298 research outputs found
Application of Expurgated PPM to Indoor Visible Light Communications - Part I: Single-User Systems
Visible light communications (VLC) in indoor environments suffer from the
limited bandwidth of LEDs as well as from the inter-symbol interference (ISI)
imposed by multipath. In this work, transmission schemes to improve the
performance of indoor optical wireless communication (OWC) systems are
introduced. Expurgated pulse-position modulation (EPPM) is proposed for this
application since it can provide a wide range of peak to average power ratios
(PAPR) needed for dimming of the indoor illumination. A correlation decoder
used at the receiver is shown to be optimal for indoor VLC systems, which are
shot noise and background-light limited. Interleaving applied on EPPM in order
to decrease the ISI effect in dispersive VLC channels can significantly
decrease the error probability. The proposed interleaving technique makes EPPM
a better modulation option compared to PPM for VLC systems or any other
dispersive OWC system. An overlapped EPPM pulse technique is proposed to
increase the transmission rate when bandwidth-limited white LEDs are used as
sources.Comment: Journal of Lightwave Technolog
High-Speed Visible Light Indoor Networks Based on Optical Orthogonal Codes and Combinatorial Designs
Interconnecting devices in an indoor environment using the illumination
system and white light emitting diodes (LED) requires adaptive networking
techniques that can provide network access for multiple users. Two techniques
based on multilevel signaling and optical orthogonal codes (OOC) are explored
in this paper in order to provide simultaneous multiple access in an indoor
multiuser network. Balanced incomplete block designs (BIBD) are used to
construct multilevel symbols for M-ary signaling. Using these multilevel
symbols we are able to control the optical peak to average power ratio (PAPR)
in the system, and hereby control the dimming level. In the first technique,
the M-ary data of each user is first encoded using the OOC codeword that is
assigned to that user, and then it is fed into a BIBD encoder to generate a
multilevel signal. The second multiple access method uses sub-sets of a BIBD
code to apply multilevel expurgated pulse-position modulation (MEPPM) to the
data of each user. While the first approach has a larger Hamming distance
between the symbols of each user, the latter can provide higher bit-rates for
users in VLC systems with bandwidth-limited LEDs
Application of Expurgated PPM to Indoor Visible Light Communications - Part II: Access Networks
Providing network access for multiple users in a visible light communication
(VLC) system that utilizes white light emitting diodes (LED) as sources
requires new networking techniques adapted to the lighting features. In this
paper we introduce two multiple access techniques using expurgated PPM (EPPM)
that can be implemented using LEDs and support lighting features such as
dimming. Multilevel symbols are used to provide M-ary signaling for multiple
users using multilevel EPPM (MEPPM). Using these multiple-access schemes we are
able to control the optical peak to average power ratio (PAPR) in the system,
and hereby control the dimming level. In the first technique, the M-ary data of
each user is first encoded using an optical orthogonal code (OOC) assigned to
the user, and the result is fed into a EPPM encoder to generate a multilevel
signal. The second multiple access method uses sub-sets of the EPPM
constellation to apply MEPPM to the data of each user. While the first approach
has a larger Hamming distance between the symbols of each user, the latter can
provide higher bit-rates for users in VLC systems using bandwidth-limited LEDs.Comment: Journal of Lightwave Technology. arXiv admin note: substantial text
overlap with arXiv:1308.074
Scalable Hash-Based Estimation of Divergence Measures
We propose a scalable divergence estimation method based on hashing. Consider
two continuous random variables and whose densities have bounded
support. We consider a particular locality sensitive random hashing, and
consider the ratio of samples in each hash bin having non-zero numbers of Y
samples. We prove that the weighted average of these ratios over all of the
hash bins converges to f-divergences between the two samples sets. We show that
the proposed estimator is optimal in terms of both MSE rate and computational
complexity. We derive the MSE rates for two families of smooth functions; the
H\"{o}lder smoothness class and differentiable functions. In particular, it is
proved that if the density functions have bounded derivatives up to the order
, where is the dimension of samples, the optimal parametric MSE rate
of can be achieved. The computational complexity is shown to be
, which is optimal. To the best of our knowledge, this is the first
empirical divergence estimator that has optimal computational complexity and
achieves the optimal parametric MSE estimation rate.Comment: 11 pages, Proceedings of the 21st International Conference on
Artificial Intelligence and Statistics (AISTATS) 2018, Lanzarote, Spai
Learning the Number of Autoregressive Mixtures in Time Series Using the Gap Statistics
Using a proper model to characterize a time series is crucial in making
accurate predictions. In this work we use time-varying autoregressive process
(TVAR) to describe non-stationary time series and model it as a mixture of
multiple stable autoregressive (AR) processes. We introduce a new model
selection technique based on Gap statistics to learn the appropriate number of
AR filters needed to model a time series. We define a new distance measure
between stable AR filters and draw a reference curve that is used to measure
how much adding a new AR filter improves the performance of the model, and then
choose the number of AR filters that has the maximum gap with the reference
curve. To that end, we propose a new method in order to generate uniform random
stable AR filters in root domain. Numerical results are provided demonstrating
the performance of the proposed approach.Comment: This paper has been accepted by 2015 IEEE International Conference on
Data Minin
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