Search Results (140)

Multi-hop relaying can solve the problems of limited single-hop wireless communication distance, poor signal quality, or the inability to communicate directly by “relaying” data transmission through multiple intermediate nodes. It serves as the cornerstone for building large-scale, highly reliable, and self-adapting wireless networks, especially for the Internet of Things (IoT) and future 6G. This paper focuses on a decode-and-forward (DF) multi-hop relay network that employs simultaneous wireless information and power transfer (SWIPT) technology, with relays operating in a passive state. We first investigate the optimization of the power splitting (PS) ratio at each relay, given the source node transmit power, to maximize end-to-end network throughput. Subsequently, we jointly optimized the PS ratios and the source transmit power to minimize the source transmit power while satisfying the system’s minimum quality of service (QoS) requirement. Although both problems are non-convex, they can be reformulated as convex optimization problems. Closed-form optimal solutions are then derived based on the Karush–Kuhn–Tucker (KKT) conditions and a recursive method, respectively. Moreover, we find that the closed-form optimal solutions for the PS ratios corresponding to the two problems are identical. Through simulations, we validate that the performance of the two proposed schemes based on the closed-form solutions is optimal, while also demonstrating their extremely fast algorithm execution speeds, thereby proving the deployment value of the two proposed schemes in practical communication scenarios. Full article

Battery-Free Sensor Nodes (BFSNs) used in Simultaneous Wireless Information and Power Transfer (SWIPT) systems often rely on lightweight communication protocols with minimal security overhead due to strict energy constraints. As a result, conventional protocol-dependent security mechanisms cannot be employed, leaving BFSNs vulnerable to replay, spoofing, and other security threats. This paper explores a protocol-independent security mechanism that enhances BFSN security by exploiting the power wave for controlled backscattering. The method introduces a Manchester-encoded digital private key generated by the BFSN’s low-power microcontroller and backscattered through a polarization-shifting module enabled by a fail-safe RF switch, thereby avoiding the need for a dedicated backscattering rectifier. A LoRaWAN-based BFSN integrating this add-on module was implemented to experimentally validate the approach. Results show successful extraction of the backscattered key with minimal energy overhead (approximately 95 µJ for a 3 ms identification sequence), while the original high-efficiency RF rectifier used for harvesting remains unmodified. The orthogonal polarization between the incoming and backscattered waves additionally reduces clutter and cross-jamming effects. These findings demonstrate that secure identification can be seamlessly incorporated into existing BFSNs without altering their core architecture, offering an easy-to-integrate and energy-efficient solution for improving security in SWIPT-based sensing systems. Full article

In this work, a dual-band, dual-mode, circularly polarized fully woven textile antenna with capability for Simultaneous Wireless Information and Power Transfer (SWIPT) in wearable applications is presented. The power and the data transfer modes work at 2.4 and 5.4 GHz, respectively. The radiating element is based on a square patch with an asymmetrical U-shaped slot and a chamfered corner. A single-diode rectifier, required for the power transfer mode, is mounted on a carrier thread and then connected to the antenna through a T-match network located at one of the patch corners. This feeding technique simultaneously provides complex conjugate matching to the rectifier and circular polarization. On the other hand, a coaxial probe port is used for the data transfer mode. A prototype was implemented and experimentally characterized. Regarding the power transfer mode, the measured RF-DC conversion efficiency is about 50% when the available power at the rectifier input is −10 dBm, and the axial ratio is smaller than 3 dB. In the data transfer mode, the antenna gain and the axial ratio are 0 and 2 dB, respectively. The experimental results are in good agreement with simulations, validating the proposed structure and design methods, and they are comparable to the state of the art for textile antennas/rectennas. Furthermore, the combination of the fully woven technology and the proposed single-layer layout provides a large degree of integration and robustness, which are valuable characteristics for wearable devices. Full article

Simultaneous Wireless Information and Power Transfer (SWIPT) integrated with non-orthogonal multiple access (NOMA) offers a promising solution for energy-efficient Internet of Things (IoT) applications in the context of increasingly scarce spectrum resources. This paper addresses the energy efficiency (EE) maximization problem in a downlink cooperative SWIPT-NOMA network, where user cooperation is employed to mitigate the near-far effect and enhance network performance. We formulate the EE optimization problem for a multi-user scenario by jointly optimizing the transmission time, the power allocation ratio, and the transmission power of the near user in the cooperative SWIPT-NOMA network, and we propose a cooperative SWIPT-NOMA energy efficiency allocation algorithm. Firstly, the fractional programming problem for EE maximization is transformed into a more tractable form using the Dinkelbach method. Subsequently, the resource allocation variables are iteratively updated via variable substitution, successive convex approximation, and the Lagrangian dual method until the algorithm converges. Extensive simulations are conducted to evaluate the performance of the proposed algorithm under various conditions and to compare it with existing schemes. The proposed algorithm enhances network energy efficiency while ensuring user throughput, providing a more efficient resource allocation solution for wireless communication networks. Full article

The integration of movable antenna (MA) and reconfigurable intelligent surfaces (RIS) offers promising potential for enhancing simultaneous wireless information and power transfer (SWIPT) systems. In this paper, we investigate a novel MA-enabled RIS-assisted SWIPT framework, where both RIS and MA are jointly exploited to provide additional spatial degrees of freedom and reconfigurable propagation channels. Then, we formulate an energy harvesting maximization problem under communication reliability constraints by jointly optimizing the base station beamforming, RIS phase shifts, and MA positions. To tackle the proposed non-convexity problem, an efficient alternating optimization (AO) algorithm is developed, which is based on successive convex approximation (SCA) and second-order Taylor expansion. The obtained simulation outcomes reveal that incorporating MA into RIS-assisted SWIPT systems leads to notable performance gains over both conventional RIS schemes and fixed-antenna benchmarks. Full article

In new wireless ecosystems, simultaneous wireless information and power transfer (SWIPT) and cooperative non-orthogonal multiple access (CNOMA) together make a potential design model. These systems enhance spectral efficiency (SE), energy efficiency (EE), and data interchange reliability by combining energy harvesting (EH), superposition coding (SC), and relay-assisted transmission. Despite this, CNOMA’s energy efficiency is still constrained by the fact that relay nodes servicing multiple users require a significant amount of power. Most previous studies look at performance as if imperfect successive interference cancellation (SIC) were possible. To solve these problems, this study presents a multiuser SWIPT-enabled cooperative wavelet NOMA (CWNOMA) framework that reduces imperfect SIC, inter-symbol interference (ISI), and inter-user interference. SWIPT-CWNOMA enhances overall energy efficiency (EE), keeps relays functional, and maintains data transmission strong for users by obtaining energy from received signals. The proposed architecture is evaluated against traditional CNOMA and orthogonal multiple access (OMA) in both perfect and imperfect scenarios with SIC. The authors derive closed-form formulas for EE, signal-to-interference-plus-noise ratio (SINR), and achievable rate to support the analysis. Residual error because of imperfect SIC for near users shows lower values in a varying range of SNR. Across 0–30 dB SNR, SWIPT-CWNOMA achieves, on average, $1.4$ times higher energy efficiency, approximately $4.7$ lower BER, and $1.9$ times higher achievable rate than OFDMA, which establishes SWIPT-CWNOMA as a promising candidate for next-generation energy-efficient wireless networks. Full article

Low power consumption is critical for wireless communication, particularly for the Internet of Things (IoT) applications. Addressing these energy conservation requirements, 5G-Advanced (5G-A) introduces the Reduced Capability (RedCap) concept, incorporating techniques such as Discontinuous Reception (DRX), Extended DRX (eDRX), Wake-up Signal (WUS), and Wake-up Receiver (WUR). Nevertheless, there remains scope for further optimization. Focusing on improving energy efficiency for 5G-A and 6G, in this study we propose a simultaneous wireless information and power transfer (SWIPT) cooperative communication scheme leveraging environment backscattering and wake-up receiver technology, specifically designed to enhance the energy conservation performance of IoT devices and the energy efficiency of communication links, while extending the application scenarios for WUS. By establishing a backscattering system comprising a base station, a sensor equipped with a WUR module, and a receiving terminal, the system harvests both energy and information from ambient sources utilizing SWIPT technology. This approach reduces the sensor’s communication power consumption and formulates an energy efficiency optimization problem for the communication link, subject to constraints on base station transmit power and the power splitting ratio. This research ultimately maximizes communication link energy efficiency with WUS participation, satisfying current IoT energy conservation requirements and contributing significantly to the sustainable development of batteryless IoT and future communication networks. Full article

Unmanned aerial vehicles (UAVs) are a promising technology for future sixth-generation (6G) wireless networks. They are airborne vehicles that act either as as flying relays or base stations (BS) to provide the line-of-sight (LOS) transmission, enable wide-area coverage, and increase the spectral efficiency. In this work, a UAV is employed to forward information from the BS to distant users using a decode-and-forward (DF) protocol. The BS serves ground users through UAV by employing non-orthogonal multiple access (NOMA). The UAV relay will be wirelessly powered and harvests energy from the BS by applying a simultaneous wireless information and power transfer (SWIPT) technique. To further improve overall performance, the near user will act as a full-duplex (FD) relay to forward the far user’s information by applying cooperative non-orthogonal multiple access (C-NOMA). The proposed scheme considers a practical detection order using a feasible successive interference cancellation (SIC) operation. Additionally, a relay power control method is introduced for the near user to guarantee a reliable cooperative link. In the proposed scheme, a low-complexity closed-form power allocation is derived to maximize the minimum achievable rate. Numerical results demonstrate that the power allocation scheme significantly improves the far user’s rate performance, and the proposed scheme guarantees a higher target rate and outperforms the conventional NOMA, half-duplex (HD) C-NOMA, and FD C-NOMA with fixed power allocation (FPA) and fractional transmit power allocation (FTPA) schemes. Full article

This paper presents an analytical framework for the channel capacity evaluation of simultaneous wireless information and power transfer (SWIPT)-enabled opportunistic amplify-and-forward (OAF) relaying systems over Rayleigh fading channels. For the SWIPT, we employ a power splitter (PS) at the relay, which splits the received signal into the information transmission and the energy-harvesting parts. By modeling the partial channel state information (P-CSI)-based SWIPT OAF system as an equivalent non-SWIPT OAF configuration, a semi-lower bound and a new upper bound on the ergodic channel capacity are derived. A refined approximation is then obtained by averaging these bounds, yielding a simple yet accurate analytical estimate of the true capacity. Simulation results confirm that the proposed approximations closely track the actual performance across a wide range of signal-to-noise ratios (SNRs) and relay configurations. They further demonstrate that SR-based relay selection provides higher capacity than RD-based selection, primarily due to its direct influence on energy harvesting efficiency at the relay. In addition, diversity advantages manifest mainly as SNR improvements, rather than as gains in diversity order. The proposed framework thus serves as a practical and insightful tool for the capacity analysis and design of SWIPT-enabled cooperative networks, with direct relevance to energy-constrained Internet of Things (IoT) and wireless sensor applications. Full article

This paper investigates a simultaneous wireless information and power transfer (SWIPT) decode-and-forward (DF) relay network, where a source node transmits data to a destination node through the assistance of multi-hop passive relays. We employ the time-switching (TS) protocol, enabling the relays to harvest energy from the received previous hop signal to support data forwarding. We first prove that the system throughput monotonically increases with the transmit power of the source node. Next, by employing logarithmic transformations, we convert the non-convex problem of obtaining optimal TS ratios at each relay to maximize the system throughput into a convex optimization problem. Comprehensively taking into account the convergence rate, computational complexity per iteration, and robustness, we selected the log barrier method—a type of interior point method—to address this convex optimization problem, along with providing a detailed implementation procedure. The simulation results validate the optimality of the proposed method and demonstrate its applicability to practical communication systems. For instance, the proposed scheme achieves 1437.3 bps throughput at 40 dBm maximum source power in a 2-relay network—278.6% higher than that of the scheme with TS ratio fixed at 0.75 (379.68 bps). On the other hand, it converges within a 1.36 ms computation time for 5 relays, 6 orders of magnitude faster than exhaustive search (1730 s). Full article

The transfer-efficient power allocation problem for downlink simultaneous wireless information and power transfer (SWIPT) is investigated in massive multiple-input multiple-output (MIMO) systems in this paper. In the considered system, the base station (BS) equipped with a large number of antennas simultaneously transmits information and sends energy signals to multiple information and energy terminals equipped with a single antenna. The aim is to maximize transfer efficiency while meeting quality-of-service (QoS) requirements for all terminals. First, the closed-form expressions of achievable rates for each information terminal and the harvested energy for each energy terminal are obtained. Then, two optimization problems are formulated according to the obtained expressions, with the purpose of maximizing information transfer efficiency (ITE) and energy transfer efficiency (ETE). The maximizations of ITE and ETE are fractional programming problems and are difficult to solve directly. For this reason, the iterative optimization algorithm is proposed to solve the ITE maximization problem by transforming it into a subtractive form and then utilizing a successive convex approximation (SCA) method. Following a similar approach, another iterative optimization algorithm is proposed to solve the ETE maximization problem by transforming it into a subtractive form and then utilizing a linear programming method. Finally, numerical results demonstrate that the two iterative optimization algorithms can achieve good ITE and ETE, and we also reveal the trade-off between them in this work. Full article

This paper investigates the error rate performance of simultaneous wireless information and power transfer (SWIPT) systems employing opportunistic amplify-and-forward (OAF) relaying under Rayleigh fading conditions. To support both data forwarding and energy harvesting at relays, a power splitting (PS) mechanism is applied. We derive exact and asymptotic symbol error rate (SER) expressions using moment-generating function (MGF) methods, providing analytical insights into how the power splitting ratio $\rho$ and the quality of source–relay (SR) and relay–destination (RD) links jointly affect system behavior. Additionally, we propose a novel approximation that interprets the SWIPT-OAF configuration as an equivalent non-SWIPT OAF model. This enables tractable performance analysis while preserving key diversity characteristics. The framework is extended to include scenarios with partial channel state information (CSI) and $N_{\mathrm{th}}$ best relay selection, addressing practical concerns such as limited relay availability and imperfect decision-making. Extensive simulations validate the theoretical analysis and demonstrate the robustness of the proposed approach under a wide range of signal-to-noise ratio (SNR) and channel conditions. These findings contribute to a flexible and scalable design strategy for SWIPT-OAF relay systems, making them suitable for deployment in emerging wireless sensor and internet of things (IoT) networks. Full article

Terahertz (THz) communications and simultaneous wireless information and power transfer (SWIPT) hold the potential to energize battery-less Internet-of-Things (IoT) devices while enabling multi-gigabit data transmission. However, severe path loss, blockages, and rectifier nonlinearity significantly hinder both throughput and harvested energy. Additionally, high-power THz beams pose safety concerns by potentially exceeding specific absorption rate (SAR) limits. We propose a sensing-adaptive power-focusing (APF) framework in which a reconfigurable intelligent surface (RIS) embeds low-rate THz sensors. Real-time backscatter measurements construct a spatial map used for the joint optimisation of (i) RIS phase configurations, (ii) multi-tone SWIPT waveforms, and (iii) nonlinear power-splitting ratios. A weighted MMSE inner loop maximizes the data rate, while an outer alternating optimisation applies semidefinite relaxation to enforce passive-element constraints and SAR compliance. Full-stack simulations at 0.3 THz with 20 GHz bandwidth and up to 256 RIS elements show that APF (i) improves the rate–energy Pareto frontier by 30–75% over recent adaptive baselines; (ii) achieves a 150% gain in harvested energy and a 440 Mbps peak per-user rate; (iii) reduces energy-efficiency variance by half while maintaining a Jain fairness index of 0.999;; and (iv) caps SAR at 1.6 W/kg, which is 20% below the IEEE C95.1 safety threshold. The algorithm converges in seven iterations and executes within <3 ms on a Cortex-A78 processor, ensuring compliance with real-time 6G control budgets. The proposed architecture supports sustainable THz-powered networks for smart factories, digital-twin logistics, wire-free extended reality (XR), and low-maintenance structural health monitors, combining high-capacity communication, safe wireless power transfer, and carbon-aware operation for future 6G cyber–physical systems. Full article

Federated edge learning (FEEL) is an innovative approach that facilitates collaborative training among numerous distributed edge devices while eliminating the need to transfer sensitive information. However, the practical deployment of FEEL faces significant constraints, owing to the limited and asymmetric computational and communication resources of these devices, along with their energy availability. To this end, we propose a novel asymmetry-tolerant training approach for FEEL, enabled via simultaneous wireless information and power transfer (SWIPT). This framework leverages SWIPT to offer sustainable energy support for devices while enabling them to train models with varying intensities. Given a limited energy budget, we highlight the critical trade-off between heterogeneous local training intensities and the quality of wireless transmission, suggesting that the design of local training and wireless transmission should be closely integrated, rather than treated as separate entities. To elucidate this perspective, we rigorously derive a new explicit upper bound that captures the combined impact of local training accuracy and the mean square error of wireless aggregation on the convergence performance of FEEL. To maximize overall system performance, we formulate two key optimization problems: the first aims to maximize the energy harvesting capability among all devices, while the second addresses the joint learning–communication optimization under the optimal energy harvesting solution. Comprehensive experiments demonstrate that our proposed framework achieves significant performance improvements compared to existing baselines. Full article

This paper presents an analytical study of the bit error rate (BER) and signal-to-noise ratio (SNR) performance in simultaneous wireless information and power transfer (SWIPT) amplify-and-forward (AF) relaying systems over Rayleigh fading channels. A power-splitting (PS) protocol is employed at the energy-constrained relay to divide the received signal for concurrent energy harvesting and information processing. Closed-form and asymptotic BER expressions are derived based on exact and bounded moment-generating functions (MGFs), offering insights into how the SNR balance between the source–relay (SR) and relay–destination (RD) links influences system performance. An asymptotic BER expression further reveals that a SWIPT AF relay system can be interpreted as a generalized AF relaying model, sharing the same diversity order as conventional AF systems. Based on this interpretation, an optimization method for the PS factor is proposed, effectively reducing the BER by reinforcing the weaker link. Simulation results confirm the tightness of the derived expressions and the effectiveness of the optimization strategy. Moreover, the analytical framework is extended to multiple SWIPT relaying systems, where multiple relays operate with individually optimized PS ratios. For such configurations, approximations for the system BER, outage probability, and channel capacity are derived and validated. Results demonstrate that increasing the number of relays significantly improves system performance, and the proposed analysis accurately captures these performance gains under varying channel conditions. Full article