Beamforming-Aided NOMA Expedites Collaborative Multiuser Computational Offloading

This correspondence proposes a novel multiuser computational offloading scheme for a fog-based scenario. Specifically, a controlling user (CU) distributes its computational tasks to multiple trusted helping users (HUs) by exploiting both nonorthogonal multiple access (NOMA) and beamforming. First, social relationships between the CU and HUs are exploited for the selection of trusted HUs. Then, the HUs having sufficient computing resources and high social trust are selected and grouped into multiple pairs. For the sake of improving the spectral efficiency, NOMA is invoked for simultaneously supporting several HUs. Meanwhile, a process of zero-forcing beamforming is used by the CU to completely eliminate the interpair interference, hence further enhancing the sum rate. By analyzing the achievable rate and energy consumption of the uplink and downlink transmission, an energy consumption minimization problem is formulated subject to the constraints of signal-to-interference plus noise ratio and transmission latency. We design a user-pairing and resource allocation algorithm for successively optimizing the power allocation and computational task distribution, while satisfying the classic Karush–Kuhn–Tucker conditions. Our numerical results demonstrate that by combining the social relationships, the computational capacities, and the channel conditions, the proposed multiuser computational offloading scheme relying on social trust, NOMA, and beamforming improves the energy consumption, sum rate, and transmission latency.