Active spectrum sensing with sequential sub-Nyquist sampling

In this paper we propose a new receiver architecture for optimum active sequential sensing via sub-Nyquist sampling. The sensing strategy we propose is formulated as a sequential utility optimization problem, where the chosen utility functions strikes the desired balance between exploration and exploitation, typical in most spectrum sensing problem. To introduce the optimization variables, we first introduce the analog front-end architecture envisioned. Second, we characterize the optimal policy (under constraints on the sensing matrix) and derive the approximation factor for the greedy approach. Numerical simulations showcase the benefits of the proposed adaptive design.