Beamforming aided NOMA expedites collaborative multiuser computational off-loading

Wang, Li, Guan, Mengling, Ai, Yutong, Chen, Yingyang, Jiao, Bingli and Hanzo, Lajos (2018) Beamforming aided NOMA expedites collaborative multiuser computational off-loading. IEEE Transactions on Vehicular Technology. (doi:10.1109/TVT.2018.2853675).

Abstract

This paper proposes a novel multiuser computational off-loading scheme for a fog-based scenario. Specifically, a computing user (CU) distributes its computational tasks to multiple trusted helping users (HUs) by exploiting both nonorthogonal multiple access (NOMA) and beamforming. Firstly, 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 (ZFBF) is used by the CU to completely eliminate the inter-pair interference, hence further enhancing the sum rate. By analysing 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 (SINR) 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 KuhnTucker (KKT) conditions. Our numerical results demonstrate that by the combining the social relationships, the computational capacities and the channel conditions, the proposed multiuser computational off-loading scheme relying on social trust, NOMA and beamforming improves the energy consumption, sum rate as well as transmission latency.

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Contributors

Author: Lajos Hanzo

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