  We examine power spectrum estimation from wide-sense stationary signals
received at different wireless sensors. We organize multiple sensors into
several groups, where each group estimates the temporal correlation only at
particular lags, which are different from group to group. A fusion centre
collects all the correlation estimates from different groups of sensors, and
uses them to estimate the power spectrum. This reduces the required sampling
rate per sensor. We further investigate the conditions required for the system
matrix to have full column rank, which allows for a least-squares
reconstruction method.
