  In this paper, we present the cognitive radio system design with partial
channel state information known at the transmitter (CSIT).We replace the dirty
paper coding (DPC) used in the cognitive radio with full CSIT by the linear
assignment Gel'fand-Pinsker coding (LA-GPC), which can utilize the limited
knowledge of the channel more efficiently. Based on the achievable rate derived
from the LA-GPC, two optimization problems under the fast and slow fading
channels are formulated. We derive semianalytical solutions to find the
relaying ratios and precoding coefficients. The critical observation is that
the complex rate functions in these problems are closely related to ratios of
quadratic form. Simulation results show that the proposed semi-analytical
solutions perform close to the optimal solutions found by brute-force search,
and outperform the systems based on naive DPC. Asymptotic analysis also shows
that these solutions converge to the optimal ones solved with full CSIT when
the K-factor of Rician channel approaches infinity. Moreover, a new coding
scheme is proposed to implement the LA-GPC in practice. Simulation results show
that the proposed practical coding scheme can efficiently reach the theoretical
rate performance.
