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Mobile edge computing (MEC), as a prospective computing paradigm, can augment the computation capabilities of mobile devices through offloading the complex computational tasks from simple devices to MEC-enabled base station (BS) covering them. However, how to achieve optimal schedule remains a problem due to various practical challenges including imperfect estimation of channel state information (CSI), stochastic tasks arrivals and time-varying channel situation. By using Lyapunov optimization theory and Lagrange dual decomposition technique, we propose an optimal dynamic offloading and resource scheduling (oDors) approach to maximize a system utility balancing throughput and fairness under imperfect estimation of CSI. We derive the analytical bounds for the time-averaged data queues length and system throughput achieved by the proposed approach which depends on the …