Distributed Power Control Based on LQR and LQG Regulator for a Cognitive Radio Network

Considering ideal channel model and random time-varying channel model, we propose two decentralized power control strategies on the basis of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) regulator respectively using a state- space model for a cognitive radio network (CRN). In this strategy, the interference temperature (IT) constraint is transformed to a performance index controlled by adjusting target signal to interference plus noise ratio (SINR). And each active secondary user (SU) controls its transmission power related with its instantaneous SINR to track the target SINR and minimize the given performance index. Simulation results show that the two proposed power control strategies are effective and valid for the guarantee of SINR and IT requirements of both SUs and primary user (PU).