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In Internet of Things scenarios, the problem of restricted energy and limited computation capability of user node usually exists. To address the problem, a multiple‐input‐multiple‐output full‐duplex multi‐hop relay simultaneous wireless information and power transfer (SWIPT) mobile‐edge computing (MEC) system is proposed in this paper, where energy harvesting model is non‐linear. With the aid of MEC and SWIPT, user node equipped with power splitting receiver can locally execute computation tasks or offload partial or all of it to access point associated with an MEC server by using its battery energy, and harvest energy to replenish its battery while downloading the computation results. In addition, the system introduces full‐duplex multi‐hop relay and non‐linear energy model to improve network coverage and model practical energy harvesting circuit. Aiming at minimising the system energy consumption, an energy efficient optimisation problem is formulated while satisfying the latency and energy constraints. Since the original problem is non‐linear and non‐convex, it is converted into two subproblems and successive convex approximation‐based algorithm and geometric programming‐based algorithm based alternating optimisation technique are adopted to solve them. Numerical results verify the superiority of the proposed optimisation scheme compared with other benchmark schemes. [ABSTRACT FROM AUTHOR]

The simultaneous wireless information and power transfer (SWIPT) technique has been considered as a promising approach to prolong the lifetime of energy-constraint wireless sensor networks (WSNs). In this paper, a multiple-input multiple-output (MIMO) full-duplex (FD) bidirectional wireless sensor network (BWSN) with SWIPT is investigated. Based on minimum total mean-square-error (total-MSE) criterion, a joint optimization problem for source and relay beamforming and source receiving subject to transmitting power and harvesting energy constraints is established. Since this problem is non-convex, an iterative algorithm based on feasible point pursuit-successive convex approximation (FPP-SCA) is derived to obtain a local optimum. Moreover, considering the scenarios in which source and relay nodes equipped with the same and different numbers of antennas, a low-complexity diagonalizing design-based scheme is employed to simplify each non-convex subproblem into convex problems and to reduce the computational complexity. Numerical results of the total-MSE and bit error rate (BER) are implemented to demonstrate the performance of the two different schemes. [ABSTRACT FROM AUTHOR]

We consider a multiple-input multiple-output amplify-and-forward wireless multiple-hop sensor network (WMSN). The simultaneous wireless information and power transfer technology is deployed to potentially achieve an autonomous system. We investigate two practical receiver schemes, which are the power splitting (PS) and the time switching (TS). The power splitting receiver splits received signals into two streams, one for information decoding (ID) and the other for energy harvesting (EH). On the other hand, the time switching receiver only serves in ID mode or energy harvesting mode during a certain time slot. Subject to transmit power constraints and destination harvested energy constraint, we aim to obtain a joint beam-forming solution of source and relay precoders to maximize the maximum achievable rate of the WSN. In order to make the non-convex problem tractable, diagonalization-based alternating optimization algorithms are proposed. Numerical results show the convergence and good performance of the proposed algorithms under both PS and TS protocols. [ABSTRACT FROM AUTHOR]

The simultaneous wireless information and power transfer (SWIPT) technique has been regarded as an appealing approach to prolong the lifetime of wireless sensor networks. However, co-channel interferences with SWIPT in wireless networks have not been investigated from a green communication perspective. In this paper, joint transmit and receive beamforming design for a full-duplex multiple-input multiple-output amplify-and-forward relay system with simultaneous wireless information and power transfer in WSNs is investigated. Multiple co-channel interferers are considered at the relay and destination sensor nodes. To minimize the mean-squared-error of the system, joint source and relay beamforming optimization is proposed while guaranteeing the transmit power constraints and destination's energy harvesting constraint. An iterative algorithm based on alternating optimization with successive convex approximation which converges to a local optimum is proposed to solve the non-convex problem. Moreover, a low-complexity scheme is derived to reduce the computational complexity. Simulations for MSE versus iterations and MSE versus signal-to-noise ratio (SNR) demonstrate the convergence and good performance of the proposed schemes. [ABSTRACT FROM AUTHOR]