Cognitive Radio with Partial Channel State Information at the Transmitter

In this paper, we present the design of cognitive radio in the Rician channel with partial channel state information 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 achieve better error performance when there is only partial CSIT. Based on the achievable rate derived from the LA-GPC, two optimization problems under the fast and slow fading channels are formulated. We derive semi-analytical solutions to find the relaying ratios and precoding coefficients. We also show that the parameters derived by the proposed methods converge to the optimal full CSIT solutions in the asymptotic cases. This result verifies the correctness of the proposed methods asymptotically. Moreover, a new coding scheme is proposed to implement the LA-GPC in practice. 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. Simulation results also show that the proposed practical coding scheme can effectively approach the theoretical rate performance.