A robust, real‑time telemetry protocol for miniaturized neural implants using off‑the‑shelf hardware.

Correlations of 100 MC radio propagation with certain meteorological variables

Multi-hop routing in mobile ad hoc networks (MANETs) requires good resource managing protocols. The efficient route from source to destination in the network is identified by determining the level of signal strength from intermediate hops. The link quality between the intermediate nodes is determined by calculating the signal strength level. The received signal strength is one method to estimate the medium characteristics and distance between the intermediate nodes which is one of the quality of service required by the network. The nodes with high signal strength and high bandwidth are identified as minimal delay nodes so as to determine the reliable path. The data is sent through minimal delay nodes in the shortest path from source to destination. The better link quality improves the performance metrics such as packet delivery ratio, throughput and simultaneously reduces the control message overheads, average and end-to-end delay compared to some of the existing routing protocols. The experimental study shows that the proposed routing protocol is 30% better in packet delivery ratio, throughput, reduced control message overheads, average and end-to-end delay than the existing stable and delay constrained routing protocol.

Mobile ad-hoc network is a grouping of movable nodes whose mutual effort creates the temporary infrastructure less topology. Nodes or devices communicate each other through radio range, intermediate devices and signal strength based mechanism. Mobile devices work with limited energy because mobile device contain battery that helps only to activate the devices. In previous related work, number of researcher enhanced the network life time by deploying energy consumption routing (ECR), Max-Min Battery cost routing (MMBCR) and many more techniques. In this paper, signal strength, transmission power requirement and location based approach is applied that helps to increase the reliability of the network with low overhead. Node locations are calculated through relative coordinate based mechanism. Signal strength is inversely proportional to location of nodes. It means signal strength is higher if node location is near, and on the other end, lower is the signal strength if far is the location of the node. Source to receiver path are selected on the basis of near node and higher signal strength and low transmission power, which increase the network performance in every aspect of network parameters. The proposed work is simulated through network simulator-2. Simulated result gives the higher data sends and receives rate and also calculates energy used, residual energy of network, receiving signal strength of each node, and node location in every discrete time interval.

Various WSN applications use hierarchical routing protocol for routing sensed data to the sink. LEACH is one of the widely used hierarchical, distributed clustering protocol in WSN. In LEACH, Non-Cluster head Nodes decide to join a cluster head based on Received Signal Strength (RSS) of receiving HELLO packets from CHs making it vulnerable to HELLO Flood attack. A laptop-class adversary node can broadcast packets advertising it as cluster head with higher signal strength, all sensor nodes will select it as cluster head and send join packet into it, thinking that the adversary is in their range and thus, the whole network will be in a state of confusion. Existing solutions for detection of HELLO flood attack are either cryptographic which are less suitable in terms of memory and battery power, or non-cryptographic which involves sending the test packet for detection. This increases communication overhead as the energy required for transmission of the packet is far more than the energy required for processing/calculation. Based on these facts, a non-cryptographic solution for HELLO flood attack detection is proposed in this paper in which the no. of times the test packet is transmitted is greatly reduced. The simulation results showed detection of adversary nodes with minimal communication overhead as the number of test packets sent for detection is reduced from 20-35 to 10-14 (approx.).

In high-speed railway (HSR) communication, the handover becomes more frequent for the high mobility of trains. In this letter, a precoding based handover scheme is proposed to reduce the ping-pong handover trigger rate and improve the HSR system stability. Specifically, the precoding vectors of serving and target cell are jointly designed to maximize the difference in received signal strength between the two cells during the handover preparation phase. And the optimal precoding vectors is solved through the concave-convex process and the second-order cone programming transformation. The simulation results show that the proposed handover scheme can effectively alleviate the occurrence of ping-pong handover and ensure the system stability of HSR communication. The system has higher signal strength than with the traditional scheme.

A promising solution to achieve high spectral efficiency and to improve coverage and throughput in 5G cellular systems is the deployment of Heterogeneous Ultra-Dense Networks (H-UDN). However, a key challenge for H-UDN is to manage user mobility and handovers among the cells. In this paper, we propose using a Markov decision process based on the received signal strength. Based on the User Equipment (UE) location, the UE selects the most efficient handover scheme. However, having an H-UDN, the UE may receive the worse received signal. Hence, we introduce the Stackelberg competition model in order to increase the relay node to be selected. This will guarantee communication quality and the load balancing of the system. The simulation result shows that the UE selection of the station with the highest signal strength is based on the distance between the UE and the station and the transmitted power.

This study examines the impact of atmospheric variables on the propagation of digital terrestrial television signals from Ogun State Television, located in Abeokuta, Ogun State, Nigeria, with a focus on the relationship between weather parameters and surface radio refractivity. Data on received signal strength and meteorological factors such as temperature, relative humidity, and atmospheric pressure were collected over 12 months. The analysis revealed significant seasonal variations, with higher relative humidity and surface refractivity observed during the rainy season (April to October) compared to the dry season (November to February). The study found that the lowest signal strength occurred in June, probably due to increased rainfall, while the highest signal strength was recorded in February. The results indicate that surface radio refractivity is influenced by climatic conditions, with higher values during the rainy season, affecting the performance of UHF signal propagation. These findings provide valuable information for radio engineers in the design and optimization of microwave communication systems in regions with similar climatic conditions.

Wireless local area network (WLAN) fingerprint-based localization has become the most attractive and popular approach for indoor localization. However, the primary concern for its practical implementation is the laborious manual effort of calibrating sufficient location-labeled fingerprints. The Semi-supervised extreme learning machine (SELM) performs well in reducing calibration effort. Traditional SELM methods only use Received signal strength (RSS) information to construct the neighbor graph and ignores location information, which helps recognizing prior information for manifold alignments. We propose Composite SELM (CSELM) method by using both RSS signals and location information to construct composite graph. Besides, the issue of unlabeled RSS data quality has not been solved. We propose a novel approach called Composite semisupervised extreme learning machine with unlabeled RSS Quality estimation (CSELM-QE) that takes into account the quality of unlabeled RSS data and combines the composite neighbor graph, which considers location information in the semi-supervised extreme learning machine. Experimental results show that the CSELM-QE could construct a precise localization model, reduce the calibration effort for radio map construction and improve localization accuracy. Our quality estimation method can be applied to other methods that need to retain high quality unlabeled Received signal strength data to improve model accuracy.

Firing heads are a widely used term for the initiation device of perforating gun systems and other pyrotechnical devices deployed on wireline and tubing-conveyed perforating (TCP) operations. The perforating systems have improved dramatically since the first successful commercial TCP job was performed in 1970 using a mechanically initiating firing head. Over the last several decades, the technological development of the TCP firing systems have rendered perforating systems more robust, safer, and operationally flexible. Recently, perforating firing heads have been mainly designed on the basis of hydraulic and mechanical operation, which typically requires the shearing of pins through pressure activation or use a drop bar to create mechanical impact. Features, such as firing delay or multiple pressure-cycle operation, have been developed, with additional complexity. Such mechanical systems are not always precise in operation due to tolerances and can be influenced by variations in downhole conditions, such as temperature, pressure, and duration. The electronic firing heads introduced over two decades ago provided immunity to variations of downhole conditions, offered improved accuracy and control, and eliminated the need for high-pressure pulses normally required to activate a hydraulic firing head. Communication relied upon a coded low-pressure command sequence of pulses. This introduced a safer, more efficient, and economical method for a wide range of downhole explosive operations. The most recent advancements in the electronic firing head have been enabled by wireless acoustic telemetry. This evolution step provides a perforating firing head combinable with drill stem testing assemblies. The wireless technology-enabled electronic firing head is the integration of two proven technologies: the electronic intelligent low-pressure firing head and the wireless acoustic telemetry system. The electronic firing head enabled by wireless acoustic telemetry system allows multizone drill stem testing (DST), independently or selectively with comingled reservoir, providing the ability to initiate guns where pressure activation is not possible. We describe the evolution of the firing system and operation of this newly developed and advanced acoustically actuated electronic firing head. Two case studies summarize the benefits and capabilities of the firing head enabled by the wireless acoustic telemetry system.

For using continuous fractional voltage tracking (CFVT) it is crucial to know both, the optimal voltage fraction \(\varepsilon _\text {opt}\), and the actual transducer’s open-circuit voltage \(V_\text {g,oc}\). Therefore, this chapter presents a novel fully-analog load matching detector, which merges these two requirements: it is programmable for the needed \(\varepsilon _\text {opt}\), monitors a proportional measure to \(V_\text {g,oc}\left( t \right) \), and links both to a single output signal. This output signal indicates either the presence of an over-load or under-load condition. Thus, this detector can directly control a wide range of switch-mode converters. The review shows common methods to determine \(\varepsilon _\text {opt}\), and further related techniques for programming an input resistance of a SMPS for reasons of harvesting at the MPP. The details of the detection principle are explained, is followed by the circuit implementation with focus on low current consumption and wide voltage range operation. Simulation results of continuous tracking for both kinds of sources, AC and DC, show the efficient \(\,\mu \)W power operation.KeywordsBoost ConverterSense ResistorMinimum VoltageVoltage RippleDiscontinuous Conduction ModeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We propose an ultra-low power interconnect bus for millimeter-scale wireless sensor nodes. Using only 4 IO pads, the bus minimizes the required chip real estate, enabling ultrasmall form factors in modular sensor node designs. Low power is achieved using a “clockless” design of member nodes while aggressive power gating allows an ultra-low power standby mode with only 53 gates powered on. An integrated wakeup scheme is compatible with PMUs that have a special low power standby mode. The MBus is fully synthesizable and uses robust timing. Implemented in a 3 module system in 180nm technology, Mbus achieves 8nW of standby power and 17.5 pJ/bit/chip.

An investigation into the Received Signal Strength Indicator (RSSI) dependency on receiver antenna height in UHF band is conducted. The results show a high correlation between RSSI and height on channels with high signal strength. There is approximately 2.5 dBm RSSI gain per 1 m increase in height above ground up to 8.5 m. From 8.5 m to 12 m, there is no consistent observable increase in RSSI. Furthermore, the geolocation spectrum database’s (GLSD) view of white space in the television band is compared with the ground truth. Results show signal presence on some of the channels indicated free by the spectrum database. These findings imply that an increase in transmission range of UHF links can be achieved by increasing receiver height. White space devices using A GLSD should additionally require spectrum scanning to determine clear channels.

This paper describes a novel technology for controlling a fully autonomous wheelchair, using a Bluetooth Low Energy (BLE) beacon. Our framework, in particular, enables the beacon substrate (Received Signal Strength Indicator) to allow machine learning for fully autonomous wheelchair control, namely for the beacon model. Location awareness is computed for the smooth locomotion control of a motorized wheelchair. As a result, low current consumption is achieved to allow lasting battery life. In this paper, we provide several results relevant to this, and future remarks.

Nowadays many systems with diverse technologies such as (GPS, Wi-Fi, Bluetooth, ZigBee, Ultra Wide Band, Ultrasounds, Infrared, etc) can be used for indoor location. One of the biggest challenges in indoor location systems is to determine the actual indoor position of the user using a smart device (Phone, PC, etc), due to their instability, cost, high-power consumption, low accuracy and low precision. To overcome those problems, we have designed, implemented and emulated an indoor location system based on RSSI (Receive Signal Strength indicator) of the Bluetooth low energy 4.0 (BLE). BLE 4.0 technology is more advantageous in terms of long life expectancy, our approach is based on the deployment of equidistant nodes on the ceiling. The nodes are programmed to broadcast a periodic beacon at a time pace of 400ms and then to enter sleep mode. When a smart device enters within the broadcasting range, it locates the three access points (nodes) with the highest signal strength. This information can be calculated using one of the several localization algorithms (Dilatation). The proposed Dilatation algorithm can be easily implemented in the hardware due to its low complexity, the method can be successful even when using a few numbers of nodes. In average the system has about 0.5 ~ 1 meters of error.

Mobile devices are increasingly relied upon in user's daily lives. This dependence supports a growing network of mobile device charging hubs in public spaces such as airports. Unfortunately, the public nature of these hubs make them vulnerable to tampering. By embedding illicit power meters in the charging stations an attacker can launch power side-channel attacks aimed at inferring user activity on smartphones (e.g., web browsing or typing patterns). In this paper, we present three power side-channel attacks that can be launched by an adversary during the phone charging process. Such attacks use machine learning to identify unique patterns hidden in the measured current draw and infer information about a user's activity. To defend against these attacks, we design and rigorously evaluate two defense mechanisms, a hardware-based and software-based solution. The defenses randomly perturb the current drawn during charging thereby masking the unique patterns of the user's activities. Our experiments show that the two defenses force each one of the attacks to perform no better than random guessing. In practice, the user would only need to choose one of the defensive mechanisms to protect themselves against intrusions involving power draw analysis.