Improved Joint Spectrum Sensing and Power Allocation for Cognitive Radio Networks Using Probabilistic Spectrum Access

Abstract

In this paper, by employing a probabilistic spectrum access (PSA) scheme, we perform optimal disjoint and joint spectrum sensing and downlink power allocation methods in a cognitive radio (CR) network. For the spectrum sensing, we consider a cooperative framework, in which cognitive sensors cooperate via energy-detection-based soft spectrum sensing. The proposed optimization problems related to disjoint and joint spectrum sensing and power allocation are formulated with two main objectives: first, minimizing the false-alarm probability under constant probability of detection; and second, maximizing the average opportunistic CR data rate under limited detection probability and limited CR power budget. These optimization problems are in fact the functional-based optimization problems, in which the optimization parameter is a functional of the measured energy by CR sensors, where the optimal solution is obtained using Euler-Lagrange equation. Spectrum sensing is then performed by using the optimal functional inside a PSA framework. The advantages of the proposed approach are confirmed through several numerical results.