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Performance of Convolutional Coded Dual Header Pulse Interval Modulation in Infrared Links

Performance of Convolutional Coded Dual Header Pulse Interval Modulation in Infrared Links. S. Rajbhandari, Z. Ghassemlooy, and N. M. Aldibbiat Optical Communications Research Group, School of Computing, Engineering and Information Sciences, The University of Northumbria, Newcastle, U.K.

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Performance of Convolutional Coded Dual Header Pulse Interval Modulation in Infrared Links

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  1. Performance of Convolutional Coded Dual Header Pulse Interval Modulation in Infrared Links S. Rajbhandari, Z. Ghassemlooy, and N. M. AldibbiatOptical Communications Research Group, School of Computing, Engineering and Information Sciences, The University of Northumbria, Newcastle, U.K. Web site: http://soe.unn.ac.uk/ocr PGNET2006

  2. Optical Wireless – Advantage • High unregulated bandwidth, 200 THz in the 700-1500 nm range • No multipath fading • Low cost • Small cell size • Can not penetrate through wall- same frequency can be utilized in adjacent rooms PGNET2006

  3. Issues for Practical Implementations • Intense ambient noise. • Average transmitted power is limited due to eye safety reasons. • Can not penetrate through wall-need to instant infrared access point. • Large area photo-detectors - limits the bandwidth. PGNET2006

  4. Modulation Techniques • Modulation scheme must be power efficient as far as possible because the maximum power that can be transmitted is limited because of eye safety. • On-Off Keying (OOK), Pulse Position Modulation (PPM) , Digital Pulse Interval Modulation (DPIM) , Dual Header Pulse Position Modulation (DH-PIM), Differential Amplitude Pulse-Position Modulation (DAPPM) PGNET2006

  5. Modulation Techniques PGNET2006

  6. DH-PIM • Header and Information section for every symbol. • Two headers, having same time duration. • Information section consist of empty slots which are equal to the decimal equivalent or decimal equivalent of one’s complement of the symbol depending upon the symbol. • Power efficient compared to OOK • Bandwidth efficient compared to PPM and DPIM. • Built in slot and symbol synchronisation capability. PGNET2006

  7. Why use Error Control Coding? • Improves the reliability of system. • Improves the Signal to Noise ratio (SNR) required to achieve the same error probability. • Efficient utilizationof available bandwidth and power. PGNET2006

  8. Convolutional Coded DH-PIM(CC-DH-PIM) • Linear block codes and Trellis coding is difficult (if not impossible ) to apply in DH-PIM because of variable symbol length. • So either convolutional code or modification of convolutional codes are only alternatives. • There has no report that the convolutional code is applied to DH-PIM system as far as author’s knowledge. PGNET2006

  9. System Block Diagram PGNET2006

  10. State Diagram • Depending upon the symbol and preceding symbol, four headers are possible. • Generally headers are [11 10 11] or [11 01 01] for symbol of magnitude less than (2M-1)/2 or greater than or equal this value respectively. • The header can be [00 10 11 ] or [00 01 01] if the present symbol is preceded by symbol of magnitude 2M-1. • So there is only limited paths in trellis diagram. • No state transition form ‘d’ to ‘d’. • The transfer function and error bound needs to be modified for CC-DH-PIM encoder. PGNET2006

  11. CC-DH-PIM Symbol PGNET2006

  12. Error Bound Error Bound for general convolutional encoder PGNET2006

  13. Error Bound • The upper error bound for CC-DH-PIM is less than or equal to the error bound for general encoder • Fixed header patterns limits trellis paths. • Only finite set of paths. PGNET2006

  14. Comparisons of Uncoded and Coded DH-PIM A code gain of greater than 3 dB for slot error rate of 10-4 PGNET2006

  15. Comparisons of Different Modulation Scheme CC-DH-PIM1 offer the best performance compared with PPM and DH-PIM . Show up to 10-10! PGNET2006

  16. Convolutional Coded DH-PIM having different constraint Length Improved performance can be obtained by increasing the constraint length of encoder at the cost of complexity. PGNET2006

  17. Conclusions • Applying convolutional coding to the DH-PIM improves the performance of system. • (3,1,2) Convolutional encoded DH-PIM requires 4-5 dB less SNR compared to uncoded DH-PIM. • Further improvement can be obtained by increasing the constraint length. PGNET2006

  18. Thank you! PGNET2006

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