Radio Frequency Signal Propagation Research Articles

Environmental causality calibration: Advancing WLAN RF fingerprinting for precise indoor localization.

In recent years, considerable and valuable research progress has been made in indoor positioning technologies based on WLAN Radio Frequency (RF) fingerprinting, identifying it as one of the most promising positioning technologies with substantial potential for wider adoption. However, indoor environmental factors significantly influence the propagation of wireless RF signals, resulting in a considerable decrease in positioning accuracy as the indoor environmental conditions vary. Thus, effectively mitigating the impact of indoor environmental factors on WLAN RF fingerprinting-based positioning systems has become a crucial research problem. Currently, there is a dearth of comprehensive research on the influence of indoor climatic factors, particularly the variations in relative humidity, on the propagation of WLAN RF signals within indoor spaces and its consequential impact on positioning accuracy. To address the aforementioned issues, this paper proposes an Adaptive expansion fingerprint database (AeFd) model based on a regression learning algorithm. The AeFd, through the design of a relationship model describing the interaction between fingerprint databases under varying relative humidity, allows the fingerprint database expanded by AeFd to dynamically adapt to the changes in indoor relative humidity. Our experiments show that using the AeFd model with the KNN algorithm, a 5% performance improvement was observed over 10 days and an 8% improvement over 10 months. According to experimental test results, the fingerprint database expansion model AeFd proposed in this paper can effectively expand the fingerprint database under different relative humidity levels, thereby significantly enhancing the positioning performance of the system and improving its stability.

Statistical Characterization and Modeling of Radio Frequency Signal Propagation in Mobile Broadband Cellular Next Generation Wireless Networks

An accurate assessment of the spatial and temporal radio frequency channel characteristics is essential for complex signal processing and cellular network optimization. Current research has employed numerous models to figure out how much signal propagation loss occurs along the propagation paths. However, there are issues in finding the right model for a particular terrain because these models are not universally applicable. By employing the lognormal function and the Maximum Likelihood model, a hybrid probabilistic statistical distribution model was evolved. Three LTE cell site locations in Port Harcourt, Nigeria, were used to create a hybrid model that describes the functional stochastic signal propagation loss in the area. The evaluated Maximum Likelihood model accurately estimates the relevant wireless channel properties based on observed field data. The minor square regression approach and the proposed hybrid parameter estimation methodology are compared. When it comes to estimating standard deviation errors as well as the root mean square errors, the ML-based approach consistently outperforms the least square regression model. Finally, the proposed hybrid probabilistic statistical distribution model would be useful for mobile broadband network planning in related wireless propagation conditions.

Investigation of Radio Frequency Signal Propagation of Wireless Services in Oyo, Oyo State, South Western Nigeria

This study reported the investigation of the Radio Frequency (RF) signal propagation of Global System for Mobile Communications (GSM) coverage in Emmanuel Alayande College of Education (EACOED), Oyo, Oyo State, Nigeria. The study aims at amplifying the quality of service and augment end users' sensitivity of the wireless services operation. The drive test method is adopted with estimation of coverage level and received signal strength. The Network Cell Info Lite application installed in three INFINIX GSM mobile phones was employed to take the measurement of the signal strength received from the transmitting stations of different mobile networks. The results of the study revealed that MTN has the maximum signal strength with a mean value of - 68.33 dBm, directly followed by Globacom (-80.41 dBm) and Airtel with -83.13 dBm. The Airtel signal has a conspicuously invariable poor performance with coverage level of 41.66 %. Conversely, the MTN and Globacom signal reception are observed to surpass the Airtel network within the college premises with 83.33 % and 60.41 % coverage level respectively. This implies that the signal quality for MTN and Globacom networks were comparatively disseminated within the college with inconsequential fluctuations in quality while Airtel signal is subsided and weaken. The poor performance in some areas was due to the presence of physical impediments and far distances location of base station antennas in the promulgation locations. This study therefore suggested that Airtel and Globacom Base Transceiver Stations (BTS) should be positioned within the college to improve good network reportage level.

Impact of biaxial birefringence in polar ice at radio frequencies on signal polarizations in ultrahigh energy neutrino detection

It is known that polar ice is birefringent and that this can have implications for in-ice radio detection of ultrahigh energy neutrinos. Previous investigations of the effects of birefringence on the propagation of radio-frequency signals in ice have found that it can cause time delays between pulses in different polarizations in in-ice neutrino experiments, and can have polarization-dependent effects on power in radar echoes at oblique angles in polar ice. I report, for the first time, on implications for the received power in different polarizations in high energy neutrino experiments, where the source of the emitted signal is in the ice, a biaxial treatment at radio wavelengths is used, and the signals propagate at oblique angles. I describe a model for this and compare with published results from the SPICE in-ice calibration pulser system at South Pole, where unexpectedly high cross-polarization power has been reported for some geometries. The data shows behaviors indicative of the need for a biaxial treatment of birefringence inducing nontrivial rotations of the signal polarization. The behaviors include, but are not limited to, a time delay that would leave an imprint in the power spectrum. I explain why this time delay has the potential to serve as both an in-ice neutrino signature and a measurement of the distance to the interaction. While further work is needed, I expect that proper handling of the effects presented here will increase the science potential of ultrahigh energy neutrino experiments, and may impact the optimal designs of next-generation detectors.

A dual channel and node mobility based cognitive approach to optimize wireless networks in coal mines

This study investigates the network capability by introducing a self-adaptive cognition approach that can sense and dynamically configure the communication channel requirements to optimize the wireless links in coal mines. The cognitive scheme based on dual-channel is initiated to sense the optimal channel of transmission and the multi-node mobility system is employed to cover the area of the network where signal strength is below the threshold level. The searching model of target nodes is presented to locate the field of intermittent link and cognitive controlled mobile nodes are utilized to restore the site of intermittent link. The visible light communication (VLC) and radio frequency (RF) channels are integrated into a cognition access point and the channel modeling of both links is performed to evaluate their performance in the hostile environment of coal mines. Multi-mode waveguide and geometrical optic (GO) models are employed in the modeling of RF signal propagation and the ray-tracing approach based on Lambertian radiation pattern (LRP) is utilized to characterize the visible light propagation. The estimation of received signal power and other evaluating parameters of communication reveals the significance of the proposed study against the challenges of intermittent links in coal mines.

Robot Localization in Tunnels: Combining Discrete Features in a Pose Graph Framework.

Robot localization inside tunnels is a challenging task due to the special conditions of these environments. The GPS-denied nature of these scenarios, coupled with the low visibility, slippery and irregular surfaces, and lack of distinguishable visual and structural features, make traditional robotics methods based on cameras, lasers, or wheel encoders unreliable. Fortunately, tunnels provide other types of valuable information that can be used for localization purposes. On the one hand, radio frequency signal propagation in these types of scenarios shows a predictable periodic structure (periodic fadings) under certain settings, and on the other hand, tunnels present structural characteristics (e.g., galleries, emergency shelters) that must comply with safety regulations. The solution presented in this paper consists of detecting both types of features to be introduced as discrete sources of information in an alternative graph-based localization approach. The results obtained from experiments conducted in a real tunnel demonstrate the validity and suitability of the proposed system for inspection applications.

Wireless 5G Radiofrequency Technology — An Overview of Small Cell Exposures, Standards and Science

5G small cell antenna systems are among the latest technologies that support wireless communications by the transmission of radiofrequency (RF) signals. Coded RF signals in the range of 0.6 to 47 GHz from fixed small cell antennas supplement wireless communications from 3G and 4G wireless systems. This paper describes the propagation of RF signals from a pole-mounted 5G antenna and how the signal strength declines with distance for a representative installation operating at 39 GHz. The far field exposure from the antenna is compared to those from multiple natural and man-made RF sources. In the United States, RF exposure standards are issued by the Federal Communications Commission. We review the history and derivation of these standards in relation to other national and international standard-setting bodies. Some have raised concern as to whether sufficient health and safety studies have been performed on RF from 5G systems, but the commonality of RF frequencies up to 300 GHz enables health agencies and standard-setting bodies to assess the potential for effects across this frequency spectrum. A 5G RF signal does not have a different mode of action than a lower frequency communication signal; both involve tissue heating at sufficient field strengths. The key difference for 5G frequencies above 6 GHz is that the body's electrical properties better limit energy deposition to a shallow depth, largely confined to superficial layers of the skin. Research to date has not provided a reliable scientific basis to conclude that RF communication signals at 5G or other frequencies will cause or contribute to adverse health effects.

A Radio Propagation Model for Dense Wireless Networks

This paper proposes a model of radio frequency signal propagation in the free space that can be used not only in the far field region of the transmitting antenna like the Friis propagation model for large scale fading, but it can also be employed when the antennas are very close to each other. The modeling starts from a transfer function of the exact two-port network model used to represent the coupling between two antennas in free space. The Z parameter network of the system is used to model the power attenuation as function of the distance between the antennas. Subsequently, a new mathematical model is proposed and compared with the Z parameter network model and shown to have small mean squared error. Such model has the advantage of replacing the Friis formula without the restriction to avoid measuring signals in the near field of the antenna. Furthermore, some practical experiments are carried out in an open field environment and the results are compared. The validity of the new model is demonstrated which can be used for any distance between the antennas and, therefore, it can also be employed to model dense wireless networks.

Path Loss Models for Low-Power, Low-Data Rate Sensor Nodes for Smart Car Parking Systems

Smart parking management systems need to keep up with the state of parking spots at all times. This is efficiently accomplished via sensor nodes that detect vehicles and update the system’s state as it changes in real time. When sensor nodes use wireless communication as their primary communication link, the deployment approach becomes important, since it directly affects network connectivity, cost, and lifetime. The main factor to consider when deploying wireless sensor networks (WSN) in parking environments is the prediction of radio frequency (RF) signal propagation. Inaccurate propagation models lead to systems that under- or over-perform, both of which negatively affect WSN performance. Most of the existing RF propagation models are created to support cellular systems environments, which drastically differ from indoor/outdoor parking environments—few or no model exists that accurately predict RF signal propagation in parking environments. Therefore, there is a need for models that accurately characterize RF signal propagation in these environments. This paper proposes empirical path loss models for WSN deployment in indoor and outdoor car parking lots. The proposed models are compared with theoretical models. Theoretical models deviate from the proposed models and the measured values by 10% to 46%. The provided models, as well as the measured data, can be used for efficient planning and deployment of WSN in various proposed smart cities, intelligent transportation, and parking lot systems.

Communication Characteristics of Faulted Overhead High Voltage Power Lines at Low Radio Frequencies

This paper derives a model of high-voltage overhead power line under fault conditions at low radio frequencies. The derived model is essential for design of communication systems to reliably transfer information over high voltage power lines. In addition, the model can also benefit advanced systems for power-line fault detection and classification exploiting the phenomenon of changed conditions on faulted power line, resulting in change of low radio frequency signal propagation. The methodology used in the paper is based on the multiconductor system analysis and propagation of electromagnetic waves over the power lines. The model for the high voltage power line under normal operation is validated using actual measurements obtained on 400 kV power line. The proposed model of faulted power lines extends the validated power-line model under normal operation. Simulation results are provided for typical power line faults and typical fault locations. Results clearly indicate sensitivity of power-line frequency response on different fault types.

Device-Free RF Human Body Fall Detection and Localization in Industrial Workplaces

Fall detection and localization of human operators inside a workspace are major issues in ensuring a safe working environment. Recent research has shown that the perturbations of the radio-frequency (RF) signals commonly adopted for wireless communications can also be used as sensing tools for device-free human motion detection. Device-free RF-based human sensing applications range from tag-less body localization to detection and monitoring of human well-being (e-Health). In this paper, we propose a real-time system for human body motion sensing with special focus on joint body localization and fall detection. The proposed system continuously monitors and processes the RF signals emitted by industry-compliant radio devices operating in the 2.4 GHz ISM band and supporting machine-to-machine communication functions. Human-induced diffraction and multipath phenomena that affect RF signal propagation are leveraged for body localization while for fall detection a hidden Markov model is applied to discern different postures of the operator and to detect safety-relevant events by tracking the received signal strength indicator footprints. Fall detection performances are corroborated by extensive experimental measurements in different settings. In addition, we propose also a sensor fusion tool that is able to integrate the device-free RF-based sensing system within an industrial image sensors framework. Preliminary results, conducted during field trial measurements, confirm the effectiveness of the proposed approach in terms of localization accuracy, and sensitivity/specificity to correctly detect a fall event from preimpact postures.

Radio Channel Propagation Characterization and Link Reliability Estimation in Shadowed Suburban Macrocells

The reliability of packet data transmissions under large scale fading is a key issue in wireless mobile networks and has been studied by many researchers, but mostly through simulation and analytical modelling. In this research paper, a realistic methodological approach has been employed to better characterize and quantify the impact of the shadow fading effect on High Speed Packet Access (HSPA) network reliability in different suburban environment scenarios. In this regard, radio frequency signal propagation measurement was first conducted using mobile drive test investigation procedure in hilly, open and residential terrains. By using regression analysis on the RF field data, the long term attenuation pattern of the measured signal power was obtained and the power decaying propagation exponent varied between 2.50 and 3.03. From the characterized pathloss model parameters obtained in the measurements, the HSPA link reliability has been evaluated using the Packet Error rate outage (PE-Outage) probability analysis. Furthermore, the impact of signal power variability on the user equipment terminal has been quantified with and without shadow fading. The results showed that shadow fading can have a significant impact on network reliability. The simplified approach adopted can be useful for a methodical evaluation of system reliability in similar mobile broadband networks deployed in more challenging environments.

Advanced Smoothing Approach of RSSI and LQI for Indoor Localization System

Ubiquitous indoor environments often contain substantial amounts of metal and other similar reflective materials that affect the propagation of radio frequency signals in important ways, causing severe multipath effects, including noise and interference, when measuring the signal strength between sender and receiver. To minimize the noise level, this study proposes advanced fusion filter (AFF) and improved fusion filter (IFF) using received signal strength indicator (RSSI) and link quality indicator (LQI) by using feedback filter. The aim of this research was to provide a low cost, simple technique based on RSSI and LQI values, provided by ZigBee module without considering needs to change the system according to specific indoor environments. The proposed technique could efficiently decrease huge amount of noise level from the original signal. To check the performance of the proposed technique, this study applied median filter and Savitzky-Golay filter to compare the performance of AFF and IFF. Further, the statistical analysis technique of cross-correlation method was used to check the similarity between original signal and filtered signal. The simulation results demonstrate the efficiency of the proposed RF-based indoor location determination.

Effect of the disturbed region of the ionosphere on the propagation of radio-frequency signals

Based on geometrical optics, expressions have been obtained for the estimate of changes in the amplitude and bearing of radio-frequency signals after their passage through an ionosphere region disturbed by a heating facility.

Topside electron density profiles observed at low latitudes by COSMIC and compared with in situ ion densities measured by C/NOFS

AbstractElectron density height profiles (EDPs) play critical roles in accurately tracing the propagation of radio frequency signals through the topside ionosphere. The Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) satellites were designed to provide this information during GPS radio occultation events. However, due to the reliance of COSMIC data reduction on inverse Abel transformations, questions persist about the accuracy of its EDP products. The Communication/Navigation Outage Forecasting System (C/NOFS) satellite in a low‐inclination orbit offers new opportunities for empirically testing the accuracy of topside EDPs from COSMIC over the altitude range 400 to 800 km. We report here on the results of a feasibility study covering the interval 24–25 October 2011 in which a large magnetic storm occurred. We identified universal times when C/NOFS passed within 6° × 60° rectangles centered at the latitudes and longitudes of the tangent line for COSMIC EDPs. We also compared COSMIC EDPs with those predicted by two widely used models. Our analysis shows that during a very large fraction of the available events, ion densities measured by C/NOFS were in closer agreement with COSMIC EDPs than were model predictions at the same altitudes. We also use the COSMIC and C/NOFS data sets to assess stormtime effects on the low‐latitude ionosphere. During the main phase of the storm both local densities and vertical total electron content rose on the dayside, but decreased on the nightside. During recovery both quantities quickly reverted toward their quiet‐time levels.

Indoor Propagation Investigation From a 2.4 GHz Waist Mounted Beacon

Indoor positioning techniques are being considered for use within team sports where players are tracked and recorded providing coaching assistance. While Global Positioning System (GPS) is the de facto standard employed to estimate the location of players, this is unsuitable for accurate indoor positioning due to roof and wall signal obstruction. Over a dozen techniques have been suggested for wireless indoor positioning of static and/or moving objects with improved methods for limiting the position estimation errors. For those indoor techniques that rely on radio frequency (RF) signal propagation, propagation statistics are useful in determining path loss and signal degradation. This static indoor propagation knowledge is critical in the design of wireless indoor positioning systems and ultimately the accuracy of the position estimation. Signal path propagation losses and variations produced from shadowing, multipath, fading, scattering or diffraction from objects can hinder the designer's efforts to provide a reliable and accurate positioning system. However, sporting indoor environments generally have an open floor area where play is conducted free from objects apart from the players themselves. At the elite sporting level these indoor play areas are designed and constructed under international specifications. Consequently, static wireless RF signal propagation knowledge obtained from one of these commonly built play areas is applicable to hundreds of other venues around the world. Many of these indoor sporting areas are used for a variety of sports, for example, basketball, volleyball, indoor cricket, indoor soccer, netball and handball. A player positioning installation could potentially be used for all of these sports. This paper reports the wireless RF signal propagation of a 2.4GHz waist mounted beacon for an indoor sporting venue ‘play area’, which has been designed to international standards. A basketball court constructed of highly polished wood was chosen as the sample ‘play area’. Propagation models are discussed and comparisons between predicted and measured results demonstrate the validity of the technique.

RF Propagation Patterns at 915 MHz and 2.4 GHz Bands for In-Field Wireless Sensor Networks

Abstract. The objective of this study was to evaluate and compare in-field radio frequency signal propagation and data transmission performance of a wireless sensor network (WSN) in the 915 MHz and 2.4 GHz bands in a wheat field. Two types of wireless sensor nodes using 915 MHz and 2.4 GHz carrier frequencies were tested. Two nodes with the same carrier frequency were wirelessly connected, one as a receiver and another as a transmitter. Indexed packets transmitted from the transmitter were captured by a spectrum analyzer to measure path-loss and simultaneously received by the receiver to calculate packet delivery rate (PDR). Field experiments were conducted on a research farm at Oklahoma State University where wheat was planted. Impact factors on RF signal propagation considered included: plant canopy height, carrier frequency, transmitter height, receiver height, and transmitter-to-receiver distance (T-R distance). Analysis of impact factors’ influences on path-loss indicated that in-field RF signal path-loss was more subject to all separate impact factors as well as their interactions when using the higher carrier frequency. Pearson’s correlation results indicated that path-loss and PDR were more correlated with each other when the plants between the transmitter and receiver were higher than both types of nodes. Estimated marginal means plots indicated that for all plant canopy heights, the lowest path-loss could be achieved when the transmitter was installed at a height of 2 m and the receiver was installed at a height of 3 m using both types of nodes. At distances of 80 and 70 m, data communication was stable for the 915 MHz and 2.4 GHz nodes, respectively, for wheat field WSN applications when the transmitter and receiver antennas were at a minimum height of 1.0 m above ground and the wheat had a maximum plant height of 0.8 m.

A Fusion Approach of RSSI and LQI for Indoor Localization System Using Adaptive Smoothers

Due to the ease of development and inexpensiveness, indoor localization systems are getting a significant attention but, with recent advancement in context and location aware technologies, the solutions for indoor tracking and localization had become more critical. Ranging methods play a basic role in the localization system, in which received signal strength indicator- (RSSI-) based ranging technique gets the most attraction. To predict the position of an unknown node, RSSI measurement is an easy and reliable method for distance estimation. In indoor environments, the accuracy of the RSSI-based localization method is affected by strong variation, specially often containing substantial amounts of metal and other such reflective materials that affect the propagation of radio-frequency signals in nontrivial ways, causing multipath effects, dead spots, noise, and interference. This paper proposes an adaptive smoother based location and tracking algorithm for indoor positioning by making fusion of RSSI and link quality indicator (LQI), which is particularly well suited to support context aware computing. The experimental results showed that the proposed mathematical method can reduce the average error around 25%, and it is always better than the other existing interference avoidance algorithms.

Energy harvesting from radio frequency propagation using piezoelectric cantilevers

This work reports an induced strain in a piezoelectric cantilever due to radio frequency signal propagation. The piezoelectric actuator is coupled to radio frequency (RF) line through a gap of 0.25 mm. When a voltage signal of 10 Vpp propagates in the line it sets an alternating current in the actuator electrodes. This flowing current drives the piezoelectric cantilever to mechanical movement, especially when the frequency of the RF signal matches the mechanical resonant frequency of the cantilever. Output voltage signals versus frequency for both mechanical vibrational and RF signal excitations have been measured using different loads.

Effects of nuclear explosions on the ionosphere

The ionization produced in the lower ionosphere by x-rays, β-particles from neutron decay and β and γ-radiation from fission debris from a nuclear burst is examined. The effects of this increased ionization on the propagation of radio frequency signals in the various bands is considered.