  Mobile edge computing (MEC) integrated with multiple radio access
technologies (RATs) is a promising technique for satisfying the growing
low-latency computation demand of emerging intelligent internet of things (IoT)
applications. Under the distributed MapReduce framework, this paper
investigates the joint RAT selection and transceiver design for over-the-air
(OTA) aggregation of intermediate values (IVAs) in wireless multiuser MEC
systems, while taking into account the energy budget constraint for the local
computing and IVA transmission per wireless device (WD). We aim to minimize the
weighted sum of the computation mean squared error (MSE) of the aggregated IVA
at the RAT receivers, the WDs' IVA transmission cost, and the associated
transmission time delay, which is a mixed-integer and non-convex problem. Based
on the Lagrange duality method and primal decomposition, we develop a
low-complexity algorithm by solving the WDs' RAT selection problem, the WDs'
transmit coefficients optimization problem, and the aggregation beamforming
problem. Extensive numerical results are provided to demonstrate the
effectiveness and merit of our proposed algorithm as compared with other
existing schemes.
