Energy-Efficient Resource Allocation for OFDM-Based Cognitive Radio Networks with Imperfect Spectrum Sensing

Abstract

In this study, energy-efficient (EE) resource allocation in orthogonal frequency division multiplexing-based cognitive radio networks with imperfect spectrum sensing is investigated. We present a new EE model by considering the sensing errors. Optimizing such an EE expression saves valuable resources, such as battery life, by selectively allocating power to underutilized subcarriers, and also achieves EE gain compared with general EE expression. Given that the primary user’s interference tolerance can be defined as either the Peak Interference Power (PIP) constraint or Average Interference Power (AIP) constraint for all subchannels, we compare the EE performance for the two interference power constraints. Finally, we propose an optimal EE resource allocation scheme based on the quasiconcave relation between the EE and transmit power. Simulations show that the new EE design improves EE compared with the conventional EE design, and the EE is higher with AIP constraint than that with PIP constrain under certain interference power.