This work considers the design of capacity approaching, non-uniform optical intensity signaling in the presence of average and peak amplitude constraints. It is known that the capacity achieving input distribution is discrete with a finite number of mass points, finding it requires complex non-linear optimization at every SNR. A simple expression for a capacity-approaching distribution is derived via source entropy maximization. For queries Aishwarya palsinghaishwarya@gmail.com

1. Channel Capacity and Uniform/Non-
Uniform Signaling for FSO Channels
SUBMITTED BY:
AISHWARYA (00696402810)

2. Introduction
 FSO(Free Space Optical)Channels.
Block diagram of an Optical Intensity Direct Detection Communication System.
Effects of Atmospheric Turbulence on Optical Intensity Signaling(Challenges)
Channel Capacity Approaching
Non-Uniform Signaling vs Uniform Signaling
Non-Uniform Signaling Algorithm(Block Diagram)
Coding Schemes for FSO Channels
Conclusion
Applications

3. Why Free Space Optics (FSO)?
FSO vs Radio-Frequency (RF)
RF
Spectrum is scarce and low
bandwidth
Spectrum is regulated
Suffers from multi-path fading
Susceptible to eavesdropping
Large components
FSO
A single FSO channel can
offers Tb/s throughput
 Spectrum is large and license
free (very dense reuse)
 Small components
 Secure
 Transmission range limited by
weather condition
 Are very difficult to intercept

4. Why Free Space Optics (FSO)?
FSO vs Fiber Optic
Fiber Optic
High cost
Requires permits for
digging
(Rights of Way)
Trenching
Time consuming
installation
Mobility impossible
FSO
 No permits (especially through
the window)
 No digging
 No fees
 Faster installation
 Mobility/reconfigurability
possible

6. Challenges

7. Reduced
SNR due to
Atmospheric
Turbulance
SNR is improved by
increasing the mass
points.
As the mass points are
increased curve
becomes uniform and
thus uniformity
indicates the
improvement in SNRs.

8. Non-Uniform
Signalling vs
Uniform
Signalling
Figure 1 indicates mutual
information vs SNR curve
using uniform input
distribution.
Figure 2 shows mutual
information vs SNR curves
using uniform as well as non
uniform input distribution.
In figure 2 red line shows
non uniform and blue line
shows uniform input
distribution.

9. Channel
Capacity
and
Information
Rates
Earlier we showed that
by increasing mass
points we can improve
the SNR
But the data is finite so
we can increase mass
points finitely and not
infinitely.
So now in order to
increase the SNR
further we are using
non-uniform input
distributin.

10. Non-Uniform Signalling Algorithm
SYSTEM MODEL FOR MULTILEVEL
CODING (MLC) AND MAPPING SCHEME
FOR OPTICAL INTENSITY CHANNELS
WITH NON-UNIFORM CHANNEL INPUT
DISTRIBUTION.
SYSTEM MODEL FOR MULTI-
STAGE DECODERS (MSD).

11. Coding Schemes
Earlier ppm was used when the channel capacity was considered to be
infinite as noise was assumed to be null.
Later on due to interference of AWGN pam was used.
And now, non uniform OOK is used in order to overshadow the effects
of atmospheric turbulence.

12. Constellation Diagrams

13. Conclusion
 Earlier Non- Linear Complex Optimization input distribution technique
was adopted.
 Due to increase in complexity in order to increase the SNRs new
input distribution technique i.e. Source Entropy Maximization was
adopted.
 Furthermore, uniform signaling also didn’t prove beneficial so non-
uniform signaling method was used.
 Nowadays we use maxentropic non-uniform signaling (or input
distribution).

14. Applications of FSO Communications
Infra-red (IR) communications (remote control applications)
 Visible light communications (VLC) for indoor applications
 Non-line-of-sight (NLOS) ultraviolet (UV) communications
 Inter-satellite communications
 Underwater communications
 Terrestrial optical communications
 Hybrid RF/FSO communications
 Optical quantum communications

15. References
Channel Capacity and Non-Uniform Signaling for Free-Space Optical
Intensity Channels.
By: Ahmed A. Farid, Student Member, IEEE, and Steve Hranilovic, Senior
Member, IEEE
Capacity of and Coding for Multiple-Aperture, Wireless, Optical
Communications. By: Shane M. Haas
Effect of fog on free-space optical links employing imaging receivers.
By: Reza Nasiri Mahalati* and Joseph M. Kahn