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Recently, channel extrapolation has been widely investigated in frequencydivision duplex (FDD) massive MIMO systems. However, in time division duplex(TDD) fifth generation (5G) new radio (NR) systems, the channel extrapolationproblem also arises due to the hopping uplink pilot pattern, which has not beenfully researched yet. This paper addresses this gap by formulating a channelextrapolation problem in TDD massive MIMO-OFDM systems for 5G NR, incorporatingimperfection factors. A novel two-stage two-dimensional (2D) channelextrapolation scheme in both frequency and time domain is proposed, designed tomitigate the negative effects of imperfection factors and ensure high-accuracychannel estimation. Specifically, in the channel estimation stage, we propose anovel multi-band and multi-timeslot based high-resolution parameter estimationalgorithm to achieve 2D channel extrapolation in the presence of imperfectionfactors. Then, to avoid repeated multi-timeslot based channel estimation, achannel tracking stage is designed during the subsequent time instants, inwhich a sparse Markov channel model is formulated to capture the dynamicsparsity of massive MIMO-OFDM channels under the influence of imperfectionfactors. Next, an expectation-maximization (EM) based compressive channeltracking algorithm is designed to jointly estimate unknown imperfection andchannel parameters by exploiting the high-resolution prior information of thedelay/angle parameters from the previous timeslots. Simulation resultsunderscore the superior performance of our proposed channel extrapolationscheme over baselines.

A Two-Stage 2D Channel Extrapolation Scheme for TDD 5G NR Systems