Subcarrier and power allocation in cognitive OFDM systems under imperfect CSI with smart channel estimation

Abstract

Cognitive radio (CR) employing OFDM has drawn many interests in designing efficient radio resource allocation schemes. Most of the existing works considered the cognitive scenario under perfect knowledge of system state, such as channel state information (CSI) and sensing information (SI). However, it is serious to properly regulate the interference caused by secondary users (SUs) to each primary user (PU). In this paper, we focus on the design and analysis of subcarrier and power allocation scheme under imperfect CSI for cognitive OFDM systems. A smart way using training preamble is presented to obtain the CSI of Rayleigh block-fading channel between the transmitter and receiver. During the training phase, the receiver estimates the channel and feeds the estimate back to the transmitter. During the transmission phase, a two-step algorithm for capacity maximization is proposed to obtain the subcarrier assignment and power allocation for each SU. It is shown by extensive simulation and analysis that, by increasing the number of training symbols, the total capacity can be largely enhanced.