Wireless Systems Research Articles

Meta‐heuristic optimization techniques for scheduling in multiple‐input multiple‐output multiple‐access channel system

SummaryIn a highly dense multiple‐input multiple‐output (MIMO) communication system, proper resource allocation is exceedingly challenging. The simultaneous selection of antennas at the base‐station (BS) and scheduling of users in an uplink multiple access channel (MAC) system add up to the signal processing load in the MIMO wireless system. The method chosen for combining the user scheduling and antenna selection must have a very low computational complexity. However, the exhaustive search algorithm (ESA), which achieves the best sum‐rate capacity in a MIMO‐MAC system, has a very high level of complexity. In this paper, we use a metaheuristic‐based optimization algorithms to optimize the sum‐rate capacity in a MAC system with significantly less computational complexity. First, we use the beluga whale optimization (BWO) metaheuristic method to solve the optimization problem. The BWO is a swarm‐based algorithm that draws inspiration from beluga whale behavior. An improved BWO (iBWO) is also presented and is utilized for the same optimization challenge. The proposed iBWO scheme improves the search capability of the algorithm and thereby ensures better exploration and exploitation capabilities of the beluga whales. We compare the performance of these algorithms with a standard differential evolution (DE) algorithm. The simulation results demonstrate that the proposed iBWO is a very competitive meta‐heuristic algorithm for solving optimization problems. The proposed iBWO algorithm achieves near optimal throughput in a MIMO‐MAC system. Also, the computational complexity related to the suggested optimization technique in a MIMO‐MAC system is found to be very less compared with the complexity related to ESA.

Self‐attention convolutional neural network optimized with Remora Optimization Algorithm for energy aware resource management in Non‐orthogonal Multiple Access networks

SummaryNon‐orthogonal multiple access (NOMA) is an efficient technology for future wireless communication systems. The resource management on NOMA networks is flattering for improving energy efficiency (EE) of systems. Therefore, self‐attention convolutional neural network (SACNN) optimized with Remora Optimization Algorithm (ROA) for energy aware resource management in NOMA network (SACNN‐ROA‐EE) is proposed in this paper for solving user allocation, channel allocation, and power allocation problems. The Matching‐Coalition approach is considered to face the user allocation issue, and the SACNN is considered to face the channel allocation and power allocation problems. SACNN does not adopt any optimization methods to determine the optimal parameters in channel allocation and power allocation. Therefore, the ROA is applied to optimize the SACNN weight parameters. The proposed technique is activated in MATLAB, and its efficacy is analyzed with under performances metrics, such as minimum user rate, sum rate, energy, and spectral performance. The proposed SACNN‐ROA‐EE attains 24.35%, 27.84%, and 38.58% better sum rate and 27.45%, 43.28%, 30.56% better EE compared with existing methods, such as EE utilizing communication deep neural network optimized with power allocation optimization (PAO‐CDNN‐EE), EE under deep transfer deterministic policy gradient along deep deterministic policy gradient approach (DPPGA‐DTDPPG‐EE), and EE utilizing deep reinforcement learning with baseline algorithms (BA‐DRL‐EE), respectively.

IoT-based Tracking Cattle Health Monitoring System Using Wireless Sensors

Maintaining the health of dairy cows is essential to raising the production of dairy products worldwide. Due to the numerous health problems that cows face, the unpredictability of disease outbreaks, and the high cost of producing new animals, dairy farmers are beginning to lose faith in the industry. To increase milk production, producers must thus employ effective technological methods for monitoring the health of their cows. This research examined many automated wireless sensor-based dairy cow health monitoring systems. The primary goal of smart surveillance systems based on wireless sensor networks (WSNs) in agricultural optimization is to continuously monitor the health of dairy cows. For interested farmers to keep an eye on their cattle's whereabouts throughout the day from many locations, this monitoring device needs to be deployed in both local and remote agricultural areas. A database would hold the information gathered by the automated system. Farmers can then use farm automation to acquire data so they can implement efficient farm management practices. Moreover, WSN is a low-cost tool designed specifically to detect diseases in dairy cows. This technological advancement in agricultural automation would help increase output by lowering the need for human intervention. This page provides an overview of all livestock tracking methods along with a summary of the problems and difficulties they face

Machine Learning Strategies for Reconfigurable Intelligent Surface-Assisted Communication Systems—A Review

Machine learning (ML) algorithms have been widely used to improve the performance of telecommunications systems, including reconfigurable intelligent surface (RIS)-assisted wireless communication systems. The RIS can be considered a key part of the backbone of sixth-generation (6G) communication mainly due to its electromagnetic properties for controlling the propagation of the signals in the wireless channel. The ML-optimized (RIS)-assisted wireless communication systems can be an effective alternative to mitigate the degradation suffered by the signal in the wireless channel, providing significant advantages in the system’s performance. However, the variety of approaches, system configurations, and channel conditions make it difficult to determine the best technique or group of techniques for effectively implementing an optimal solution. This paper presents a comprehensive review of the reported frameworks in the literature that apply ML and RISs to improve the overall performance of the wireless communication system. This paper compares the ML strategies that can be used to address the RIS-assisted system design. The systems are classified according to the ML method, the databases used, the implementation complexity, and the reported performance gains. Finally, we shed light on the challenges and opportunities in designing and implementing future RIS-assisted wireless communication systems based on ML strategies.

Experimental Investigation of Water-based Beam Reconfigurable Dielectric Resonator Antenna

Abstract In the present article, a novel dielectric resonator antenna (DRA) for the control of radiated beams is presented. The proposed DRA is capable of not only reconfiguring the beam width and gain, but also generating single, double, and multiple beams without changing the shape of the antenna. The DRA consists of a cuboid-shaped dielectric resonator having two chambers for storing the water. By varying the water levels in the chambers the beam width can be varied from 56° to 116° and gain 9.8 dBi to 5.86 dBi at the operating frequency of 9.2 GHz. In addition, multiple beams can also be produced by reducing the water level in one chamber. The prototype of the proposed DRA is fabricated and measured for different water levels. The simulated and measured results are in close agreement. The proposed DRA can find its potential application in microwave, space, and wireless communication systems

Enhancing secret key distribution through advanced color modulation in visible light communication

Visible light communication (VLC) has emerged as a dynamic area of research poised to revolutionize high-speed wireless communication. VLC technology uses light-emitting diodes (LEDs) within existing infrastructure to emit light within the visible spectrum. VLC complements traditional radio frequency (RF) communications, addressing its inherent limitations and drawbacks. To navigate the demands of modern urban environments, VLC systems must prioritize secure data transmission, accessibility, and economic feasibility, particularly within the framework of smart cities. We introduce what is to our knowledge a novel privacy-enhanced VLC system for optical wireless communication. Leveraging color data modulation techniques and the intricacies of a hyperchaotic three-dimensional map, this innovative approach ensures robust security. By employing diverse LED colors for data transmission and exploiting the unpredictable mathematical properties of hyperchaotic maps, enhanced privacy is achieved. The performance of the proposed system was rigorously evaluated through various tests, manipulating initial control parameters of the encryption process with the hyperchaotic map, as well as adjusting message length and content. Tests were conducted over a 1 m connection distance at a symbol transmission rate of 2 baud. Remarkably, the proposed system demonstrated high accuracy in message recovery, achieving a symbol error rate (SER) of only 0.02 at an incident optical power of 22 µW. We highlight the critical importance of precise decryption parameter values in the proposed method, demonstrating the necessity for accuracy within the range of 10−15 for each decryption parameter; it underscores the indispensability of meticulous parameter calibration to ensure the correct decryption of transmitted symbols. These results pave the way for applications where absolute security is imperative, particularly in smart city environments, such as for key distribution purposes.

Exploring and Analyzing a Hybrid PAPR Reduction Method for OFDM Optimization

Orthogonal Frequency Division Multiplexing (OFDM) is a effective modulation technique widely used in modern communication systems, including 5G and wireless networks because of its high spectral efficiency and robustness towards multipath fading. However, OFDM signals are characterized by a high Peak-to-Average Power Ratio (PAPR), which can severely impact the power efficiency and operational cost of these systems. This research investigates and analyse effectiveness of two conventional PAPR reduction methods that is Selective Mapping (SLM), and Partial Transmit Sequence (PTS) with incorporating their approach of PAPR reduction to develop a hybrid variant: SLM-PTS. This study utilized MATLAB simulations to implement and test each PAPR reduction technique on a standard OFDM system model. Parameters such as the number of subcarriers, oversampling factor, and modulation types were systematically varied to analyze the impact on PAPR, BER, and computational complexity. The effectiveness of each technique was measured using the Complementary Cumulative Distribution Function (CCDF) of PAPR values and BER performance under different channel conditions. Key findings reveal that hybrid techniques, particularly SLM & PTS, offer significant improvements in PAPR reduction compared to traditional methods alone, without a corresponding increase in BER or computational overhead. The research underscores the potential of hybrid PAPR reduction techniques to significantly enhance the efficiency and reliability of OFDM systems. These findings have important implications for the design and optimization of next-generation wireless communication systems, suggesting that hybrid approaches can provide a balanced solution to the longstanding issue of PAPR in OFDM transmissions. This study contributes valuable insights into the practical application of combined PAPR reduction strategies, offering a pathway toward more power-efficient and robust OFDM technologies. Keywords : OFDM, PAPR, CCDF, SLM and PTS

A Wireless Noninvasive Blood Pressure Measurement System Using MAX30102 and Random Forest Regressor for Photoplethysmography Signals

Hypertension, often termed “the silent killer”, is associated with cardiovascular risk and requires regular blood pressure (BP) monitoring. However, existing methods are cumbersome and require medical expertise, which is worsened by the need for physical contact, particularly during situations such as the coronavirus pandemic that started in 2019 (COVID-19). This study aimed to develop a cuffless, continuous, and accurate BP measurement system using a photoplethysmography (PPG) sensor and a microcontroller via PPG signals. The system utilizes a MAX30102 sensor and ESP-WROOM-32 microcontroller to capture PPG signals that undergo noise reduction during preprocessing. Peak detection and feature extraction algorithms were introduced, and their output data were used to train a machine learning model for BP prediction. Tuning the model resulted in identifying the best-performing model when using a dataset from six subjects with a total of 114 records, thereby achieving a coefficient of determination of 0.37/0.46 and a mean absolute error value of 4.38/4.49 using the random forest algorithm. Integrating this model into a web-based graphical user interface enables its implementation. One probable limitation arises from the small sample size (six participants) of healthy young individuals under seated conditions, thereby potentially hindering the proposed model’s ability to learn and generalize patterns effectively. Increasing the number of participants with diverse ages and medical histories can enhance the accuracy of the proposed model. Nevertheless, this innovative device successfully addresses the need for convenient, remote BP monitoring, particularly during situations like the COVID-19 pandemic, thus making it a promising tool for cardiovascular health management.

Analysis and design of wireless power transfer system with anti-misalignment constant voltage output characteristics

Analysis and design of wireless power transfer system with anti-misalignment constant voltage output characteristics

Mobility-Enhancement Simultaneous Optical Wireless Communication and Energy Harvesting System for IoUT

Mobility-Enhancement Simultaneous Optical Wireless Communication and Energy Harvesting System for IoUT

A three‐dimensional parabolic equation with fast reordered‐alternate direction decomposition in atmosphere duct environment

AbstractIn the design and optimisation of marine wireless communication and navigation systems, a thorough investigation of radio wave propagation characteristics under atmospheric ducting conditions is essential. The authors aim to enhance the efficiency of radio wave propagation loss prediction in marine atmospheric ducting environments, proposing a prediction model based on Fast Reordered‐Alternate Direction Decomposition (FR‐ADD). By approximating the diffraction term into three independent components, exploiting the commutative properties of the Fourier transform to reduce the spatial dimensions, and incorporating a rapid algorithm for the parabolic equation, the model optimises the stepping process and significantly improves computational efficiency. Simulation experiments demonstrate that, in the long‐distance and complex marine ducting environments, the model not only maintains prediction accuracy but also substantially reduces computational load and prediction time, effectively realising over‐the‐horizon propagation prediction. In the experiment of radio wave propagation characteristics in the Yellow and Bohai Seas, the simulation data from the FR‐ADD model showed significant correlation with actual measurements and simulations from the AREPS software, confirming the method's efficiency and practicality.

Spatial sensitivity synthesis based on alternate projection for the machine‐learning‐based coding digital receiving array

AbstractRecently, a novel low‐cost coding digital receiving array based on machine learning (ML‐CDRA) has been proposed to reduce the required radio frequency channels in modern wireless systems. The spatial sensitivity of ML‐CDRA is studied which describes the spatial accumulation gain in different directions. It is demonstrated that the spatial sensitivity is determined by the encoding network, decoding network, and beamforming criterion. To obtain the desired spatial sensitivity, a spatial sensitivity synthesis method is proposed based on the alternate projection by optimising the encoding network with the constraint of amplitude‐phase quantisation. Simulation results show that the proposed method can significantly improve the spatial sensitivity of ML‐CDRA. Furthermore, in the directions of interest, the spatial accumulation gain of ML‐CDRA can exceed the full‐channel digital receiving array.

An Adaptive Behavioral Intervention for Weight Loss Management

Lifestyle interventions for weight loss are difficult to implement in clinical practice. Self-managed mobile health implementations without or with added support after unsuccessful weight loss attempts could offer effective population-level obesity management. To test whether a wireless feedback system (WFS) yields noninferior weight loss vs WFS plus telephone coaching and whether participants who do not respond to initial treatment achieve greater weight loss with more vs less vigorous step-up interventions. In this noninferiority randomized trial, 400 adults aged 18 to 60 years with a body mass index of 27 to 45 were randomized in a 1:1 ratio to undergo 3 months of treatment initially with WFS or WFS plus coaching at a US academic medical center between June 2017 and March 2021. Participants attaining suboptimal weight loss were rerandomized to undergo modest or vigorous step-up intervention. The WFS included a Wi-Fi activity tracker and scale transmitting data to a smartphone app to provide daily feedback on progress in lifestyle change and weight loss, and WFS plus coaching added 12 weekly 10- to 15-minute supportive coaching calls delivered by bachelor's degree-level health promotionists viewing participants' self-monitoring data on a dashboard; step-up interventions included supportive messaging via mobile device screen notifications (app-based screen alerts) without or with coaching or powdered meal replacement. Participants and staff were unblinded and outcome assessors were blinded to treatment randomization. The primary outcome was the between-group difference in 6-month weight change, with the noninferiority margin defined as a difference in weight change of -2.5 kg; secondary outcomes included between-group differences for all participants in weight change at 3 and 12 months and between-group 6-month weight change difference among nonresponders exposed to modest vs vigorous step-up interventions. Among 400 participants (mean [SD] age, 40.5 [11.2] years; 305 [76.3%] women; 81 participants were Black and 266 were White; mean [SD] body mass index, 34.4 [4.3]) randomized to undergo WFS (n = 199) vs WFS plus coaching (n = 201), outcome data were available for 342 participants (85.5%) at 6 months. Six-month weight loss was -2.8 kg (95% CI, -3.5 to -2.0) for the WFS group and -4.8 kg (95% CI, -5.5 to -4.1) for participants in the WFS plus coaching group (difference in weight change, -2.0 kg [90% CI, -2.9 to -1.1]; P < .001); the 90% CI included the noninferiority margin of -2.5 kg. Weight change differences were comparable at 3 and 12 months and, among nonresponders, at 6 months, with no difference by step-up therapy. A wireless feedback system (Wi-Fi activity tracker and scale with smartphone app to provide daily feedback) was not noninferior to the same system with added coaching. Continued efforts are needed to identify strategies for weight loss management and to accurately select interventions for different individuals to achieve weight loss goals. ClinicalTrials.gov Identifier: NCT02997943.

Extreme learning machine and correntropy criterion-based hybrid precoder for 5G wireless communication systems

Extreme learning machine and correntropy criterion-based hybrid precoder for 5G wireless communication systems

Analysis of the outage performance of energy-harvesting cooperative-NOMA system with relay selection methods

Recent years have witnessed the remarkable progress in wireless communication systems due to the escalating demand for higher data rates, improved reliability, and increased energy efficiency. In this regard, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technology, enhancing spectral efficiency and accommodating multiple users concurrently within the same time and frequency resources. Simultaneously, the energy harvesting has surfaced as a sustainable solution, converting ambient environmental energy into usable electrical power for operating communication nodes. This paper proposes a cooperative NOMA transmission scheme integrating energy harvesting and utilizing Least Squares (LS) channel estimation for precise Channel State Information (CSI) acquisition. The objective is to establish an optimal communication path from source to destination. Relay selection methods: Optimal Relay Selection (ORS) and Max-Min Relay Selection (MMRS), are compared, focusing on their impact on the system performance. The analysis considers the influence of the number of relays and power allocation factor on the system, with a specific emphasis on the outage probability expressions. Comparative analysis between the cooperative-NOMA and the traditional cooperative relaying without NOMA reveals the superior performance of the cooperative-NOMA. Additionally, the ORS scheme outperforms MMRS in terms of the outage performance.

Design of a mid-field wireless power transmission system for deep-tissue implants.

Implantable medical devices are being valued as one of the developments of wireless biomedical technology. This paper presents a mid-field wireless power transmission (WPT) system, which is designed for implantable applications and operates at the 2.40-2.48 GHz band of Industrial, Scientific, and Medical (ISM). A new compact transmitter structure is proposed, and a small 4-C planar ring antenna is designed as the receiving element. A measurement setup is fulfilled on porcine tissues to verify the power transmission system. The experimental results show that the operating bandwidth is 2.2-2.62 GHz and the transmission coefficient can reach -26.32 dB at a distance of 50 mm. The effects of tissue differences, placement depth, and different transmission distances were also measured. The displacement and deflection tolerances between the transmitter and the implant receiver also have good performance. In the safety standard of specific absorption rate, for the 1 W output power from the mid-field transmitter, the receiving power of the implantable antenna at the mid-field distance can reach 79.6 mW. With measurements of different implantation and transmission distance on pork, the mid-field power transmission efficiency is proven and shows the high performance of the system.

Energy efficiency assessment of wireless system exploiting multiple reconfigurable intelligent surfaces with hardware impairments

AbstractThis article explores a practical scenario with hardware impairments (HIs) in a multireconfigurable intelligent surface (RIS) assisted wireless system. This approach is based on a mathematical analysis of the performance of the HI‐RIS system. To this end, a closed‐form expression of the energy efficiency (EE) and its asymptotic behavior, particularly in regions with high transmit power, are derived. Next, an analysis was conducted to compare the EE of the HI‐RIS system with those of relevant systems: the ideal hardware (ID)‐RIS system, HI‐point‐to‐point (P2P) system (without RISs), and ID‐P2P system (without RISs). The numerical findings unequivocally demonstrate that the incorporation of RISs substantially enhances the EE of the HI‐RIS system, particularly at high transmit rates. However, at low transmit rates, the EE of the HI‐RIS system less than that of the HI‐P2P system. This trend is also reflected in the EEs of the ID‐RIS and ID‐P2P systems. Moreover, the significant impact of HI on the EEs of the HI‐RIS and HI‐P2P systems is analyzed. The effects of crucial system parameters, such as the number of reflecting elements, frequencies of WiFi networks, and fading order, are comprehensively determined to provide insights into the behaviors of the HI‐RIS system. The outage probability and throughput behaviors of the HI‐RIS system are also evaluated to comprehensively analyze of the benefits of RISs and the effects of HI. Finally, the accuracy of the derived expressions was verified using Monte Carlo simulations.

Slots and stubs incorporated annular ring-shaped compact microstrip antenna with circular polarization characteristics for wireless UWB communication systems

A circularly polarized (CP) antenna with ultra-wideband resonance and a broad axial ratio bandwidth is designed for UWB communication systems. The prescribed design comprises of a modified annular ring-shaped radiator and a modified step-graded slots loaded partial ground plane. The projected antenna is prototyped on FR4 substrate of 35 × 30 × 1.6 mm3. To achieve wide axial ratio bandwidth, a rectangular vertical slot is inserted into the radiating patch and two stubs are embedded into the monopole ground plane, which is configured with step graded rectangular slots. The simulation results are verified by testing the fabricated protype. The proposed design operates at UWB spectrum with an ultra-wide impedance bandwidth (IBW) of 134.57%, centered at 10.7 GHz, covering 3.5 GHz to 17.9 GHz frequency spectrum. Furthermore, it demonstrates circular polarization characteristics with a broad axial ratio bandwidth (ARBW) of 96.29% expanding from 3.5–10 GHz (6500 MHz). Its peak gain reaches to 8.7 dBi and a maximum radiation efficiency of 95% is achieved within the operating band. The results (measured and simulated) obtained in terms of S11, axial ratio, gain and efficiency and radiation patterns exhibit high agreement. The presented antenna could be a suitable choice for 5.5 GHz Worldwide Interoperability for Microwave Access (Wi-Max), 5.2/5.8 GHz Wireless local area network (WLAN), X-band satellite communication (downlink: 7.25–7.745 GHz, uplink: 7.9–8.4 GHz), UWB communication systems, and other applications in microwave C, X, Ku bands due to its superior characteristics.

5G Channel Estimation using Deep Learning

The abstract focuses on the integration of 5G channel estimation and the vulnerability of deep learning models, specifically in the context of OFDM signals, while employing a student-teacher model architecture. Channel estimation is a crucial aspect of 5G communication systems, ensuring reliable data transmission in dynamic wireless environments. Simultaneously, the advent of deep learning introduces susceptibility to adversarial attacks, where malicious inputs can deceive the model's predictions. This paper explores the intricate relationship between 5G channel estimation and deep learning vulnerabilities, emphasising the application of a student-teacher model to enhance system robustness. By delving into the nuances of OFDM signals, the study aims to provide a comprehensive understanding of how these elements intertwine, offering insights into potential security enhancements for next-generation wireless communication systems.

Ternary nano-composite wireless ammonia sensor based on Polyaniline/CuTsPc/AgNPs for food intelligent packaging

The integration of gas sensing unit and low-cost wireless communication equipment enables real-time detection of various environmental gases, which is of great significance for food safety, medical diagnosis and environmental monitoring. In this study, copper phthalocyanine powder (CuTsPc) was prepared by high temperature solid phase melting technology. Ternary ammonia sensors with exceptional sensitivity to ammonia and conductivity were successfully fabricated by growing polyaniline/copper phthalocyanine/silver nanoparticles (PANI/CuTsPc/AgNPs) composites on polyethylene terephthalate films by in-situ polymerization. The morphology and composition of the films were characterized by FTIR, XRD and SEM, respectively. The ammonia sensing performance of the films at room temperature was systematically investigated. It is found that the flexible PANI/CuTsPc/AgNPs gas sensor exhibited rapid response time (61 s), fast recovery time (19 s), low theoretical detection limit (0.234 ppm), high response value (3.6 towards 500 ppm NH3), and excellent stability at room temperature. These remarkable response characteristics can be attributed to the synergistic effect between protonic acid-doped PANI, CuTsPc derivatives with an electron-withdrawing group, and AgNPs possessing both chemical sensitisation and electron sensitisation. Finally, the sensor material was transformed into a label antenna pattern as well as sensor transducer through series and parallel antenna loop access methods to create a wireless sensor system based on near-field communication (NFC). This system can offer real-time sensing and monitoring of changes in food packaging environment by non-contact recognition way, making it highly promising for future applications in intelligent packaging.