Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next-generation wireless networks As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service requirements In this paper, we present a comprehensive literature review on the research progresses in wireless networks with RF energy harvesting capability, which is referred to as RF energy harvesting networks (RF-EHNs) First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations and review the communication protocols specially designed for RF-EHNs We also explore various key design issues in the development of RF-EHNs according to the network types, ie, single-hop networks, multiantenna networks, relay networks, and cognitive radio networks Finally, we envision some open research directions

Wireless Networks With RF Energy Harvesting: A Contemporary Survey

It is now well known that employing channel adaptive signaling in wireless communication systems can yield large improvements in almost any performance metric. Unfortunately, many kinds of channel adaptive techniques have been deemed impractical in the past because of the problem of obtaining channel knowledge at the transmitter. The transmitter in many systems (such as those using frequency division duplexing) can not leverage techniques such as training to obtain channel state information. Over the last few years, research has repeatedly shown that allowing the receiver to send a small number of information bits about the channel conditions to the transmitter can allow near optimal channel adaptation. These practical systems, which are commonly referred to as limited or finite-rate feedback systems, supply benefits nearly identical to unrealizable perfect transmitter channel knowledge systems when they are judiciously designed. In this tutorial, we provide a broad look at the field of limited feedback wireless communications. We review work in systems using various combinations of single antenna, multiple antenna, narrowband, broadband, single-user, and multiuser technology. We also provide a synopsis of the role of limited feedback in the standardization of next generation wireless systems.

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An overview of limited feedback in wireless communication systems

The performance of wireless communication is fundamentally constrained by the limited battery life of wireless devices, the operations of which are frequently disrupted due to the need of manual battery replacement/recharging. The recent advance in RF-enabled wireless energy transfer (WET) technology provides an attractive solution named wireless powered communication (WPC), where the wireless devices are powered by dedicated wireless power transmitters to provide continuous and stable microwave energy over the air. As a key enabling technology for truly perpetual communications, WPC opens up the potential to build a network with larger throughput, higher robustness, and increased flexibility compared to its battery-powered counterpart. However, the combination of wireless energy and information transmissions also raises many new research problems and implementation issues that need to be addressed. In this article, we provide an overview of stateof- the-art RF-enabled WET technologies and their applications to wireless communications, highlighting the key design challenges, solutions, and opportunities ahead.

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Wireless powered communication: opportunities and challenges

Iterative waterfilling power allocation algorithm for Gaussian interference channels is investigated The system is formulated as a non-cooperative game Based on the measured interference powers, the users maximize their own throughput by iteratively adjusting their power allocations The Nash equilib- rium in this game is a fixed point of such iterative algorithm Both synchronous and asynchronous power update are considered Some sufficient conditions under which the algorithm converges to the Nash equilibrium are derived

Convergence of Iterative Waterfilling Algorithm for Gaussian Interference Channels

The full diversity gain provided by a multi-antenna channel can be achieved by transmit beamforming and receive combining. This requires the knowledge of channel state information (CSI) at the transmitter which is difficult to obtain in practice. Quantized beamforming where fixed codebooks known at both the transmitter and the receiver are used to quantize the CSI has been proposed to solve this problem. Most recent works focus attention on limited feedback codebook design for the uncorrelated Rayleigh fading channel. Such designs are sub-optimal when used in correlated channels. In this paper, we propose systematic codebook design for correlated channels when channel statistical information is known at the transmitter. This design is motivated by studying the performance of pure statistical beamforming in correlated channels and is implemented by maps that can rotate and scale spherical caps on the Grassmannian manifold. Based on this study, we show that even statistical beamforming is near-optimal if the transmitter covariance matrix is ill-conditioned and receiver covariance matrix is well-conditioned. This leads to a partitioning of the transmit and receive covariance spaces based on their conditioning with variable feedback requirements to achieve an operational performance level in the different partitions. When channel statistics are difficult to obtain at the transmitter, we propose a universal codebook design (also implemented by the rotation-scaling maps) that is robust to channel statistics. Numerical studies show that even few bits of feedback, when applied with our designs, lead to near perfect CSI performance in a variety of correlated channel conditions.

Systematic Codebook Designs for Quantized Beamforming in Correlated MIMO Channels

In this paper, a simple algorithm for adaptation of the complex baseband weights of a transmit antenna array using feedback from the receiver is proposed and analyzed. The system utilizes stochastic gradient adaptation to maximize the power delivered to the receiver for a constrained transmission power, which provides both fading diversity and beam steering gain. Dual perturbed transmission weight vectors are time multiplexed onto the pilot signal, and the receiver generates feedback selecting the perturbed weight vector which delivers greater power. This feedback is used to provide weight adaptation at the transmitter, and this adaptation is shown to be an update by a coarse estimate of the gradient of the delivered power. The performance of the algorithm is analyzed in terms of convergence and tracking of an AR1 fading channel, with simulations confirming the analysis. Bit error rate (BER) simulations in a dynamic fading channel show that the algorithm outperforms previously proposed vector selection feedback, and in slower fading, the algorithm substantially outperforms diversity space time coding.

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A simple gradient sign algorithm for transmit antenna weight adaptation with feedback

In this correspondence, we develop techniques to efficiently quantize channel covariance matrices in multiple-input multiple-output (MIMO) Rayleigh fading environments. While these covariance matrices change less frequently than the channel matrices themselves, this information needs to be updated when it does change. Furthermore, these covariance matrices have significantly more parameters to quantize than their channel matrix counterparts. Since many applications focus on utilizing the strongest eigenmodes of the channel covariance matrix and since these matrices tend to be low-rank, we focus on efficiently quantizing the dominant eigenvectors of these matrices. We develop Lloyd-type algorithms based on training data from the environment to develop our codebooks. We also develop an algorithm based on the reduced-parameter Kronecker and Weichselberger models to generate codebooks with reduced real-time codeword search.

J. R. Zeidler

Papers

A simple gradient sign algorithm for transmit antenna weight adaptation with feedback

Techniques for MIMO Channel Covariance Matrix Quantization