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This paper considers a multi-user simultaneous wireless information and power transfer (SWIPT) system with a non-linear energy harvesting model, in which a multi-antenna base station (BS) estimates the downlink channel state information (CSI) via uplink pilots. Each single-antenna user is equipped with a power splitter. Three crucial issues on resource management for this system include: (i) power-efficient improvement, (ii) user-fairness guarantee, and (iii) non-ideal channel reciprocity effect mitigation. Potentially, a resource allocation scheme to address jointly such issues can be devised by using the framework of multi-objective optimization. However, the resulting problem might be complex to solve since the three issues hold different characteristics. Therefore, we propose a novel method to design the resource allocation scheme. In particular, the principle of our method relies on structuralizing mathematically the issues into a cross-layer multi-level optimization problem. On this basis, we then devise solving algorithms and closed-form solutions. Moreover, to instantly adapt the CSI changes in practice while reducing computational burdens, we propose a closed-form suboptimal solution to tackle the problem. Finally, we provide numerical results to show the achievable performance gains using the optimal and suboptimal solutions, and then validate the proposed resource allocation scheme.Index Terms-Energy harvesting, simultaneous wireless information and power transfer, resource allocation.

Inspired by the direct use of alternating current (AC) for computation, we propose a novel integrated information and energy receiver architecture for simultaneous wireless information and power transfer (SWIPT) networks. In this context, the AC computing method, in which wirelessly harvested AC energy is directly used to supply the computing block of receivers, enhances not only computational ability but also energy efficiency over the conventional direct current (DC) one. Further, we aim to manage the trade-off between the information decoding (ID) and energy harvesting (EH) optimally while taking imperfect channel estimation into account. It results in a worst-case optimization problem of maximizing the data rate under the constraints of an EH requirement, the energy needed for supplying the AC computational logic, and a transmit power budget. Then, we propose a method to derive closed-form optimal solutions. The numerical results demonstrate that the proposed architecture with AC computing significantly improves the rate-energy region. Index TermsEnergy harvesting, simultaneous wireless information and power transfer, Internet of Things.

In this paper, we consider a multi-input multioutput (MIMO) non-orthogonal multiple access (NOMA) network consisting of one source and two legitimate users (LUs), so-called near and far users according to their distances to the source, and one passive eavesdropper, over Nakagami-m fading channels. Specifically, we investigate the cases where the signals of the far user might or might not be successfully decoded at the eavesdropper and the near user. Thus, we aim to design a transmit antenna selection (TAS) secure communication protocol for the network; where, two TAS solutions, namely Solutions I and II, are proposed. Specifically, solutions I and II focus on maximizing the received signal power between the source and the near user, and between the source and the far user, respectively. Accordingly, exact and asymptotic closed-form expressions for the secrecy outage probability of the LUs and the overall system are derived. Our analytical results corroborated by Monte Carlo simulation indicate that the secrecy performance could be significantly improved by properly selecting the power allocation coefficients and increasing the number of antennas at the source and the LUs. Interestingly, solution II is shown to provide a better overall secrecy performance over solution I.Index Terms-Transmit antenna selection, MIMO, nonorthorgonal multiple access, physical layer security.

Green radio communication is an emerging topic since the overall footprint of information and communication technology (ICT) services is predicted to triple between 2007 and 2020. Given this research line, energy harvesting (EH) and wireless power transfer (WPT) networks can be evaluated as promising approaches. In this paper, an overview of recent trends for future green networks on the platforms of EH and WPT is provided. By rethinking the application of radio frequency (RF)-WPT, a new concept, namely green RF-WTP, is introduced. Accordingly, opening challenges and promising combinations among current technologies, such as small-cell, millimeter (mm)wave, and Internet of Things (IoT) networks, are discussed in details to seek solutions for the question with how to re-green the future networks?