Rectenna System Development Using Harmonic Balance and S-Parameters for an RF Energy Harvester.

With the escalating demand for Radio Frequency Identification (RFID) technology and the Internet of Things (IoT), there is a growing need for sustainable and autonomous power solutions to energize low-powered devices. Consequently, there is a critical imperative to mitigate dependency on batteries during passive operation. This paper proposes the conceptual framework of rectenna architecture-based radio frequency energy harvesters' performance, specifically optimized for low-power device applications. The proposed prototype utilizes the surroundings' Wi-Fi signals within the 2.4 GHz frequency band. The design integrates a seven-stage Cockroft-Walton rectifier featuring a Schottky diode HSMS286C and MA4E2054B1-1146T, a low-pass filter, and a fractal antenna. Preliminary simulations conducted using Advanced Design System (ADS) reveal that a voltage of 3.53 V can be harvested by employing a 1.57 mm thickness Rogers 5880 printed circuit board (PCB) substrate with an MA4E2054B1-1146T rectifier prototype, given a minimum power input of -10 dBm (0.1 mW). Integrating the fabricated rectifier and fractal antenna successfully yields a 1.5 V DC output from Wi-Fi signals, demonstrable by illuminating a red LED. These findings underscore the viability of deploying a fractal antenna-based radio frequency (RF) harvester for empowering small electronic devices.

Artificial Intelligence-Assisted RFID Tag-Integrated Multi-Sensor for Quality Assessment and Sensing.

Radio frequency identification (RFID) is well known as an identification, track, and trace approach and is considered to be the key physical layer technology for the industrial internet of things (IIoT). However, IIoT systems have to introduce additional complex sensor networks for pervasive monitoring, and there are still challenges related to item-level sensing and data recording. To overcome the shortage, this work proposes an artificial intelligence (AI)-assisted RFID-based multi-sensing technology. Both passive and semi-passive RFID tag-integrated multi-sensors are developed. The main contributions and the novelty of this investigation are as follows. A UHF RFID tag-integrated multi-sensor with a boosted charge pump is proposed; it enables high RF signal sensitivity and a long operational range. The whole hardware design, including the antenna and energy harvester, are studied. Moreover, a demonstration with real-world ham product sensing data is conducted. This work also proposes and successfully demonstrates the integration of machine learning algorithms, specifically the NARX neural network, with RFID sensing data for food product quality assessment and sensing (QAS). This application of machine learning to RFID-generated data for quality assessment is also a novel aspect of the research. The deployment of an autoregressive model with an exogenous input (NARX) neural network model, tailored for nonlinear processes, emerges as the most effective, achieving a root mean square error (RMSE) of 0.007 and an R-squared value of 0.99 for ham product QAS. By deploying the technology, low-cost, timely, and flexible product QAS can be achieved in manufacturing industries, which helps product quality improvement and the optimization of the manufacturing line and supply chain.

A High-Performance Circularly Polarized and Harmonic Rejection Rectenna for Electromagnetic Energy Harvesting.

This paper presents a novel circularly polarized rectenna designed for efficient electromagnetic energy harvesting at the 2.45 GHz ISM band. A compact antenna structure is designed to achieve high performance in terms of radiation efficiency, axial ratio, directivity, effective area, and harmonic rejection over the entire bandwidth of the ISM frequency band. The optimized rectifier circuit enhances the RF harvested energy efficiency, with an AC-to-DC conversion efficiency ranging from 36% to 70% for low-level input power ranging from -10 dBm to 0 dBm. The stable output of DC power confirms the suitability of this design for various practical applications, including wireless sensor networks, energy harvesting power supplies, medical implants, and environmental monitoring systems. Experimental validation, which includes both the reflection coefficient and radiation patterns of the designed antenna, confirms the accuracy of the simulation. The study found that the proposed energy harvesting system has a high total efficiency ranging from 53% to 63% and is well-suited for low-power energy harvesting (0 dBm) from ambient electromagnetic radiation. The proposed circularly polarized rectenna is a competitive option for efficient electromagnetic energy harvesting, both as a standalone unit and in an array, due to its high performance, feasibility, and versatility in meeting various energy harvesting requirements. This makes it a promising and cost-effective solution for various wireless communication applications, offering great potential for efficient energy harvesting from ambient electromagnetic radiation.

A Compact RF Energy Harvesting Wireless Sensor Node with an Energy Intensity Adaptive Management Algorithm.

This paper presents a compact RF energy harvesting wireless sensor node with the antenna, rectifier, energy management circuits, and load integrated on a single printed circuit board and a total size of 53 mm × 59.77 mm × 4.5 mm. By etching rectangular slots in the radiation patch, the antenna area is reduced by 13.9%. The antenna is tested to have an S11 of -24.9 dB at 2.437 GHz and a maximum gain of 4.8 dBi. The rectifier has a maximum RF-to-DC conversion efficiency of 52.53% at 7 dBm input energy. The proposed WSN can achieve self-powered operation at a distance of 13.4 m from the transmitter source. To enhance the conversion efficiency under different input energy densities, this paper establishes an energy model for two operating modes and proposes an energy-intensity adaptive management algorithm. The experiments demonstrated that the proposed WSN can effectively distinguish between the two operating modes based on input energy intensity and realize efficient energy management.

Design of a High-Efficiency DC-DC Boost Converter for RF Energy Harvesting IoT Sensors.

In this paper, an optimal design of a high-efficiency DC-DC boost converter is proposed for RF energy harvesting Internet of Things (IoT) sensors. Since the output DC voltage of the RF-DC rectifier for RF energy harvesting varies considerably depending on the RF input power, the DC-DC boost converter following the RF-DC rectifier is required to achieve high power conversion efficiency (PCE) in a wide input voltage range. Therefore, based on the loss analysis and modeling of an inductor-based DC-DC boost converter, an optimal design method of design parameters, including inductance and peak inductor current, is proposed to obtain the maximum PCE by minimizing the total loss according to different input voltages in a wide input voltage range. A high-efficiency DC-DC boost converter for RF energy harvesting applications is designed using a 65 nm CMOS process. The modeled total losses agree well with the circuit simulation results and the proposed loss modeling results accurately predict the optimal design parameters to obtain the maximum PCE. Based on the proposed loss modeling, the optimally designed DC-DC boost converter achieves a power conversion efficiency of 96.5% at a low input voltage of 0.1 V and a peak efficiency of 98.4% at an input voltage of 0.4 V.

A Capacitive DC-DC Boost Converter with Gate Bias Boosting and Dynamic Body Biasing for an RF Energy Harvesting System.

In this paper, a fully integrated capacitive DC-DC boost converter for ultra-low-power internet of things (IoT) applications operating with RF energy harvesting is proposed. A DC-DC boost converter is needed to boost the low output voltage of the RF energy harvester to provide a high voltage to the load. However, a boost converter operating at a low voltage supplied by ambient RF energy harvesting has a problem in that power conversion efficiency is significantly lowered. The proposed on-chip capacitive DC-DC boost converter simultaneously applies gate bias boosting and dynamic body biasing techniques using only the internal boosted voltage without an additional circuit that increases power loss to boost the voltage, achieving high efficiency at an input voltage as low as 0.1 V. The designed capacitive boost converter achieves a peak power conversion efficiency (PCE) of 33.8% at a very low input voltage of 0.1 V, a 14% improvement over the peak PCE of the conventional cross-coupled charge pump. A maximum peak PCE of 80.1% is achieved at an input voltage of 200 mV and a load current of 3 µA. The proposed capacitive boost converter is implemented with a total flying capacitance of 60 pF, suitable for on-chip integration.

Self-Sustainable Biomedical Devices Powered by RF Energy: A Review.

Wearable and implantable medical devices (IMDs) have come a long way in the past few decades and have contributed to the development of many personalized health monitoring and therapeutic applications. Sustaining these devices with reliable and long-term power supply is still an ongoing challenge. This review discusses the challenges and milestones in energizing wearable and IMDs using the RF energy harvesting (RFEH) technique. The review highlights the main integrating frontend blocks such as the wearable and implantable antenna design, matching network, and rectifier topologies. The advantages and bottlenecks of adopting RFEH technology in wearable and IMDs are reviewed, along with the system elements and characteristics that enable these devices to operate in an optimized manner. The applications of RFEH in wearable and IMDs medical devices are elaborated in the final section of this review. This article summarizes the recent developments in RFEH, highlights the gaps, and explores future research opportunities.

Maximizing Average Throughput of Cooperative Cognitive Radio Networks Based on Energy Harvesting.

Energy harvesting (EH) and cooperative communication techniques have been widely used in cognitive radio networks. However, most studies on throughput in energy-harvesting cooperative cognitive radio networks (EH-CCRNs) are end-to-end, which ignores the overall working state of the network. For the above problems, under the premise of prioritizing the communication quality of short-range users, this paper focuses on the optimization of the EH-CCRN average throughput, with energy and transmission power as constraints. The formulated problem was an unsolved non-deterministic polynomial-time hardness (NP-hard) problem. To make it tractable to solve, a multi-user time-power resource allocation algorithm (M-TPRA) is proposed, which is based on sub-gradient descent and unary linear optimization methods. Simulation results show that the M-TPRA algorithm can improve the average throughput of the network. In addition, the energy consumed by executing the M-TPRA algorithm is analyzed.

Design of a Highly Efficient Wideband Multi-Frequency Ambient RF Energy Harvester.

For low input radio frequency (RF) power from -35 to 5 dBm, a novel quad-band RF energy harvester (RFEH) with an improved impedance matching network (IMN) is proposed to overcome the poor conversion efficiency and limited RF power range of the ambient environment. In this research, an RF spectral survey was performed in the semi-urban region of Malaysia, and using these results, a multi-frequency highly sensitive RF energy harvester was designed to harvest energy from available frequency bands within the 0.8 GHz to 2.6 GHz frequency range. Firstly, a new IMN is implemented to improve the rectifying circuit's efficiency in ambient conditions. Secondly, a self-complementary log-periodic higher bandwidth antenna is proposed. Finally, the design and manufacture of the proposed RF harvester's prototype are carried out and tested to realize its output in the desired frequency bands. For an accumulative -15 dBm input RF power that is uniformly universal across the four radio frequency bands, the harvester's calculated dc rectification efficiency is about 35 percent and reaches 52 percent at -20 dBm. Measurement in an ambient RF setting shows that the proposed harvester is able to harvest dc energy at -20 dBm up to 0.678 V.

A New RF Energy Harvesting System Based on Two Architectures to Enhance the DC Output Voltage for WSN Feeding.

In this paper, a new RF Energy Harvesting (RF-EH) system for Wireless Sensor Network (WSN) feeding is proposed. It is based on two different monitored architectures using switch circuits controlled by the input powers. One architecture is more adapted to high input powers and the other to low input powers. The two different architectures and the system are designed and realized on Teflon glass substrate with a relative permittivity of 2.1 and thickness of 0.67 mm. They are tested separately as a function of the distance from the relay antenna. A new multiband antenna with a size of 40 × 30 mm2 is used for both architectures and the system. The measured antenna gains are 2.7 dB, 2.9 dB, and 2.55 dB for the frequencies of 1.8 GHz, 2.1 GHz, and 2.66 GHz corresponding to the mobile communication networks, respectively. The rectifier consists of two Schottky diodes forming a full-wave rectifier and voltage doubler. The maximum measured RF-to-DC conversion efficiency is 71.5%. The proposed RF-EH system provides a maximum DC output voltage of 5.6 V and 3.15 V for an open and 2 kΩ resistance load, respectively.

A Highly Efficient RF-DC Converter for Energy Harvesting Applications Using a Threshold Voltage Cancellation Scheme.

In this paper, a self-threshold voltage (Vth) compensated Radio Frequency to Direct Current (RF-DC) converter operating at 900 MHz and 2.4 GHz is proposed for RF energy harvesting applications. The threshold voltage of the rectifying devices is compensated by the bias voltage generated by the auxiliary transistors and output DC voltage. The auxiliary transistors compensate the threshold voltage (Vth) of the PMOS rectifying device while the threshold voltage (Vth) of the NMOS rectifying device is compensated by the output DC voltage. The proposed RF-DC converter was implemented in 180 nm Complementary Metal-Oxide Semiconductor (CMOS) technology. The experimental results show that the proposed design achieves better performance at both 900 MHz and 2.4 GHz frequencies in terms of PCE, output voltage, sensitivity, and effective area. The peak power conversion efficiency (PCE) of 38.5% at -12 dBm across a 1 MΩ load for 900 MHz frequency was achieved. Similarly, for 2.4 GHz frequency, the proposed circuit achieves a peak PCE of 26.5% at -6 dBm across a 1 MΩ load. The proposed RF-DC converter circuit shows a sensitivity of -20 dBm across a 1 MΩ load and produces a 1 V output DC voltage.

A New Compact Triple-Band Triangular Patch Antenna for RF Energy Harvesting Applications in IoT Devices.

This work proposes a new compact triple-band triangular patch antenna for RF energy harvesting applications in IoT devices. It is realized on Teflon glass substrate with a thickness of 0.67 mm and a relative permittivity of 2.1. Four versions of this antenna have been designed and realized with inclinations of 0°, 30°, 60° and 90° to study the impact of the tilting on their characteristics (S11 parameter, radiation pattern, gain) and to explore the possibilities of their implementation in the architectures of electronic equipment according to the available space. The antenna is also realized on waterproof paper with a thickness of 0.1 mm and a relative permittivity of 1.4 for biomedical domain. All the antennas (vertical antenna, tilted antennas and antenna realized on waterproof paper) have a size of 39 × 9 mm2 and cover the 2.45 GHz and 5.2 GHz Wi-Fi bands and the 8.2 GHz band. A good agreement is obtained between measured and simulated results. Radiation patterns show that all the antennas are omnidirectional for 2.45 GHz and pseudo-omnidirectional for 5.2 GHz and 8.2 GHz with maximum measured gains of 2.6 dBi, 4.55 dBi and 6 dBi, respectively. The maximum measured radiation efficiencies for the three antenna configurations are, respectively, of 75%, 70% and 72%. The Specific Absorption Rate (SAR) for the antenna bound on the human body is of 1.1 W/kg, 0.71 W/kg and 0.45 W/kg, respectively, for the three frequencies 2.45 GHz, 5.2 GHz and 8.2 GHz. All these antennas are then applied to realize RF energy harvesting systems. These systems are designed, realized and tested for the frequency 2.45 GHz, -20 dBm input power and 2 kΩ resistance load. The maximum measured output DC power is of 7.68 µW with a maximum RF-to-DC conversion efficiency of 77%.

Boosting Quantum Battery-Based IoT Gadgets via RF-Enabled Energy Harvesting.

The search for a highly portable and efficient supply of energy to run small-scale wireless gadgets has captivated the human race for the past few years. As a part of this quest, the idea of realizing a Quantum battery (QB) seems promising. Like any other practically tractable system, the design of QBs also involve several critical challenges. The main problem in this context is to ensure a lossless environment pertaining to the closed-system design of the QB, which is extremely difficult to realize in practice. Herein, we model and optimize various aspects of a Radio-Frequency (RF) Energy Harvesting (EH)-assisted, QB-enabled Internet-of-Things (IoT) system. Several RF-EH modules (in the form of micro- or nano-meter-sized integrated circuits (ICs)) are placed in parallel at the IoT receiver device, and the overall correspondingly harvested energy helps the involved Quantum sources achieve the so-called quasi-stable state. Concretely, the Quantum sources absorb the energy of photons that are emitted by a photon-emitting device controlled by a micro-controller, which also manages the overall harvested energy from the RF-EH ICs. To investigate the considered framework, we first minimize the total transmit power under the constraints on overall harvested energy and the number of RF-EH ICs at the QB-enabled wireless IoT device. Next, we optimize the number of RF-EH ICs, subject to the constraints on total transmit power and overall harvested energy. Correspondingly, we obtain suitable analytical solutions to the above-mentioned problems, respectively, and also cross-validate them using a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results, which are both theoretical and simulations based, by taking a range of operating system parameters into account.

A Fully-Integrated Ambient RF Energy Harvesting System with 423-µW Output Power.

This paper proposes a 2.4-GHz fully-integrated single-frequency multi-channel RF energy harvesting (RFEH) system with increased harvested power density. The RFEH can produce an output power of ~423-µW in harvesting ambient RF energy. The front-end consists of an on-chip impedance matching network with a stacked rectifier concurrently matched to a 50 Ω input source. The circuit mitigates the "dead-zone" by enhancing the pumping efficiency, achieved through the increase of Vgs drivability of the proposed internal gate boosting 6-stage low-input voltage charge pump and the 5-stage shared-auxiliary-biasing ring-voltage-controlled-oscillator (VCO) integrated to improve the start-up. The RFEH system, simulated in 180-nm complementary metal-oxide-semiconductor (CMOS), occupies an active area of 1.02 mm2. Post-layout simulations show a peak power conversion efficiency(PCE) of 21.15%, driving a 3.3-kΩ load at an input power of 0 dBm and sensitivity of -14.1 dBm corresponding to an output voltage, Vout,RFEH of 1.25 V.

Subjective symptoms of SMFs and RF energy, and risk perception among staff working with MR scanners within two public hospitals in South Africa.

This study assessed subjective symptoms associated with exposure to static magnetic fields (SMFs) and radiofrequency (RF) energy, and perceived safety risk of scanners among magnetic resonance (MR) staff working in the 1.5 and 3 T MRI units. A questionnaire survey was completed by 77 clinical imaging staff working in two hospitals (A and B) in the Mangaung metropolitan region. 50 participants working with the MR scanners were regarded as exposed group and 27 participants from CT scan and X-ray departments were classified as control group. The study comprised 57% females and 43% male participants with an average MRI experience of 5.4 years. Using logistic regression, tinnitus was significantly different between various job titles (p< .034) and it was reported more often (OR 8:00; CI 1.51, 15.17) by those who worked on a 3 T scanner. Increased years of MRI experience was a significant predictor of headache (p< .05), and reporting of nausea was significantly different between various job titles (p < .01). There was an increased risks of reporting vertigo often among female participants (OR: 4.43; CI 0.91, 21.47), those with 5-15 years of MRI experience (OR: 2.09; CI 0.47, 9.34), and those with a light to moderate workload (OR: 2.70; CI 0.49, 14.86). Using linear regression, presence in zone IV during image acquisitioning was the only significant predictor for the sensation of glowing (p < .000). Movement of head/ upper body in the scanner bore was a significant predictor of nausea (p< .026), vertigo (p< .014), instability when standing (p< .014), and a metallic taste (p< .031). There was no correlation between reporting of symptoms and perceived risk of scanners. However, shift duration (rs = 0.576), movement of head/upper body in the scanner bore (rs = 0.424), and strength of the scanners (rs = 0.299) were significantly correlated with perceived risk of scanners. MRI safety training and a comprehensive occupational health and safety program are necessary.

Age of Information Minimization for Radio Frequency Energy-Harvesting Cognitive Radio Networks.

The Age of Information (AoI) measures the freshness of information and is a critic performance metric for time-sensitive applications. In this paper, we consider a radio frequency energy-harvesting cognitive radio network, where the secondary user harvests energy from the primary users' transmissions and opportunistically accesses the primary users' licensed spectrum to deliver the status-update data pack. We aim to minimize the AoI subject to the energy causality and spectrum constraints by optimizing the sensing and update decisions. We formulate the AoI minimization problem as a partially observable Markov decision process and solve it via dynamic programming. Simulation results verify that our proposed policy is significantly superior to the myopic policy under different parameter settings.

A Dual-Band Wide-Input-Range Adaptive CMOS RF-DC Converter for Ambient RF Energy Harvesting.

In this paper, a dual-band wide-input-range adaptive radio frequency-to-direct current (RF-DC) converter operating in the 0.9 GHz and 2.4 GHz bands is proposed for ambient RF energy harvesting. The proposed dual-band RF-DC converter adopts a dual-band impedance-matching network to harvest RF energy from multiple frequency bands. To solve the problem consisting in the great degradation of the power conversion efficiency (PCE) of a multi-band rectifier according to the RF input power range because the available RF input power range is different according to the frequency band, the proposed dual-band RF rectifier adopts an adaptive configuration that changes the operation mode so that the number of stages is optimized. Since the optimum peak PCE can be obtained according to the RF input power, the PCE can be increased over a wide RF input power range of multiple bands. When dual-band RF input powers of 0.9 GHz and 2.4 GHz were applied, a peak PCE of 67.1% at an input power of -12 dBm and a peak PCE of 62.9% at an input power of -19 dBm were achieved. The input sensitivity to obtain an output voltage of 1 V was -17 dBm, and the RF input power range with a PCE greater than 20% was 21 dB. The proposed design achieved the highest peak PCE and the widest RF input power range compared with previously reported CMOS multi-band rectifiers.

Quad-Band Rectenna for Ambient Radio Frequency (RF) Energy Harvesting.

RF power is broadly available in both urban and semi-urban areas and thus exhibits as a promising candidate for ambient energy scavenging sources. In this research, a high-efficiency quad-band rectenna is designed for ambient RF wireless energy scavenging over the frequency range from 0.8 to 2.5 GHz. Firstly, the detailed characteristics (i.e., available frequency bands and associated power density levels) of the ambient RF power are studied and analyzed. The data (i.e., RF survey results) are then applied to aid the design of a new quad-band RF harvester. A newly designed impedance matching network (IMN) with an additional L-network in a third-branch of dual-port rectifier circuit is familiarized to increase the performance and RF-to-DC conversion efficiency of the harvester with comparatively very low input RF power density levels. A dual-polarized multi-frequency bow-tie antenna is designed, which has a wide bandwidth (BW) and is miniature in size. The dual cross planer structure internal triangular shape and co-axial feeding are used to decrease the size and enhance the antenna performance. Consequently, the suggested RF harvester is designed to cover all available frequency bands, including part of most mobile phone and wireless local area network (WLAN) bands in Malaysia, while the optimum resistance value for maximum dc rectification efficiency (up to 48%) is from 1 to 10 kΩ. The measurement result in the ambient environment (i.e., both indoor and outdoor) depicts that the new harvester is able to harvest dc voltage of 124.3 and 191.0 mV, respectively, which can be used for low power sensors and wireless applications.

Secrecy Performance Maximization for Underlay CR Networks with an Energy Harvesting Jammer.

This paper investigates the secrecy communication in an underlay cognitive radio (CR) networks with one primary user (PU) as well as multiple PUs, where the radio frequency (RF) energy-harvesting secondary user (SU) transmits the confidential information to the destination in the presence of a potential eavesdropper. We introduce a RF energy-harvesting secondary jammer (SJ) to secure the SU transmissions. The system works in time slots, where each time slot is divided into the energy transfer (ET) phase and the information transfer (IT) phase. In ET phase, the SU and SJ capture energy from the PU transmissions; in the IT phase, the SU uses the harvested energy to transmit information to the destination without causing the harmful interference to the PU transmissions, while the SJ utilizes the captured energy to generate jamming signals to the eavesdropper to secure the SU transmissions. We aim to maximize the secrecy rate for SU transmissionsby jointly optimizing the time allocation between ET phase and IT phase and the transmit power allocation at the SU and SJ. We first formulate the secrecy rate maximization as non-convex optimization problems. Then, we propose efficient nested form algorithms for the non-convex problems. In the outer layer, we obtain the optimal time allocation by the one dimension search method. In the inner layer, we obtain the optimal transmit power allocation by the DC programming, where the Lagrange duality method is employed to solve the convex approximation problem. Simulation results verify that the proposed schemes essentially improve the secrecy rate of the secondary network as compared to the benchmark schemes.

Metamaterial-Integrated High-Gain Rectenna for RF Sensing and Energy Harvesting Applications.

This paper presents a metamaterial (MTM)-integrated high-gain rectenna for RF sensing and energy harvesting applications that operates at 2.45 GHz, an industry, science, medicine (ISM) band. The novel MTM superstrate approach with a three-layered integration method is firstly introduced for rectenna applications. The integrated rectenna consists of three layers, where the first layer is an MTM superstrate consisting of four-by-four MTM unit cell arrays, the second layer a patch antenna, and the third layer a rectifier circuit. By integrating the MTM superstrate on top of the patch antenna, the gain of the antenna is enhanced, owing to its beam focusing capability of the MTM superstrate. This induces the increase of the captured RF power at the rectifier input, resulting in high-output DC power and high entire end-to-end efficiency. A parametric analysis is performed in order to optimize the near-zero property of the MTM unit cell. In addition, the effects of the number of MTM unit cells on the performance of the integrated rectenna are studied. A prototype MTM-integrated rectenna, which is designed on an RO5880 substrate, is fabricated and characterized. The measured gain of the MTM-integrated rectenna is 11.87 dB. It shows a gain improvement of 6.12 dB compared to a counterpart patch antenna without an MTM superstrate and a maximum RF-DC conversion efficiency of 78.9% at an input RF power of 9 dBm. This results in the improvement of the RF-DC efficiency from 39.2% to 78.9% and the increase of the output DC power from 0.7 mW to 6.27 mW (a factor of 8.96 improvements). The demonstrated MTM-integrated rectenna has shown outstanding performance compared to other previously reported work. We emphasize that the demonstrated MTM-integrated rectenna has a low design complexity compared with other work, as the MTM superstrate layer is integrated on top of the simple patch antenna and rectifier circuit. In addition, the number of MTM units can be determined depending on applications. It is highly envisioned that the demonstrated MTM-integrated rectenna will provide new possibilities for practical energy harvesting applications with improved antenna gain and efficiency in various IoT environments.