  Multipath propagation of radio waves in indoor/outdoor environments shows a
highly irregular behavior as a function of time. Typical modeling of this
phenomenon assumes the received signal is a stochastic process composed of the
superposition of various altered replicas of the transmitted one, their
amplitudes and phases being drawn from specific probability densities. We set
out to explore the hypothesis of the presence of deterministic chaos in signals
propagating inside various buildings at the University of Calgary. The
correlation dimension versus embedding dimension saturates to a value between 3
and 4 for various antenna polarizations. The full Liapunov spectrum calculated
contains two positive exponents and yields through the Kaplan-Yorke conjecture
the same dimension obtained from the correlation sum. The presence of strange
attractors in multipath propagation hints to better ways to predict the
behaviour of the signal and better methods to counter the effects of
interference. The use of Neural Networks in non linear prediction will be
illustrated in an example and potential applications of same will be
highlighted.
