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In this work, based on the hybrid generalized approximate message passing(HyGAMP) algorithm, we propose the message-scheduling GAMP (MSGAMP) algorithmin order to address the problem of joint active device detection and channelestimation in an uplink grant-free massive MIMO system scenario. In MSGAMP, weapply three different scheduling techniques based on the Residual BeliefPropagation (RBP) in which messages are generated using the latest availableinformation. With a much lower computational cost than the state-of-the-artalgorithms, MSGAMP-type schemes exhibits good performance in terms of activityerror rate and normalized mean squared error, requiring a small number ofiterations for convergence. %

Study of Joint Activity Detection and Channel Estimation Based on Message Passing with RBP Scheduling for MTC