Quanzhong Li

Secure Relay Beamforming for Simultaneous Wireless Information and Power Transfer in Nonregenerative Relay Networks

For simultaneous wireless information and power transfer (SWIPT), secure communication is an important issue. In this correspondence, we study the secure relay beamforming (SRB) scheme for SWIPT in a nonregenerative multiantenna relay network. We propose a constrained concave convex procedure (CCCP)-based iterative algorithm that is able to achieve a local optimum, where the secrecy rate is maximized, and the relay transmit power and energy harvesting constraints are satisfied. Simulation results have shown that our proposed CCCP-based iterative algorithm achieves a larger secrecy rate and lower computational complexity than the convectional SRB schemes. Since the CCCP-based iterative algorithm is still complex, we propose a semidefinite programming (SDP)-based noniterative suboptimal algorithm and a closed-form suboptimal algorithm. It is shown that when the maximum transmit power of the relay to noise power ratio is high, the SDP-based noniterative suboptimal algorithm performs close to the CCCP-based iterative algorithm.

Robust Secure Transmission in MISO Simultaneous Wireless Information and Power Transfer System

The secure transmission in the multiple-input-single-output simultaneous wireless information and power transfer (SWIPT) system is an important issue. Considering channel uncertainties, we investigate the robust secure transmission scheme, which maximizes the worst-case secrecy rate under transmit power constraint and energy-harvesting (EH) constraint. The optimization problem is a nonconvex problem. Omitting the rank-one constraint on transmit covariance, it is transformed into a solvable semidefinite program (SDP) where the rank relaxation performance upper bound is obtained. Since the obtained rank relaxation transmit covariance may not be rank one, we propose a lower bound-based rank-one suboptimal (LB-Sub) solution by employing Charnes-Cooper transformation. We also propose the suboptimal Gaussian randomized (GR) solutions based on the rank relaxation upper bound and the lower bound, respectively. Simulation results have shown that our proposed LB-Sub solution and suboptimal GR solution based on the rank relaxation upper bound outperform the nonrobust scheme.

Cooperative Jamming Aided Robust Secure Transmission for Wireless Information and Power Transfer in MISO Channels

Considering simultaneous wireless information and power transfer (SWIPT), we investigate cooperative-jamming (CJ) aided robust secure transmission design in multiple-input-single-output channels, where a cooperative jammer introduces jamming interferences and assists a source to supply wireless power for both an energy receiver and a legitimate destination. The destination employs a power splitting (PS) scheme to split the received signals for both information decoding and energy harvesting (EH). Compared with conventional transmission without SWIPT, the transmission with SWIPT should satisfy additional worst-case EH constraints. Furthermore, the PS scheme introduces an additional multiplicative optimization variable, i.e., the PS factor. Our objective is to maximize worst-case secrecy rate under transmit power constraints and worst-case EH constraints. We propose to decouple the problem into three optimization problems and employ alternating optimization algorithm to obtain the locally optimal solution. For the optimization of transmit covariance matrices and PS factor, we propose to employ the S-procedure and its extension to reformulate it as a convex semidefinite programming. It is shown through the simulation results that our proposed CJ aided robust secure transmission scheme outperforms the robust direct transmission scheme without CJ and the CJ aided non-robust scheme.

Beamforming in Non-Regenerative Two-Way Multi-Antenna Relay Networks for Simultaneous Wireless Information and Power Transfer

Simultaneous wireless information and power transfer (SWIPT) is able to prolong the lifetime of energy constrained wireless networks. In this paper, we consider the relay beamforming design problem for SWIPT scheme in a non-regenerative two-way multi-antenna relay network. Our objective is to maximize the sum rate of two-way relay network under the transmit power constraint at relay and the energy harvesting (EH) constraint at EH receiver. For the non-convex EH-constrained relay beamforming optimization problem, we propose an iterative algorithm to find the global optimal solution based on semidefinite programming and rank-one decomposition theorem. To reduce computational complexity of global optimal solution, we transform the EH-constrained optimization problem to a difference of convex programming and propose a constrained concave convex procedure based iterative algorithm to find a local optimum. To further reduce the complexity, we propose a suboptimal solution based on the generalized eigenvectors method. When the case of multi-antenna sources is considered, we propose the alternating optimization based iterative algorithms. It is shown from simulations that considering the EH constraint, our proposed schemes outperform conventional relay beamforming schemes in the literature.

Relay Beamforming for Amplify-and-Forward Multi-Antenna Relay Networks with Energy Harvesting Constraint

For amplify-and-forward multi-antenna relay networks with energy harvesting (EH) constraint, we study the optimal relay beamforming problem which maximizes the achievable rate from source to information-decoding receiver subject to the transmit power constraint at relay and the EH constraint at EH receiver. Because of the EH constraint, the beamforming problem is not convex. We propose the optimal beamforming scheme by converting the beamforming problem into a convex semidefinite programming with the rank-one relaxation and Charnes-Cooper transformation. We also propose a suboptimal closed-form beamforming scheme. It is shown from simulations that when the maximum allowable relay transmit power to noise power ratio is high, the performance of proposed suboptimal scheme approaches that of the optimal scheme.

Robust Transceiver Design for Wireless Information and Power Transmission in Underlay MIMO Cognitive Radio Networks

In this letter, we investigate the robust transceiver design problem for simultaneous wireless information and power transfer in multiple-input-multiple-output underlay cognitive radio networks where the channel uncertainties are modeled by the worst-case model. Our objective is to maximize the sum harvested power at energy harvesting receivers while guaranteeing the required minimum mean-square-error at the secondary information-decoding (ID) receiver and the interference constraints at the primary receivers. We propose to alternatively optimize the transmit covariance matrix at secondary transmitter and the preprocessing matrix at secondary ID receiver. Simulation results have shown that the robust transceiver design has significant performance gain over the non-robust one.

Robust Beamforming for Cognitive Multi-Antenna Relay Networks with Bounded Channel Uncertainties

In cognitive relay networks, the interferences from secondary users (SUs) and relays to primary users are constrained to be lower than a threshold. The interference constraints are difficult to satisfy when the channel state information (CSI) is imperfect. In this paper, we propose a robust beamforming scheme for the multi-antenna non-regenerative cognitive relay network where the multi-antenna relay with imperfect CSIs helps the communication of single-antenna SU. Our objective is to design a robust beamforming scheme which maximizes the system capacity subject to transmit power constraint and interference constraints. The bounded channel uncertainties are modeled using the worst-case model. The robust beamforming problem, neglecting the correlation of channel uncertainties, is reformulated as a convex semidefinite programming (SDP) by rank-one relaxation. This convex SDP is related with the worst-case relay transmit power minimization problem, which is further reformulated as a convex SDP, whose rank-one solution is proved to exist. Thus, we propose the suboptimal solution to the robust beamforming problem which is found effectively by solving two convex SDPs. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

Robust Beamforming for Nonorthogonal Multiple-Access Systems in MISO Channels

Nonorthogonal multiple access (NOMA) is a promising technology in future mobile communication systems. In this paper, considering that the base station knows imperfect channel state information (CSI), we investigate the robust beamforming design problem for NOMA systems in multiple-input-single-output (MISO) channels. Modeling channel uncertainties by the worst-case model, we aim at maximizing the worst-case achievable sum rate subject to the transmit power constraint at the base station. We propose to decouple the nonconvex optimization problem into four optimization problems and employ an alternating optimization algorithm to solve the problem. Simulation results demonstrate that our proposed robust beamforming scheme outperforms the orthogonal multiple-access scheme.

Robust Secure Beamforming in MISO Full-Duplex Two-Way Secure Communications

Considering worst-case channel uncertainties, we investigate the robust secure beamforming design problem in multiple-input-single-output (MISO) full-duplex, two-way secure communications. Our objective is to maximize worst-case sum secrecy rate under weak secrecy conditions and individual transmit power constraints. Since the objective function of the optimization problem includes both convex and concave terms, we propose to transform convex terms into linear terms. We decouple the problem into four optimization problems and employ the alternating optimization algorithm to obtain the locally optimal solution. Simulation results demonstrate that our proposed robust secure beamforming scheme outperforms the nonrobust one. It is also found that when the regions of channel uncertainties and the individual transmit power constraints are sufficiently large, because of self-interference, the proposed two-way robust secure communication is proactively degraded to one-way communication.

Secure Relay Beamforming for SWIPT in Amplify-and-Forward Two-Way Relay Networks

In this paper, we investigate the secure relay beamforming problem for simultaneous wireless information and power transfer (SWIPT) in an amplify-and-forward (AF) two-way relay network. We consider scenarios that the eavesdroppers channel state information (CSI) is and is not available. When the eavesdroppers CSI is available, our objective is to maximize the achievable secrecy sum rate under transmit power constraint and energy harvesting constraint. Since the optimization problem is nonconvex, we derive its performance upper bound, which requires 2-D search, where a semidefinite programming is solved in each step. We also propose an upper bound-based rank-one solution by employing the Gaussian randomization method. To reduce computational complexity, we transform the optimization problem into a difference-of-convex programming and propose a sequential parametric convex approximation (SPCA)-based iterative algorithm to find a locally optimal solution. Furthermore, we also propose a zero-forcing (ZF)-based suboptimal solution. Simulation results demonstrate that the upper bound-based rank-one solution archives the performance almost the same as the upper bound that has high computational complexity. The low-complexity SPCA-based locally optimal solution performs close to the upper bound. The ZF-based suboptimal solution has the lowest computational complexity among the proposed solutions. When the eavesdroppers CSI is not available, we propose an artificial noise-aided secure relay beamforming scheme.