Distributed Power Allocation Based on Robust Hinfinity Control for Cognitive Radio Network with Time-Varying Channel Uncertainties

Considering a random time-varying channel model, we propose a decentralized power allocation (PA) scheme based on ${{\cal H}_\infty }$ control theory for a cognitive radio network (CRN) under dynamic formulation by state space model with exogenous input. In this state space model, we transform the interference temperature (IT) constraint and the target signal to interference plus noise ratio (SINR) tracking to a weighted control performance index. We design a ${{\cal H}_\infty }$ controller to make the index minimum to obtain a reasonable target SINR. In the PA scheme, each active secondary user (SU) controls its transmit power related with its instantaneous SINR to track the target SINR. Simulation results show that the proposed strategy using ${{\cal H}_\infty }$ controller is effective and valid for the SINR and IT requirements of both SUs and primary user (PU).