On Capacity-Achieving Distributions for Complex AWGN Channels Under Nonlinear Power Constraints and Their Applications to SWIPT

Varasteh, Morteza; Rassouli, Borzoo; Clerckx, Bruno

doi:10.1109/tit.2020.2998464

Cited by 37 publications

(50 citation statements)

References 31 publications

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“…This assumption is very optimistic given the dependency of the delivered DC power on higher order statistics of the channel input distribution [36], [37]. Nonetheless, from the fundamental limits point of view, any more realistic model would induce fundamental limits that are more pessimistic than the results presented in the following sections.…”

Section: B Energy Transmission Taskmentioning

confidence: 99%

Simultaneous Information and Energy Transmission in the Two-User Gaussian Interference Channel

Khalfet

Perlaza

2019

IEEE J. Select. Areas Commun.

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In this paper, the fundamental limits of simultaneous information and energy transmission (SIET) in the two-user Gaussian interference channel (G-IC) with and without perfect channel-output feedback are approximated by two regions in each case, i.e., an achievable region and a converse region. When the energy transmission rate is normalized by the maximum energy rate, the approximation is within a constat gap. In the proof of achievability, the key idea is the use of power-splitting between two signal components: an information-carrying component and a no-information component. The construction of the former is based on random coding arguments, whereas the latter consists in a deterministic sequence known by all transmitters and receivers. The proof of the converse is obtained via cut-set bounds, genieaided channel models, Fano's inequality and some concentration inequalities considering that channel inputs might have a positive mean. Finally, the energy transmission enhancement due to feedback is quantified and it is shown that feedback can at most double the energy transmission rate at high signal to noise ratios.

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Section: B Energy Transmission Taskmentioning

confidence: 99%

Simultaneous Information and Energy Transmission in the Two-User Gaussian Interference Channel

Khalfet

Perlaza

2019

IEEE J. Select. Areas Commun.

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“…Even larger gains can be obtained using asymmetric Gaussian inputs [117] and on-off keying (or also called flash signaling) [118]. Indeed, real Gaussian modulation outperforms CSCG modulation despite the same average input power P r rf to the rectifier.…”

Section: Signal Processing Techniques For Wiptmentioning

confidence: 99%

“…Relaxing the constraints on Gaussian inputs, it is remarkably shown in [118] that the capacity of an AWGN channel under transmit average power and target delivered power constraints as characterized by Problem ( 48)-( 50) is obtained by adopting a combination of CSCG and on-off-keying inputs. Let E G denote the output DC power with the input x ∼ CN (0, P ).…”

Section: Signal Processing Techniques For Wiptmentioning

confidence: 99%

“…with l ≥ 1. Such a distribution has indeed a low probability of output DC power P r dc (x) (blue solid line) corresponding to the complex Gaussian inputs with asymmetric power allocation [118]. The transmitted information rate is maximized for P i = Pr = P/2 and delivered power is maximized when P i = 0, Pr = P or P i = P , Pr = 0.…”

Section: Signal Processing Techniques For Wiptmentioning

confidence: 99%

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Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing

Clerckx

Huang

Varshney

et al. 2021

IEEE J. Sel. Top. Signal Process.

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Wireless power transfer (WPT) is an emerging paradigm that will enable using wireless to its full potential in future networks, not only to convey information but also to deliver energy. Such networks will enable trillions of future low-power devices to sense, compute, connect, and energize anywhere, anytime, and on the move. The design of such future networks brings new challenges and opportunities for signal processing, machine learning, sensing, and computing so as to make the best use of the RF radiations, spectrum, and network infrastructure in providing cost-effective and realtime power supplies to wireless devices and enable wirelesspowered applications. In this paper, we first review recent signal processing techniques to make WPT and wireless information and power transfer (WIPT) as efficient as possible. Topics include high-power amplifier and energy harvester nonlinearities, active and passive beamforming, intelligent reflecting surfaces, receive combining with multi-antenna harvester, modulation, coding, waveform, large-scale (massive) multiple-input multipleoutput (MIMO), channel acquisition, transmit diversity, multiuser power region characterization, coordinated multipoint, and distributed antenna systems. Then, we overview two different design methodologies: the model and optimize approach relying on analytical system models, modern convex optimization, and communication/information theory, and the learning approach based on data-driven end-to-end learning and physics-based learning. We discuss the pros and cons of each approach, especially when accounting for various nonlinearities in wireless-powered networks, and identify interesting emerging opportunities for the approaches to complement each other. Finally, we identify new emerging wireless technologies where WPT may play a key role-wireless-powered mobile edge computing and wirelesspowered sensing-arguing WPT, communication, computation, and sensing must be jointly designed.

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“…Several attempts have discussed the optimal input symbol distribution for information transfer for a given wireless power transfer constraint [18,19]. Moreover, several works have studied potential modulation schemes to improve the PCE in SWIPT systems [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Transmission Strategy for Simultaneous Wireless Information and Power Transfer with a Non-Linear Rectifier Model

et al. 2020

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Most studies determining data rate or power conversion efficiency (PCE) of simultaneous wireless information and power transfer (SWIPT) focus on ideal models for the non-linear energy harvester, or focus on simplified waveforms that carry no information. In this paper, we study SWIPT using realistic waveforms and a measurement-based energy harvesting model. For a special class of multisine waveforms carrying only information in the phase, we analyze PCE as a function of waveform design, including the impact of pre-equalization to mitigate wireless channel distortion. A balanced pre-equalizer that trades off between the peak-to-average power ratio (PAPR) and signal to noise ratio, maximizing the total PCE is proposed. The impact on the information rate of the analyzed waveforms is also presented. The results show that balanced pre-equalizers can improve the total PCE more than three times within 5% rate loss compared to the pre-equalizer that solely maximizes the signal PAPR or the capacity using the same transmit power. We also show that the maximum normalized PCE is increased by a factor of two by only allowing phase modulation to ensure the PAPR of one symbol, compared to traditional modulation schemes that carry information in both phase and amplitude to maximize spectral efficiency.

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On Capacity-Achieving Distributions for Complex AWGN Channels Under Nonlinear Power Constraints and Their Applications to SWIPT

Cited by 37 publications

References 31 publications

Simultaneous Information and Energy Transmission in the Two-User Gaussian Interference Channel

Simultaneous Information and Energy Transmission in the Two-User Gaussian Interference Channel

Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing

Transmission Strategy for Simultaneous Wireless Information and Power Transfer with a Non-Linear Rectifier Model

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