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This letter studies a non-orthogonal multiple-access (NOMA)-based mobile edge computing (MEC) system. In order to enhance communication coverage and energy efficiency, intelligent reflecting surface (IRS) is proposed, which is deployed to assist computation offloading from end users to an access point (AP) equipped with an edge server. We aim to minimize the sum energy consumption by jointly optimizing the transmit powers, transmission time, offloading partitions and IRS phase shift. To address the non-convex formulated problem, we first derive the optimal solution of transmit power in closed-form, and then decouple the reformulated problem into two subproblems and employ alternating optimization (AO) technique to solve it. Numerical results validate that the proposed IRS assisted NOMA-based MEC scheme can yield superior performance in comparison with other benchmark schemes. [ABSTRACT FROM AUTHOR]

A full-duplex, amplify-and-forward multiple relay system employing simultaneous wireless information and power transfer receivers operating in interference channels is studied. Since all links want to maximize their own achievable rate, a power allocation problem under transmit power and energy harvesting constraints is developed. Through alternative optimization, a distributed iterative water-filling algorithm based on game theory with provable convergence is devised. The existence and uniqueness of a Nash equilibrium point are both guaranteed and the convergence of the proposed algorithm is examined using a diagonally strict concavity condition. Numerical results show that the proposed algorithm is convergent and can achieve a higher sum rate than previous schemes. [ABSTRACT FROM AUTHOR]

A multi-user multiple-input single-output simultaneous wireless information and power transfer full-duplex system with imperfect channel state information is considered. Under the assumption that the unknown channel estimation error is within a certain range, the self-interference cannot be suppressed completely at the base station and at the multi-user nodes. The proposed design problem is formulated as maximizing the average harvested energy of multi-user nodes and maintaining the signal-to-interference-plus-noise ratio requirement, which is proved to be non-convex. Utilizing semidefinite relaxation and S-procedure methods, a convex optimization problem of optimal beamforming vector for the multi-antenna transmitter is obtained. Moreover, semidefinite relaxation is proved to be tight by showing the existence of rank-one optimal solutions. Simulation results are presented to verify the robustness and effectiveness of the proposed algorithm compared with the non-robust design. [ABSTRACT FROM AUTHOR]

A simultaneous wireless information and power transfer scheme for amplify-and-forward relay systems with a direct source–receiver link is investigated. According to the minimum-mean-square-error criterion, we formulate a joint beamforming problem under an energy harvesting constraint at the receiver plus transmitting power constraints at source and relay. Using an iterative algorithm, the non-convex problem is decoupled into two subproblems. A successive convex approximation method with iterative algorithm is designed for obtaining the local optimum. Assuming that \mathbf Ms\leq {\mathbf {min}(\mathbf {N}, \mathbf Md)} , we propose a simplified measure using singular value decomposition and generalized singular value decomposition techniques. Numerical results for the number of iterations and bit error rate are carried out to evaluate the performance of the three different schemes. [ABSTRACT FROM PUBLISHER]

A multiple-input multiple-output two-way amplify-and-forward relay network with energy harvesting is considered in this paper. Under the transmit power constraints at sources and relay, a beamforming design problem is formulated, which minimizes the total mean square error while still guaranteeing sufficient energy harvested at the sources. Since this problem is nonconvex, an alternating optimization method based on generalized singular value decomposition (GSVD) is proposed and the algorithm is proved to be convergent. Moreover, based on the successive convex approximation, an iterative refinement is further designed to improve the solution quality of the GSVD scheme. Numerical results show good performance of the proposed schemes. [ABSTRACT FROM PUBLISHER]

A full-duplex (FD) two-way relay channel (TWRC) with multiple antennas is considered. For this three-node network, the beamforming design needs to suppress self-interference (SI). While a traditional way is to apply zero forcing (ZF) for SI mitigation, it may harm the desired signals. In this paper, a design that reserves a fraction of SI is proposed by solving a quality-of-service (QoS) constrained beamforming design problem. Since the problem is challenging due to the loop SI, a convergence-guaranteed alternating optimization (AO) algorithm is proposed to jointly design the relay–user beamformers. Numerical results show that the proposed scheme outperforms ZF method and achieves a transmit power value close to the ideal case. [ABSTRACT FROM PUBLISHER]

A full-duplex MIMO amplify-and-forward relay network with simultaneous wireless information and power transfer is considered. Based on the minimum mean-square-error criterion, this letter formulates a joint optimization problem of source and relay beamformers under their transmit powers’ constraints and the user’s energy-harvesting constraint. Through alternating optimization, a joint beamforming design with successive convex approximation is derived, which is proved to converge. To reduce the complexity, a low-complexity channel parallelization-based design is also proposed. Numerical results for the MSE and BER show that the proposed schemes perform well for this system. [ABSTRACT FROM PUBLISHER]

A MIMO two-hop relay network with power-splitting-based relaying is considered. Using a minimum mean-square-error criterion, the joint source-relay optimization problem with transmit power constraint and relay energy harvesting constraint is formulated. In order to address this non-convex problem, an iterative algorithm is proposed which converges to a local optimum. The Lagrangian dual function and successive convex approximation are used for solution. To reduce the computational complexity, a diagonalizing beamforming scheme is employed using singular value decomposition, water-filling and successive convex approximation. Results for MSE versus iterations and bit-error-rate versus signal-to-noise ratio demonstrate the good performance of the proposed schemes. [ABSTRACT FROM PUBLISHER]

This letter considers a compute-and-forward two-way relaying channel with simultaneous wireless information and power transfer based on nested lattice codes. Two single-antenna nodes exchange information via a multi-antenna intermediate relay station. Meanwhile, energies in wireless signals are beamed and flow from the relay to terminals for static circuit consumption Pc and uplink transmission power Pi. The optimization problem is formulated to minimize the transmit power Pr of relay, while guaranteeing the minimal transmission rate at each terminal. We propose an efficient iterative algorithm to jointly design the beam-former, receiver and power splitter, based on semi-definite relaxation and programming. Numerical results of transmission power comparisons validate our analysis. [ABSTRACT FROM PUBLISHER]