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This paper investigates the achievable rate of MIMO cognitive radio network when one primary user (PU) and multiple secondary users (SU) are present, where the latter adopt dirty paper coding (DPC) to cancel the interference of PU's transmission at their receivers. Perfect channel state information is assumed at receivers, while only the statistic information of channels are known at the transmitters. We formulate an optimization problem to maximize the achievable rate of the system under the constraints of power limits of each transmitter, where the requirement of not affecting PU's transmission rate is also incorporated. An algorithm is proposed to jointly determine the inflation factors in DPC method and the input covariance matrix of each SU. Simulations show that the proposed problem achieves better achievable rate when compared with the existing results without compromising PU's transmission rate.