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In this paper, we investigate secure transmission in a massive multiple-input multiple-output system adopting low-resolution digital-to-analog converters (DACs). Artificial noise (AN) is deliberately transmitted simultaneously with the confidential signals to degrade the eavesdropper’s channel quality. By applying the Bussgang theorem, a DAC quantization model is developed which facilitates the analysis of the asymptotic achievable secrecy rate. Interestingly, for a fixed power allocation factor $\phi $ , low-resolution DACs typically result in a secrecy rate loss, but in certain cases, they provide superior performance, e.g., at low signal-to-noise ratio (SNR). Specifically, we derive a closed-form SNR threshold which determines whether low-resolution or high-resolution DACs are preferable for improving the secrecy rate. Furthermore, a closed-form expression for the optimal $\phi $ is derived. With AN generated in the null-space of the user channel and the optimal $\phi $ , low-resolution DACs inevitably cause secrecy rate loss. On the other hand, for random AN with the optimal $\phi $ , the secrecy rate is hardly affected by the DAC resolution because the negative impact of the quantization noise can be compensated by reducing the AN power. All the derived analytical results are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper, we study the resource allocation algorithm design for multiple-input single-output (MISO) multicarrier non-orthogonal multiple access (MC-NOMA) systems, in which a full-duplex base station serves multiple half-duplex uplink and downlink users on the same subcarrier simultaneously. The resource allocation is optimized for maximization of the weighted system throughput while the information leakage is constrained and artificial noise is injected to guarantee secure communication in the presence of multiple potential eavesdroppers. To this end, we formulate a robust non-convex optimization problem taking into account the imperfect channel state information of the eavesdropping channels and the quality-of-service requirements of the legitimate users. Despite the non-convexity of the optimization problem, we solve it optimally by applying monotonic optimization which yields the optimal beamforming, artificial noise design, subcarrier allocation, and power allocation policy. The optimal resource allocation policy serves as a performance benchmark since the corresponding monotonic optimization-based algorithm entails a high computational complexity. Hence, we also develop a low-complexity suboptimal resource allocation algorithm which converges to a locally optimal solution. Our simulation results reveal that the performance of the suboptimal algorithm closely approaches that of the optimal algorithm. Besides, the proposed optimal MISO NOMA system can not only ensure downlink and uplink communication security simultaneously but also provides a significant system secrecy rate improvement compared with the traditional MISO orthogonal multiple access systems and two other baseline schemes. [ABSTRACT FROM AUTHOR]