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In this paper, the problem of maximizing the sum of data rates of all usersin an intelligent reflecting surface (IRS)-assisted millimeter wave multicastmultiple-input multiple-output communication system is studied. In theconsidered model, one IRS is deployed to assist the communication from amultiantenna base station (BS) to the multi-antenna users that are clusteredinto several groups. Our goal is to maximize the sum rate of all users byjointly optimizing the transmit beamforming matrices of the BS, the receivebeamforming matrices of the users, and the phase shifts of the IRS. To solvethis non-convex problem, we first use a block diagonalization method torepresent the beamforming matrices of the BS and the users by the phase shiftsof the IRS. Then, substituting the expressions of the beamforming matrices ofthe BS and the users, the original sum-rate maximization problem can betransformed into a problem that only needs to optimize the phase shifts of theIRS. To solve the transformed problem, a manifold method is used. Simulationresults show that the proposed scheme can achieve up to 28.6% gain in terms ofthe sum rate of all users compared to the algorithm that optimizes the hybridbeamforming matrices of the BS and the users using our proposed scheme andrandomly determines the phase shifts of the IRS.

Beamforming Design for the Performance Optimization of Intelligent Reflecting Surface Assisted Multicast MIMO Networks