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MIC-CPE2010, Jordan Optimizing the Performance of Digital Pulse Interval Modulation with Guard Slots for Diffuse Indoor Optical Wireless Links Z. Ghassemlooy and S Rajbhandari Optical Communication Research Group, School of CEIS, Northumbria University, Newcastle upon Tyne, UK http://soe.unn.ac.uk/ocr/

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MIC-CPE2010, Jordan Outline Indoor optical wireless communication Modulation techniques DPIM Techniques to reduce ISI Decoding Scheme for DPIM(nGS) Scheme Threshold decoding Hybrid decoding scheme Maximizing the likelihood (ML) of a pulse Results and discussions Conclusions

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MIC-CPE2010, Jordan Optical Wireless System: Overview 1 M. Kavehrad, Scientific American Magazine, July 2007, pp. 82-87. Typical optical wireless system components Optical wireless connectivity 1 U ses light beams (visible and infrared) propagating through the atmosphere or space to carry information. Optical transmitter -Light emitting diodes -Laser diodes Optical receiver -p-i-n photodiodes -Avalanche photodiodes Links -Line-of-sight (LOS) -Non-LOS -Hybrid

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MIC-CPE2010, Jordan Digital Modulation Schemes On-off keying (OOK) Pulse position modulation (PPM) Digital pulse interval modulation (DPIM) Dual-header pulse interval modulation (DH-PIM) Subcarrier modulation

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MIC-CPE2010, Jordan Digital Pulse Modulation Schemes DPIM

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MIC-CPE2010, Jordan The DPIM Scheme An anisochronous modulation technique A symbol is composed of a pulse of one slot duration followed by a series of empty slots: where d j-1 is j empty slot(s), j = 0,..., D and D is the decimal value of a i. DPIM signal is defined as: p(t) - rectangular pulse shape, Ts - slot duration b i - set of random variables representing a pulse/no pulse in the nth Ts

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MIC-CPE2010, Jordan Why DPIM ? An excellent compromise between the bandwidth and the power efficiencies. Higher bandwidth efficiency than PPM. Higher power efficiency than OOK. Easy to implement compared to more complex modulation scheme like DH-PIM. 2345678 -16 -14 -12 -10 -8 -6 -4 -2 0 Bit Resolution, M Normalized Power Requirement (dB) DH-PIM 2 PPM DH-PIM 1 DPIM

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MIC-CPE2010, Jordan Indoor Optical Wireless Links The key issues: -Eye safety -shift from 900 nm to 1550 nm - eye retina is less sensitive to optical radiation -power efficient modulation techniques -Mobility and blocking -is a problem in diffuse configurations (i.e. Non- LOS), thus resulting in: -reduced data rates -increased path loss -multipath induced inter-symbol-interference (ISI)

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MIC-CPE2010, Jordan Indoor OWC - Diffuse Links Pulse spreading due to the different path delays leading to intersymbol interference (ISI) ISI is the limiting factor in achieving higher data rates Diffuse links are characterised by RMS delay spread The impulse response in the Ceiling bounce model is: LOS Diffuse Diffuse shadowed LOS shadowed where u(t) is the unit step function Fig. Impulse response of indoor optical wireless channel

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MIC-CPE2010, Jordan Techniques to Reduce ISI Maximum likelihood sequence detection The optimum solution to reduce ISI Difficult to implement due to high complexity and large delay Practical implementation is not feasible for DPIM due to variable symbol length Equalization Trade-off between complexity and performance Preferred due to lower complexity compared to MLSD Channel estimation is necessary Guard slots (GSs) Simple to implement without additional complexity Effective in moderately dispersive channel Ineffective in highly dispersive channel

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MIC-CPE2010, Jordan DPIM with Guard Slots to Reduces ISI The postcursor slot immediately following a pulse is most severely effected due to ISI. Adding GSs immediately following a pulse can be effective in reducing the ISI. Clear overlapping in the constellation of DPIM(0GS). Hence difficult to assign a fixed threshold level. The constellation of 0s and 1s are clearly separated for DPIM(1GS). However, distance is clearly reduced. Fig. Scatter plots of received signals at D T = 0.3 for DPIM(0GS). red= 0, blue =1 Fig. Scatter plots of received signals at D T = 0.3 for DPIM(1GS). red= 0, blue =1

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MIC-CPE2010, Jordan Decoding Scheme for DPIM(nGS) Scheme Decoding schemes: Threshold decoding Hybrid decoding scheme Maximizing the likelihood (ML) of a pulse Fig. The block diagram of the DPIM system.

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MIC-CPE2010, Jordan Threshold Decoding A threshold level set at half the peak amplitude is non-optimum in diffuse channel. ISI reduces the minimum Euclidean distance d min. Threshold level needs to be adjusted accordingly. The optimum threshold level is given by: where c i is the channel taps Error probability can be approximated as : The predicted and simulated SER against the SNR for the 8 and 16- DPIM schemes at D t = 0.01 and 0.1.

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MIC-CPE2010, Jordan Hybrid Decoding Scheme Soft decoding is difficult to implement due to non-uniform symbol length. Valid DPIM(1GS) symbol always has a 010 sequence except for the all zero sequence. Unique slot sequence in DPIM(1GS) can be exploit for hybrid decoding. The decoding algorithm can be summarised as: Valid DPIM(1GS) sequence 000 0010 010 0100 The probability of correctly decoding a pulse is given by:

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MIC-CPE2010, Jordan Maximizing the Likelihood (ML) of a Pulse In DPIM scheme with n GSs, a pulse should always be followed by n empty slots. Taking two slots into consideration (00, 01, 10) are the only valid DPIM(1GS) sequence. The approach taken here is to maximize a-Posterior probability of a pulse. i.e. If the posterior probability of sequence (10) is greater than posterior probabilities of (00) and (01) sequence, decode the bit sequence as (10) else decode present bit as 0.

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MIC-CPE2010, Jordan Results and Discussions A fixed threshold level of 0.5 demonstrates the worst performance. The ML detection scheme offers the best performance. All other decoding approaches show improved performance compared to the DPIM (0GS). The optimum threshold decoding offer significantly improved performance compared to a fixed threshold decoding. Fig. The NOPRs against the normalized delay spreads for 8-DPIM (0 &1GS) for different decoding algorithms and a SER of 10 -6.

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MIC-CPE2010, Jordan Results and Discussions Hybrid decoding offers improved performance compared to the optimum threshold level. The advantage of the ML detection scheme can be observed at higher values of D T. A difference of ~ 3.4 dB and ~ 2.8 dB can be observed between the ML detection and the hybrid decoding at D T = 0.4 for 8 and 16- DPIM(1GS), respectively. The reduction in NOPR increases with D T. The requires ~ 0.8 dB and ~ 2.2 dB lower optical power compared to a fixed threshold scheme at D T = 0.1 and 0.2, respectively for 8- DPIM(1GS). However, differences in NOPR for and are ~ 0.6 dB and ~ 6.5 dB at D T = 0.1 and 0.2, respectively for 16-DPIM(1GS). The hybrid decoding scheme offers improved performance compared to the optimum threshold level. The ML detection offers the least NOPR for D T > 0.2. Since ISI is small for D T 0.2). A difference of ~ 3.4 dB and ~ 2.8 dB can be observed between the ML detection and the hybrid decoding at D T = 0.4 for 8 and 16- DPIM(1GS), respectively. Fig. The NOPRs against the normalized delay spreads for 16-DPIM (0 &1GS) for different decoding algorithms and a SER of 10 -6.

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MIC-CPE2010, Jordan Conclusion A number of decoding approaches has been proposed and studied for DPIM(1GS) The decoding algorithm exploits the unique slot sequence of DPIM(1GS) The fixed threshold based decoding schemes is the non- optimum for diffuse links. A hybrid decoding scheme surpasses the performance of the optimum thresholding. The ML decoding of a pulse offered the best performance. The system complexity using the ML detection scheme is not significantly higher than that of a threshold detector, ML detection is practically recommendable.

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MIC-CPE2010, Jordan Questions? Thank you!

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