Low Data Rate Research Articles

High-rate bridge displacement monitoring with low-rate virtual reference station data

We present a new Global Navigation Satellite Systems (GNSS) positioning approach that utilizes low-rate Virtual Reference Station (VRS) data to achieve high-rate displacement monitoring. The method integrates tightly the VRS technology with asynchronous Real-Time Kinematic (RTK) method to overcome the limitation of VRS in high-rate structural health monitoring (SHM) applications. When this approach is used, no local reference station is required so that the efforts and cost of setting up reference stations can be avoided. Experiments with datasets from a controlled shaking platform and a long-span bridge in Hong Kong with both temperature and typhoon excitations have indicated that the proposed approach worked effectively. The results demonstrated that when a baseline exceeded about 3 km, the vertical errors of RTK GNSS positioning could be up to about 15.9 mm (standard deviations), insufficient for most SHM applications. In this case, the proposed method enhanced the accuracy by about 60% to 6.0 mm when using VRS data openly available in Hong Kong. The accuracy achieved was equivalent to that of RTK positioning using a 1.2 km baseline. The shaking platform trial demonstrated that the monitoring station could be up-sampled to 100 Hz without a noticeable loss in accuracy. The proposed method could capture precisely the peak frequencies and amplitudes of vibrations, with errors as low as 0.001 Hz and 0.1 mm. This method broadens the applicability of GNSS positioning in SHM applications.

Enhancing sustainable healthcare practices through energy-efficient wireless body area networks

This paper explores how the integration and performance of Wireless Body Area Networks (WBANs) contribute to sustainable healthcare practices. WBANs play a crucial role in reducing the environmental footprint of healthcare systems by providing continuous monitoring that can prevent unnecessary hospitalizations and reduce the consumption of disposable medical supplies. Additionally, the design of WBANs using environmentally friendly materials, low-power devices, and recyclable components is discussed to optimize the sustainability of healthcare practices. To enhance infrastructure, services, and quality of life, new technologies have been integrated to improve WBANs. Patients' essential health data may be continuously and instantly collected thanks to these networks, and healthcare providers can receive the data right away for quick analysis and action. WBANs have healthcare benefits, but there are also major drawbacks. Technologies that can combine low power consumption, minimal delay, and high enough data rates are needed for WBANs in order to support a variety of medical applications. The effectiveness of the LoRaWAN and IEEE 802.15.6 technologies in WBAN is assessed in this paper. With the use of seven crucial metrics which are throughput, arrival rate, delay, energy consumption, residual energy, network lifetime, and packet delivery ratio (PDR), this paper seeks to study which technology is appropriate with WBANs using NS3 as a simulation program. With network parameters, 1000 seconds, and 50 nodes, the paper evaluated the performance of each technology. The results show that IEEE 802.15.6 is superior in terms of throughput, PDR, and arrival rate whereas LoRaWAN is superior in terms of energy consumption, residual energy, network lifetime, and delay.

Performance investigation of a VLC-PDM based UWOC system under adverse underwater conditions with varying chlorophyll levels

Underwater Wireless Optical Communication (UWOC) has emerged as a promising solution to meet the growing demand for high-speed, reliable communication in marine environments. The limitations of traditional acoustic and radio frequency (RF) communication methods in underwater settings, such as low data rates, high latency, and susceptibility to environmental conditions, have propelled the exploration of optical communication technologies. This work introduces a Visible Light Communication (VLC)-based UWOC system employing Polarization Division Multiplexing (PDM) to enhance data transmission rates and system performance. The proposed system capitalizes on the advantages of VLC, including high bandwidth, low latency, and immunity to electromagnetic interference, to achieve efficient underwater communication. By incorporating PDM, the system effectively doubles the channel capacity without increasing the bandwidth, achieving a data transmission rate of 1Gbps per channel. The performance of the proposed system was evaluated under various underwater conditions, including freshwater, clear ocean water, coastal water, and turbid ocean water with different chlorophyll concentrations. The results demonstrated the system's ability to maintain a low Bit Error Rate (BER) across diverse marine environments, showcasing its potential for real-world applications in underwater communication networks.

Dynamic Injection and Permutation Coding for Enhanced Data Transmission.

In this paper, we propose a novel approach to enhance spectral efficiency in communication systems by dynamically adjusting the mapping between cyclic permutation coding (CPC) and its injected form. By monitoring channel conditions such as interference levels and impulsive noise strength, the system optimises the coding scheme to maximise data transmission reliability and efficiency. The CPC method employed in this work maps information bits onto non-binary symbols in a cyclic manner, aiming to improve the Hamming distance between mapped symbols. To address challenges such as low data rates inherent in permutation coding, injection techniques are introduced by removing δ column(s) from the CPC codebook. Comparative analyses demonstrate that the proposed dynamic adaptation scheme outperforms conventional permutation coding and injection schemes. Additionally, we present a generalised mathematical expression to describe the relationship between the spectral efficiencies of both coding schemes. This dynamic approach ensures efficient and reliable communication in environments with varying levels of interference and impulsive noise, highlighting its potential applicability to systems like power line communications.

Performance Comparison of CC AODV and Optimized AODV K-Means Clustering Using NS3

Nowadays, many studies have been interested in Ad Hoc Wireless Networks because of their low cost, when there is a need to communicate using a network without any infrastructure. Ad Hoc On-Demand Distance Vector (AODV) is a routing protocol for mobile ad hoc networks (MANET) and other wireless ad hoc networks. AODV was co-developed in July 2003 at the NOKIA Research Center, University of California, Santa Barbara and University of Cincinnati by C. Perkins, E. Belding-Rover an S.Das. AODV is a routing protocol used by ZigBee - a low power wireless ad hoc network with low data rates. AODV is included in the proactive routing protocol. The advantage of using this routing protocol is that it has economical resources, because resources are not needed to store information about routes to other nodes. However, this AODV has a drawback, namely the packet that will be sent has a long delay in anti-node origin waiting for the protocol to find the path to be passed. There are many papers that optimize AODV, including CC AODV and K Means Clustering AODV. Based on the paper “CC-AODV: An effective multiple paths congestion control AODV”, a control scheme called CC AODV has been created, namely managing routing conditions by significantly increasing packet sending rates while reducing packet drop rates, and based on the paper “An Energy Efficient Clustering Using K-Means and AODV Routing Protocol in Ad hoc Networks”. Based on both paper, in this study the objectives to be achieved are: a) Analyze the performance of using CC AODV and K Means Clustering AODV based on the number of nodes. b) how much influence the number of nodes has on the performance of CC AODV and K Means clustering AODV c) Performance analysis is performed on throughput, end to end delay, packet loss, packet delivery ratio. This paper begins by looking at the literature covering MANET, AODV, CC AODV, and K-Means Clustering AODV. On the result section the test results such as end to end delay, throughput, packet delivery ratio, and packet loss ratio are documented. The conclusion summarizes key points and is followed by the references.

5G as Communication Platform for Solar Tower Plants

Wiring of heliostat fields for solar tower plants is a cost factor that becomes more important as the overall cost target is decreasing. Wireless heliostats with radio communication and autarchic energy supply have therefore been proposed in the past. But none of the communication solutions investigated so far could realistically scale to commercial size plants with tens of thousands of heliostats. Moreover, the digitalization of CSP plants with numerous mobile and stationary sensor systems requires a suitable data communication, too. The new generation of mobile radio communication (5G) is capable of handling the heterogenous communication profile portfolio comprising large numbers of units with low data rates – like heliostats - and few units with very large data volume – like e.g. drone-based camera systems. The communication requirements of a typical solar tower installation are assessed in this work and a data traffic model is created for the most relevant communication channels. The various existing 5G implementations are assessed to find the most suitable solution. Different operator models for 5G are considered and their applicability in CSP target countries is discussed. A simulation test case is presented that models the radio communication traffic of a heliostat field control during a cloud passage. Finally, the experimental 5G campus network is introduced that is currently installed at the Solar Tower Jülich research plant and will be operated in the upcoming months to demonstrate the technical feasibility of 5G radio for communication in solar fields.

Progressive updates of convolutional neural networks for enhanced reliability in small satellite applications

Small satellites enable many important applications for both economic and scientific purposes. Many of these applications are inherently data-centric and rely on large amounts of high-resolution satellite imagery to be delivered in a timely manner. However, communicating this data to Earth is challenging due to intermittent connectivity, high packet losses, low data rates, and similar issues. Therefore, efficient onboard prioritization and data processing are essential for future satellite missions. Machine learning methods, such as deep neural networks, are very suitable for such prioritization, as they are already used extensively for satellite imagery processing and they can be deployed onboard of satellites. However, updating them to support new classification requirements when the satellite is already in orbit is difficult, as often multiple passes are required to complete model transmission due to the communication challenges. To cope with this issue, we propose a progressive transmission mechanism for model updates, which leverages vector quantization and arithmetic coding. Our mechanism allows to achieve high accuracies even with partially updated models. Evaluation results show that our mechanism significantly outperforms other less optimized transmission schemes.

A CRITIC-CODAS Approach for Ranking WirelessCommunication Technologies in Precision Agriculture: Application to Irrigation System

This study evaluates and ranks wireless communication technologies for agricultural irrigation systems using the CRITIC-CODAS multi-criteria decision-making method. Technologies including WSN, LPWAN, LoRa, 5G, IoT, and NB-IoT are compared based on range, power consumption, data rate, coverage, latency, battery life, and device density. The CRITIC method is used to objectively determine criteria weights, with data rate, latency, and battery life emerging as the most important factors. 5G ranks highest with its superior data rate and device density, but its high-power needs may limit suitability for remote agriculture. IoT offers a balanced option across multiple criteria, while WSN excels in power efficiency and battery life. LPWAN, LoRa, and NB-IoT provide excellent range and battery life for wide-area, low-power applications despite lower data rates. The analysis provides a framework for stakeholders to select appropriate technologies based on specific agricultural requirements. Matching wireless technologies to irrigation needs can enhance agricultural sustainability and productivity. Further research could explore technology combinations, cost factors, and real-world testing. This systematic evaluation approach can be extended to other smart agriculture applications to optimize technology adoption.

Sprite Durations Measured With a Neuromorphic Sensor

AbstractNeuromorphic sensors have inherently‐fast speeds and low data rates, which potentially make them ideal for the observation of transient sources, such as lightning and sprites. Particularly, for remote observations. In this article, we report the first observations of sprites from the ground with a neuromorphic sensor. These observations are accompanied by measurements with established instruments such as low‐light level and high‐frame rate cameras. We determine that neuromorphic sensors can capture sprites and determine their duration to an accuracy of roughly 6 ms. Average sprite durations were found to be 55 ms within our data set. We have also ascertained that sprites may be too dim for the neuromorphic sensors to resolve the internal spatiotemporal dynamics, at least without the aid of intensifiers.

Voice Over for Home Security System

The Smart Home Voice Control Hub is an advanced, integrated system design to seamlessly manage and operate a variety of smart home devices using voice commands. Recent years have witnessed significant advancements in home automation driven by wireless technologies. Among these, the IEEE 802.15.4 standard, RF, stands out for its low data rate, extended battery lif e, and secure networking capabilities. This article details a method for testing voice control implementation in smart homes, emphasizing compatibility with existing infrastructure. Utilizing low-power RF wireless modules and a microcontroller, the system caters to the needs of elderly and disabled individuals living independently. By focusing on voice recognition, it off ers enhanced security and control over household lighting and appliances. Experimental validation demonstrates the system's effectiveness in practical applications.

Intelligent architecture and platforms for private edge cloud systems: A review

The development of cloud, fog, and edge computing has led to great advances in reducing latency and saving bandwidth, and these methods have therefore been broadly applied in various domains, including healthcare, transportation, and the Internet of Things (IoT). Traditional edge computing solutions have proven to be insufficient in fulfilling the demanding prerequisites of low latency and high data rates. Additionally, publicly available edge cloud solutions fail to meet the required standards for ensuring privacy protection. Consequently, Private Edge Cloud Systems (PECSs) have garnered attention as a prospective solution owing to their capacity to mitigate privacy risks and their significant computing capacity. PECS research has seen significant growth, but there is a lack of detailed review of its issues, approaches, and applications in the literature. To explore the potential application value of PECS, this paper provides a systematic review of intelligent platforms and architecture for PECSs. Specifically, an overview of the fundamental characteristics of PECSs is provided. Second, we classify intelligent platforms and architectures and analyze their implementation techniques and realization methods. Third, we discuss four specific application scenarios. Finally, promising future research directions are discussed. The findings of this research show that PECSs can effectively meet the requirements for low latency and privacy protection and are a fertile domain for further research.

Design and performance evaluation of SEANet, a software-defined networking platform for the Internet of Underwater Things

This paper presents the design and performance evaluation of the SEANet platform, a software-defined acoustic modem designed for enhancing underwater networking and Internet of Underwater Things (IoUT) applications. Addressing the limitations of traditional acoustic modems, which suffer from low data rates and rigid architectures, SEANet introduces a versatile, adaptive framework capable of reconfiguring all layers of the protocol stack in real-time to accommodate diverse marine applications. The platform integrates high-performance, wideband data converters with modular hardware and software components, enabling real-time adaptation to changing environmental and operational conditions. Experimental evaluations conducted in oceanic settings demonstrate the SEANet capability to significantly exceed the performance of existing commercial underwater modems, supporting data rates up to 150 kbit/s and effectively doubling the performance metrics of conventional systems. Our robust testing also highlights the SEANet proficiency in channel estimation, Orthogonal Frequency-Division Multiplexing (OFDM) link establishment, and interoperability through the JANUS communication standard. Our results underscore the SEANet potential to transform underwater communication technologies, providing a scalable and efficient solution that supports high data rate applications and fosters the expansion of IoUT deployments.

Cooperative MAC Protocol based on Best Data Rate (CMAC-DR)

As wireless signals are broadcast in nature, which implies that, a broadcast communication purposive to a predetermined destination may be received by a non-intended intermediate station. Cooperative transference, which employ interposed stations to pass on the eavesdropped data to attain the contrast gains, has a substantial capability to revamp the channeling effectiveness in wireless systems. In this it is evident that having cooperation amid stations in a wireless system can accomplish higher throughput with enhanced network lifetime. Proffered work bestows a model for medium access layer called Cooperative MAC protocol based on optimal Data Rate (CMAC-DR). In the proffered work, stations with more data rate aid stations having lesser data rate in their communication by redirecting their congestion. In CMAC-DR model, utilizing the conveyance of eavesdropped information, potential helper stations with more data rate Send out Helper Ready to Send (HRTS), the stations with less data rate maintains a table, called Co-op table of potential helper stations, that can aid in its transmissions. During communication, the source station with low data rate chooses either transmitting by the way of a helper station, so that it lowers the end to end transference delay and increases the throughput or opt only direct transmission, if no potential helper is found or if CMAC-DR becomes an overhead. By analyzing varied simulated scenarios, CMAC-DR evaluates the elevation in the overall network lifetime, throughput and minimization of delay. The CMAC-DR protocol is unambiguous and in accordant with legacy 802.11 also when compared to this, we find improved performance in terms of delay throughput and network lifetime since data rate is considered as relay selection condition.

A low-complexity crest factor reduction design for 5G NR sub-6 GHz digital front-end with restricted peak regrowth

In recent years, orthogonal frequency division multiplexing (OFDM) has gained widespread adoption in communication technologies, exemplified by long-term evolution (LTE), 5th generation new radio (5G NR sub-6 GHz), and others. These technologies are instrumental in meeting the increasing demands for high data rates, throughput, and reliable downlink network access. However, a notable challenge associated with OFDM is the high peak-to-average power ratio (PAPR), imposing limitations on the efficiency of power amplifiers that often operate with significant back-offs. To mitigate this issue, the widely employed crest factor reduction (CFR) technique aims to enhance efficiency. This paper introduces a novel CFR methodology utilizing mixed and multi-iterative signal distortion-based techniques. Our approach is versatile, demonstrating effectiveness for low-bandwidth signals like LTE, as well as large-bandwidth signals reaching up to 100 MHz, as seen in 5G NR FR1. Also, digital up-sampling used to achieve the required high sample rate causes the issue of peak regrowth even after the required PAPR reduction achieved by CFR processing, which defeats the purpose of CFR. Our proposed design offers a solution to this challenge, enabling operation at a low data rate before digital up-sampling while effectively mitigating peak regrowth. Importantly, the implementation significantly reduces FPGA resource utilization, alleviating the complexity associated with multiple-input multiple-output (MIMO) radio systems. Demonstrating compliance with 3rd generation partnership project (3GPP) specifications for 5G NR on a real-time testbed, our approach stands as a practical and efficient solution for contemporary communication systems.

Detection and recognition of Chinese porcelain inlay images of traditional Lingnan architectural decoration based on YOLOv4 technology

With the rapid development of machine learning technology, it has become possible to automatically identify cultural heritage elements in traditional buildings. This research aimed to develop a machine learning model based on the YOLOv4 architecture to identify the traditional Chinese porcelain inlay pattern in the Lingnan region. The researchers collected and annotated a large quantity of Lingnan Chinese porcelain inlay image data and then used these data to train the studied model. The research results show that (1) the model in this study was specifically adjusted to effectively identify a variety of Chinese porcelain inlay pattern types, including traditional patterns such as plum blossoms and camellias. (2) In the 116th epoch, the model showed excellent generalization ability, and the verification loss reached the lowest value of 0.88. The lowest training loss in the 195th epoch was 0.99, indicating that the model reached an optimal balance point for both recognition accuracy and processing speed. (3) By comparing different models for detecting Chinese porcelain inlay images across 581 pictures, our YOLOv4 model demonstrated greater accuracy in most classification tasks than did the YOLOv8 model, especially in the classification of chrysanthemums, where it achieved an accuracy rate of 87.5%, significantly outperforming YOLOv8 by 58.82%. However, the study also revealed that under certain conditions, such as detecting apples and pears in low-light environments, YOLOv8 showed a lower missing data rate, highlighting the limitations of our model in dealing with complex detection conditions.

Ultra-low power, high-data rate, fully on-chip radio frequency on-off keying receiver for internet-of-things applications

Despite the enormous potential of energy-efficient receivers for wireless sensor networks, the large power consumption or limited data rate support impedes its extensive applications. Here, we present an energy-efficient, ultra-low power, higher data rate supporting, completely on-chip radio-frequency receiver frontend for on-off keying modulated signals in the 2.4 GHz industrial, scientific, and medical band. This compact-sized receiver is achieved by implementing temperature-resilient oscillator, pseudo-differential mixer, and a wideband detector while avoiding bulky external components such as bulk-acoustic wave resonators, crystal oscillators. Measurement results demonstrate that the proposed on-off keying receiver can decode low power level radio-frequency signals up to 5 Mbps data rate while consuming only 178 µW power. This work also demonstrates support for lower data rates at reduced power. Since the proposed receiver operates in different power modes, it can be integrated in diverse applications including internet-of-things devices and continuously monitoring biomedical/wearable implants.

Polling Mechanisms for Industrial IoT Applications in Long-Range Wide-Area Networks

LoRaWAN is a low-power wide-area network (LPWAN) technology that is well suited for industrial IoT (IIoT) applications. One of the challenges of using LoRaWAN for IIoT is the need to collect data from a large number of devices. Polling is a common way to collect data from devices, but it can be inefficient for LoRaWANs, which are designed for low data rates and long battery life. LoRaWAN devices operating in two specific modes can receive messages from a gateway even when they are not sending data themselves. This allows the gateway to send commands to devices at any time, without having to wait for them to check for messages. This paper proposes various polling mechanisms for industrial IoT applications in LoRaWANs and presents specific considerations for designing efficient polling mechanisms in the context of industrial IoT applications leveraging LoRaWAN technology.

Medical Data in Wireless Body Area Networks: Device Authentication Techniques and Threat Mitigation Strategies Based on a Token-Based Communication Approach

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a ‘data train’ and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data.

Design and Implementation of Low Power and High Data Rate Edge Coded Signaling Architecture for IoT Devices

Abstract Edge coded signaling (ECS) is a recently introduced communication protocol designed for single-channel signaling among constrained internet of things (IoT) nodes. This study aims to enhance the data rate of ECS, without increasing the clock frequency or power consumption. The goal is to develop an improved protocol that maintains the inherent advantages of ECS while achieving a higher data rate. The proposed solution, double data rate ECS (DDR-ECS), leverages both pulse edges of the ECS pulse stream for information encoding, drawing an analogy to DDR memory systems. The study presents a detailed design of low-power architecture for the DDR-ECS transceiver. This design was synthesized using a 65 nm ASIC process to evaluate its performance in terms of power consumption, gate count, and data rate. The synthesis results demonstrate that the DDR-ECS transceiver preserves the key features of ECS, including tolerance to clock frequency variations and compatibility with lightweight cryptographic algorithms. It effectively doubles the dynamic data rate to the range of 12–73.5 Mb/s while consuming an equivalent power of 13 μW and occupying a compact form factor of only 1,755 gates. The introduction of DDR-ECS represents a significant advancement in the ECS protocol, offering a novel approach to doubling the data rate without increasing the clock frequency or power envelope. This innovation retains the simplicity and efficiency of ECS, providing an enhanced communication solution for constrained IoT nodes.

AC-FPSK modulation for low-energy and low data rate optical wireless communications

This article proposes an amalgam of phase-shift keying and asymmetrically clipped frequency-shift keying (i.e., AC-FPSK) for low-energy/low-data rate optical wireless communications. We design a near-optimal, low-complexity harmonic receiver by analyzing the AC-FPSK time-domain (TD) and frequency-domain (FD) waveforms. The Euclidean distance analysis between AC-FPSK waveform pairs yields lower and upper bounds for theoretical bit error probability. Using numerical simulations, we present an exhaustive evaluation of the optimal cardinality of PSK, which illustrates the superiority of AC-FPSK. We show that AC-FPSK provides better energy efficiency versus spectral efficiency trade-off than state-of-the-art AC-FSK, direct current-FPSK, pulse amplitude modulation, and asymmetrically clipped optical orthogonal frequency division multiplexing. We also demonstrate that by making a suitable choice for the cardinality of PSK, the proposed 2-tap harmonic receiver for AC-FPSK can reach a similar complexity as the AC-FSK harmonic receiver.