Design of the cognitive radio with partial channel state information at the transmitter

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 then derive semi-analytical solutions to the relaying ratios and precoding coefficients of these two problems. Simulation results show that the proposed semi-analytical solutions perform close to the optimal solutions found by brute-force search, and outperform the systems base 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 channels approaches infinity.