We study the problem of communicating sensor readings over a
Gaussian multiaccess channel. We focus on the scenario that each
sensor observes a single random variable, and transmits it using
certain signaling in a shared channel. The objective is the design
of channel waveforms (i.e., the signal constellation) to facilitate
the estimation of field parameters from the channel output. In
case of symmetric channel gains, it is shown that Pulse
Position Modulation} (PPM) (i.e., simultaneous transmission of
pulses timed according to the sensed data) is asymptotically
optimal in the limit of large number of sensors. In particular, we
show that the PPM together with a variant of the
maximum-likelihood estimator achieves the Cramer-Rao bound
asymptotically. We then extend the asymptotic analysis of PPM to
fading channels, and compare the performance of PPM with other
approaches that allocate orthogonal channels to sensors such as
TDMA.