Robust Power Allocation in Cognitive Radio Networks with Uncertain Knowledge of Interference

We study the secondary user power allocation problem in cognitive radio networks with uncertain knowledge of interference information. We capture the channel uncertainty in the chance-constrained formulation where interference to primary users is guaranteed to be below a given threshold with high probability. However, the formulation is nonconvex, hence, we approximate the nonconvex problem with a safe convex problem by invoking robust optimization theory. Via extensive simulations under various channel conditions, we verify that our power allocation design based on the chance-constrained formulation guarantees interference constraint with high probability while enlarging the feasible region of secondary user's power.