Unified receivers (URs) have emerged as a promising architecture for simultaneous wireless information and power transfer (SWIPT), since a common rectifying front-end enables information decoding (ID) and energy harvesting (EH) from the same rectified output. However, rectification is nonlinear due to the diode, while the capacitor introduces memory across symbols, making constellation design over the channel challenging. In this paper, we study constellation design for nonlinear UR-SWIPT channels in both memoryless and memory regimes. First, we propose a tractable unified rectification model that captures both (i) the nonlinear steady-state mapping and (ii) the asymmetric capacitor charging/discharging dynamics under transient operation. To isolate the impact of rectification with memory on ID, we study the information-based design. In this setting, we develop a state-adaptive policy with an algorithmic constellation design that accounts for the rectifier state and shapes the constellation in the observation domain. By approximating the rectifier state distribution, we derive a closed-form average symbol error rate (SER) expression and characterize the rate-reliability (R-R) tradeoff. We then seek constellations that minimize the SER under average transmit power and EH constraints. We address the resulting energy-constrained setting in the memoryless regime using an autoencoder-based framework that embeds the nonlinear rectification model as a differentiable channel block. Numerical results validate the proposed models, demonstrate the impact of memory on the R-R tradeoff, and show how learned constellations adapt to EH requirements in the rate-energy tradeoff.

Movable antenna arrays are a new paradigm that offers enhanced performance to future wireless systems. Compared to a fixed array, the flexibility and reconfigurability of a movable antenna array enables better performance in detecting signals with multiple carrier frequencies and from various directions. The Rydberg atomic sensor is another emerging optical technology that is sensitive to radio frequency (RF) signals. Capitalizing on its portability and the ability to detect signals with multiple carrier frequencies, the Rydberg sensor is a promising device for movable arrays. As the first paper to study the combination of atomic sensors and movable antenna arrays, we propose two new algorithms (golden-Search algorithm and basic firefly algorithm) to control the design of a two-dimensional (2-D) movable Rydberg sensor array. In addition, we also propose the novel boost-firefly method to enhance the design of two or more subarrays for decoding different carrier frequencies simultaneously. Simulation results reveal that the proposed algorithms can achieve better performance for both single array and multiple subarray designs compared to fixed array and randomly-designed array benchmarks.

In this paper, we propose a lightwave power transfer-enabled underwater optical integrated sensing and communication (O-ISAC) system, where an access point (AP) mounted on a seasurface ship transmits lightwave signals to two nodes, namely (i) a seabed sensor that harvests energy and transmits uplink information to the AP, and (ii) a sensing target whose position is estimated by the AP using an array of pinhole cameras. To capture practical deployment conditions, the ship attitude variation is modeled through its roll, pitch, and yaw angles, each following a Gaussian distribution under low-to-moderate sea states. Closed-form approximations are derived for the mean squared error (MSE) of target localization and the achievable uplink data rate. Analytical and simulation results demonstrate excellent agreement, validating the proposed models and derived expressions, while revealing the fundamental communication-sensing tradeoff in the O-ISAC system. The results further provide valuable design insights, including the optimal camera placement on the ship to minimize localization error, achieving a minimum MSE of 10^-2 m^2 with multiple cameras under roll, pitch, and yaw angle variation of 10^∘, and the optimal harvest-use ratio of 0.55 for the considered setup.

In this study, we explore a terahertz (THz) wireless power transfer (WPT) system. Since traditional Schottky diodes may be inefficient for THz rectification, we focus on a resonant tunneling diode (RTD)-based rectifier. Such rectifiers are generally characterized by a non- monotonic energy harvesting (EH) behavior, where an increase in input power may not necessarily correspond to higher levels of harvested power. To this end, we propose the exploitation of fluid antennas (FAs) to align the non- monotonic rectification of RTDs with favorable channel realizations. More specifically, a generalized piecewise linear function is adopted in order to approximate the instantaneous input-output power relationship. Based on this, we derive an analytical framework in terms of the energy outage probability and the average harvested power for three FA port selection policies, namely (i) the input-based selection, (ii) the harvesting-based selection, and (iii) the random selection, each corresponding to different performance. The impact of channel estimation errors on the port selection strategies is then examined, revealing a trade-off between the number of estimated ports and harvested power. To further improve EH performance, we introduce a new receiver architecture featuring a power splitter, multiple RTD-based EH circuits and a DC combiner. Based on this, we provide two dynamic power splitting schemes tailored to avoid inefficient rectification regions. Numerical results which validate our analysis, reveal a novel utilization of FAs, stemming from the alignment of the port selection process with the non- monotonic harvesting characteristics. Finally, our findings demonstrate that the proposed receiver architecture can yield significant gains in harvested power.

Quantum key distribution (QKD) is a potential technology suitable for fulfilling the stringent requirements of upcoming 6G wireless networks in terms of privacy and security. Nevertheless, QKD systems have several practical limitations in terms of hardware design and implementation, making them vulnerable to malicious attacks. Specifically, we adopt a detection scheme using a single-photon avalanche diode and due to the avalanche effect, a secondary photon is emitted, called backflash, which can be captured by an eavesdropper. To mitigate this security loophole and enhance the secrecy performance, we consider a selection mechanism which schedules a single user for secret key exchange purposes. In particular, we propose an intelligent two-stage selection scheme in a multiuser free-space optical QKD deployment. We derive closed-form expressions for the secrecy success probability by considering a generalized pointing error model. Our results confirm that the proposed scheme yields significant secrecy gains over conventional methods.

In this paper, we propose a novel simultaneous wireless information and power transfer (SWIPT) technique that employs orthogonal frequency-division multiplexing (OFDM)-based waveforms. The proposed scheme jointly designs particular characteristics of the waveform, in such a way as to enable efficient energy harvesting (EH) and low-complexity information transmission. Specifically, information is embedded into two dimensions by modulating the peak-to-average-power-ratio and the position of the power peak. The receiver relies on an integrated circuit architecture that utilizes a low-complexity envelope detector for the information decoding process. We propose two low-complexity suboptimal detection rules and additionally consider maximum likelihood detection. The performance of the proposed technique is approximately evaluated in terms of the symbol error probability and average harvested power. We show that the tradeoff between rate and energy in terms of parameters that arises can be controlled accordingly to achieve diverse requirements in terms of EH and/or information transfer. The presented approach transforms conventional OFDM transmitters to SWIPT devices without costly architectural modifications, thus making it appropriate for practical applications.

Due to their low-complexity and energy-efficiency, unified simultaneous wireless information and power transfer (U-SWIPT) receivers are especially suitable for low-power Internet of Things (IoT) applications. Towards accurately modeling practical operating conditions, in this study, we provide a unified transient framework for a dual-diode U-SWIPT that jointly accounts for diode nonlinearity and capacitor-induced memory effects. The proposed model accurately describes the inherent time dependence of the rectifier, highlighting its fundamental impact on both energy harvesting (EH) and information decoding (ID) processes. Based on the provided memory-aware model, we design a low-complexity adaptive detector that learns the nonlinear state transition dynamics and performs decision-directed detection with linear complexity. The proposed detection scheme approaches maximum likelihood sequence detection (MLSD) performance in memory-dominated regimes, while avoiding the exponential search required by classical sequence detection. Overall, these results demonstrate that properly exploiting rectifier memory provides a better tradeoff between data rate and reliability for U-SWIPT receivers.

This letter proposes the integration of on-off digital noise (OODN) modulation with fluid antenna systems (FASs). A unified analytical framework is developed to evaluate the performance of FAS- assisted OODN receivers over additive white Gaussian noise and generalized ąp̨p̨ą-μ fading channels. The analysis incorporates fluid antenna port selection, the number of available ports, and spatial correlation. Analytical expressions for the average bit error probability are derived and the achievable diversity order is characterized. All expressions are validated through Monte Carlo simulations. Results demonstrate that the spatial diversity provided by the FAS significantly enhances the reliability of OODN transmissions while preserving their inherent low-complexity, non-coherent operation without carrier-phase recovery. The proposed framework establishes a new research direction for energy-efficient Internet of Things (IoT) and machine-type communication systems.

Unified receivers (URs) for simultaneous wireless information and power transfer (SWIPT) exploit rectified signals to perform both information decoding (ID) and energy harvesting (EH). This work investigates amplitude constellation designs, tailored for UR-SWIPT architectures, that jointly optimize ID reliability and EH efficiency. The nonlinear behavior of rectifying circuits, however, makes optimal constellation design analytically intractable. We address this by modeling the UR-SWIPT link as an autoencoder, allowing us to learn constellations that minimize symbol error rate while satisfying average transmit power and EH constraints. Towards optimizing decoding accuracy, we further present an algorithmic approach that pre-compensates for the rectifier nonlinearities and yields the optimal information-only constellation. Numerical results validate the efficacy of the proposed framework, demonstrating its adaptability across various energy requirements and operating power levels. The learned constellations consistently outperform conventional modulation schemes and approach near-optimal rate-energy tradeoff. A key feature is a high-amplitude symbol, enabling the system to meet the EH requirements while allowing for reliable decoding.

This paper investigates the performance of tunable liquid lens (TLL)-assisted receivers in large-scale visible light communication (VLC) systems under random receiver orientation. A simple electrowetting-based TLL architecture is proposed, capable of dynamically steering the incident optical signal toward the photodiode receiver by adjusting the orientation of the liquid interface. The proposed architecture enhances the desired signal reception while mitigating interference from neighboring access points (APs). The spatial distribution of APs is modeled using a Matérn hard-core point process, whereas receiver orientation is characterized by uniformly distributed azimuth angles and Gaussian-distributed polar angles. Furthermore, a tractable mathematical optical channel model is developed to capture the combined effects of AP/receiver locations, receiver orientation, and lens adjustment angles on the VLC channel gain. Based on this framework, three lens orientation strategies, namely best signal reception (BSR), closest LED selection, and vertical upward lens orientation, are proposed to improve system performance under dynamic receiver conditions. Using stochastic geometry tools, exact and approximate analytical expressions for the outage probability are derived for each scheme. Numerical results verify the accuracy of the developed analysis and demonstrate that the proposed TLL-assisted receiver architecture significantly improves the robustness of VLC systems under severe receiver orientation fluctuations and dense AP deployments. In particular, the BSR scheme reduces the outage probability by $57.1\%$ compared with conventional fixed-lens receivers at an AP height of $3.5$ m and AP density of $0.2~\text{m}^{-2}$. The presented analytical framework and numerical results provide useful design insights for the deployment of future TLL-assisted VLC networks.

In this letter, we investigate the design of chaotic signal-based transmit waveforms in a multi-functional reconfigurable intelligent surface (MF-RIS)-aided set-up for simultaneous wireless information and power transfer. We propose a differential chaos shift keying-based MF-RIS-aided set-up, where the MF-RIS is partitioned into three non-overlapping surfaces. The elements of the first sub-surface perform energy harvesting (EH), which in turn, provide the required power to the other two sub-surfaces responsible for transmission and reflection of the incident signal. By considering a frequency selective scenario and a realistic EH model, we characterize the chaotic MF-RIS-aided system in terms of its EH performance and the associated bit error rate. Thereafter, we characterize the harvested energy-bit error rate trade-off and derive a lower bound on the number of elements required to operate in the EH mode. Accordingly, we propose novel transmit waveform designs to demonstrate the importance of the choice of appropriate system parameters in the context of achieving self-sustainability.

The majority in existing energy harvesting (EH) models utilize complex analysis and often overlook the memory effects of the system’s low-pass filter (LPF). In this work, we aim to fill this gap and propose a simple yet effective approach to model the receiver’s output and capture the LPF’s memory. Specifically, we analyze two fundamental circuits: the half-wave rectifier (HWR) and the diplexer-based receiver (DBR). By using circuit analysis, we derive mathematical models for each receiver’s output, validated through circuit simulations. We then investigate these models in the context of integrated simultaneous wireless information and power transfer (SWIPT) receivers. For the HWR, we consider amplitude modulation and, using communication theory tools, we evaluate the performance in terms of bit error rate (BER) for both maximum likelihood (ML) and ML sequence detection (MLSD) schemes. Our results reveal the impact of memory-induced intersymbol interference on the BER and indicate that MLSD is necessary towards achieving higher data rates. For the DBR, we show that its LPF exhibits similar characteristics to the HWR yet is able to achieve better EH performance due to the lack of signal splitting. Finally, we explore the DBR’s band-pass filter output for information decoding, highlighting its capability to also use phase modulation. Clearly the DBR stands out as a more flexible receiver, while the HWR’s simple design makes it ideal for devices with limited resources.

Reconfigurability is a desired characteristic of future communication networks. From a transceiver’s standpoint, this can be materialized through the implementation of fluid antennas (FAs). An FA consists of a dielectric holder, in which a radiating liquid moves between pre-defined locations (called ports) that serve as the transceiver’s antennas. Due to the nature of liquids, FAs can practically take any size and shape, making them both flexible and reconfigurable. In this paper, we deal with the outage probability of FAs under general fading channels, where a port is scheduled based on selection combining. An analytical framework is provided for the performance with and without errors due to post-scheduling delays. We show that although FAs achieve maximum diversity, this cannot be realized in the presence of delays. Hence, a linear prediction scheme is proposed that overcomes delays and restores the lost diversity by predicting the next scheduled port. Moreover, we design space-time coded modulations that exploit the FA’s sequential operation with space-time rotations and code diversity. The derived expressions for the pairwise error probability and average word error rate give an accurate estimate of the performance. We illustrate that the proposed design attains maximum diversity, while keeping a low-complexity receiver, thereby confirming the feasibility of FAs.

In this paper, we study the fundamental limits of simultaneous semantic information and power transfer in wireless networks, where we consider both the point-to-point case as well as the Gaussian multiple access channel (MAC). Specifically, for the point-to-point case, we consider a three-party communication system, where a transmitter aims to simultaneously convey semantic information to an information receiver and energy to an energy harvesting receiver (ER). An achievable and a converse region in terms of information and energy rates are presented for both the discrete memoryless (DM) and Gaussian channel. For the DM channel, the achievable region is obtained by utilizing the asymptotic equipartition property and a converse region is obtained by using outer bounds on the semantic information rates. For the Gaussian channel, we characterize an achievable region by applying a power splitting technique between the information and the semantic context parts. A converse region is obtained that provides an estimate on the information-energy capacity while taking into account semantics. On the other hand, for the Gaussian MAC case, we consider an hybrid setup where a semantic transmitter and a conventional transmitter are employed subject to an energy harvesting constraint at the ER. Specifically, we characterize the semantic-bit information energy region, by providing an achievable and a converse region. Numerical results show that in both cases a higher performance can be achieved in terms of information and energy rates when considering a low semantic ambiguity code in comparison to the classical coding scheme (without semantic). Moreover, in the context of Gaussian MAC, it is shown that it is preferable to use semantic communications in scenarios with low signal-to-noise ratio (SNR), while conventional communications is more suitable at high SNRs.

As wireless communication systems continue to grow rapidly, high-performance antennas become increasingly crucial for expanding coverage, improving capacity, and enhancing transmission quality. In light of this, research has focused considerable attention on liquid antennas due to their unique characteristics, which include small size, flexibility, reconfigurability and transparency. Recently, graphene liquid has been explored for numerous applications due to its low cost, high conductivity, flexibility, and ease of processing. Specifically for antenna applications, graphene liquid performs better than conventional liquid metal. This paper presents a graphene-liquid antenna with beam reconfiguration ability for sub-6 GHz communication system. The graphene-liquid movement within the microfluidic channel is taken into consideration by the reconfiguration mechanism. The antenna achieves beam reconfiguration in 360° directions with 6 dBi of gain at 5.5 GHz, featuring a wideband impedance bandwidth of 24

In this paper, we investigate a new index modulation (IM) scheme for reconfigurable intelligent surface (RIS)-assisted communications with 1-bit RIS phase resolution. In addition to the traditional modulated symbols, extra bits of information are embedded in the binary RIS phase vector by indexing the cardinality of the positive phases shifts. To maximize capacity, the IM-based RIS vector is selected so as to maximize the signal-to-noise ratio at the receiver. The proposed IM design requires the solution of a quadratic binary optimization problem with an equality constraint at the transmitter as well as a quadratic unconstrained binary optimization (QUBO) problem at the receiver. Since commercial solvers cannot directly handle constraints, a penalty method that embeds the equality constraint in the objective function is investigated. To overcome the empirical tuning of the penalty parameter, an iterative Augmented Lagrangian optimization technique is also investigated where a QUBO problem is solved at each iteration. The proposed design and associated mathematical framework are tested in a real-world quantum annealing device provided by D-WAVE. Rigorous experimental results demonstrate that the D-WAVE heuristic efficiently solves the considered combinatorial problems. Furthermore, theoretical bounds on the average capacity are provided. Both experimental and theoretical results show that the proposed design outperforms conventional counterparts.

In this work, an integrated communication, sensing and power transfer (ICSPT) system is investigated, which is assisted by the employment of an unmanned aerial vehicle (UAV) acting as a base station. Under this system, the optimization of the UAV trajectory is studied for limited battery lifetime, so that the weighted sensing signal-to-noise ratio (SNR), communication SNR and harvested power is maximized subject to the service area and flight duration constraints. A general and flexible theoretical framework is proposed for the solution of the formulated optimization problem, based on tools from reinforcement learning (RL), that models the considered ICSPT system as a Markov decision process (MDP). In order to solve the developed MDP, a novel model-free algorithm is provided based on the Q-learning method. We show, through numerical simulation results, the validity of the proposed framework and its superiority compared to other benchmark scenarios that consider a fixed UAV trajectory or random UAV movements.

This paper investigates the problem of transmit waveform design in the context of a chaotic signal-based self-sustainable reconfigurable intelligent surface (RIS)-aided system for simultaneous wireless information and power transfer (SWIPT). Specifically, we propose a differential chaos shift keying (DCSK)-based RIS-aided point-to-point set-up, where the RIS is partitioned into two non-overlapping surfaces. The elements of the first sub-surface perform energy harvesting (EH), which in turn, provide the required power to the other sub-surface operating in the information transfer (IT) mode. In this framework, by considering a generalized frequency-selective Nakagami-m fading scenario as well as the nonlinearities of the EH process, we derive closed-form analytical expressions for both the bit error rate (BER) at the receiver and the harvested power at the RIS. Our analysis demonstrates, that both these performance metrics depend on the parameters of the wireless channel, the transmit waveform design, and the number of reflecting elements at the RIS, which switch between the IT and EH modes, depending on the application requirements. Moreover, we show that, having more reflecting elements in the IT mode is not always beneficial and also, for a given acceptable BER, we derive a lower bound on the number of RIS elements that need to be operated in the EH mode. Furthermore, for a fixed RIS configuration, we investigate a trade-off between the achievable BER and the harvested power at the RIS and accordingly, we propose appropriate transmit waveform designs. Finally, our numerical results illustrate the importance of our intelligent DCSK-based waveform design on the considered framework.

Chaotic dynamical systems have attracted considerable attention due to their inherent randomness and high sensitivity to initial conditions, which makes them ideal for secure wireless communications. Beyond security, these same characteristics also make chaotic signals particularly effective for wireless power transfer (WPT) applications. On the other hand, connectivity along with self-sustainability are the two cornerstones of the upcoming sixth generation (6G) standard for radio communications. Consequently, with the massive increase in wireless devices and sensors, the concept of self-sustainable wireless networks is becoming more relevant. The aspect of WPT to the widely spread wireless devices and simultaneous wireless information and power transfer (SWIPT) among these devices will play a crucial role in the 6G communication systems. In this context, it has been experimentally observed that chaotic signals result in better WPT performance as compared to the existing benchmark schemes. Hence, in this paper, we characterize the generalized WPT performance of the multi-dimensional chaotic signals and present the use case of the Lorenz and the Henon chaotic systems. Moreover, we provide a novel differential chaos shift keying (DCSK)-based WPT receiver architecture ideal for enhanced energy harvesting (EH). Furthermore, we propose DCSK-based transmit waveform designs for multi-antenna SWIPT architectures and investigate the impact of the rate-energy trade-off. Our goal is to explore these aspects of the chaotic signals and discuss their relevance in the context of both WPT and SWIPT.

This paper presents a tunable liquid lens (TLL)-assisted indoor mobile visible light communication system. To mitigate performance degradation caused by user mobility and random receiver orientation, an electrowetting cuboid TLL is used at the receiver. By dynamically controlling the orientation angle of the liquid surface through voltage adjustments, signal reception and overall system performance are enhanced. An accurate mathematical framework is developed to model channel gains, and two lens optimization strategies, namely (i) the best signal reception (BSR), and (ii) the vertically upward lens orientation (VULO) are introduced for improved performance. Closed form expressions for the outage probability are derived for each scheme for practical mobility and receiver orientation conditions. Numerical results demonstrate that the proposed TLL and lens adjustment strategies significantly reduce the outage probability compared to fixed lens and no lens receivers across various mobility and orientation conditions. Specifically, the outage probability is improved from 1× 10^-1 to 3× 10^-3 at a transmit power of 12 dBW under a 8^∘ polar angle variation in random receiver orientation using the BSR scheme.