Abstract:
One of the major problems in wireless communications is compensating for the time-varying
intersymbol interference (ISI) due to multipath. Underwater acoustic communications
is one such type of wireless communications in which the channel is
highly dynamic and the amount of ISI due to multipath is relatively large. In the
underwater acoustic channel, associated with each of the deterministic propagation
paths are macro-multipath fluctuations which depend on large scale environmental
features and geometry, and micro-multipath fluctuations which are dependent on
small scale environmental inhomogeneities. For arrivals which are unsaturated or
partially saturated, the fluctuations in ISI are dominated by the macro-multipath
fluctuations resulting in correlated fluctuations between different taps of the sampled
channel impulse response. Traditional recursive least squares (RLS) algorithms used
for adapting channel equalizers do not exploit this structure. A channel subspace
post-filtering algorithm that treats the least squares channel estimate as a noisy time
series and exploits the channel correlation structure to reduce the channel estimation
error is presented. The improvement in performance of the algorithm with respect to
traditional least squares algorithms is predicted theoretically, and demonstrated using
both simulation and experimental data. An adaptive equalizer structure that explicitly
uses this improved estimate of the channel impulse response is discussed. The
improvement in performance of such an equalizer due to the use of the post-filtered
estimate is also predicted theoretically, and demonstrated using both simulation and
experimental data.
