  This paper studies energy-efficient power allocation schemes for secondary
users in sensing-based spectrum sharing cognitive radio systems. It is assumed
that secondary users first perform channel sensing possibly with errors and
then initiate data transmission with different power levels based on sensing
decisions. The circuit power is taken into account in total power consumption.
In this setting, the optimization problem is to maximize energy efficiency (EE)
subject to peak/average transmission power constraints and peak/average
interference constraints. By exploiting quasiconcave property of EE
maximization problem, the original problem is transformed into an equivalent
parameterized concave problem and an iterative power allocation algorithm based
on Dinkelbach's method is proposed. The optimal power levels are identified in
the presence of different levels of channel side information (CSI) regarding
the transmission and interference links at the secondary transmitter, namely
perfect CSI of both transmission and interference links, perfect CSI of the
transmission link and imperfect CSI of the interference link, imperfect CSI of
both links or only statistical CSI of both links. Through numerical results,
the impact of sensing performance, different types of CSI availability, and
transmit and interference power constraints on the EE of the secondary users is
analyzed.
