On CS Image Reconstruction Using LDPC Code Over Radio Mobile Channel (original) (raw)

References

  1. Donoho, D. L. (2006). Compressed sensing. IEEE Transactions on Information Theory, 52(4), 1289–1306.
    Article MathSciNet MATH Google Scholar
  2. Polania, L. F., Carrillo, R. E., Blanco-Velasco, M., & Barner, K. E. (2015). Exploiting prior knowledge in compressed sensing wireless ECG systems. IEEE Journal of Biomedical and Health Informatics, 19(2), 508–519.
    Article Google Scholar
  3. Majumdar, A., & Ward, R. K. (2015). Energy efficient EEG sensing and transmission for wireless body area networks: A blind compressed sensing approach. Biomedical Signal Processing and Control, 20, 1–9.
    Article Google Scholar
  4. Zhang, Z., Jung, T. P., Makeig, S., & Rao, B. D. (2013). Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning. IEEE Transactions on Biomedical Engineering, 60(2), 300–309.
    Article Google Scholar
  5. Wang, L., Lu, K., & Liu, P. (2015). Compressed sensing of a remote sensing image based on the priors of the reference image. IEEE Geoscience and Remote Sensing Letters, 12(4), 736–740.
    Article Google Scholar
  6. Li, S., Da Xu, L., & Wang, X. (2013). Compressed sensing signal and data acquisition in wireless sensor networks and internet of things. IEEE Transactions on Industrial Informatics, 9(4), 2177–2186.
    Article MathSciNet Google Scholar
  7. Feng, L., Axel, L., Chandarana, H., Block, K. T., Sodickson, D. K., & Otazo, R. (2016). XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing. Magnetic Resonance in Medicine, 75(2), 775–788.
    Article Google Scholar
  8. Zhang, Y., Zhang, L. Y., Zhou, J., Liu, L., Chen, F., & He, X. (2016). A review of compressive sensing in information security field. IEEE Access, 4, 2507–2519.
    Article Google Scholar
  9. Ohlsson, H., Yang, A. Y., Dong, R., & Sastry, S. S. (2013). Nonlinear basis pursuit. In: Signals, systems and computers, 2013 Asilomar conference on IEEE (pp. 115–119).
  10. Wang, J., Kwon, S., & Shim, B. (2012). Generalized orthogonal matching pursuit. IEEE Transactions on Signal Processing, 60(12), 6202–6216.
    Article MathSciNet Google Scholar
  11. Yang, Z., Zhang, C., Deng, J., & Lu, W. (2011). Orthonormal expansion \(\ell _{1}\)-minimization algorithms for compressed sensing. IEEE Transactions on Signal Processing, 59(12), 6285–6290.
    Article MathSciNet Google Scholar
  12. Egiazarian, K., Foi, A., & Katkovnik, V. (2007). Compressed sensing image reconstruction via recursive spatially adaptive filtering. In Image processing, 2007. ICIP 2007. IEEE international conference on IEEE (Vol. 1, pp. 549–I–552).
  13. IEEE Networks, (2016). Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: Review, challenges, and a case study. 30(2), 54–61.
  14. Pramanik, A., Patil, G., & Borman, L. (2013). Small length quasi-cyclic LDPC code for wireless applications. In Emerging research areas and 2013 international conference on microelectronics, communications and renewable energy (AICERA/ICMiCR), 2013 annual international conference on IEEE (pp. 1–5).
  15. Gallager, R. (1962). Low-density parity-check codes. IRE Transactions on Information Theory, 8(1), 21–28.
    Article MathSciNet MATH Google Scholar
  16. Porcello, J. C. (2015). Implementing High data rate, low density parity check (LDPC) decoders for large codes using FPGAs. In Aerospace conference, 2015 IEEE (pp. 1–7).
  17. Aimin, Z., & Senjie, Y. (2009). A modified belief propagation decoding algorithm of LDPC codes for fast convergence. In Communication software and networks, 2009. ICCSN’09. International conference on IEEE (pp. 516–520).
  18. Healy, C. T., & de Lamare, R. C. (2016). Design of ldpc codes based on multipath emd strategies for progressive edge growth. IEEE Transactions on Communications, 64(8), 3208–3219.
    Article Google Scholar
  19. Han, W., & Huang, J. (2013). A block-PEG construction method for LDPC codes. In Electronics information and emergency communication (ICEIEC), 2013 IEEE 4th international conference on IEEE (pp. 274–277).
  20. Khodaiemehr, H., & Kiani, D. (2017). Construction and encoding of QC-LDPC codes using group rings. IEEE Transactions on Information Theory, 63(4), 2039–2060.
    Article MathSciNet MATH Google Scholar
  21. Zhang, J. B., Yu, Y., Chen, Z. Y., & Li, Z. Z. (2017). A new method for constructing parity check matrix of QC-LDPC codes based on shortening RS codes for wireless sensor networks. Sustainable Computing: Informatics and Systems. https://doi.org/10.1016/j.suscom.2017.09.001.
    Google Scholar
  22. Paolini, E., Fossorier, M. P., & Chiani, M. (2010). Generalized and doubly generalized LDPC codes with random component codes for the binary erasure channel. IEEE Transactions on Information Theory, 56(4), 1651–1672.
    Article MathSciNet MATH Google Scholar
  23. IEEE standard. (2009). IEEE Standard for local and metropolitan area networks Part 16: Air interface for broadband wireless access systems. IEEE Std 802.16-2009 (Revision of IEEE Std 802.16-2004), 1-2080. https://doi.org/10.1109/IEEESTD.2009.5062485.
  24. Steiner, F., Böcherer, G., & Liva, G. (2016). Protograph-based LDPC code design for shaped bit-metric decoding. IEEE Journal on Selected Areas in Communications, 34(2), 397–407.
    Article Google Scholar
  25. Baron, D., Sarvotham, S., & Baraniuk, R. G. (2010). Bayesian compressive sensing via belief propagation. IEEE Transactions on Signal Processing, 58(1), 269–280.
    Article MathSciNet Google Scholar
  26. Bayati, M., & Montanari, A. (2011). The dynamics of message passing on dense graphs, with applications to compressed sensing. IEEE Transactions on Information Theory, 57(2), 764–785.
    Article MathSciNet MATH Google Scholar
  27. Zhang, F., & Pfister, H. D. (2012). Verification decoding of high-rate LDPC codes with applications in compressed sensing. IEEE Transactions on Information Theory, 58(8), 5042–5058.
    Article MathSciNet MATH Google Scholar
  28. Akçakaya, M., Park, J., & Tarokh, V. (2011). A coding theory approach to noisy compressive sensing using low density frames. IEEE Transactions on Signal Processing, 59(11), 5369–5379.
    Article MathSciNet Google Scholar
  29. Pham, H. V., Dai, W., & Milenkovic, O. (2009). Sublinear compressive sensing reconstruction via belief propagation decoding. In Information theory, 2009. ISIT 2009. IEEE international symposium on IEEE (pp. 674–678).
  30. Lu, W., Kpalma, K., & Ronsin, J. (2012). Sparse binary matrices of LDPC codes for compressed sensing. In Data compression conference (DCC) (pp. 10).
  31. Dimakis, A. G., Smarandache, R., & Vontobel, P. O. (2012). LDPC codes for compressed sensing. IEEE Transactions on Information Theory, 58(5), 3093–3114.
    Article MathSciNet MATH Google Scholar
  32. Chen, F., Lim, F., Abari, O., Chandrakasan, A., & Stojanovic, V. (2013). Energy-aware design of compressed sensing systems for wireless sensors under performance and reliability constraints. IEEE Transactions on Circuits and Systems I: Regular Papers, 60(3), 650–661.
    Article MathSciNet Google Scholar
  33. Pramanik, A., & Maity, S. P. (2015). On CS reconstruction images using LDPC code over radio mobile channel. In Wireless communications, vehicular technology, information theory, aerospace and electronic systems (VITAE), 2015 5th international conference on IEEE.
  34. Candes, E. J., Romberg, J. K., & Tao, T. (2006). Stable signal recovery from incomplete and inaccurate measurements. Communications on Pure and Applied Mathematics, 59(8), 1207–1223.
    Article MathSciNet MATH Google Scholar
  35. Hayashi, K., Nagahara, M., & Tanaka, T. (2013). A user’s guide to compressed sensing for communications systems. IEICE Transactions on Communications, 96(3), 685–712.
    Article Google Scholar
  36. Richardson, T. J., & Urbanke, R. L. (2001). Efficient encoding of low-density parity-check codes. IEEE Transactions on Information Theory, 47(2), 638–656.
    Article MathSciNet MATH Google Scholar
  37. Das, S., & Suganthan, P. N. (2011). Differential evolution: A survey of the state-of-the-art. IEEE Transactions on Evolutionary Computation, 15(1), 4–31.
    Article Google Scholar
  38. Qin, A. K., Huang, V. L., & Suganthan, P. N. (2009). Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Transactions on Evolutionary Computation, 13(2), 398–417.
    Article Google Scholar

Download references