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RIS-Assisted Over-the-Air Computation in Millimeter Wave Communication Networks

Over-the-air computation (AirComp) and millimeter wave (mmWave) communications have the feasibility to perform fast wireless data aggregation (WDA) by allowing simultaneous transmissions and providing abundant spectral resources, respectively. However, AirComp is limited by the link with the worst channel condition, while mmWave communications are vulnerable to the blockages. To address these issues, this paper proposes to leverage reconfigurable intelligent surface (RIS) aided AirComp for WDA in mmWave communication networks. To enhance the system performance, we formulate an optimization problem to minimize the mean-squared error (MSE) of WDA by jointly optimizing the receive beamforming vector of the access point, the transmit scalars of devices, and the phase-shift matrix of the RIS. To this end, we derive the closed-form expression of transmit scalars and then propose a Riemannian conjugate gradient algorithm, which can efficiently tackle the unit-modulus constraints with a low computational complexity. Compared to the baseline algorithms, simulation results reveal that the proposed algorithm achieves a faster convergence rate and a smaller MSE.