Optimized Multiuser Computation Offloading with Multi-Antenna NOMA

Mobile edge computing (MEC) has been regarded as a promising technique to enhance the computation capabilities of wireless devices, by enabling them to offload computationintensive tasks to base stations (BSs) at the network edge. This paper studies a new multiuser MEC system with multiantenna non-orthogonal multiple access (NOMA)-based computation offloading. In this system, multiple users simultaneously offload their computation tasks to one multi-antenna BS over the same time/frequency resources for remote execution, and the BS uses successive interference cancellation (SIC) for information decoding. We consider the partial offloading case, such that each user can partition the computation task into two parts for local computing and offloading, respectively. Under this setup, we minimize the weighted sum of the energy consumption at all users subject to their computation latency constraints. The decision variables include the task partition, local central processing unit (CPU) frequencies, and offloading power and rates at the users, and the SIC decoding order at the BS. We present an efficient algorithm to obtain the globally optimal solution to this problem by applying the Lagrange dual method. Numerical results show that the proposed NOMA-based partial offloading design can significantly improve the energy efficiency of the multiuser MEC system, as compared to benchmark schemes with orthogonal multiple access (OMA)-based partial offloading, and with only local computing or full offloading.