Radio Interface Research Articles

Wood gas generator management system for vehicles

This article presents the design and development aspects of a software package and hardware configuration which are allows for the preparation and supply of an air-fuel mixture to a car’s internal combustion engines which using charcoal or firewood as fuel. The software package and hardware should be implemented as a fuel control system. The microcomputer processes the signals from the sensors and allows you to receive data using the semi-automatic control of the fuel system, in addition collects statistical data and provides telemetry output to the dashboard or on the remote display and can be controlled via wireless interface. The following information is recorded in the database: state of sensors, current system settings and actions performed by the user. A remote device running on the Android operating system is connected via the widespread wireless Bluetooth communication channel, real time information about the system and the fuel system control interface are displayed in graphical form.

A Fully-Integrated 64-Channel Wireless Neural Interfacing SoC Achieving 110 dB AFE PSRR and Supporting 54 Mb/s Symbol Rate, Meter-Range Wireless Data Transmission

This brief presents a 64-channel fully-integrated wireless neural interfacing SoC implemented in a 65 nm CMOS process. To minimize the weight and size of the head-stage connected to the small experimental animals, the system is designed to be powered by either a single-coil 13.56 MHz wireless power receiver or a small-sized button cell battery. A replica-biased 0.35 V 110 dB PSRR LNA is introduced to tolerate the power supply noise inherently in wireless power harvesting and save power consumption. The recorded neural data is transmitted wirelessly by a 2.4/3.2 GHz dual-band OOK transmitter, which supports 54 Mb/s symbol rate, 44 pJ/bit meter-range wireless data transmission. To reduce the transmission BER, forward error correction with convolutional code and cyclic redundancy code is adopted.

Electroencephalographic spectral analysis from a wireless low-cost brain-computer interface for symptom capture of auditory verbal hallucinations in schizophrenia

Electroencephalographic spectral analysis from a wireless low-cost brain-computer interface for symptom capture of auditory verbal hallucinations in schizophrenia

Abstract 112: Galvanotactic Smart Bandage For Wireless Wound Healing

Background: Approximately thirty million people in the United States suffer from diabetes. The prevalence of diabetic foot ulcers (DFUs) in this population is 13%. There is a pressing need to develop effective therapies to treat chronic wounds robustly. Current standard of care wound dressings are passive and cannot actively respond to variations in the wound environment. Smart bandages are well positioned to address these challenges with their ability to integrate (bio)sensors for real-time monitoring and active wound care treatment. Current smart bandage technologies have demonstrated significant promise in their ability to sense physiological conditions. This includes detecting pH of the wound, temperature, oxygen, moisture, mechanical and electrical changes. To our knowledge there have not been significant advancements in incorporating sensing technologies to deliver active wound care. We believe this can be achieved using a multidisciplinary approach combining electrical and chemical engineering with the fundamentals of cellular and biomolecular processes in wound healing directed towards high resolution, in situ tissue regeneration. Methods: A flexible printed wireless stimulator was designed and fabricated to deliver directional energy across a wound gradient. Subsequently a low impedance PEDOT:PSS electrode was designed to optimize the skin and stimulator interface, producing a robust gel with tunable adhesion properties. The smart bandage was evaluated in an excisional diabetic and C57BL6/J murine wound healing model. A parabiosis model was used to evaluate circulating cell migration into the wound bed. Single cell analyses were performed to evaluate changes in cell populations as a direct result of induced electrical stimulation. In vitro validation was performed to elucidate in vivo results. Results: Wireless electrical stimulation resulted in significantly accelerated wound closure, when compared to controls, in both a diabetic and C57BL6/J murine excisional wound healing model. Complete epidermal recovery was observed, with a thicker collagen network and increased dermal thickness. Greater neovascularization and appendage formation were observed in the treatment groups. Single cell analyses revealed higher proliferation and remodeling regulatory markers expressed across treated groups. In vitro co-culture validation experiments demonstrated accelerated proliferation, mitotic rate and tube formation when compared to controls. Conclusion: Our data demonstrates the functionality of a robust wireless interface for wound healing. This novel treatment modality will integrate AI processing components for the development of a closed-loop functional stimulator. By combining the domain expertise of nanofabrication, mechanotransduction, fibrosis and molecular/cellular analyses, we are developing a novel chronically stable and robust smart bandage that will pave the way for the next generation of palliative wound care.

Wireless Epidermal Six-Axis Inertial Measurement Units for Real-Time Joint Angle Estimation

Technological advances in wireless communications, miniaturized sensors, and low-power electronics have made it possible to implement integrated wireless body area networks (WBANs). These developments enable the applications of wireless wearable systems for diagnosis, health monitoring, rehabilitation, and dependency care. Across the current range of commercial wearable devices, the products are not firmly fixed to the human body. To minimize data error caused by movement of the human body and to achieve accurate measurements, it is essential to bring the wearable device close to the skin. This paper presents the implementation of a patch-type, six-axis inertial measurement unit (IMU) with wireless communication technology. The device comprises hard-electronic components on a stretchable elastic substrate for application in epidermal electronics, to collect precise data from the human body. Instead of the commonly used cleanroom processes of implementing devices on a stretchable substrate, a simple and inexpensive “cut-solder-paste” method is adopted to fabricate complex, convoluted interconnections. Thus, the signal distortions in the proposed device can be minimized during various physical activities and skin deformations when used in gait analysis. The inertial sensor data measured from the motion of the body can be sent in real-time via Bluetooth to any processing unit enabled with such a widespread standard wireless interface. For performance evaluation, the implemented device is mounted on a rotation plate in order to compare performance with the conventional product. In addition, an experiment on joint angle estimation is performed by attaching the device to an actual human body. The preliminary results of the device indicate the potential to monitor people in remote settings for applications in mobile health, human-computer interfaces (HCIs), and wearable robots.

A survey on space-aerial-terrestrial integrated 5G networks

Thanks to their inherent advantages including large radio coverage and less dependence on terrestrial infrastructures, space and aerial networks can play an important role in 5G for ubiquitous coverage, large area broadcast services, and emergency communications. The space-aerial-terrestrial integrated networks (SATIN) are envisioned as an important trend of 5G evolution. However, due to distinct features including high altitude, moving platforms, large beam footprint and constrained payload, satellite networks are usually designed with unique protocols and functionalities, which hamper the integration of satellite networks with terrestrial mobile networks. The SATIN face many unprecedented technical challenges to achieve optimum performance, seamless user experience, and integrated security protection. This article makes a comprehensive overview of the latest researches from academia and industry to achieve the integrated 5G system. We first introduce the satellite and mobile technology trends, then present the vision of SATIN and related works in the area. Key enabling technologies from perspectives of the radio interface, networking, and security are discussed in depth. Then related standardization initiatives, especially the latest studies at 3GPP, and major industry research projects on non-terrestrial integrated 5G are reviewed. Important open issues are identified to inspire future studies for a fully integrated 5G system.

Adaptive Positioning Systems Based on Multiple Wireless Interfaces for Industrial IoT in Harsh Manufacturing Environments

As the industrial sector is becoming ever more flexible in order to improve productivity, legacy interfaces for industrial applications must evolve to enhance efficiency and must adapt to achieve higher elasticity and reliability in harsh manufacturing environments. The localization of machines, sensors and workers inside the industrial premises is one of such interfaces used by many applications. Current localization-based systems are unable to deal with highly variable conditions, meaning that the solutions working well in stationary systems suffer from considerable difficulties in harsh environments, such as factories. As a result, the precision of localization techniques is not satisfactory in most industrial applications. This paper fills in the existing gap between static approaches and dynamic indoor positioning systems, by presenting a solution adapting the system to highly changeable conditions. The proposed solution makes use of a Machine Learning-based feedback loop that learns the variability of the environment. This feedback makes continuous fingerprint calibration feasible even in the presence of different machines and Industrial Internet of Things sensors that introduce variations to the electromagnetic environment. This paper also presents a comprehensive indoor positioning system solution that reduces complexity of hardware, meaning that a multi-standard-transceiver infrastructure may be adopted with reduced capital and operational expenditures. We have developed the system from scratch and have conducted an extensive range of testbed experiments showing that the multi-technology transceiver feature is capable of increasing positioning accuracy, as well as of introducing permanent fingerprints calibration at harsh industrial premises.

A New Technique for Improving the Estimation of a Reflective Optical Color Sensor

This paper proposes and experimentally demonstrates a novel technique of a precise color estimation by using a low cost reflective optical color sensor. The digital output signal of this sensor is a pulses series with a frequency proportional to the intensity of the incident light. In this sensor, three independent detector output signals with optimized spectral responsiveness allow discrimination between red, green and blue (RGB) light spectral components. The analytical expressions for RGB absorption efficiencies, which detect the color information, have been derived. An experimental set-up has been designed to determine the color difference, involving design of a portable color analyzer with wired and wireless computer interface. The detailed description and implementation of each design element are presented, while a developed algorithm is also discussed. The proposed algorithm apply a linear transformation to realize standardized colorimetric RGB and CIE31-XYZ color space coordinates responses. To that end, a correlation of the sensor outputs is established, a wide band correction matrix in old estimations is replaced by many narrowband correction matrices and the CIE standard curves of wavelengths are extracted and used to select a suitable narrowband correction matrix. Also, the sequential algorithm has been parallelized to reduce the response time in multiple measurement applications which need the big data processing. The experimental results in the vision spectrum confirm the theoretical analysis. Based on the findings of this experiment, the proposed system constitutes a high resolution and low cost solution for various color-sensing applications and colorimetric fields.

D-RoF and A-RoF Interfaces in an All-Optical Fronthaul of 5G Mobile Systems

This paper presents a solution for enabling the coexistence of digitized radio-over-fiber (D-RoF) and analog radio-over-fiber (A-RoF) interfaces operating in the optical fronthaul of 5G mobile systems. In the first section, we formulate the need to introduce new technologies to the cloud/centralized radio access network (C-RAN) (Next Generation RAN (NG-RAN) in 5G systems). A proposition of construction of the optical remote radio head (O-RRH)/gNodeB—distributed unit (gNB-DU), which will enable the operation of digital Splits/Options and new proposed analog Splits/Options, is presented. The methods performing calculations of bit rate and optical bandwidth demand in the fronthaul/midhaul, with reference to the parameters of the new-radio-release-15 (NR-Rel-15) wireless interface and subsequent releases, towards the next generations, are presented. The bandwidth demands were calculated for selected Splits/Options, and the results are shown in diagrams. A special section is devoted to description of the results achieved and presenting potential applications of the proposed construction of a radio-photonic device as well as new Splits/Options of the next generation fronthaul/midhaul.

Characteristic analysis of wireless local area network's received signal strength indication in indoor positioning

The indoor positioning method based on received signal strength indication (RSSI) ranging is a lack of systematic quantitative research on the factors affecting the characteristics of indoor RSSI, which affect the accuracy of positioning. This paper quantitatively analyzes the characteristics of the 2.4 GHz RSSI collected in indoor scenes from the following four aspects: antenna orientation of the receiver, type of wireless network interface card (NIC) of the receiver, time period of the data measurement and height difference between the transmitting and receiving antenna. The experimental results show that: (i) the RSSI value measured is the strongest when the antenna of the receiver is vertically oriented to the antenna of the transmitter, while the weakest when the antenna is vertically back-facing and the difference between the strongest signal and the weakest signal is 20-25% at the same test point; (ii) the wider the measurement range of NIC, the more conducive to data collection; (iii) the distribution of RSSI signals generated by an access point at a fixed position is inconsistent with time; (iv) when the height of receiving antenna is 0.5 m different from each other, the path loss index of ranging model produces a deviation of about 10%.

Artificial bee colony optimization based energy-efficient wireless network interface selection for industrial mobile devices

Management of energy is a crucial challenge for mobile devices, having the network activity frequently taking up a considerable part of the energy in the overall system. The important goal of this work is to offer energy efficiency for mobile handhelds. The industrial mobile devices in the recent times are fitted with several wireless network interfaces, these devices function with less battery power. In mobile handhelds, each user is able to run multiple applications with the purpose of have particular Quality of Service (QoS) requirements. Hence, it would be beneficial for a multi-interface terminal to simultaneously use two or more interfaces to gain in performance. So satisfying the QoS becomes very difficult task. An energy-effective Adaptive Wireless Network Interface Selection (AWNIS) with Artificial Bee Colony (ABC) is proposed in this paper. AWNIS-ABC algorithm chooses the best of the wireless network interface in regard to the energy consumed by taking the QoS of the link into consideration as well as following a hi-speed network interface-selection interval based on the scenario in the network. Then Hidden Semi Markov Model (HSMM) is introduced for searching the detouring paths if the energy state of a given relay node is very less to utilize the required interface, which ensures timely delivery. Also, it provides the diversification of the route paths in the network with the purpose of extending the lifetime of the network. An alternate path is proposed for reliable data delivery beforehand the route path encounters a breakage owing to energy exhaustion is found. A number of wireless network interfaces in mobile devices are utilized in improving the energy efficiency, satisfaction of QoS occurring during data transfer. The simulation of the network is implemented via the Network Simulator 2(NS2).

Fiber optical multifunctional human-machine interface for motion capture, temperature, and contact force monitoring

A compact and wireless multifunctional human-machine interface (HMI) based on fiber Bragg grating (FBG) technology is presented. The interface is embedded into a glove and enables the motion capture of a human hand with finger tracking and hand wrist rotation monitoring, as well as temperature and contact force detection. For the realization of a complex hand tracking, a novel fiber optical rotation sensor based on three-dimensional shape sensing with Edge-FBG is presented. The data are evaluated within a micro-interrogator and wireless transferred to a smart glass in real-time. The HMI addressed different applications in motion capture for virtual reality (VR) or augmented reality (AR).

A Context-Aware Data-Driven Algorithm for Small Cell Site Selection in Cellular Networks

In mobile networks, detecting and eliminating areas with poor performance is key to optimize end-user experience. In spite of the vast set of measurements provided by current mobile networks, cellular operators have problems to pinpoint problematic locations because the origin of such measurements (i.e., user location) is not registered in most cases. At the same time, social networks generate a huge amount of data that can be used to infer population density. In this paper, a data-driven methodology is proposed to detect the best sites for new small cells to improve network performance based on attributes of connections, such as radio link throughput or data volume, in the radio interface. Unlike state-of-the-art approaches, based on data from only one source (e.g., radio signal level measurements or social media), the proposed method combines data from radio connection traces stored in the network management system and geolocated posts from social networks. This information is enriched with user context information inferred from traffic attributes. The method is tested with a large trace dataset from a live Long Term Evolution (LTE) network and a database of geotagged messages from two social networks (Twitter and Flickr).

Balancing Power and Rate Control for Improved Congestion Control in Cellular V2X Communication Environments

The Society of Automotive Engineers (SAE) J2945/1 standard prescribes a wireless channel congestion control algorithm for periodic Basic Safety Messages (BSMs) in vehicular safety communication. The algorithm is designed to work with the Dedicated Short Range Communication (DSRC) technology as the radio interface, and utilizes transmit (Tx) power control and rate control elements for the periodic BSM transmissions, which are supposed to work in a complementary manner. An equivalent standard is being made for the cellular vehicle-to-everything (C-V2X) communication environment, and it is expected that the J2945/1 congestion control algorithm will be reused. Unfortunately, we find that when transplanted to the C-V2X communication environment, the J2945/1 algorithm exhibits a poor balance between the two control elements under congestion. Specifically, the Tx rate control is pushed to its limit much earlier than the Tx power control. We believe that this is due to the new relation formed between the respective inputs to the control elements, channel busy ratio (CBR) and the vehicle density (VD), induced by the different radio technology used in the C-V2X communication. The consequence of the unbalanced control dynamics is the degraded update delay of neighboring vehicles' kinematics due to the over-exerted rate control, which potentially undermines the driving safety. In this paper, we propose to adjust the rate control function to react to congestion in a more relaxed manner so that the power control contributes more actively to the overall congestion control. With the re-balancing between the control elements, we show that the update delay improves, where larger improvements are obtained in closer, more safety-critical distances from the BSM transmitter. We believe that in future efforts to define the standard congestion control algorithm for the C-V2X environment, the balanced control aspect as explored in this paper should be considered in the design phase.

Encrypted Traffic Classification Based on Unsupervised Learning in Cellular Radio Access Networks

Traffic classification will be a key aspect in the operation of future 5G cellular networks, where services of very different nature will coexist. Unfortunately, data encryption makes this task very difficult. To overcome this issue, flow-based schemes have been proposed based on payload-independent features extracted from the Internet Protocol (IP) traffic flow. However, such an approach relies on the use of expensive traffic probes in the core network. Alternatively, in this paper, an offline method for encrypted traffic classification in the radio interface is presented. The method divides connections per service class by analyzing only features in radio connection traces collected by base stations. For this purpose, it relies on unsupervised learning, namely agglomerative hierarchical clustering. Thus, it can be applied in the absence of labeled data (seldom available in operational cellular networks). Likewise, it can also identify new services launched in the network. Method assessment is performed over a real trace dataset taken from a live Long Term Evolution (LTE) network. Results show that traffic shares per application class estimated by the proposed method are similar to those provided by a vendor report.

Amaran: An Unmanned Robotic Coconut Tree Climber and Harvester

There is an acute shortage of human coconut tree climbers to harvest coconuts in India and other developing countries. The consequential diminished availability of skilled tree climbers, to pass along the trade secrets to the succeeding generations, highlights the exigent need for an unmanned coconut-tree-climber as an alternative solution. This article presents Amaran, a novel robotic coconut tree climber and harvester. Amaran is comprised of a harvester with a distinctive robotic arm (RA) and a cutter, which can be attached to a ring-shaped frame that can be fastened to a coconut tree. Amaran can be controlled, through a wireless interface, either by an operator on the ground or via a smartphone-based app. Once dispositioned in the vicinity of the coconut bunch, the cutter is commanded to harvest the coconuts by cutting the stem of the bunch attached to the tree. Verification of the Amaran robot's viability was confirmed by tests conducted on a coconut tree set up in the design lab. Subsequently, the design of the Amaran robot was validated by field tests on a coconut farm. In this article, we discuss the design of the Amaran body and harvester. Amaran's dexterity in climbing and harvesting coconuts can be challenged by height, circumference, and inclination of the tree. Experimental results show that Amaran can successfully climb trees up to 15.2 m tall, circumferences ranging from 0.66 to 0.92 m, and tree trunk inclinations of up to 30°.

Queueing Analysis of Dynamic Power Management Schemes for Mobile Devices

In this paper, we analyze a queueing system under the dyadic server control, workload control and delivery deadlines of data blocks. From the viewpoint of efficient power management for the wireless interface of a smart mobile device, we first focus on deriving the mean length of an arbitrary cycle time and then investigate the mean energy expenditure during the cycle. Some numerical examples are shown with respect to several control parameters. We conduct simulations to evaluate the proposed analytic energy consumption models. Experiments are also performed by implementing a test program on an off-the-shelf smartphone. Our results can serve as quantitative guidelines for the efficient power management of wireless interfaces in mobile devices.

A portable ECG for recording and flexible development of algorithms and stress detection

Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.

An Implantable Body Channel Communication System With 3.7-pJ/b Reception and 34-pJ/b Transmission Efficiencies

We present an energy-efficient reception and transmission scheme based on the exploitation of the conductive properties of the body for wireless neural interface applications. High efficiencies were achieved with: 1) a three-level clock-embedded direct digital signaling scheme in the transmitter (TX) and 2) with a squaring clock extraction enabling data recovery scheme using a clocked-comparator in the receiver (RX). Additionally, the output voltage of the TX was boosted to secure the link budget of the RX. As a result, the RX and TX consumed 62 and 566 $\mu \text{W}$ , respectively, for a rated output power of 185 $\mu \text{W}$ and achieved a maximum data rate of 16.7 Mb/s. These operational characteristics corresponded to the energy consumptions of 3.7 pJ per received bit and 34 pJ per transmitted bit, demonstrating a promising potential for use in implanted devices.

Signal Strength-Aware Adaptive Offloading with Local Image Preprocessing for Energy Efficient Mobile Devices

To prolong battery life of mobile devices, image processing applications often exploit offloading techniques which run some or all of the computations on remote servers. Unfortunately, the existing offloading techniques do not consider the fact that data transmission time and energy consumption of wireless network interfaces exponentially increase when signal strength decreases. In this paper, we propose an adaptive offloading for image processing applications, which considers wireless signal strength. To improve performance and energy efficiency of offloading, we also propose to adaptively exploit local preprocessing (executing image preprocessing on local mobile devices), considering wireless signal strength; the local preprocessing usually reduces the size of transmission image in offloading. Our proposed technique estimates performance and energy consumption of the following three methods, depending on the wireless signal strength: 1) local execution (executing all the computations on the local mobile devices), 2) offloading without local preprocessing, and 3) offloading with local preprocessing. Based on the estimated performance and energy consumption, our technique employs one among the three methods, which is expected to result in the best performance or energy efficiency. In our evaluation on an off-the-shelf smartphone, when a user prefers performance to energy, our proposed technique improves performance by 27.1 percent, compared to the conventional offloading technique that does not consider the signal strength. On the other hand, when a user prefers energy to performance, our proposed technique saves system-wide (not just CPU nor wireless network interface) energy consumption by 26.3 percent, on average, compared to the conventional offloading technique.