Jin Teong Ong

Bio: Jin Teong Ong is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Attenuation & Site diversity. The author has an hindex of 12, co-authored 31 publications receiving 547 citations.

GPS-Derived PWV for Rainfall Nowcasting in Tropical Region

Abstract: In this paper, a simple algorithm is proposed to perform the nowcasting of rainfall in the tropical region. The algorithm applies global positioning system-derived precipitable water vapor (PWV) values and its second derivative for the short-term prediction of rainfall. The proposed algorithm incorporates the seasonal dependency of PWV values for the prediction of a rain event in the coming 5 min based on the past 30 min of PWV data. This proposed algorithm is based on the statistical study of four-year PWV and rainfall data from a station in Singapore and is validated using two-year independent data for the same station. The results show that the algorithm can achieve an average true detection rate and a false alarm rate of 87.7% and 38.6%, respectively. To analyze the applicability of the proposed algorithm, further validations are done using one-year data from one independent station from Singapore and two-year data from one station from Brazil. It is shown that the proposed algorithm performs well for both the independent stations. For the station from Brazil, the average true detection and false alarm rates are around 84.7% and 37%, respectively. All these observations suggest that the proposed algorithm is reliable and works well with a good detection rate.

Truncated Gamma Drop Size Distribution Models for Rain Attenuation in Singapore

Abstract: A model that is less sensitive to errors in the extreme small and large drop diameters, the gamma model with central moments (3, 4 and 6), is proposed to model the rain drop size distribution of Singapore. This is because, the rain rate estimated using measured drop size distribution shows that the contributions of lower drop diameters are small as compared to the central drop diameters. This is expected since the sensitivity of the Joss distrometer degrades for small drop diameters. The lower drop diameters are therefore removed from the drop size data and the gamma model is redesigned for its moments. The effects of the removal of a particular rain drop size diameter on the specific rain attenuation (in dB) and the slant-path rain attenuation calculations with forward scattering coefficients for vertical polarization are analyzed at Ku-band, Ka-band and Q-band frequencies. It is concluded that the sensitivity of the Joss distrometer although affects the rain rate estimation at low rain rates, does not affect the slant path rain attenuation on microwave links. Therefore, the small drop diameters can be ignored completely for slant path rain attenuation calculations in the tropical region of Singapore.

Performance of Site Diversity Investigated Through RADAR Derived Results

Abstract: Site diversity is an effective rain attenuation mitigation technique, especially in the tropical region with high rainfall rate. The impact of different factors such as site separation distance, frequency, elevation angle, polarization angle, baseline orientation and wind direction is assessed. Results are compared to those reported in existing literature and also compared to the commonly used ITU-R site diversity prediction models. The effect of the wind direction on site diversity is also presented. It can be observed that diversity gain is highly dependent on the site separation distance, elevation angle and wind direction but independent of the frequency, baseline angle and polarization angle of the signal. This study is useful for the implementation of site diversity as a rain attenuation mitigation technique.

Raindrop size distribution using method of moments for terrestrial and satellite communication applications in Singapore

Abstract: As communication services using higher frequencies are growing rapidly in the tropics, there is an increasing need for a finer model to predict the attenuation due to rain. The raindrop size distribution (DSD) is one of the major sources of error in any prediction model, mainly because of its variability in both space and time. The DSD parameters are computed from distrometer data that are classified into stratiform and convective types using S-band radar data. The method of moments is employed to estimate the parameters of lognormal DSD. The modeled DSD parameters are optimized by examining the root mean square (RMS) error and the average probability ratio (APR) in estimation of the rain rate, rain attenuation, and radar reflectivity factor simultaneously. The proposed model gives maximum (close to unity) APR and minimum RMS error when compared to any other set of DSD parameters.

Ka-band land mobile satellite channel model incorporating weather effects

Abstract: A Ka-band land mobile satellite (LMS) channel model which is able to take into account weather impairments is proposed. The statistics of the received signal and the BER performance of the system under the proposed channel model are obtained and compared with the results generated using Loo's weather-affected LMS channel model. The proposed Ka-band (20/30 GHz) LMS channel model is shown to be more reasonable as it gives realistic results.

Transponder systems for automatic identification purposes

Abstract: A method of communicating between an interrogator (10) and at least a first and second transponder (12). The transponders (12) are separately located within a first and a second vehicle (20) travelling within a first and a second traffic lane, respectively. The method has the steps of providing a first and a second LF antenna (16) associated with and proximity to a first and a second traffic lane, respectively. From each of the first and second LF antennas (16) a continuous LF subcarrier is transmitted to serve as a clock signal for each antenna's associated transponder (12). Initially, a wake-up signal is sent by each of the LF antennas (16) to its associated transponder (12). Following the wake-up signal, a unique lane code is sent by each of the LF antennas (16) to its associated transponder (12). The transponder (12) stores its unique lane code in its memory (70). The transponder then sends a UHF response in a pre-determined time period depending on the unique lane code stored in each of the transponders (12). The time period in which the transponder (12) sends its UHF response is unique to that transponder (12) so that interference between responding transponders (12)is avoided. Other devices, systems and methods are also disclosed.

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

Abstract: A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).

Single Aircraft Integration of Remote Sensing and In Situ Sampling for the Study of Cloud Microphysics and Dynamics

Abstract: Clouds are a critical component of the Earth's coupled water and energy cycles. Poor understanding of cloud–radiation–dynamics feedbacks results in large uncertainties in forecasting human-induced climate changes. Better understanding of cloud microphysical and dynamical processes is critical to improving cloud parameterizations in climate models as well as in cloud-resolving models. Airborne in situ and remote sensing can make critical contributions to progress. Here, a new integrated cloud observation capability developed for the University of Wyoming King Air is described. The suite of instruments includes the Wyoming Cloud Lidar, a 183- GHz microwave radiometer, the Wyoming Cloud Radar, and in situ probes. Combined use of these remote sensor measurements yields more complete descriptions of the vertical structure of cloud microphysical properties and of cloud-scale dynamics than that attainable through ground-based remote sensing or in situ sampling alone. Together with detailed in situ data on aeroso...

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

Abstract: A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an altitude around 20 km and is instrumental for providing communication services. Triggered by the technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels and the battery energy density, and fueled by the flourishing industry ecosystems, the HAPS exerts itself as an indispensable component of the next generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature survey. We highlight the undiscovered potential of HAPS systems, and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a costeffective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are delineated. The notable contribution of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The provided extensive overview of the literature is crucial for substantiating our vision that that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).

Real Measurement Study for Rain Rate and Rain Attenuation Conducted Over 26 GHz Microwave 5G Link System in Malaysia

Abstract: In this paper, real measurements were conducted to investigate the impact of rain on the propagation of millimeter waves at 26 GHz. The measurements were accomplished using a microwave fifth generation radio link system with 1.3 km path length implemented at Universiti Teknologi Malaysia Johor Bahru, Malaysia. The implemented system consisted of Ericsson CN500 mini E-link, radio unit, rain gauge, and data logger. The measurements were attained and logged daily for a continuous year, with 1-min time intervals. Next, the MATLAB software was used to process and analyze the annual rain rate and rain attenuation, including for the worst month. From the analyzed results, it was found that at 0.01% percentage of time, the rain rate was 120 mm/hr; while the specific rain attenuation was 26.2 dB/km and the total rain attenuation over 1.3 km was 34 dB. In addition, the statistics acquired from the measurements for the worst month were lower than what was predicted by the international telecommunication union (ITU) model; around 51% and 34% for the rain rate and rain attenuation, respectively. The average percentage of error calculated between the measurements and predicted results for the rain rate and rain attenuation were 143% and 159%, respectively. Thus, it can be concluded that the statistics for the worst month in Malaysia is lower than what was predicted by the ITU model.