In this paper, we investigate the power allocation problem in massive multiple-input-multiple-output cognitive radio networks. We propose an orthogonal pilot sharing scheme at pilot transmission phase, where secondary users are allowed to use pilots for channel estimation only when there are temporarily unused orthogonal pilots. Following this, we formulate the power allocation optimization problem of the secondary network (SN) to maximize the downlink sum rate of the SN subject to the total transmit power and primary users' signal-interference-plus-noise-ratio constraints. Next, we transform the original (nonconvex) problem into a convex one by using convex approximation techniques and propose an iterative algorithm to obtain the solution. Furthermore, we prove that the proposed algorithm converges to Karush-Kuhn-Tucker points of the original problem. Meanwhile, the impact of the number of the secondary base station (SBS) antennas or the primary BS (PBS) antennas on the downlink rate of the SN and primary network is theoretically studied. Finally, the numerical results present the downlink sum rate of the SN under different parameters through our proposed algorithm.
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