Distributed Power Allocation Based on LQG Regulator With Adaptive Weight and Switching Scheme for Cognitive Radio Networks

We present a distributed power allocation algorithm for a cognitive radio network (CRN), where the underlying secondary users (SUs) share the same licensed spectrum with the primary users (PUs). Based on the target signal-to-interference-plus-noise ratio (target-SINR) tracking power control (TPC) algorithm in a conventional network, the power allocation problem is modeled as a state-space model with exogenous input that includes varying channel state information (CSI) and some parameter measurement errors. This power allocation algorithm is actually a state feedback controller from the linear quadratic Gaussian (LQG) solution, which is used to guarantee the SINR requirement of the SUs and keep the interference temperature (IT) constraint of all PUs under a given threshold. Considering the quality of service (QoS) of the SU, an adaptive control weight and a switching safety margin of the IT threshold are introduced in this algorithm to achieve better performance. Analysis and simulation results show the effectiveness and advantages of the proposed power allocation scheme, designed based on control theory, compared with those of other traditional algorithms designed based on optimization.