5 research outputs found

    Wireless Information and Energy Transfer for Two-Hop Non-Regenerative MIMO-OFDM Relay Networks

    Full text link
    This paper investigates the simultaneous wireless information and energy transfer for the non-regenerative multipleinput multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) relaying system. By considering two practical receiver architectures, we present two protocols, time switchingbased relaying (TSR) and power splitting-based relaying (PSR). To explore the system performance limit, we formulate two optimization problems to maximize the end-to-end achievable information rate with the full channel state information (CSI) assumption. Since both problems are non-convex and have no known solution method, we firstly derive some explicit results by theoretical analysis and then design effective algorithms for them. Numerical results show that the performances of both protocols are greatly affected by the relay position. Specifically, PSR and TSR show very different behaviors to the variation of relay position. The achievable information rate of PSR monotonically decreases when the relay moves from the source towards the destination, but for TSR, the performance is relatively worse when the relay is placed in the middle of the source and the destination. This is the first time to observe such a phenomenon. In addition, it is also shown that PSR always outperforms TSR in such a MIMO-OFDM relaying system. Moreover, the effect of the number of antennas and the number of subcarriers are also discussed.Comment: 16 pages, 12 figures, to appear in IEEE Selected Areas in Communication

    Wireless information and energy transfer in nonregenerative OFDM AF relay systems.

    Get PDF
    Energy harvesting (EH) is a promising strategy to prolong the operation of energy-constrained wireless systems. Simultaneous wireless information and energy transfer (SWIET) is a potential EH technique which has recently drawn significant attention. By employing SWIET at relay nodes in wireless relay systems, the relay nodes can harvest energy and receive information from their source nodes simultaneously as radio signals can carry energy as well as information at the same time, which solves the energy scarcity problem for wireless relay nodes. In this paper, we study SWIET for nonregenerative orthogonal-frequency-division multiplexing (OFDM) amplify-and-forward systems in order to maximize the end-to-end achievable rate by optimizing resource allocation. Firstly, we propose an optimal energy-transfer power allocation policy which utilizes the diversity provided by OFDM modulation. We then validate that the ordered-signal-to-noise ratio (SNR) subcarrier pairing (SP) is the optimal SP scheme. After that, we investigate the information-transfer power allocation (IPA) and EH time optimization problem which is formulated as a non-convex optimization problem. By making the approximation at high SNR regime, we convert this non-convex optimization problem into a quasi-convex programming problem, where an algorithm is derived to jointly optimize the IPA and EH time. By analytical analysis, we validate that the proposed resource allocation scheme has much lower computational complexity than peer studies in the literature. Finally, simulation results verify the optimality of our proposed resource allocation scheme

    Transceiver Optimization for Wireless Powered Time-Division Duplex MU-MIMO Systems: Non-Robust and Robust Designs

    Get PDF
    Wireless powered communication (WPC) has been considered as one of the key technologies in the Internet of Things (IoT) applications. In this paper, we study a wireless powered time-division duplex (TDD) multiuser multiple-input multiple-output (MU-MIMO) system, where the base station (BS) has its own power supply and all users can harvest radio frequency (RF) energy from the BS. We aim to maximize the users' information rates by jointly optimizing the duration of users' time slots and the signal covariance matrices of the BS and users. Different to the commonly used sum rate and max-min rate criteria, the proportional fairness of users' rates is considered in the objective function. We first study the ideal case with the perfect channel state information (CSI), and show that the non-convex proportionally fair rate optimization problem can be transformed into an equivalent convex optimization problem. Then we consider practical systems with imperfect CSI, where the CSI mismatch follows a Gaussian distribution. A chance-constrained robust system design is proposed for this scenario, where the Bernstein inequality is applied to convert the chance constraints into the convex constraints. Finally, we consider a more general case where only partial knowledge of the CSI mismatch is available. In this case, the conditional value-at-risk (CVaR) method is applied to solve the distributionally robust system rate optimization problem. Simulation results are presented to show the effectiveness of the proposed algorithms
    corecore