350381MathSciNetView ArticleGoogle Scholar
  14. Kim J, Pottie G: On punctured trellis-coded modulation. IEEE Transactions on Information Theory 1996,42(2):627-636. 10.1109/18.485732View ArticleMATHGoogle Scholar
  15. Berrou C, Glavieux A: Near optimum error correcting coding and decoding: turbo-codes. IEEE Transactions on Communications 1996,44(10):1261-1271. 10.1109/26.539767View ArticleGoogle Scholar
  16. Gallager R: Low-Density Parity-Check Codes. MIT Press, Cambridge, Mass, USA; 1963.Google Scholar
  17. Shapiro J: Embedded image coding using zerotrees of wavelet coefficients. IEEE Transactions on Signal Processing 1993,41(12):3445-3462. 10.1109/78.258085View ArticleMATHGoogle Scholar
  18. Proakis J: Digital Communications. 4th edition. McGraw-Hill, New York, NY, USA; 2001.Google Scholar
  19. Wicker S: Error Control Coding Systems for Digital Communication and Storage. Prentice-Hall, Englewood Cliffs, NJ, USA; 1995.Google Scholar
  20. Pei Y, Modestino J: Multi-layered video transmission over wireless channels using an adaptive modulation and coding scheme. Proceedings of International Conference on Image Processing (ICIP '01), October 2001, Thessaloniki, Greece 1009-1012.Google Scholar
  21. Bahl L, Cocke J, Jelinek F, Raviv J: Optimal decoding of linear codes for minimizing symbol error rate. IEEE Transactions on Information Theory 1974,20(2):284-287.MathSciNetView ArticleMATHGoogle Scholar
  22. Fragouli C, Wesel R: Turbo-encoder design for symbol-interleaved parallel concatenated trellis-coded modulation. IEEE Transactions on Communications 2001,49(3):425-435. 10.1109/26.911450View ArticleMATHGoogle Scholar
  23. Robertson P, Worz T: Bandwidth-efficient turbo trellis-coded modulation using punctured component codes. IEEE Journals on Selected Areas in Communications 1998,16(2):206-218. 10.1109/49.661109View ArticleGoogle Scholar
  24. Goff S, Glavieux A, Berrou C: Turbo-codes and high spectral efficiency modulation. Proceedings of International Conference on Creationism (ICC '94), May 1994, New Orleans, La, USA 3: 1255-1259.Google Scholar
  25. Richardson T, Shokrollahi A, Urbanke R: Design of capacity-approaching irregular low-density parity-check codes. IEEE Transactions on Information Theory 2001,47(1):619-637.MathSciNetView ArticleMATHGoogle Scholar
  26. Narayanan K, Altunbas I, Narayanaswami R: Design of codes for minimum shift keying based on density evolution. IEEE Transactions on Communications 2003,51(8):1283-1295. 10.1109/TCOMM.2003.815076View ArticleGoogle Scholar
  27. Hou J, Siegel PH, Milstein L, Pfister H: Capacity-approaching bandwidth-efficient coded modulation schemes based on low-density parity-check codes. IEEE Transactions on Information Theory 2003,49(9):2141-2154. 10.1109/TIT.2003.815777MathSciNetView ArticleMATHGoogle Scholar
  28. Alouini M, Tang X, Goldsmith A: An adaptive modulation scheme for simultaneous voice and datatransmission over fading channels. IEEE Journal on Selected Areas in Communications 1999,17(5):837-850. 10.1109/49.768199View ArticleGoogle Scholar