Abstract:
Local Area Networks (LAN’s) are being expanded over large geographic areas and
they are used in many business fields. Thus, communication links between buildings
are to be optimized in order to achieve high transmission rates, high performance
levels, low cost and ease of deployment. Free-Space Optics (FSO) is a communication
system that achieves all of the above objectives and, thus, constitutes a strong
candidate solution for such networks.
FSO systems are based on transmitting information through light beams in free atmosphere
and they suffer from fading due to atmospheric scintillations. Fading effects can
be reduced by deploying laser arrays and photo-detector arrays at the transmitter and
receiver sides respectively. Such systems are referred to as Multiple-Input-Multiple-
Output (MIMO) FSO systems. In addition to their robustness against fading, MIMO
FSO systems can also enhance the data rate since the array of lasers can be driven
by independent information sources.
Fading over FSO channels is often modeled by either Log-Normal or Rayleigh distributions.
In this context, the first contribution of this work consists of an analytical
characterization of the diversity order that can be achieved by MIMO FSO systems
over such channels. Based on the Erlang approximation, closed-form expressions of
the error-rate and channel-capacity were derived. These simple expressions offer useful
insights on the performance gains that can be achieved at a given Signal-to-Noise
Ratio (SNR).
On the other hand, for estimating the values of the transmitted signals, exiting MIMO
FSO systems are often associated with Maximum-Likelihood (ML) decoders. Although
these decoders achieve the smallest error rate, they suffer from an increased
complexity since the required decoding time increases exponentially with the size
of the transmitted constellation. The second contribution of this work consists of
proposing two novel simplified ML decoders that reduce the processing time without
increasing the error rate. We also propose suboptimal versions of these decoders
that present the advantage of very fast convergence times at the expense of a slight increase in the error rate. All the presented analysis and designs are supported by
simulations and analytical proofs.
