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For ultralow-power Internet of Things, we consider a monostatic multiantenna backscatter communication network (MBCN) supporting massive devices through nonorthogonal multiple access (NOMA) over space division multiple access (SDMA). For the network, we optimize the transmit beamforming (BF) for signal excitation of a reader, reflection coefficients of devices for backscattering and energy harvesting, and receive BF for information decoding at the reader toward the maximum fairness in data collection. We first show that the optimization problem for the MBCN without successive interference cancellation (SIC) has a similarity with the problem considered for a wireless power communication network but the conventional algorithm is not applicable to the MBCN with SIC. Thus, we propose a new alternating optimization algorithm that is applicable to both problems with and without SIC at a lower complexity. Simulation results show that the proposed algorithm provides a remarkable gain over the conventional one for the MBCN with SIC while exhibiting a similar performance for the MBCN without SIC. In addition, NOMA/SDMA enhanced by the proposed algorithm increases the minimum system throughput as well as the total energy harvested in the network by utilizing limited resources more effectively for a larger number of devices.

Beamforming and Reflection Coefficient Control for Multiantenna Backscatter Communication With Nonorthogonal Multiple Access