1 research outputs found
Energy-Efficient Power Adaptation for Cognitive Radio Systems under Imperfect Channel Sensing
In this paper, energy efficient power adaptation is considered in
sensing-based spectrum sharing cognitive radio systems in which secondary users
first perform channel sensing and then initiate data transmission with two
power levels based on the sensing decisions (e.g., idle or busy). It is assumed
that spectrum sensing is performed by the cognitive secondary users, albeit
with possible errors. In this setting, the optimization problem of maximizing
the energy efficiency (EE) subject to peak/average transmission power
constraints and average interference constraints is considered. The circuit
power is taken into account for total power consumption. By exploiting the
quasiconcave property of the EE maximization problem, the original problem is
transformed into an equivalent parameterized concave problem and Dinkelbach's
method-based iterative power adaptation algorithm is proposed. The impact of
sensing performance, peak/average transmit power constraints and average
interference constraint on the energy efficiency of cognitive radio systems is
analyzed.Comment: To Appear at 2014 IEEE INFOCOM Workshop on Green Cognitive
Communications and Computing Networks. Some typos are fixe