This paper investigates the capacity-power trade-off in quantum communication channels under energy harvesting (EH) constraints, introducing a novel framework for analyzing the impact of the harvested energy requirements on the achievable channel capacity. We extend the conventional study of quantum channel capacity by incorporating realistic EH models into the analysis for both discrete-variable and continuous-variable quantum channels. Specifically, we explore the amplitude damping channel and quantum erasure channel as representative examples of discrete channels as well as the lossy bosonic channel and additive Gaussian noise channel for the continuous variable case. For each channel, we derive the capacity-power function by solving appropriate optimization problems that balance information transfer and EH requirements. Our results reveal critical insights into the interplay between quantum information transfer and EH constraints, highlighting fundamental trade-offs that are essential for designing an efficient quantum communication systems with EH.
This paper investigates the capacity-power trade-off in quantum communication channels under energy harvesting (EH) constraints, introducing a novel framework for analyzing the impact of the harvested energy requirements on the achievable channel capacity. We extend the conventional study of quantum channel capacity by incorporating realistic EH models into the analysis for both discrete-variable and continuous-variable quantum channels. Specifically, we explore the amplitude damping channel and quantum erasure channel as representative examples of discrete channels as well as the lossy bosonic channel and additive Gaussian noise channel for the continuous variable case. For each channel, we derive the capacity-power function by solving appropriate optimization problems that balance information transfer and EH requirements. Our results reveal critical insights into the interplay between quantum information transfer and EH constraints, highlighting fundamental trade-offs that are essential for designing an efficient quantum communication systems with EH.
This paper introduces a new framework for quantum simultaneous information and power transfer (QSIPT), enabling the joint use of quantum states for classical information and energy transfer in quantum communication systems. We propose a model in which quantum states simultaneously transmit classical information through a quantum channel and transfer energy to an energy harvesting (EH) receiver. The trade-off between communication rate and harvested energy is characterized by the capacity-power function, defined for both discrete-variable (DV) and continuous-variable (CV) quantum channels. For DV channels, we derive properties of the capacity-power function, providing analytical upper and lower bounds for the amplitude damping channel and an exact closed-form characterization for the quantum erasure channel. For CV channels, we extend the framework by introducing a generalized beam-splitter (BS) receiver with adjustable transmissivity, jointly optimized with a transmitter mean-photon-number budget, splitting the channel output between the information decoder and the EH receiver. We analyze the capacity-power and achievable-rate-power trade-off under various Gaussian encoding schemes, including coherent, squeezed, and thermal states, for both lossy bosonic and additive Gaussian noise channels. Closed-form expressions are derived for coherent-state encoding under the joint photon-number-budget and adjustable-transmissivity formulation; squeezed-state inputs are evaluated numerically. Our results show that, within the considered displaced Gaussian encoding class, coherent states achieve the best capacity-power trade-off, squeezed states do not outperform coherent-state encoding under the phase-insensitive channel and passive receiver architecture, and thermal states enable energy transfer without supporting reliable communication.
Quantum capacity gives the fundamental limit of information transmission through a channel. However, evaluating the quantum capacities of a continuous-variable bosonic quantum channel, as well as finding an optimal code to achieve the optimal information transmission rate, is in general challenging. In this work, we derive the quantum capacity and entanglement-assisted quantum capacity of the bosonic continuous-variable erasure channel when subject to energy constraints. We then construct random codes based on scrambling information within the typical subspace of the encoding state and prove that these codes are asymptotically optimal up to a constant gap. Finally, using our random coding scheme we design a bosonic variation of the Hayden-Preskill protocol and find that information recovery depends on the ratio between the input and output modes. This is in contrast with the conventional discrete-variable scenario which requires only a fixed number of additional output qudits.
We investigate the secrecy performance and energy-efficiency trade-offs associated to the secure communication between a full-duplex (FD) power beacon (PB) and an energy harvesting (EH) device, in the presence of an eavesdropper. Specifically, we analyze the feasibility of a jamming strategy implemented at the FD-PB under several practical constraints, such as imperfect self-interference (SI) cancellation, EH non-linearity, channel aging and energy-information correlation. The design of the optimal time-splitting factor for the simultaneous wireless information and power transfer (SWIPT) strategy, the adequacy of different beamforming strategies for proper system operation, and the impact of channel correlation between the energy and information transmission phases in SWIPT are thoroughly discussed. Results indicate that under practical constraints such as EH non-linearity and imperfect SI cancellation, the transmit powers at the FD-PB for the generation of energy and jamming signals are the key parameters to be optimized from both points of view: secrecy and energy efficiency. We also verify the positive impact of correlation between the energy and information links in wireless power transfer systems, from a physical layer security perspective.
Simultaneous wireless information and power transfer (SWIPT) has recently gathered much research interest from both academia and industry as a key enabler of energy harvesting Internet-of-things (IoT) networks. Due to a number of growing use cases of such networks, it is important to study their performance limits from the perspective of physical layer security (PLS). With this intent, this work aims to provide a novel analysis of the ergodic secrecy capacity of a SWIPT system is provided for Rician and Nakagami- m faded communication links. For a realistic evaluation of the system, the imperfections of channel estimations for different receiver designs of the SWIPT-based IoT systems have been taken into account. Subsequently, the closed-form expressions of the ergodic secrecy capacities for the considered scenario are provided and, then, validated through extensive simulations. The results indicate that an error ceiling appears due to imperfect channel estimation at high values of signal-to-noise ratio (SNR). More importantly, the secrecy capacity under different channel conditions stops increasing beyond a certain limit, despite an increase of the main link SNR. The in-depth analysis of secrecy-energy trade-off has also been performed and a comparison has been provided for imperfect and perfect channel estimation cases. As part of the continuous evolution of IoT networks, the results provided in this work can help in identifying the secrecy limits of IoT networks in the presence of multiple eavesdroppers.
The quest for finding a small-sized energy supply to run the small-scale wireless gadgets, with almost an infinite lifetime, has intrigued humankind since past several decades. In this context, the concept of Quantum batteries has come into limelight more recently to serve the purpose. However, the main issue revolving around the closed-system design of Quantum batteries is to ensure a loss-less environment, which is extremely difficult to realize in practice. In this paper, we present the modeling and optimization aspects of a Radio-Frequency (RF) Energy Harvesting (EH) assisted Quantum battery, wherein several EH modules (in the form of micro- or nano- sized integrated circuits (ICs)) help each of the involved Quantum sources achieve the so-called quasi-stable state. Specifically, a micro-controller manages the overall harvested energy from the RF-EH ICs and a photon emitting device, such that the emitted photons are absorbed by the electrons in the Quantum sources. In order to precisely model and optimize the considered framework, we formulate a transmit power minimization problem for an RF-based wireless system to optimize the number of RF-EH ICs under the given EH constraints at the Quantum battery-enabled wireless device. We obtain an analytical solution to the above-mentioned problem using a rational approach, while additionally seeking another solution obtained via a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results by taking a range of system parameters into account.
We consider the multiple-input multiple-output (MIMO) wiretap channel under a minimum receiver-side power constraint in addition to the usual maximum transmitter-side power constraint. This problem is motivated by energy harvesting communications with wireless energy transfer, where an added goal is to deliver a minimum amount of energy to a receiver in addition to delivering secure data to another receiver. In this paper, we characterize the exact secrecy capacity of the MIMO wiretap channel under transmitter and receiver-side power constraints. We first show that solving this problem is equivalent to solving the secrecy capacity of a wiretap channel with a double-sided correlation matrix constraint on the channel input. We show the converse by extending the channel enhancement technique to our case. We present two achievable schemes that achieve the secrecy capacity: the first achievable scheme uses a Gaussian codebook with a fixed mean, and the second achievable scheme uses artificial noise (or cooperative jamming) together with a Gaussian codebook. The role of the mean or the artificial noise is to enable energy transfer without sacrificing from the secure rate. This is the first instance of a channel model where either the use of a mean signal or use of channel prefixing via artificial noise is strictly necessary in the MIMO wiretap channel.