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This paper addresses the mobility problem in massive multiple-inputmultiple-output systems, which leads to significant performance losses in thepractical deployment of the fifth generation mobile communication networks. Wepropose a novel channel prediction method based on multi-dimensional matrixpencil (MDMP), which estimates the path parameters by exploiting theangular-frequency-domain and angular-time-domain structures of the widebandchannel. The MDMP method also entails a novel path pairing scheme to pair thedelay and Doppler, based on the super-resolution property of the angleestimation. Our method is able to deal with the realistic constraint oftime-varying path delays introduced by user movements, which has not beenconsidered so far in the literature. We prove theoretically that in thescenario with time-varying path delays, the prediction error converges to zerowith the increasing number of the base station (BS) antennas, providing thatonly two arbitrary channel samples are known. We also derive a lower-bound ofthe number of the BS antennas to achieve a satisfactory performance. Simulationresults under the industrial channel model of 3GPP demonstrate that ourproposed MDMP method approaches the performance of the stationary scenario evenwhen the users' velocity reaches 120 km/h and the latency of the channel stateinformation is as large as 16 ms.

A Multi-Dimensional Matrix Pencil-Based Channel Prediction Method for Massive MIMO with Mobility