Data Rate Research Articles

Design of higher gain linearly polarized 2×2 microstrip patch array antenna for wireless communication

The fifth-generation technology is popular and best as far as data rates are concerned for wireless applications. To meet the increased demand of the modern world for faithful communication, this research work is carried out. In this approach, a single patch, 1×2 array, and 2×2 array are designed using a low-cost FR4 dielectric substrate ( =4.4) covering the 3.3–3.8 GHz frequency band. Due to the lack of gain from arrays in the present research, an attempt is made to achieve excellent gain from arrays with a minimum number of patches. First, the gain of a single inset-fed antenna is compared with another normal single patch of the same thickness but with an additional air dielectric medium. Next, the second single patch is extended to obtain a rectangular 1×2 array and a 2×2 array antenna. A second single patch measuring 50×32.5×0.8 mm is designed assuming an infinite ground plane. It has 3mm air gap between the patch strip and the ground. Air acts as a second dielectric layer that reduces power loss. This allows a maximum gain of 15.2 dB with a return loss of -22 dB. Also, antenna efficiency and bandwidth are 91% and 267.69 MHz, respectively.

Low-power body-coupled transceiver for miniaturized body area networks

As wearable devices continue to proliferate, seamlessly integrating them into wireless body-area networks (WBANs) becomes increasingly crucial. Body-coupled communication (BCC) emerges as a promising WBAN technology, utilizing the human body itself as a transmission channel. This paper presents a novel BCC transceiver designed for efficiency and miniaturization. The proposed transceiver prioritizes reliable data transmission with a convolutional encoder. It leverages a simple direct digital synthesizer (DDS) for frequency shift keying (FSK) modulation, minimizing chip area. At the receiver, a Viterbi decoder (VD) ensures accurate data recovery. This design shines in its resource efficiency. It occupies less than 1% of an Artix-7 FPGA, operates at 268.77 MHz with a mere 111 mW power consumption, and achieves a remarkable data rate of 13.78 Mbps. This translates to a hardware efficiency of 44.46 Kbps/slice, surpassing existing transceivers. Moreover, the BCC transceiver exhibits a stellar bit error rate (BER) of over 10⁻⁷ under realistic body channel conditions. Overall, this work presents a highly efficient BCC transceiver with significant improvements in chip area, power consumption, and data rate compared to existing designs. This paves the way for practical and miniaturized WBAN solutions for future wearable applications.

A low-power AE b-value sensor for structural health monitoring

An increase in the quantity of aging infrastructure has become a major social issue. It is thus necessary to properly maintain and manage aging infrastructure, which incurs increasingly large maintenance costs. Therefore, there is a demand for maintenance and management using low-cost and wide-application technologies such as Internet of Things (IoT). We propose a unique, ultra-low-power acoustic emission b-value sensor for structural health monitoring. Acoustic emission (AE) is an elastic wave generated by crack generation or growth inside a material. The characteristics of AE, such as waveform, source frequency, source location, and velocity, can indicate damage affecting material strength. When focusing on the source frequency, the b-value, which is the slope of AE amplitude-frequency distribution derived from the source frequency, is important and widely used as an indicator of material integrity. The proposed sensor was developed to detect this b-value trend more conveniently than ever and to achieve continuous structural or machinery health monitoring. We pursued two key points: ultra-low power consumption and long-distance wireless transmission, which enabled the AE sensor to be applied as an IoT sensor. The wake-on-AE algorithm, which wakes the sensor when AE waves reach the sensor, enables AE sensing to consume a very low current of 172μA on two dry batteries. Generally, the waveform of AE is very short in duration, such as microseconds to milliseconds. If the sensor did not wake up and take measurements in such a short time, the AE wave would pass, and the sensor would fail to measure AE. Therefore, we developed a unique analog- digital co-circuit technology that uses a peak-hold circuit to extract AE features with less sampling. In addition, sensor edges reduce data rates through statistical analysis and transmit data using low-power wide-area networks. In this paper, we present validation results obtained with the sensor on bearings. We performed validation experiments with faulty and normal bearings, generating AEs with different b-values. The developed sensor, operated with two dry batteries, and the AE measurement systems for verification simultaneously acquired the AE generated by the bearing rotation. As a result, we successfully confirmed that the developed sensor provides almost the same results as conventional AE systems in b-value measurement with ultra-low power consumption.

Dynamic base station allocation for 6G wireless networks through narrow neural network

The 6G wireless communication system will utilize the terahertz (THz) frequency band (0.1-10 THz) to meet customer demand for increased data rates and ultra-high-speed communication in future applications. The exponential surge in data traffic, which is supported by dynamic resource allocation. To mitigate this challenge, the use of artificial intelligence-based methods, such as narrow neural network (NNN), can help to smooth the performance of the network. In this paper, an NNN-based approach for dynamic base station allocation for 6G wireless networks is proposed 14 different 6G parameters used to train the NNN model, initially achieving an accuracy of 89.5% and an F1 score of 0.72 for 200 users. Results demonstrate the efficacy of the proposed NNN approach for dynamic decision-making in 6G networks and its potential for application in other domains where similar problems exist. Moreover, the proposed narrow neural network model shows improved results with an increase in number of users and decrease in fully connected layers and regularization strength (lambda). The validation accuracy received is 98.9% and 99.6% for thousand users with single fully connected layer, none (linear) activation function and regularization strength lambda values of 0.01 and 0.001.

60 GHz millimeter-wave indoor propagation path loss models for modified indoor environments

The 60 GHz band has been selected for short-range communication systems to meet consumers’ needs for high data rates. However, this frequency is attenuated by obstacles. This study addresses the limitations of the 60 GHz band by modifying indoor environments with square loop (SL) frequency selective surfaces (FSSs) wallpaper, thereby increasing its utilization. The SL FSS wallpaper response at a 61.5 GHz frequency has been analyzed using both MATLAB and CST Studio Suite software. ‘Wireless InSite’ is also used to demonstrate enhanced wave propagation in a building modified with SL FSSs wallpaper. The demonstration is applied to multiple input multiple output system to verify the effectiveness of FSSs on such systems’ capacity, as well as the effect of the human body on capacity. Simulation results presented here show that modifying a building using SL FSS wallpaper is an attractive scheme for significantly improving the indoor 60 GHz wireless communications band. This paper also presents and compares two large-scale indoor propagation path loss models, the close-in (CI) free space reference distance model and the floating intercept (FI) model. Data obtained from ‘Wireless InSite’ over distances ranging from 4 to 14.31 m is analyzed. Results show that the CI model provides good estimation and exhibits stable behavior over frequencies and distances, with a solid physical basis and less computational complexity when compared to the FI model.

A wireless-power and data-transfer using inductive RF link and ASK modulation

This paper aims to present a novel trans-cutanaeous, wireless and an efficient radio frequency (RF) inductive power and data link (IPDL) based on amplitude shift key (ASK) - modulator with an efficient ‘Class-E’– RF ‘power amplifier’ that is applicable to implantable medical devices (IMDs). The IPDL system comprises an external device placed on exterior to human skin to transmitting power and data to IMDs like implantable micro-systems (cardiac pacemakers, cochlear implants, retinal implants, deep brain stimulators) to excite and monitor respective neural and muscular system. The entire system is designed to operate with a ‘low-band-frequency’ of 4 MHz by avoiding the problem of tissue heating. A practical model for the IPDL with results is presented. Various graphs such as frequency vs primary coil/secondary coil output are plotted and shown. Typical specifications of the exterior device, namely, the modulation-index (MI) and the modulation-rate (MR) are 40% and 4.3% respectively with a data rate of 172 Kbps. The design is simulated with electronic workbench MULTISIM 12.0 and TINA Ver 9.

PAPR reduction techniques Optimization-based OFDM signal for wireless communication systems

OFDM (Orthogonal Frequency Division Multiplexing) is a widely used modulation technique in many standards such as Wi-Fi (Wireless Fidelity), LTE (Long Term Evolution), and 4G. It allows for high transmission data rates and excellent spectral efficiency. However, one of the main limitations of OFDM is its high PAPR (Peak-to-Average Power Ratio). In this paper, we will first describe some methods to reduce the PAPR associated with OFDM signal. We will discuss some methods such as the clipping, the Selective mapping SLM, the Partial Transmit Sequence (PTS), and the Tone Reservation (TR). Let's list their advantages and disadvantages before focusing on the TR method which we will detail. This work aims to improve the performance of the TR method in terms of speed of convergence and reduction of the PAPR, using the conjugate different algorithms while respecting the frequency specifications of the IEEE 802.11a standard. The proposed algorithm which is based on the gradient method, Conjugate gradient methods, and Quasi-Newton method shows good performance regarding PAPR reduction and speed of convergence. The choice of an appropriate technique depends on several factors: required PAPR reduction, acceptable complexity, and performances (spectral efficiency, latency, etc.). A trade-off must be found in practice between these different criteria. It has been shown that the Quasi-Newton method algorithm with its two variants converges more quickly.

5G Wireless Technology: Spectrum Sharing and Heterogeneous Networks

Abstract: This paper addresses the critical challenge of 5G network cell planning, emphasizing the essential role of estimating the number of cells or base stations required for a given area and user bandwidth. The proposed model explores four scenarios with varying network parameters to determine the optimal base station deployment. The increasing demand for 5G networks necessitates a focus on small cells or femtocells, offering advantages such as consistent coverage, power adjustment, energy efficiency, and higher data rates. However, deploying excessive femtocells may lead to unnecessary handovers, requiring optimization strategies. The study introduces an analytical model for heterogeneous cellular networks, integrating fourth and fifth-generation systems. The model, represented by a two dimensional Markov Chain, employs a novel decomposition approach for analyzing system performance measures. Validation is conducted through simulation and simultaneous equation systems. The proliferation of mobile devices and data traffic necessitates dense 5G network deployments, with small cells gaining traction due to their versatile coverage, power adaptability, energy efficiency, and higher data rates. However, an excessive deployment of small cells can lead to frequent handovers, prompting the need for enhanced handover strategies and coexistence with other technologies in the 5G landscape. The paper concludes by highlighting the impending need for practical implementation testing of 5G systems, emphasizing the significant role of small cell deployments. It discusses an initiative focusing on testing small cellenabled operator business models in real-world scenarios, anticipating the pivotal role of small cells in future 5G systems.

Effect of the correlated color temperature of a phosphor-converted LED on indoor visible light communication

Correlated color temperature (CCT) is an important parameter of the phosphor-converted LED (PC-LED); international standards specify its range in different scenarios. However, little has been done to investigate the effect of CCT on the performance of visible light communication (VLC). In this paper, we propose an analytical model for the transmission performance of an LED VLC system based on the dual components of blue and yellow light from the luminescence mechanism of the PC-LED. On this basis, the effects of CCT on the PC-LED’s input current and output optical power between the dual components are analyzed. The simulation results show that the increase of CCT expands the modulation bandwidth of the PC-LED, and the trend of the BER with CCT is also related to the transmission data rate. In addition, the maximum data rate of the PC-LED with CCT from 2700 K to 6500 K under a certain transmission distance is also simulated in this paper.

Miniaturized high signal-to-noise ratio optical air data system using a compact multi-axis parallel transceiver for airborne application

We have developed a miniaturized multi-channel parallel optical air data system with high signal-to-noise ratio for airborne application. In the system, we designed a fiber amplifier with multi-channel high-energy output that was respectively used as the transmitting signals and a compact multi-axis transceiver with an entrance pupil diameter of 70 mm that was used to receive multi-channel signals simultaneously. We demonstrated the performance of our system both on ground and on board. On ground, the measured line-of-sight speed had an average error of 0.02 m/s and a standard deviation of 0.15 m/s. On board, the standard deviation between the true air speed, angle of attack, and angle of sideslip measured by our system and a commercial Swiss air data system was 1 kt, 0.68°, and 0.54°, respectively, and those standard deviation between our system and a system with the same design but employing multiple single-axis telescopes with entrance pupil diameter of 30 mm was 0.34 kt, 0.36°, and 0.28°, respectively. The signal-to-noise ratio of our system was 4.5 times higher than that of the system with small single-axis telescopes. Our system is very promising for airborne applications because of its small volume, high signal-to-noise ratio, and high data rate.

A Learning-Based Energy-Efficient Device Grouping Mechanism for Massive Machine-Type Communication in the Context of Beyond 5G Networks

With the increasing demand for high data rates, low delay, and extended battery life, managing massive machine-type communication (mMTC) in the beyond 5G (B5G) context is challenging. MMTC devices, which play a role in developing the Internet of Things (IoT) and smart cities, need to transmit short amounts of data periodically within a specific time frame. Although blockchain technology is utilized for secure data storage and transfer while digital twin technology provides real-time monitoring and management of the devices, issues such as constrained time delays and network congestion persist. Without a proper data transmission strategy, most devices would fail to transmit in time, thus defying their relevance and purpose. This work investigates the problem of massive random access channel (RACH) attempts while emphasizing the energy efficiency and access latency for mMTC devices with critical missions in B5G networks. Using machine learning techniques, we propose an attention-based reinforcement learning model that orchestrates the device grouping strategy to optimize device placement. Thus, the model guarantees a higher probability of success for the devices during data transmission access, eventually leading to more efficient energy consumption. Through thorough quantitative simulations, we demonstrate that the proposed learning-based approach significantly outperforms the other baseline grouping methods.

Adaptive Mobility-Based IoT LoRa Clustering Communication Scheme

Long Range (LoRa) as a low-power wide-area technology is distinguished by its robust long-distance communications tailored for Internet of Things (IoT) networks. Because LoRa was primarily designed for stationary devices, when applied to mobile devices, they become susceptible to frequent channel attenuation. Such a condition can result in packet loss, higher energy consumption, and extended transmission times. To address these inherent challenges posed by mobility, we propose an adaptive mobility-based IoT LoRa clustering communication (AMILCC) scheme, which employs the 2D random waypoint mobility model, strategically partitions the network into optimal spreading factor (SF) regions, and incorporates an adaptive clustering approach. The AMILCC scheme is bolstered by a hybrid adaptive data rate (HADR) mechanism categorized into two approaches, namely intra-SF and inter-SF region HADRs, derived from the standard network-based ADR mechanism for stationary devices, to ensure efficient resource allocation for mobile IoT LoRa devices. Evaluation results show that, based on simulations at low mobility speeds of up to 5 m/s, AMILCC successfully maximizes the packet success ratio to the gateway (GW) by over 70%, reduces energy consumption by an average of 55.5%, and minimizes the end-to-end delay by 47.62%, outperforming stationary schemes. Consequently, AMILCC stands as a prime solution for mobile IoT LoRa networks by balancing the high packet success ratio (PSR) with reliability with energy efficiency.

A deep learning based approach for image retrieval extraction in mobile edge computing

AbstractDeep learning has been widely explored in 5G applications, including computer vision, the Internet of Things (IoT), and intermedia classification. However, applying the deep learning approach in limited-resource mobile devices is one of the most challenging issues. At the same time, users’ experience in terms of Quality of Service (QoS) (e.g., service latency, outcome accuracy, and achievable data rate) performs poorly while interacting with machine learning applications. Mobile edge computing (MEC) has been introduced as a cooperative approach to bring computation resources in proximity to end-user devices to overcome these limitations. This article aims to design a novel image reiterative extraction algorithm based on convolution neural network (CNN) learning and computational task offloading to support machine learning-based mobile applications in resource-limited and uncertain environments. Accordingly, we leverage the framework of image retrieval extraction and introduce three approaches. First, privacy preservation is strict and aims to protect personal data. Second, network traffic reduction. Third, minimizing feature matching time. Our simulation results associated with real-time experiments on a small-scale MEC server have shown the effectiveness of the proposed deep learning-based approach over existing schemes. The source code is available here: https://github.com/jamalalasadi/CNN_Image_retrieval.

5G IoT Networks

The abstract delves into how the advent of 5G is revolutionizing the Internet of Things (IoT) across various industries, with a particular focus on its ability to provide ultra-low latency, high data rates, and support for a massive number of connected devices, enabling real-time data transmission. It highlights the mutually beneficial relationship between 5G and IoT, which is driving innovation in sectors such as smart cities, healthcare, agriculture, and transportation. The abstract also addresses important challenges like security and interoperability, emphasizing the need for strategic deployment of 5G-enabled IoT solutions. Furthermore, it explores the potential of edge computing and AI-driven analytics to unlock new possibilities in IoT implementations. In summary, the abstract underscores the transformative power of 5G in shaping IoT ecosystems, offering unparalleled opportunities for innovation, efficiency, and value creation.

Multiband multiple‐input multiple‐output antenna design with high‐resolution circularly polarized wireless communication

SummaryA design problem of multiband multi‐input, multi‐output (MIMO) antenna arrays for maximal side lobe level lessening with constraint of a fixed beam width is dealt with. Multiband MIMO antenna is the most promising solution in a communication system, due to its maximal speed, higher data rate, and short‐range communication. Conversely, MIMO faces several complications including designing a proper antenna for a specific bandwidth and lesser antenna efficacy. In this manuscript, a high‐resolution CP multiband MIMO (HS‐CPMB‐MIMO) antenna design for wireless communication is proposed. MIMO antenna plays a vital part in the present wireless technology at MSA. A multiband microstrip line‐fed two‐port hybrid CPMIMO antenna is intended and fabricated. The proposed microstrip feed antenna contains a tapering structure, and the inverted L‐shaped slots in the radiating element are opened on both sides to present notches in sub‐6‐GHz frequencies. The inverted L‐shaped slots is positioned in the middle of asymmetric Z‐shaped radiating elements for enhancing the isolation among the two ports. The invention of a multiband MIMO antenna with four CP bands has an efficient ECC value because of a large L‐shaped slot in the ground as well as a protruding Z‐shape ground stub embedded with circular rings to have highly isolated cells. Finally, the proposed HS‐CPMB‐MIMO antenna design is implemented by utilizing simulation software CST Microwave Studio, and it is evaluated with the performance metrics. The simulation outcomes of the proposed HS‐CPMB‐MIMO antenna provide 36.34%, 57.36%, and 25.33% higher BW, 24.13%, 15.96%, and 21.22% higher gain compared with existing methods.

Improving Performance of MC-CDMA Systems Using UTTCM Channel Coding

Over the past decade, personal communications have witnessed exponential growth, fueled by the increasing number of connected users and the diversity of transmitted data types. This expansion necessitates a boost in the transmission systems' capacity to accommodate higher user numbers and data rates, simultaneously striving to optimize cost and complexity. Consequently, future communication systems are pivoting towards multi-carrier spread spectrum techniques (MC-CDMA), capitalizing on the robustness of OFDM multi-carrier transmissions against multipath propagation and leveraging the flexibility of the code division multiple access (CDMA) technique. This study addresses data transmission quality-related concerns within an MC-CDMA system by implementing UTTCM error correction codes. These codes aim to enhance channel spectrum efficiency and mitigate error probability. Simulation results demonstrate that the proposed transmission scheme offers significant improvements in terms of bit error rate and signal-to-noise ratio, while maximizing the bandwidth shared among users. Additionally, the incorporation of such equalization techniques as zero forcing (ZF) and minimum mean square error (MMSE), ensures extensive compensation for the channel selectivity effect.

Orbital Angular Momentum Multiplexing Architecture for OAM/SDM Passive Optical Networks

Optical Angular Momentum multiplexing (OAM) is a technology of communication systems that enables high-capacity optical communication networks. One of the most important determinants of this technology is the channel capacity, loss of power, and BER that accompany the transmission. This article proposed an OAM/SDM G-PON architecture for a MIMO-type communication system that supports (OAM/SDM G-PON)Technology. The proposed architecture is used to multiplex the downstream OAM channels and the upstream SDM channels, and an OAM multiplexer/demultiplexer (OAM-MUX/DEMUX) is used to multiplex and demultiplex the OAM channels. In the OAM/SDM G-PON system, the signal will propagate through three different mediums, each one having its own nature in influencing the power of the signal that passes through that medium. The experimental study has bidirectional transmissions with the DS/US data rate of 2.4 Gbps and Binary Phase Shift Keying (BPSK) downstream and 1.2 Gbps upstream. The observed results showed that the bit-error rate (BER) is a function of coupling angles and increases with the increasing in the OAM ring size

The Past, Present, and Future of the Internet: A Statistical, Technical, and Functional Comparison of Wired/Wireless Fixed/Mobile Internet

This paper examines the quantitative and qualitative situation of the current fixed and mobile Internet and its expected future. It provides a detailed insight into the past, present, and future of the Internet along with the development of technology and the problems that have arisen in accessing and using broadband Internet. First, the number of users and penetration rate of the Internet, the various types of services in different countries, the ranking of countries in terms of the mean and median download and upload Internet data speeds, Internet data volume, and number and location of data centers in the world are presented. The second task introduces and details twelve performance evaluation metrics for broadband Internet access. Third, different wired and wireless Internet technologies are introduced and compared based on data rate, coverage, type of infrastructure, and their advantages and disadvantages. Based on the technical and functional criteria, in the fourth work, two popular wired and wireless Internet platforms, one based on optical fiber and the other based on the 5G cellular network, are compared in the world in general and Australia in particular. Moreover, this paper has a look at Starlink as the latest satellite Internet candidate, especially for rural and remote areas. The fifth task outlines the latest technologies and emerging broadband Internet-based services and applications in the spotlight. Sixthly, it focuses on three problems in the future Internet in the world, namely the digital divide due to the different qualities of available Internet and new Internet-based services and applications of emerging technologies, the impact of the Internet on social interactions, and hacking and insecurity on the Internet. Finally, some solutions to these problems are proposed.

Non Orthogonal Multiple Access (NOMA) Using a Nonlinear Energy Harvesting Model

AbstractThis paper derives and optimizes the throughput of NOMA with nonlinear energy harvesting. The Base Station (BS) harvests energy from the received Radio Frequency signal. Then, the BS uses the nonlinear harvested power to diffuse packets to N users. We suggest to optimize harvesting time and the powers of users to optimize the data rate. The optimization of NOMA powers and the harvesting process were not yet performed with a non linear energy harvesting model. The study is performed for Rayleigh channels in the presence of nonlinear energy harvesting model. Furthermore, the theoretical results were confirmed using MATLAB computer simulations.

An Improved PAPR Reduction Scheme using Green OFDM

OFDM has become popular method to be applied in data communication as it has high data rate. Selective Mapping OFDM (SLM OFDM) is introduced to over-come the OFDM’s disadvantage which is high PAPR. SLM OFDM offers PAPR reduction by selecting OFDM waveform with the lowest PAPR among many copies of waveform candidates, U. As the world become more digitalized and demanding, Green OFDM shows up with more candidates, U^2/4, without making computation more complex. More candidates will promote more choices with lower PAPR values compare to the SLM OFDM. In the recent years, re-searchers have come out with a new improved Green OFDM version 2 with more waveform candidates to be chosen, U^2. The improved Green OFDM ver-sion 2 scheme will produce lower PAPR values compare to the SLM OFDM and the original Green OFDM. Thus, technologies with higher data transmission are able to be created.