Multi-Coset Sampling for Power Spectrum Blind Sensing
Power Spectrum Blind Sampling (PSBS) consists of a sampling procedure and a reconstruction method that is able to recover the unknown power spectrum of a random signal from the obtained sub-Nyquist-rate samples. It differs from Spectrum Blind Sampling (SBS) that aims to recover the spectrum instead of the power spectrum of the signal. In this paper, a PSBS solution is first presented based on a periodic sampling procedure. Then, a multi-coset implementation for this sampling procedure is developed by solving the so-called minimal sparse ruler problem, and the co-prime sampling technique is tailored to fit into the PSBS framework as well.