Search

Non-orthogonal multiple access (NOMA) has been deemed a promising technology to achieve high spectral efficiency. This paper investigates transmit power optimization for a multi-user multiple-input single-output (MISO) NOMA downlink system endowed with energy harvesting and physical layer security. More specifically, the system is designed to satisfy the data-link security requirements of its legitimate users while charging energy harvesting devices. To achieve that goal, we investigate a joint design on beamforming vectors and artificial noise (AN) covariance matrix. Then, an iterative difference-of-two-convex-function (D.C.) algorithm is proposed by applying the successive convex approximation (SCA) approach. To further reduce the computational complexity, a sub-optimal alternating D.C. (ADC) algorithm is devised by decoupling beamforming and mapping the AN to the null space of legitimate users. In the ADC algorithm, optimal null space and beamforming vectors are alternately solved by convex programming. Furthermore, the convergence of the proposed D.C. and ADC algorithms is derived. Extensive simulation results show that the two proposed AN-aided algorithms significantly reduce the transmit power cost over OMA and NOMA scheme without AN, especially when there are more eavesdroppers. [ABSTRACT FROM AUTHOR]

In this paper, we consider an orthogonal frequency division multiplexing (OFDM) based heterogeneous cellular network consisting of a macro cell and a small cell, where a macro-cell base station (MBS) and a small-cell base station (SBS) communicate with respective macro-cell user (MU) and small-cell user (SU) with the existence of a common eavesdropper across different OFDM subcarriers. In order to make full use of the mutual interference between MBS and SBS against eavesdropping, an artificially designed signal is emitted at MBS to cancel out the interference received at MU as well as to interfere with the common eavesdropper at each subcarriers. For the purpose of further improving the secrecy performance, a sum secrecy rate (SSR) of OFDM-based heterogeneous cellular networks is maximized by optimizing the power allocation between MBS and SBS across different OFDM subcarriers when the eavesdropper owns the global instantaneous channel state information (ICSI), thus called ICSI based SSR maximization (ICSI-SSRM). As for the case when the ICSI of wiretap channels is unknown, we propose a statistical CSI based SSR maximization (SCSI-SSRM) scheme, where the statistical characteristics of channels from MBS and SBS to eavesdropper are employed to optimally allocate powers of MBS and SBS across different subcarriers under the constraint of MBS's total transmit power. The formulated ICSI-SSRM and SCSI-SSRM problems are all non-convex due to form of the difference between two-convex (D.C.) functions. Thus, we utilize the D.C. approximation approach to respectively convert original optimization problems into convex problems. Moreover, iterative optimal power allocation algorithms for ICSI-SSRM and SCSI-SSRM schemes are also presented to obtain their respective SSR values. Simulation results illustrate that the ICSI-SSRM and SCSI-SSRM algorithms can converge to their optimal values, which confirms the correctness and validation of the proposed algorithms. In addition, numerical results are also given to show that the ICSI-SSRM and SCSI-SSRM schemes outperform conventional power allocation methods in terms of their SSR performance. [ABSTRACT FROM AUTHOR]