National Journal of RF Circuits and Wireless Systems
Aim and Scope : National Journal of RF Circuits and Wireless Systems,ISSN 3107-6807 , publishes peer-reviewed research focused on advancing knowledge in RF engineering and wireless communication systems. The journal emphasizes both theoretical innovations and practical applications, covering: RF Circuit Design: LNAs, PAs, mixers, oscillators, RFIC/MMIC, MEMS, and advanced materials. Wireless Systems: 5G/6G, IoT protocols, MIMO, OFDM, SDR, and cognitive radio. Antennas & Propagation: Reconfigurable and wearable antennas, propagation models, and RF energy harvesting. Security in Wireless: Physical layer security, jamming protection, and secure IoT networks. Testing & Simulation: Use of HSPICE, ADS, CST, OTA testing, and hardware-in-the-loop validation. Application Areas: Biomedical RF, aerospace, automotive, defense, and smart infrastructure. The journal encourages interdisciplinary submissions and maintains a rigorous peer-review policy to uphold academic integrity and innovation. Frequency of publication - It has Three issue per year Language - English Subject - Engineering Year of Starting - 2024 format of publication - Online Only ISSN- 3107-6807
SOCIETY FOR COMMUNICATION AND COMPUTER TECHNOLOGIES
AI Powered Automated Drug Delivery System with Real Time Monitoring
The healthcare sector faces significant challenges in monitoring patients’ health in real-time, especially for those with chronic conditions. Traditional patient monitoring systems lack predictive capabilities and rely heavily on manual intervention. This can lead to delays in treatment and poor health outcomes. The proposed solution utilizes cloud analytics and deep learning techniques for smart patient monitoring. By integrating wearable health devices with cloud infrastructure, the system continuously monitors patients’ vital signs such as heart rate, blood pressure, and oxygen levels. Deep learning models analyze this data to detect anomalies and predict potential health risks. The goal is to provide early detection of health deteriorations and offer personalized recommendations for treatment. This system aims to enhance patient care, reduce healthcare costs, and improve response times to critical events. Advantages include real-time monitoring, predictive analytics, remote accessibility, and the ability to offer tailored healthcare interventions.
Smart Helmet System for Real-Time Hazard Detection And Response
The increasing number of road accidents involving two-wheelers, especially due to drunk driving, underage riding, and not wearing helmets, indicates the need to include advanced safety measures. Conventional safety relies too heavily on the compliance of riders, which is seldom consistent and results in preventable injuries and fatalities. This project proposes a Smart Helmet Safety System that incorporates basic electronics and sensors with AI to promote better safety for riders and ensure that regulations are followed. An Arduino controls this system, which will monitor alcohol consumption using an MQ3 sensor, check if the rider is wearing the helmet with a limit switch, and authenticate the rider through RFID-based license scanning and AI-based facial recognition, including checking for under-age riding. Additionally, if the model experiences any vibration from accidents, it will send GPS location and alert contacts via a GSM module in no time. The novelty of this work is that by providing an overall automated solution to preventive unsafe travel and speedy emergency responses, two-wheeler travel would be safer using intelligent monitoring and control.
Two-Wheeler Safety, Rider Authentication, Accident Prevention, Emergency Response, Helmet Compliance, Alcohol Detection, Age Verification.
IoT-Based Smart Health-Monitoring Ventilator System For Enhanced Patient Safety
This work tackles the constraints of current low-resource ventilator systems. These systems sometimes lack built-in monitoring for the environment and vital signs, which reduces patient safety and increases the need for using multiple devices. The proposed solution is a smart, affordable health-monitoring ventilator system. It combines temperature, humidity, light, heart rate, blood oxygen levels, and dangerous gas detection into a single automated platform. The system’s goal is to provide constant, real-time monitoring. It also seeks to enhance comfort by automatically adjusting fans and lights, according to input from various sensors. The Arduino microcontroller handles both data gathering and control, operating effectively on its own, without needing any outside components. To improve use in both home and clinical settings, the readings are shown immediately on an LCD panel. The aim is to offer a cost-effective, space-saving, and dependable multi-parameter monitoring system, well suited for environments with limited resources. This system’s uniqueness comes from merging environmental sensing, biomedical monitoring, and automatic ventilation control into a single, completely integrated, and affordable system.
Smart Health Monitoring, Integrated Sensing, Patient Safety, Real-Time Tracking, Low-Cost Design, Automated Ventilation, Biomedical Monitoring.
RF Fingerprinting Techniques for Passive Identification of IoT Devices
At the device level, identification is an important issue in protecting wireless Internet of Things (IoT) infrastructures. The study presents an effective radio-frequency (RF) fingerprinting model of passively identifying IoT devices. Using inherent hardware flaws like I/Q imbalance, transient response and spectral distortion, the proposed system uses these flaws to create distinct RF signatures. A convolutional neural network (CNN) classifier is used to process these signatures and the recognition accuracy is 97 % of 50 types of devices. The system does not require any cryptographic keys or active handshake protocols, and provides a lightweight and scalable authentication layer to low-power IoT systems. The experimental findings support the robustness of the method when applied in the dynamic conditions of the channel, which proves that the method can support the development of device-level trust in the situation of large-scale networks.
RF fingerprinting, IoT device identification, wireless security, passive sensing, signal classification, machine learning.
Reciprocity-Driven Physical Layer Key Generation for Wireless Body Area Networks
This study proposes a lightweight, reciprocity-driven physical layer key generation scheme tailored for secure communication in Wireless Body Area Networks (WBANs). By harnessing the inherent randomness and temporal variation of on-body wireless channels, cryptographic keys are dynamically generated between wearable devices without reliance on pre-distributed secrets or computationally intensive algorithms. The protocol employs adaptive channel probing and quantization, followed by efficient error reconciliation and privacy amplification, ensuring strong key agreement even under mobility and diverse body movements. Experimental evaluations on a real WBAN testbed demonstrate high key generation rates, low bit mismatch, and resilience to passive eavesdropping, validating the scheme’s suitability for resource-constrained, low-power healthcare wearables. The results highlight the potential of physical-layer security as a practical solution for next-generation, privacy-aware health monitoring systems.
Physical Layer Security; Key Generation; Channel Reciprocity; Wireless Body Area Networks (WBANs); Wearable Devices; On-Body Communication; Cryptographic Protocols; Low-Power Security; Healthcare IoT; Eavesdropping Resistance
OTA-Validated SDR-Based mmWave RF Transceiver Architecture for 5G Wireless Communication Systems
The fast-moving development of the 5 G Wireless communication has driven the development of fully flexible and high-frequency transceiver architecture that can both support millimeter-wave (mmWave) operation and real-time reconfigurability. Here, solutions based on Software-Defined Radio (SDR) offer an easily reconfigurable operating framework that enables quick prototyping and testing performance. This article describes the design, implementation and Over-the-Air (OTA) validation of a simulation tested mmWave Software Defined Radio transceiver (SDR) operating on a 28 GHz frequency band to support 5G New Radio (NR) specifications. The architecture under design leverages reconfigurable baseband processing such as through the GNU Radio and MATLAB/Simulink platforms and high-frequency analog front-ends such as beam-steerable patch array antennas that are positively designed and optimized by means of the CST Microwave Studio. The physical layer is implemented using a USRP X310 platform supplemented with outside mmWave up/down converters and link-level simulations are used to measure parameters, like signal-to-noise ratio (SNR), error vector magnitude (EVM), and system throughput. It conducted OTA testing in controlled anechoic to prove end-to-end link performance with line-of-sight (LOS), and non-line-of-sight (NLOS). The transceiver is measured at an EVM of below 3.5% latency with an end-to-end under 2ms, and peak throughput of 600 Mbps illustrating that it is differentiated to 3GPP Release 16. These findings justify the possibility and scalability of the proposed SDR-based transceiver to be used within the 5G mmWave applications, and further developments would focus on applications to multi-antenna MIMO and AI-assisted dynamic beam management.
mmWave Transceiver Design, Software-Defined Radio (SDR), Over-the-Air (OTA) Validation, 5G Wireless Communication, Beamforming Architecture, USRP Prototyping
Ruggedized RF Transmitter Design for High-Temperature Aerospace Environments
The growing need to have reliable wireless communication systems in the aerospace platforms also requires the need to have RF transmitter architecture that can maintain its capability to operate under the extreme environment especially the high temperature and radiation environment. This paper gives full design, modeling and validation of a ruggedized RF transmitter that can be used with aerospace environment where ambient temperatures can reach a high temperature of 250C. The main building block of the proposed architecture is a power amplifier based on GaN that is predicted to have better heat tolerance and higher power ratings than silicon- or gallium arsenide-based predecessors. The system is thermally stable with temperature-compensated biasing circuit and effective thermal system with ceramic boards and heat-spreading case. The signal travel path with components radiation-hardened is used across the signal chain to provide greater survivability in high altitude and deep space conditions where total ionizing dose and latch-up conditions are major concerns. To thoroughly validate the design, a combination of ADS and CST co-simulation is used to characterize the RF performance, thermal modeling is done in COMSOL, and testing is done under both accelerated thermal cycling and radiation stress conditions. At 5.8 GHz the transmitter delivers a maximum power output of 28 dBm and high power beyond 42% power-added efficiency (PAE) and all within a wide temperature range with less than 1.2 dB variation in gain. Moreover, the system portrays stable impedance matching (S11 < -10 dB), low bit error rates when subjected to QPSK modulation, and negligible degradation of performance even under radiation dose of 100 krad(Si). This project not only proves that high temperature RF communications is not only possible in aerospace but also defines the design process of its future ruggedized communicational modules targeting high-altitude drones, planetary entry systems, and spacecraft payloads. The combination of rugged thermally and radiatively robust components in a small scale, mass producible transmitter platform is a first in the RF/harsh environment electronic arena of aerospace.
High-Temperature Electronics; Ruggedized RF Transmitter; Gallium Nitride (GaN); Aerospace Communication; Thermal Management; Radiation-Hardened Design; Power Amplifier (PA); ADS-CST Co-Simulation; Temperature-Compensated Biasing; Harsh Environment Electronics
Co-Simulation of RFIC Performance Using HSPICE and CST for Aerospace Communication Link
The evolutionary progress of aerospace communication resources requires the fabrication of high performance Radio Frequency Integrated Circuits (RFICs) that are capable of exhibiting high levels of both performance and reliability even in extreme environmental conditions, such as wide temperature variations, and radiation exposure, and also a high-frequency spectral requirement base. Conventional medicine uses circuit-based design methods, which are limited in capturing complex electromagnetic (EM) and layout-dependant parasitic effects, which make a critical impact on the performance of RFIC devices in real environments. The paper achieves this by formulation of a very well developed and strong co-simulation model that closely integrates full-wave electromagnetic circuit analysis using CST Microwave Studio and transistor-level circuit analysis using HSPICE. The methodology suggested can offer comprehensive modeling and optimization of the active and passive elements of the circuit, including circuit inductors, transmission lines, bonds, packaging, and so on. Performance factors like S parameters, voltage gain, NF, PAE, linearity and EM radiation performance are measured at Ku- and at Ka-band frequencies which are essential in the satellite-ground and inter-satellite communication links in aerospace applications. Additionally, the algorithm supports layout parasitic extraction (LPE), thermal-aware simulation, and radiation-hardened design design to achieve high precision when subjected to operational stresses most likely to be found in aerospace missions. S-parameter models of EM structures that are important in the circuit functioning are formed through the application of CST to its corresponding regions and the resulting model is directly inserted into a HSPICE simulation, which in turn, forms a feedback loop between physical effects on layout and circuit behavior. The co-simulation solution has demonstrated that it aligns well with the actual performance in addition to enabling the optimization cycle in design to be faster due to the window that is opened by removing the separation between EM design and electrical validation. Degradation in thermal robustness and performance at elevated total ionising dose (TID) are also discussed in order to illustrate resiliency. This co-simulation platform is an acceptable accuracy and scalable approach which offers a solution to RFIC designers interested in aerospace-grade transceivers, as well as to the next-generation modules of high frequency communication with improved reliability, smaller size, and reduced power.
RFIC Co-Simulation, HSPICE, CST Microwave Studio, Aerospace Communication, Ka-band, Electromagnetic Simulation, S-Parameters, Layout Parasitic Extraction, System-in-Package (SiP), Radiation-Hardened Design, EM-Circuit Integration
Ultra-Wideband RF Front-End for Real-Time Brain Signal Acquisition in Neuroprosthetic Devices
A high-performance ultra-wideband (UWB) radio frequency (RF) front-end architecture that is inherently designed with a capability to acquire brain signals in real-time in next-generation neuroprosthetic systems is presented, developed, and experimentally validated in this paper. As more wireless brain machine interfaces (BMI) and closed-loop neuroprosthetic devices become clinically useful, the RF front-end circuitry has been a critical need in support of transmission of low-amplitude, high-resolution neural activity; such as intracranial electroencephalography (iEEG) and local field potentials (LFPs) with minimal delays, high fidelity and ultra-low power requirements. The suggested front-end consists of an integrated-global positioning system (GPS) front-end architecture that is miniaturized and fully integrated including a low-noise amplifier (LNA), high-Q bandpass filter, passively conceived frequency mixer with low-phase-noise local oscillator (LO) and high-rate analog-to-digital conversion interface. The system is designed based on sophisticated 65 nm CMOS production technology and is working effectively at an operating frequency of up to 0.1-6GHz UWB and optimized in terms of implantable or wearable models. Front-end circuit-level Simulation and analysis range conjugated with Cadence and ADS determine a gain of 18.5 dB, noise figure of less than 1.2 dB and a 2.3 mW power consumption with an end-to-end latency of less than 5 microseconds, assured within the safe limits of biomedical applications. Co-simulation of electromagnetic in CST also verifies the validity of the RF signal pathway in realistic layout and packaging parasitics. A prototype was implemented in proof-of-concept cutting edge to test on synthetic brain signal emulators and wireless transmission systems having a robust performance with signal recovery below millivolts and minimum bit error rate (BER) in the context of mobility induced fading. Its high bandwidth, power, and signal integrity make the system a very promising technique in future consideration of implantable neural recording and stimulation systems. The present research establishes a basis of scalable, low-latency, and interference-tolerant RF telemetry in braincomputer interface living and paves the way to smart neuromodulation systems that provide real-time feedback.
Ultra-wideband (UWB), RF front-end, brain signal acquisition, neuroprosthetic devices, low-noise amplifier (LNA), real-time neural recording, implantable electronics, biomedical telemetry, CMOS design, wireless brain–machine interface (BMI).
Co-Simulation of ADS and CST for RFIC Performance Verification in Aerospace Communication Systems
The increasing application of high-performance communication systems in aerospace activities has spurred the prospect of advanced Radio Frequency Integrated Circuits (RFICs) which are fundamental to successful signal processing in the face of difficult activity environments. Simulation techniques used in the efficient and accurate simulation of RFICs can provide design flaws in the most perfect manner by mimicking what it will feel like under real-life circumstances to come up with the perfect performance in aerospace systems. The proposed co-simulation framework in this paper gives a new design that incorporates the Advanced Design System (ADS), and Computer Simulation Technology (CST) verifying the performance of RFICs in aerospace communication networks. The circuit level design/simulation tool so utilizes ADS (Ansys), and the full wave electromagnetic simulation tool CST (CST Global). The methodology allows a full RFIC selection to be performed that looks at several key components in an RFIC including low noise amplifier (LNA), power amplifier (PA), mixer, and oscillator. A set of case studies are performed to confirm the framework in which it is proven as improving the accuracy of simulation greatly, requiring less time to compute and optimize the performance of the calculation. The outcomes indicate that the single combined ADS-CST model provides a better estimate of RFIC performance resulting in more effective upper-level design of aerospace communication systems. To sum up, the suggested co-simulation environment turns out to be a beneficial tool to speed up the progression of RFIC and raise the dependability of aerospace communication systems.
Radio Frequency Integrated Circuits (RFICs), Co-Simulation, Advanced Design System (ADS), Computer Simulation Technology (CST), Aerospace Communication Systems, Electromagnetic Simulation
Antenna-in-Package (AiP) Integration Strategies for High-Frequency RFICs in 5G/6G Edge Devices: Design Challenges, Performance Trade-offs, and Future Opportunities
Within the context of super-fast development of 5G and perceived use of 6G wireless networks, the rate at which small, high-frequency and power efficient Radio Frequency Integrated Circuits (RFICs) that can drive edge intelligence grows fast. An attractive candidate solution is known as the Antenna-in-Package (AiP) technology, which is the concept of integrating both RF transceiver and antenna groups in the same, miniaturized component to reduce parasitic losses and provide a better performance at millimeter-wave (mmWave) and sub-THz frequencies. This paper seeks to explore the state-of-the-art AiP-based solutions to the high-frequency RFICs in the 5G/6G edge devices. The overall approach synthesizing the tools of literature review,comparative analysis, and the electromagnetic simulation considerations is used to determine the significant design bottlenecks. The most important of these difficulties are electromagnetic interference, heat risen outflow, interconnect dispenses, and constraints in substances material. Antenna gain versus beam-steering fidelity graph and form factor versus cost graph are performed. Other technologies discussed in the review include advanced packaging concepts, which include fan-out wafer-level packaging (FOWLP), system-in-package (SiP) and 3D heterogeneous integration. The paper finds a conclusion by pointing out some new research challenges such as reconfigurable AiPs, AI-enabled co-design processes, conformal flexible packages, and sub-THz antenna arrays to be used beyond 6G. The results herein offer a great basis of future research and implementation of next-generation wireless edge systems with scalable, high-performance AiP architectures to the industry.
Antenna-in-Package (AiP), Millimeter-Wave (mmWave), Radio Frequency Integrated Circuits (RFIC), 5G/6G Edge Devices, High-Frequency Packaging, Beamforming Antenna Arrays, Thermal Management in RFICs, System-in-Package (SiP), Electromagnetic Interference (EMI), 3D Heterogeneous Integration, Sub-THz Communications, Flexible and Conformal AiP, AI-Driven RF Design, Fan-Out Wafer-Level Packaging (FOWLP), Reconfigurable Antenna System
AI-Assisted Modeling and Optimization of RF Circuits Using HSPICE and Neural Metaheuristics
This paper suggests an AI-aided modeling and optimization approach to RF circuits, that combines the HSPICE simulation with the neural metaheuristic approaches, thus allowing amplifying the automation and accuracy of performance matching in circuits. Its first goal will be to overcome some of the drawbacks of manually sweeping parameters and using trial and error procedures in the common RF design process by adding a smart optimization loop that will improve important parameters including gain, return loss and power efficiency. The approach uses transistor-level modeling and waveform-accurate simulation by HSPICE and involves search of design space by a neural metaheuristic engine, i.e., the use of a hybrid neuralgenetic algorithm that explores the design space efficiently and computes no gradients. Iterative tuning is also automated so that fitness is judged using the result of the simulation and optimal parameters written back into HSPICE completing the loop. An example to prove the followed approach would be designing a Class-A RF power amplifier, at 2.4 GHz based on 0.18 micrometer CMOS technology. The optimization resulted in a 23% gain in small-signal gain, a 6 dB increase in return loss and a 30% decrease in weighted total harmonic distortion (THD) of the manually tuned designs. The difference in time of performing optimization exceeded 80 per cent, which illustrates the efficiency of the framework. The findings indicate that intensive applications of AI to conventional circuit simulators can tremendously shorten the RF design cycles and enhance the outcomes of performance. This project forms a starting point towards next generation automation of RF design across wireless and communication systems.
RF Circuit Design, HSPICE, Neural Metaheuristics, AI Optimization, Gain Enhancement, Return Loss, Power Efficiency, Circuit Automation
OTA and Hardware-in-the-Loop Testing of an SDR-Based RF Transceiver for 5G Applications
Being a fast-growing sphere of wireless communication where 5G reinvents the roadmap, the router of Software-Defined Radio (SDR)-based RF transceiver performance has been of great importance in demonstrating the efficacy of conventional systems and their readiness in meeting the strict standards as expected in the deployment process. Standard RF test techniques usually do not emulate the elaborate, dynamic propagation environments emblematic of 5G trials, especially those associated with the sub-6 GHz frequencies, along with millimeter-wave (mmWave) range. In order to fill this gap, this paper presents an overview of an end-to-end Over-the-Air (OTA) and Hardware-in-the-Loop (HIL) testing system that can combine real-time signal generation, adaptive feedback and channel emulation to test RF transceivers based on SDR technology. The test system is based on Universal Software Radio Peripheral (USRP) X310 platforms to test sub-6 GHz and National Instruments mmWave transceiver platforms to test 28 GHz. The OTA tests are made in both types of testing rooms viz. the anechoic room and reverberation rooms to characterize the system performance within the optimal environment and a multi-path environment. The HIL element, meanwhile, will utilize real-time FPGA based feedback loops that interface with the LabVIEW and MATLAB/Simulink-based environments to test closed-loop communication under closed-loop channel, user mobility and scenario interference by relying on simulated dynamic channel models. The key performance indicators such as Error Vector Magnitude (EVM), Bit Error Rate (BER) and Spectral Emission Compliance and the Beamforming Latency are measured and analyzed with reference to the 3GPP TS 38.104 standard. Findings show that the integrated testbed is an excellent way to capture the responsiveness of the transceiver to changes in the environment, real-time beam-steering, and adaptive modulation and coding scheme validation. Not only the proposed testing plan shortens the validation time, but the accuracy of the prototyping is improved and this testing procedure may be scaled to any complexity while still being cost-effective to test 5G and up-and-coming 6G transceivers before being deployed. The proposed research will also provide a useful validation process to filler the gap that exists between theoretical development of SDRs and practicality in real world performance testing thereby speeding up the realization of intelligent and reconfigurable wireless front-end systems for next generation communication networks.
5G Transceiver, Software-Defined Radio, OTA Testing, Hardware-in-the-Loop, USRP, mmWave, Beamforming, 3GPP Compliance, SDR Testbed.
Hardware-in-the-Loop Validation of SDR-Based Reconfigurable Transceivers for Tactical Wireless Communication Systems
The hardware-in-the-loop (HIL) validation framework proposed in this paper is aimed at the validation of software-defined radio (SDR)-based reconfigurable transceivers which are designed as part of wireless communication systems to operate as tactical applications. Such systems require strong and flexible operations in fast evolving, spectrum-congested and interference-prone scenarios. The proposed architecture integrates the ability to model the signals using MCRD and the SDR hardware resources in a co-simulation environment that enables closed-loop operation (across a large number of tactical scenarios). The important characteristics of the transceiver are adaption modulation schemes, and real-time channel equalizations, dynamic spectrum access, and FPGA acceleration of the baseband processing. The USRP B210 is employed to perform physical-layer transmission and reception in the HIL platform, and channel emulation modules are used that simulate urban multipath fading, Doppler shifts and jamming. As it is experimentally proven, bit error rate (BER) decreases dramatically under hostile RF circumstances under the adaptive modulation scheme up to 65 percent BER improvement and frequency hopping scheme up to 42 percent improved spectral efficiency. The model also attains sub-5 ms reconfiguration latency, which qualifies it as appropriate for time-bound functions. The findings affirm that the HIL approach can be used in benchmarking the undeniably live performance of SDR-based transceivers before they are released to the field. The suggested framework is both scalable and expandable where missions-critical RFsystems at different frequency bands and network topologies have been assessed. The future development designs will introduce cognitive adaptation by use of AI and multi-node tactical mesh networking abilities.
Hardware-in-the-Loop (HIL) Simulation, Software-Defined Radio (SDR), Reconfigurable Transceiver, Tactical Communication Systems, FPGA-Based Signal Processing, Adaptive Modulation, Dynamic Spectrum Access, Real-Time RF Validation, Bit Error Rate (BER), Channel Emulation.
Design and Performance Analysis of an Envelope-Tracking Doherty Power Amplifier for 6G Wireless Base Stations
The transition to 6G wireless communication networks requires installation of energy-efficient, high-linearity power amplifiers (PAs) as the base station RF-front-ends to address ultra-high data rates, massive connections, and onerous power limitations. The conventional PA architectures are characterized by low efficiency of the power back-off point which is experienced during power back-off especially under high peak to absolute power ratio ( PAPR ) waves which appear in broadband 6 g signals. In the efforts to solve this challenge, this paper develops a high-efficiency Doherty Power Amplifier (DPA) architecture with an Envelope Tracking (ET) that will focus on enhanced back-off efficiency and linearity of a 6G base station. The principle aim of the present work is designing, simulating and analysing an ET-enabled DPA implemented with GaN High Electron Mobility Transistor (GaN HEMT) at the 28 GHz mmWave frequency. The suggested design augments a Class-AB principle (load modulation) fundamental amplifier and a Class-C peak amplifier, whereas the ET module adjustably adjusts the drain voltage on an envelope-based correction of the RF signal to decrease power waste in terrain-off differentiations. Circuit level co-design and simulation is employed at both RF behavior, with Advanced Design System (ADS), and dynamic power supply response, with HSPICE simulation, levels. The matching network is matched in order to maximize the power transfer, and the load-pull simulations are applied to receive the best impedance conditions. Simulation results indicate that the proposed ET-DPA paves a way to a peak power-added efficiency (PAE) of 67%, small-signal gain of 13.8 dB and adjacent channel power ratio (ACPR) of -28 dBc. In addition, the amplifier achieves high efficiency (53%) at 6 dB output back-off and represents significant enhancement of conventional DPA designs. To recap it all, during envelope tracking in a Doherty architecture, an immense improvement is noticed in power efficiency and linearity in high-frequency 6G communication systems. The work provides one of the possible design strategies of energy-aware base station power amplifiers working within mmWave bands, as well as that paves the way to experimental verification and real deployment.
6G base stations, Doherty Power Amplifier (DPA), Envelope Tracking (ET), RF front-end, GaN HEMT, energy efficiency, power-added efficiency (PAE), mmWave communication, ADS simulation, linearity enhancement.
ADS–CST Co-Simulation and Performance Evaluation of MMIC Power Amplifier for Millimeter-Wave Automotive Radar Applications
This paper shows a detailed co-simulation guided design and analysis of a monolithic microwave integrated circuit (MMIC) power amplifier (PA) to be used in millimeter-wave (mmWave) automotive radar with voltage-controlled oscillator (VCO) operating at 76-81GHz band. The suggested technique is comprised of Keysight Advanced Design System (ADS) (nonlinear, circuit-level synthesis) and CST Microwave Studio (full-wave, 3D, electromagnetic (EM) simulations) to help it perform package-aware as well as prove to be layout-accurate. The MMIC PA is realized in 0.15 µm GaAs pHEMT technology and it has a two-stage common-source topology with a high-gain, power-added efficiency (PAE) optimisation. The early-stage design in ADS incorporates load-pull simulation and harmonic balance analysis of the design combined with simulation in CST to model the EM effects due to layout parasitics, ground discontinuities and interconnects. Co-simulation output performance shows small-signal gain peaking at 21 dB at 77 GHz, having a saturated output of +18.2 dBm as well as a peak PAE of 32% all with equally good input and output matching (S11 < -10 dB). The amplifier has realistic substrate and bias conditions and remains thermally stable and electromagnetically sound. The co-design method minimizes the differences between schematic and fabricated performance which facilitates reduced prototyping time and lead time and the robustness of the design. This research emphasizes that EM-circuit co-simulation plays a very crucial role in mmWave MMIC design and determines a proven approach to the design of high-performance compact power amplifiers in new generation vehicles radar and 6G communications applications.
MMIC Power Amplifier, ADS-CST Co-Simulation, Millimeter-Wave, Automotive Radar, 77 GHz, GaAs pHEMT, Power-Added Efficiency, EM-Circuit Integration
Wireless RF Sensor Network Architecture for Real-Time Damage Detection and Health Assessment in Smart Bridges
Real-time SHM systems of bridges are developing due to the growing demand of resilience and intelligence of infrastructure. As effective as the traditional wired solutions may be, they are not scalable, have a complex installation process, or have high maintenance burdens. This work suggests a wireless RF sensor system that has the capability to detect damages and evaluate the structure of the smart bridge in real-time (verified by simulation). Integrated onto distributed sensor nodes are vibration and strain sensors, low-power RF transceivers (LoRa/Zigbee), and edge-processing microcontrollers within a system that can be used to autonomously collect and locally analyse data, and transmit to a central monitoring unit wirelessly. The suggested architecture can deal with adaptive sampling, energy-efficient communication rules, and strong coverage of bridge structures with long spans. Packet delivery reliability is high (>98%) and damage alerts have sub-second latency with simulation and testbed evaluations showing node lifetime of over 24 months during the typical duty-cycled operation. In addition, the system realizes great sensitivity to pick structural abnormalities like microcracks and joint displacements. The findings confirm the viability and the robustness of the suggested RF basis WSN framework as the viable option to support the realm of constant, real-time SHM in the contemporary smart bridge infrastructure.
Wireless Sensor Network (WSN), Structural Health Monitoring (SHM), Smart Bridges, RF Communication, Damage Detection, Real-Time Monitoring, Low-Power Design, LoRa, Zigbee, Edge Processing, Infrastructure Safety, Sensor Node Architecture
Physical Layer Key Generation Using Channel Reciprocity for Secure Wireless Body Area Networks
Reliable communication over Wireless Body Area Networks (WBANs) is an essential aspect of Wireless Body Area Networks (WBANs) because the physiological data flows between wearable sensor nodes is sensitive data. The convectional cryptography methods usually apply a lot of computational complexity as well as energy overhead besides which they are not going to fit in the ultra-low-power WBANs. In the current paper a light-weight, energy-efficient Physical Layer Key Generation (PLKG) scheme the possibilities of which based on the native randomness and reciprocity of the wireless channel is used to generate secure symmetric keys is presented. With WBANs, there is a lot of temporal and spatial dynamics in the human body and its surrounding environment, which causes great variability in channel characteristics, in terms of Received Signal Strength Indicator (RSSI) and Channel State Information (CSI). Such physical layer parameters can be used as perfect entropy sources in generation of unique, unpredictable secret keys with whose knowledge, communication between nodes is possible and mutually exclusive only. The channel probing in the proposed framework is also robust, multi-bit quantization is performed adaptively, information reconciliation is performed through error correction codes, and privacy amplification is made through cryptographic hashing. We have developed a resilient system against bit mismatch and efficiently against passively eavesdropping, we guarantee the secrecy of the generated keys under adversary situation. With realistic WBAN models simulation and experiment validation shows that the proposed approach is capable of generating keystokes with very high key generation rate (50 bps) and a bit mismatch rate of lower than 3 percent as compared to existing schemes that solely relied on RSSI, making this protocol more secure and reliable to use. In addition, the framework meets the statistical randomness requirements specified by NIST and it does not leak mutual information to eavesdroppers. The scheme allows real-time use on resource-constrained devices, e.g., wearable medical devices and health-monitoring sensor, as it has low computational and memory overhead. The findings establish the feasibility of employing physical layer properties to achieve secure WBANs communication without any pre-shared keys or a centralized trust paradigm, thus, opening the way to scalable and privacy-preserving healthcare systems.
Physical Layer Security, Channel Reciprocity, Wireless Body Area Networks (WBANs), Key Generation, RSSI, Channel State Information (CSI), Quantization, Information Reconciliation, Secure Communication, Entropy Extraction
Compact CMOS-Compatible Power Amplifier with Enhanced Linearity for IoT Transmitters
Growth of Internet of things (IoT) has demanded miniaturisation, low power consumption and maximum linearity of power amplifiers (PAs) needed to be easily integrated in wireless sensor nodes with very low power and minuscule size restrictions. The design and optimization of a low profile, CMOS compatible power amplifier specifically suited to such IoT transmitters is described in this paper, with the core objective being to achieve a very low power point in operation with superb linearity in support of the most complex modulation schemes. The gears of the suggested PA are founded on the two-stage Class-AB approach, and they unite the power effectiveness and the linear amplification of the signal. The most significant improvements are adaptive biasing circuitry, which dynamically sets the quiescent current to the input envelope value, and low-cost analog predistortion (APD) scheme integrated with source degeneration to cancel third-order intermodulation products and improve adjacent channel power ratio (ACPR). It is fabricated with a 65 nm CMOS process so it can be considered low-cost andhigh-volume integration. Simulation outputs show the peak output power is 15 dBm at power-added efficiency (PAE) of 32% when amplifier is tested with 16-QAM modulated signal, which proves it capable of being used in IoT applications where linearity is required during transmission. The amplifier also has good thermal and process stability and the output performance varies little over a wide temperature range ( down to -20C and to +85C ) The core runs on a silicon die of only 0.45 mm 2, which allows it to be integrated in the system-on-chip (SoC) structures. The work emphasizes a valuable direction to reach to high-linearity RF transmission in IoT nodes with having neither great complexity of design nor space penalties, leading to more efficient and stable wireless communication subsystems in next generation of connected, low-power devices.
CMOS Power Amplifier, Internet of Things (IoT), Enhanced Linearity, Class-AB Amplifier, Adaptive Biasing, Analog Predistortion, Low-Power RF Design, Adjacent Channel Power Ratio (ACPR), Wireless Sensor Nodes, Energy-Efficient Transmitter Design
Secure and Energy-Efficient Cognitive Radio Architecture for Scalable IoT Networks in Smart Cities
The use of Internet of Things (IoT) applications, especially in smart cities, has heightened the pressure to have dependable spectrum and energy-effective communication. They cannot be served by traditional static spectrum allocation that can only support the dynamic and dense wireless deployments possible on smart urban environments. To this, this paper recommends secure and low-power cognitive radio (CR) architecture capable of addressing the scalability and sustainability of the next-gen IoT networks. Its main purposes are the optimization of spectrum, low-energy consumption, and improved security against radio-layer attacks. The suggested system unites the adaptive spectrum sensing, light-weight cryptographic modules (AES-CCM) and reinforcement learning-enabled energy management. NS-3 and MATLAB simulations are utilized to validate the architecture in terms of performance evaluation against major parameters such as power consumption, spectrum efficiency, and robustness to security attacks. The outcomes indicate a 34% decrease in energy usage of the state-of-the-art networking-IoT systems and a 45% improvement in spectrum utilization with a state-of-the-art networking-IoT systems when compared to baseline CR-IoT systems. Besides, architecture does well in blocking Primary User Emulation (PUE) and jamming attacks with a rate of>93 percent. The solution given based on a combination of a lightweight security and energy-aware control along with cognitive intelligence can be successfully used to make CR-based communication in smart cities more viable, as is indicated by the suggested solution. Future extensions will also look at live mapping on software-defined radio (SDR) and cooperative detection of threats with a federated learning model.
Cognitive Radio, IoT, Smart Cities, Spectrum Sensing, Low-Power Architecture, Security, Primary User Emulation, Dynamic Spectrum Access, NS-3 Simulation
Hybrid Beamforming and Physical Layer Security Techniques for 6G Massive MIMO Communication Systems
The present paper provides an in-depth inquiry on the topic of hybrid beamforming and physical layer security (PLS) technologies which will suit 6G massive multiple-input multiple-output (MIMO) communication systems. The first goal is to overcome both the energy-efficient beamforming and secure transmission issue with passive eavesdroppers, which is of utmost importance in 6G networks using millimeter-wave and sub-terahertz frequencies. The author suggests a new low-complexity hybrid analog-digital design of the beam forming structure which can use a sub-array structure to decrease the number of the RF chains but still generates high spatial resolution. Artificial noise (AN) is injected at particular locations within the null space of legitimate user channels; this has the effect of compromising signal quality on the capabilities of the eavesdropper only, without interfering with targeted receivers. The system architecture proposed optimizes the AN covariance matrix, analog precoder, and digital baseband precoder together in terms of the transmit power and hardware limitations. Extensive Monte-Carlo simulations under realistic propagation conditions demonstrate that the proposed approach has significantly better secrecy rate (an enhancement of up to 35% compared to conventional hybrid beamforming techniques) and a portion of energy efficiency is maintained with minimal negative impacts on robustness of the system in case of imperfect channel state information (CSI). The results attest to the effectiveness of the methodology in terms of practical and scalable 6G applications. Future extensions of the framework will be based on AI-powered adaptive beam choice and the incorporation of reconfigurable intelligent surfaces (RIS) to improve the physics-layer security.
6G, Massive MIMO, Hybrid Beamforming, Physical Layer Security, Artificial Noise, Secrecy Rate, Sub-array Architecture
Integrated HSPICE–MATLAB Framework for Thermal-Aware Simulation and Performance Analysis of RF Circuits
Under the present high speed wireless communication development trend, the RF circuits are continually submitted to thermal stress that has greatly impacted their reliability and performance. Standard methods to circuit simulation may ignore the fluctuation of the temperature in such crucial parameters including the gain, the noise figure (NF), and power consumptions. The current paper is an attempt to present an integrated co-simulation environment that consists of HSPICE and MATLAB, to achieve a thermal-aware RF circuit modeling and performance assessment. The aim will be to build an active automated simulation cycle that will present the temperature dependant phenomena of semiconducting devices under practical operating conditions. To perform electrical simulation, the framework uses HSPICE and temperature profiling, parametric control, as well as post-processing, it adopts MATLAB. The procedure is illustrated using a case study of 2.4 GHz CMOS-based Low Noise Amplifier (LNA). With a temperature ranging between 25 0 and 125 0, the simulation outcomes show that up to 18 per cent gain degradation and 12 percent increase in noise figure occur because of the temperature effect on the RF circuit. The given framework represents a scalable method proposed to analyze thermal reliability at an early stage in next-generation RF systems.
Thermal-Aware Simulation, RF Circuit Design, HSPICE–MATLAB Co-Simulation, Low Noise Amplifier (LNA), Temperature-Dependent Modeling, Performance Analysis, Gain and Noise Figure Degradation, Reliability in High-Frequency Systems
Energy-Efficient MIMO-OFDM Transceiver Design for Next-Generation Wireless IoT Systems
The superlinear spread of wireless devices in the Internet of Things (IoT), in particular, and the appearance of 6G communication networks, in general, have created urging requirements of the high-performance transceiver design that offer both spectral efficiency and energy savings. In such a circumstance, Multiple-Input Multiple-Output Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) has been found as the core technology as it has the unique capability of chasing the multipath fading and capable of high data throughput. Nevertheless, conventional MIMO-OFDM systems are normally limited by the high complexity of their hardware, and high power requirement, therefore, they cannot be applicable in the limited resource edge devices of the IoT. A new energy efficient MIMO-OFDM transceiver architecture is proposed in this paper and tailored to next generation wireless IoT system. The hybrid analog-digital beam former scheme proposed in the system has the scope to decrease the active radio-frequency (RF) chains in use by a large margin, leading to significant savings in energy usage without demining adaptation in the signal quality. Moreover, real time channel state information (CSI) based adaptive subcarrier power allocation algorithm dynamically assigns transmission power to OFDM subcarriers to prioritize energy efficiency in heterogeneous channel conditions. Simplified baseband signal processing blocks, and low-resolution analog-to-digital converters (ADCs) are also used in order to reduce computational overhead. To authenticate the proposed design, the simulation is carried out at the system-level under demanding tests in MATLAB, and the valuable performance metrics like Bit Error Rate (BER), energy efficiency, power consumption and spectral utilization are measured. Results show that it consumes power significantly, up to 45 percent less, than conventional full-digital transceivers, and they also show enhanced BER and energy-per-bit performance over a broad signal-to-noise ratio (SNR) range. The study presents a practical and scalable alternative to the way low-power, high-capacity wireless communication will be implemented in dense and heterogeneous IoT. The suggested design passes through the expectations of the 6G enabled smart environments of the future where energy efficiency, low latency, and ubiquitous access is prioritized. In future effort, this design will be scaled up to the implementation area and field verification in real-time IoT test beds.
MIMO-OFDM, Energy Efficiency, Hybrid Beamforming, Wireless IoT, Adaptive Power Allocation, Low-Power Transceiver, Subcarrier Optimization, Channel State Information (CSI), Spectral Efficiency, 6G Communication, Massive MIMO, Low-Resolution ADCs, Edge Devices, Next-Generation Wireless Systems.
Design and Evaluation of Compact Wearable Antennas for Body-Centric Wireless Communication Systems
The paper will deal with the fact that nowadays, there is growing demand in body-centric wireless communication systems (BCWCS) where compact and conformal antennas are essential to fulfill critical applications in the healthcare, defense and IOT wearable sectors. The main goal is the development of a flexible piece of fabric to create a low-profile textile-based, as well as a reasonably reliable antenna with the potential to operate quite nearby the human body, apparently, even in the circumstances with mechanical bending and movement. It is suggested that a planar monopole, which works on a felt-based substrate and elements of a conductive fabric, be used, specifically, in the 2.4 GHz ISM band. Full-wave simulations in CST Microwave Studio were analyzed to determine implemented electromagnetic performance which was fabricated and validated through electro-optical measurements in terms of return loss, radiation pattern, and over the-air (OTA). It delivered a return loss of greater than 20 dB, a bandwidth of 320 MHz and radiation efficiency of greater than 75% both in free space and on-body circumstances. OTA testing showed that the device performed stably in the bending processes (45 degrees, 90 degrees), unaffected by the various positions of the body, such as the forearm and chest. There were also SAR safety limits that were met by the antenna, signifying its appropriateness in wearables. These findings confirm the potential of the antenna in real-life body-centric communications and provide an expedient blueprint of low-profiled, power-saving, and human-friendly wireless systems via smart garments and health monitoring platforms.
Wearable Antenna, Body-Centric Communication, Textile Antenna, Over-the-Air (OTA) Testing, ISM Band, On-Body Propagation, Antenna Bending, CST Simulation
Advanced Jamming-Resilient RF Front-End Architecture for Secure, Low-Latency Mission-Critical IoT Systems
The wireless communications that are heavily used in mission-critical Internet of Things (IoT) situations, like those involved in an industrial control system, smart defense infrastructure, and emergency response networks are very vulnerable to purposeful radio frequency (RF) jamming which present high risks of operational resilience, data integrity as well as response time. The present paper suggests a sophisticated, simulation-proven, and hardware-in-the-loop (HIL)-tested jamming-tolerant RF front end system architecture that guarantees a secure, low-latency communication out of aggressive spectral environments. The system architecture includes wideband low-noise amplifier (LNA) that is reconfigurable, tunable bandpass filters realized using MEMS, and frequency-agile local oscillators that can support real-time frequency hopping spread spectrum (FHSS). To achieve adaptive threat mitigation, there has been lightweight convolutional neural network (CNN)-based jamming engine at the RF front-end to achieve dynamic spectral awareness and jamming pattern classification (e.g., tone, sweeping, and reactive jammers). Real-time signal-to-interference-plus-noise ratio (SINR) and bit error rate (BER) measurements determine whether to hop or not in a closed-loop control system. The design is confirmed with full-wave simulations in CST and behavioral modeling in MATLAB/Simulink after which the design is tested on the USRP SDRs and embedded controller in the hardware-in-the-loop testing. It has shown more than 94% a jamming resistance, latencies below 2 ms, and high throughput performance in a jammed 2.4 GHz ISM band system. The suggested RF front-end architecture ensures the provision of a scalable, hardware-efficient technique of ensuring robust and resilient wireless connection in timesensitive and security-relevant IoT implementations.
RF front-end, jamming resilience, IoT security, mission-critical systems, frequency hopping, adaptive filters, low-latency communication, ML-based jamming detection
Graphene-Assisted High-Frequency Flexible Antenna Architecture for Secure and Scalable Terahertz Communication in Smart Environments
The paper introduces the simulated design of graphene assisted high frequency flexible antenna design, which is optimized to be used as a terahertz (THz) communication in emerging smart environments. The use of graphene due to its outstanding electrical conductivity, mechanical flexibility as well as selective surface impedance allows such an antenna to perform at a frequency of 0.3-1.5 THz, a wavelength that satisfies the increasing need of ultra high speed and secure wireless communications in a 6G enabled infrastructure. The antenna is realized on polyimide substrate; a slotted patch geometry is used to increase band width and radiation patterns. Simulations in CST Microwave Studio and COMSOL Multiphysics ensure that this antenna can achieve high radiation efficiency (as well as low return loss (S11 < -20 dB) and mechanical stability (bending and curvature). In addition, physical-layer security and the prevention of the leakage of signals which occurs in densely connected smart systems exploit spatial filtering and directional properties of the emission. The proposed antenna design has low profile, conformal structure and reconfigurability, which makes it a suitable candidate for deployment in scalable applications like structural health monitoring, wearable and real-time sensor deployment on smart transport infrastructure and smart infrastructure systems.
Graphene-Based Antenna, Flexible Terahertz Communication, High-Frequency Antenna Design, Physical Layer Security, Smart Infrastructure Networks, CST Microwave Studio Simulation, Bending-Resilient Antenna Architecture, 6G Wireless Systems
MEMS-Based Tunable Bandpass Filter for Reconfigurable RF Front-End Architectures
Adaptive filtering technologies have been driven by the growing need to have flexible and reconfigurable radio frequency (RF) front-end solutions in the next generation wireless systems. In this paper, an overall design, simulation, and analysis of a tunable bandpass filter (BPF) based on MEMS that is relevant in the process of dynamic spectrum access in advanced communication systems with specific reference to the 5G and 6G spectrum 6 GHz and below. The suggested filter takes advantage of the electrostatically driven MEMS capacitive devices, integrated with a small coplanar waveguide (CPW) derivative structure, to deliver a dynamic tuning of the center frequency with a broad variety of 2.5 GHz to 5.5 GHz. It has a design with low insertion loss, large return loss, and large quality factor (Q), which allows a low consumption of power to select the signal efficiently. Mechanical modeling, simulation and optimization of the behaviors of MEMS structures (including finite element method (FEM)-based mechanical responses and tunability characteristics) were done using COMSOL Multiphysics and the performance/impedance characteristics of the RF filter over the tuning range were validated using Keysight Advanced Design System (ADS). It is found that the filter has an insertion loss that is less than 1.6 dB, the best return loss of better than 15 dB and loaded Q-factors at the minimum insertion loss points well above 100. Moreover, the filter has a high degree of linearity, power handling, ability to be combined with CMOS-compatible fabrication processes and hence could be deployed as part of software-defined radios (SDRs), cognitive radios, and adaptive transceiver modules. The solution proposed to the specified problems in the field promises to include the major issues of miniaturization, spectral agility, and low power consumption creating the scalable and cost-efficient route that will enable the use of frequency-agile front-end modules in the wireless platforms that can be introduced in the future. The current work makes the contribution to further development of MEMS-enabled RF design not only but opens the door to the development of reconfigurable and intelligent RF system that would be able to work effectively within changing communication standards and environments.
MEMS Bandpass Filter; Tunable Filters; Reconfigurable RF Front-End; Electrostatic Actuation; Coplanar Waveguide (CPW); Quality Factor (Q-Factor); 5G/6G Wireless Systems; Software-Defined Radio (SDR); S-Parameter Analysis; Adaptive RF Circuits
Ultra-Low-Power CMOS LNA Design for IoT-Enabled Wearable Biomedical Devices
This paper is aimed at producing a very energy-efficient metal-oxide-semiconductor LNA designed to suit Internet of Things (IoT) enabled wearable biomedical devices where low size, low power and noise performance are paramount requirements. Due to the fact that wearable health monitoring systems require an uninterrupted RF connection and operate on battery power, the ability to streamline the LNA is necessary to maximize equipment life without sacrificing on the quality of the connection. The following paper will design a low-power LNA that went through a simulation with 65nm CMOS, working in 2.4 GHz ISM band. The architecture of proposed LNA includes an inductive source degeneration, current reuse, and adaptive biasing to attain a low power consumption in surety of high gain and low noise performance. The design methodology is focused on the optimization of transistor size, impedance matching and reduction of bias currents calculated at the SPICE-level using Cadence Spectre platform. The simulated LNA has a voltage gain of 15.2 dB, noise figure of 1.4 dB and input return loss below -12 dB and the overall power consumption is kept low at only 340 µW. These findings are much more efficient compared than the traditional LNA designs in wearables. This paper validates the applicability of energy-constrained IoT healthcare applications in the advanced CMOS-based LNAs. The next steps will involve complete integration of RF front end and activating it experimentally with an implementation in silicon to prove it is really real-time.
CMOS LNA, Wearable Biomedical Devices, IoT Healthcare, Low Power Design, Inductive Degeneration, Noise Figure, Current Reuse, Energy-Efficient RF Front-End, 2.4 GHz ISM Band, Ultra-Low-Power Electronics
Metamaterial-Enabled Beam-Steering Antenna Architecture for Terahertz UAV Networks in Dynamic Air-to-Ground Environments
Larger-scale deployment of small drones (unmanned aerial vehicles) in future wireless networks requires high-capacity, low-latency communication infrastructure that can support the unsteady aerial conditions. Ultra-wide bandwidth and high data rate at the THz frequency bands have been expected to be one of the promising frontiers of 6G UAV communications. But the strong atmospheric absorption and directional radiating requirements at the THz frequencies are major issues when it comes to deploying strong and efficient UAV-to-ground and UAV-to-UAV communications. A new reconfigurable beam positioning antenna architecture is proposed in this paper having metamaterial surfaces optimized to communicate network of UAVs in the THz band. The design involves electronically controllable phase responses where the unit cells are tunable, thus providing agile and continuous steering of the beam through electronic controls instead of mechanical movement. The 2D array of metamaterials is a simulation-optimized model that works at 300 GHz. The validation shows that the antenna has a broad steering angle of -45O to +45 O, and a high gain of 22.3 dBi with a side lobe level of -15 dB all by means of simulation. It is lightweight and has a low-profile structure, which is an advantage that it can be very useful in smaller UAVs. The suggested architecture is tested using practical conditions of the UAV mobility and the different geometrical conditions of the links. The beam reconfiguration latency, radiation performance, and atmospherics propagation loss are all fully analyzed to define the viability of the system at the system level. The findings show that the metamaterial-based antenna would greatly enhance both the link robustness and the spectral efficiency of THz UAV networks, more so in highly dynamic air-to-ground scenarios of communications. The paper can inform the increasing pool of studies regarding adaptive and intelligent antenna systems in the 6G wireless infrastructure and also it is an opportunity to see future perspective where metamaterials can be used to enable small, lightweight, leading to new forms of directional antennas in UAV.
Terahertz (THz) communication, unmanned aerial vehicles (UAVs), beam-steering antennas, metamaterials, reconfigurable antennas, air-to-ground communication, 6G networks, directive antennas, metasurfaces, high-gain antenna design, adaptive beamforming, compact antenna arrays, dynamic wireless networks.
Design and Optimization of a Wideband Low-Noise Amplifier for 6G mmWave Applications
The even speedier advance of sixth-generation (6G) wireless communication systems requires the creation of high-performance millimeter-wave (mmWave) radio frequency (RF) front-end components that have the ability to work against large bandwidths with a greater gain and noise performance. Low-noise amplifier (LNA) is one of these elements providing that the overall sensitivity of the receiver chain, as well as the fidelity of the signal is largely dependent on it. The following paper illustrates the design and optimization of a Wideband LNA centered at mmWave 24-40 GHz band that contains several key 6G communication channels such as 28 GHz and 38 GHz bands. The advanced LNA architecture is a multi-cascade architecture with the source degeneration technology and inter-stage LC matching networks to bring the appropriate compromise between gain, noise figure (NF) and bandwidth. This design uses the 65nm CMOS technology that offers a low cost chip and supply of scalable integration into the new generation wireless systems. The main performance parameters consist of best gain of 21.8 dB, minimum NF of 2.5 dB and input reflection coefficient (S11) less than -10 dB throughout the whole L-band of 16 GHz. Resistive loading and feedback methods are used, and the stability is guaranteed up to the operating band. Schematic-level simulations are run with Key sight Advanced Design System (ADS) to achieve robust design as well as EM layout-aware simulations with CST Microwave Studio to achieve layout feasibility. The layout and package interactions have also been considered, and the design is able to take into account the effects of layout and package interaction through parasitic-aware modeling. The proposed LNA, due to its optimized performance footprint of the layout, energy consumption, and suitability for 6G-based mobile devices, small cell base stations, and IoT hubs is likely to be embedded with ease. This paper brings to the table a validated and feasible implementation methodology of wideband mmWave LNA design and establishes a platform on how the RF front-end will be integrated in more advanced 6G communication platforms.
6G, mmWave, Low-Noise Amplifier (LNA), Wideband Design, CMOS, Gain, Noise Figure, RF Front-End