Relaying Strategies for Wireless-Powered MIMO Relay Networks

This paper investigates relaying schemes in an amplify-and-forward multiple-input multiple-output relay network, where an energy-constrained relay harvests wireless power from the source information flow and can be further aided by an energy flow (EF) in the form of a wireless power transfer at the destination. However, the joint optimization of the relay matrix and the source precoder for the energy-flow-assisted (EFA) and the non-EFA (NEFA) schemes is intractable. The original rate maximization problem is transformed into an equivalent weighted mean square error minimization problem and optimized iteratively, where the global optimum of the nonconvex source precoder subproblem is achieved by semidefinite relaxation and rank reduction. The iterative algorithm finally converges. Then, the simplified EFA and NEFA schemes are proposed based on channel diagonalization, such that the matrices optimizations can be simplified to power optimizations. Closed-form solutions can be achieved. Simulation results reveal that the EFA schemes can outperform the NEFA schemes. Additionally, deploying more antennas at the relay increases the dimension of the signal space at the relay. Exploiting the additional dimension, the EF leakage in the information detecting block can be nearly separated from the information signal, such that the EF leakage can be amplified with a small coefficient.Comment: Submitted for possible journal publicatio

Joint Wireless Information and Power Transfer for an Autonomous Multiple Antenna Relay System

Considering a three-node multiple antenna relay system, this paper proposes a two-phase amplify-and-forward (AF) relaying protocol, which enables the autonomous relay to simultaneously harvest wireless power from the source information signal and from an energy signal conveyed by the destination. We first study this energy-flow-assisted (EFA) relaying in a single-input single-output (SISO) relay system and aim at maximizing the rate. By transforming the optimization problem into an equivalent convex form, a global optimum can be found. We then extend the protocol to a multiple antenna relay system. The relay processing matrix is optimized to maximize the rate. The optimization problem can be efficiently solved by eigenvalue decomposition, after linear algebra manipulation. It is observed that the benefits of the energy flow are interestingly shown only in the multiple antenna case, and it is revealed that the received information signal and the energy leakage at the relay can be nearly separated by making use of the signal space, such that the desired signal can be amplified with a larger coefficient.Comment: Accepted to IEEE Communications Letter

RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations

The increasing demand for spectral and energy efficient communication networks has spurred a great interest in energy harvesting (EH) cognitive radio networks (CRNs). Such a revolutionary technology represents a paradigm shift in the development of wireless networks, as it can simultaneously enable the efficient use of the available spectrum and the exploitation of radio frequency (RF) energy in order to reduce the reliance on traditional energy sources. This is mainly triggered by the recent advancements in microelectronics that puts forward RF energy harvesting as a plausible technique in the near future. On the other hand, it is suggested that the operation of a network relying on harvested energy needs to be redesigned to allow the network to reliably function in the long term. To this end, the aim of this survey paper is to provide a comprehensive overview of the recent development and the challenges regarding the operation of CRNs powered by RF energy. In addition, the potential open issues that might be considered for the future research are also discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Design and optimization for wireless-powered networks

Wireless Power Transfer (WPT) opens an emerging area of Wireless-Powered Networks (WPNs). In narrowband WPNs, beamforming is recognized as a key technique for enhancing information and energy transfer. However, in multi-antenna multi-sine WPT systems, not only the beamforming gain but also the rectifier nonlinearity can be exploited by a waveform design to boost the end-to-end power transfer efficiency. This thesis proposes and optimizes novel transmission strategies for two types of WPNs: narrowband autonomous relay networks and multi-antenna multi-sine WPT systems. The thesis starts by proposing a novel Energy Flow-Assisted (EFA) relaying strategy for a one-way multi-antenna Amplify-and-Forward (AF) autonomous relay network. In contrast to state-of-the-art autonomous relaying strategies, the EFA enables the relay to simultaneously harvest power from source information signals and a dedicated Energy Flow (EF) from the destination for forwarding. As a baseline, a Non-EFA (NEFA) strategy, where the relay splits power from the source signals, is also investigated. We optimize relay strategies for EFA and NEFA, so as to maximize the end-to-end rate and gain insights into the benefit of the EF. To transmit multiple data streams, we extend the EFA and the NEFA to a Multiple-Input Multiple-Output (MIMO) relay network. A novel iterative algorithm is developed to jointly optimize source precoders and relay matrices for the EFA and the NEFA, in order to maximize the end-to-end rate. Based on a channel diagonalization method, we also propose less complex EFA and NEFA algorithms. In the study of waveform designs for multi-antenna multi-sine WPT, large-scale designs with many sinewaves and transmit antennas, computationally tractable algorithms and optimal multiuser waveforms remain open challenges. To tackle these issues, we propose efficient waveform optimization algorithms to maximize the multiuser weighted-sum/minimum rectenna DC output voltage, assuming perfect Channel State Information at the Transmitter (CSIT). An optimization framework is developed to derive these waveform algorithms. Relaxing the assumption on CSIT, we propose waveform strategies for multi-antenna multi-sine WPT based on waveform selection (WS) and waveform refinement (WR), respectively. Applying the strategies, an energy transmitter can generate preferred waveforms for WPT from predesigned codebooks of waveform precoders, according to limited feedback from an energy receiver, which carries information on the harvested energy. Although the WR-based strategy is suboptimal for maximizing the average rectenna output voltage, it causes a lower overhead than the WS-based strategy. We propose novel algorithms to optimize the codebooks for the two strategies.Open Acces