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Flexible iterative receiver architecture for wireless sensor networks: a joint source and channel coding design example

Flexible iterative receiver architecture for wireless sensor networks: a joint source and channel coding design example

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Due to their computational complexity, iterative decoder components such as source and channel decoders are usually implemented using specialised dedicated hardware. This leads to the scenario where each different iterative decoder component of the receiver requires its own hardware. Due to their relatively high complexity, many capacity-approaching techniques proposed in the literature have not yet been invoked in wireless sensor network applications, despite their potential benefits of facilitating a reduced transmission power or extended communication range. Against this background, the authors propose an energy-efficient architecture comprised of multiple computation unit (CU), which is sufficiently flexible for accommodating different iterative decoder components using the same hardware. In this study, the flexible architecture is applied to Joint Source and Channel Coding (JSCC), comprising the Unary Error Correction (UEC) code, a turbo code and an iterative demodulator. The authors conceive a flexible technique for controlling the hardware, which supports a high hardware-exploitation ratio for the CU, reaching a utilisation of 88%, compared with 68% achieved in similar solutions reported in the open literature.

References

    1. 1)
      • 1. Zorzi, M., Gluhak, A.: ‘From today's intranet of things to a future internet of things: a wireless-and mobility-related view’, IEEE Wirel. Commun., 2010, 17, (6), pp. 4451.
    2. 2)
      • 2. Atzori, L., Iera, A., Morabito, G.: ‘The internet of things: a survey’, Comput. Netw., 2010, 54, (15), pp. 27872805.
    3. 3)
      • 3. Gubbi, J., Buyya, R., Marusic, S., et al: ‘Internet of things (IoT): a vision, architectural elements, and future directions’, Future Gener. Comput. Syst., 2013, 29, (7), pp. 16451660.
    4. 4)
      • 4. Brejza, M.F., Li, L., Maunder, R.G., et al: ‘20 years of turbo coding and energy-aware design guidelines for energy-constrained wireless applications’, IEEE Commun. Surv. Tutor., 2016, 18, (1), pp. 828. Available at http://eprints.soton.ac.uk/378161/.
    5. 5)
      • 5. Maunder, R.G., Weddell, A.S., Merrett, G.V., et al: ‘Iterative decoding for redistributing energy consumption in wireless sensor networks’. 2008 Proc. of 17th Int. Conf. on Computer Communications and Networks, August 2008, pp. 16.
    6. 6)
      • 6. Qassim, Y., Magana, M.E.: ‘Error-tolerant non-binary error correction code for low power wireless sensor networks’. The Int. Conf. on Information Networking 2014 (ICOIN2014), February 2014, pp. 2327.
    7. 7)
      • 7. Abedi, A.: ‘Power-efficient-coded architecture for distributed wireless sensing’, IET Wirel. Sens. Syst., 2011, 1, (3), pp. 129136. Available at http://digital-library.theiet.org/content/journals/10.1049/iet-wss.2010.0077.
    8. 8)
      • 8. Wireless medium access control (MAC) and physical layer (PHY) specifications for low-rate wireless personal area networks (WPANs)’, 2006.
    9. 9)
      • 9. Noels, N., Herzet, C., Dejonghe, A., et al: ‘Turbo synchronization: an EM algorithm interpretation’. IEEE Int. Conf. on Communications, 2003, ICC ‘03, 2003, vol. 4, pp. 29332937.
    10. 10)
      • 10. Haene, S., Burg, A., Felber, N., et al: ‘OFDM channel estimation algorithm and ASIC implementation’. 2008 4th European Conf, on Circuits and Systems for Communications, July 2008, pp. 270275.
    11. 11)
      • 11. Douillard, C., Jézéquel, M, Berrou, C.: ‘Iterative correction of intersymbol interference: turbo-equalization’, Eur. Trans. Telecommun., 1995, 6, pp. 507511.
    12. 12)
      • 12. Valenti, M., Cheng, S.: ‘Iterative demodulation and decoding of turbo-coded M-ary noncoherent orthogonal modulation’, IEEE J. Sel. Areas Commun., 2005, 23, (9), pp. 17391747.
    13. 13)
      • 13. Berrou, C., Glavieux, A., Thitimajshima, P.: ‘Near shannon limit error correcting coding and decoding: turbo codes’. Proc. of the IEEE Int. Conf. on Communications, Geneva, Switzerland, 1993, vol. 2, pp. 10641070.
    14. 14)
      • 14. Gallager, R.: ‘Low-density parity-check codes’, IEEE Trans. Inf. Theory, 1962, 8, (1), pp. 2128.
    15. 15)
      • 15. Hagenauer, J., Gortz, N.: ‘The turbo principle in joint source-channel coding’. Proc. 2003 IEEE Information Theory Workshop, 2003, pp. 275278.
    16. 16)
      • 16. Zhang, W., Jia, Y., Meng, X., et al: ‘Adaptive iterative decoding for expediting the convergence of unary error correction codes’, IEEE Trans. Veh. Technol., 2014, 64, pp. 11.
    17. 17)
      • 17. Austin, T., Blaauw, D., Mudge, T., et al: ‘Leakage current: Moore's law meets static power’, Computer, 2003, 36, (12), pp. 6875.
    18. 18)
      • 18. Li, L., Maunder, R.G., Al-Hashimi, B.M., et al: ‘A low-complexity turbo decoder architecture for energy-efficient wireless sensor networks’, IEEE Trans. Very Large Scale Integr. (VLSI) Syst., 2013, 21, (1), pp. 1422. Available at http://eprints.soton.ac.uk/271820/.
    19. 19)
      • 19. Biroli, A.D.G., Martina, M., Masera, G.: ‘An LDPC decoder architecture for wireless sensor network applications’, Sensors, 2012, 12, (12), pp. 15291543.
    20. 20)
      • 20. Brejza, M.F., Zhang, W., Maunder, R.G., et al: ‘Adaptive iterative detection for expediting the convergence of a serially concatenated unary error correction decoder, turbo decoder and an iterative demodulator’. IEEE Int. Conf. on Communications (ICC), 2015, June 2015, pp. 26032608. Available at http://eprints.soton.ac.uk/375712/.
    21. 21)
      • 21. Kim, J., Vijayanagar, K.R., Liu, W.: ‘Low-complexity distributed multiple description coding for wireless video sensor networks’, IET Wirel. Sens. Syst., 2013, 3, (3), pp. 205215. Available at http://digital-library.theiet.org/content/journals/10.1049/iet-wss.2012.0115.
    22. 22)
      • 22. Balasingham, I., Nguyen, H., Ramstad, T.: ‘Wireless sensor communication system based on direct-sum source coder’, IET Wirel. Sens. Syst., 2011, 1, (2), pp. 96104. Available at http://digital-library.theiet.org/content/journals/10.1049/iet-wss.2010.0094.
    23. 23)
      • 23. Chen, W.-T., Chen, P.-Y., Lee, W.-S., et al: ‘Design and implementation of a real time video surveillance system with wireless sensor networks’. VTC Spring 2008 – IEEE Vehicular Technology Conf., May 2008, pp. 218222.
    24. 24)
      • 24. ITU-T: ‘Series H: audiovisual and multimedia systems, infrastructure of audiovisual services coding of moving video, high efficiency video coding’, 2015. Available at www.itu.int/rec/T-REC-H.265-201504-I.
    25. 25)
      • 25. Maunder, R.G., Zhang, W., Wang, T., et al: ‘A unary error correction code for the near-capacity joint source and channel coding of symbol values from an infinite set’, IEEE Trans. Commun., 2013, 61, pp. 19771987.
    26. 26)
      • 26. Hanzo, L.L., Liew, T.H., Yeap, B.L., et al: ‘Turbo coding, turbo equalisation and space-time coding: EXIT-chart-aided near-capacity designs for wireless channels’ (John Wiley & Sons, 2011).
    27. 27)
      • 27. Yoge, D., Chandrachoodan, N.: ‘GPU implementation of a programmable turbo decoder for software defined radio applications’. VLSI Design (VLSID), 2012, pp. 149154.
    28. 28)
      • 28. Benkeser, C., Burg, A., Cupaiuolo, T., et al: ‘Design and optimization of an HSDPA turbo decoder ASIC’, IEEE J. Solid-State Circuits, 2009, 44, (1), pp. 98106.
    29. 29)
      • 29. Ilnseher, T., Kienle, F.: ‘A 2.15 GBit/s turbo code decoder for LTE advanced base station applications’. 7th Int. Symp. on Turbo Codes and Iterative Information Processing (ISTC), 2012, 2012, pp. 2125.
    30. 30)
      • 30. Studer, C., Benkeser, C., Belfanti, S., et al: ‘Design and implementation of a parallel turbo-decoder ASIC for 3GPP-LTE’, IEEE J. Solid-State Circuits, 2011, 46, (1), pp. 817.
    31. 31)
      • 31. Papaharalabos, S., Mathiopoulos, P., Masera, G., et al: ‘On optimal and near-optimal turbo decoding using generalized max operator’, IEEE Commun. Lett., 2009, 13, (7), pp. 522524.
    32. 32)
      • 32. Papaharalabos, S., Sweeney, P., Evans, B., et al: ‘Modified sum-product algorithms for decoding low-density parity-check codes’, IET Commun., 2007, 1, (3), p. 294. Available at http://digital-library.theiet.org/content/journals/10.1049/iet-com20060173.
    33. 33)
      • 33. Johnson, N.L., Kemp, A.W., Kotz, S.: ‘Univariate discrete distributions’ (John Wiley & Sons, 2005).
    34. 34)
      • 34. Li, L., Maunder, R.G., Al-Hashimi, B.M., et al: ‘Design of fixed-point processing based turbo codes using extrinsic information transfer charts’. Proc. of IEEE Vehicular Technology Conf., Ottawa, Canada, 2010, pp. 15.
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