Particle Swarm Optimization Based Power Allocation In Cognitive Wireless Networks

Abstract

In this paper, particle swarm optimization-based power allocation algorithm is investigated for an
OFDM based cognitive radio (CR) system. The transmission rate of CR user is thereby maximized,
while the interference introduced to the primary user (PU) remains within an acceptable range. The
nature inspired particle swarm optimization (PSO) algorithm has been proposed because of its
simplicity, fast convergence and better performance. The performance of PSO method is compared with
the classical power loading algorithm, e.g., water-filling used for conventional OFDM based system as
well as sub optimal loading scheme used in OFDM based CR systems. Simulation results show that for
a specific interference threshold maximum power can be allocated using proposed method compared
to classical methods resulting in improved sum transmission capacity of secondary user over allocated
subcarriers. Finally, the effect of PSO based optimal power allocation is investigated to enhance the
data rate of CR user.