Maximum-Eigenvalue-Based Sensing and Power Recognition for Multiantenna Cognitive Radio System

Spectrum sensing, as a way for a secondary user (SU) to detect the on/off status of the primary user (PU), has been well studied in the area of cognitive radio (CR) for the past ten years. It is noticed that most exiting techniques only assumed that the PU has constant transmit power, although in practice, the PU could possibly operate under more than one discrete power levels, as can be seen from many practical standards, e.g., 802.11, Global System for Mobile Communications, and Long-Term Evolution. In this paper, we investigate this new multiple primary transmit power (MPTP) scenario and propose the corresponding detection/recognition framework based on multiple-antenna configuration at the SU. Although the primary target in MPTP is still to detect the on/off status of the PU, a secondary target appears in order to identify PU's transmit power level once the PU is “detected” in the first place. To achieve these two targets, an eigenvalue-based approach is applied due to its robustness and least requirement on the knowledge of channels. To obtain the closed-form threshold expressions and the performance analysis, we adopt nonasymptotic Gaussian and Gamma approximation for the distribution of the eigenvalues of the sample covariance matrix. Simulation results are provided to verify the proposed studies.