Now showing 1 - 8 of 8
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    Detection of data symbol in a massive MIMO systems for 5G wireless communication
    The massive MIMO technique has played the most important role in 5G wireless communication. It is anticipated that the new techniques employed in massive MIMO will not only improve peak service data rates significantly, but also enhance capacity, coverage, low-latency, efficiency flexibility, compatibility and convergence, thus meeting the focusing demands imposed by optimal detection. This paper presents the optimal detection of data symbol in massive MIMO for 5G wireless communication. Based on the frequency non-selective fading MIMO channel, we consider three difference detectors for recovering the transmitted data symbols and evaluate their performance for Rayleigh fading and additive white Gaussian noise (AWGN). At the results, we show that the probability of error rate (PER) performance of the detectors are significantly discussed.
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    Identifying Geomagnetic Storms with Ionospheric Storm Scale for GNSS and Disaster Prevention
    (2020-03-01) ; ; ; ;
    Tangtrakunphaisan, Udomsit
    This paper proposes an ionospheric storm scale (I-scale) for identifying the impact of geomagnetic or ionospheric storms in the Ionosphere for GNSS (global navigation satellite system) service and disaster prevention. The I-scale in this work is computed based on the observed foF2 at Chumphon station (10.72°N, 99.37°E) over equatorial latitude from January 2004 to July 2018. The results report that the severe geomagnetic storms, i.e., IP3 and IN3, seldom occur at Chumphon with the probabilities of 0.02% and 0.07%, respectively. The probability of quiet ionospheric condition is the maximum value of 70.73%. Meanwhile, the other I-scales sometimes occur and range from 0.60% to 13.97%. The benefits of the foF2-based I-scale are to indicate the violence level of geomagnetic storms and to announce the ionospheric irregularities in practice.
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    Analysis of Bottomside Thickness Parameter-Based TEC at Equatorial and Low Latitude Stations for Global Navigation Satellite Systems
    (2018-07-02) ; ;
    Tangtrakunphaisan, Udomsit
    This paper studies the total electron content (TEC) at equatorial and low latitude stations which is computed using an equation of bottomside thickness parameter with correction factor (B2botP-new) during the solar maximum of 24th solar cycle. The computed TEC is used to compute the ionospheric time delay subsequent-tially. The ionospheric stations in this work include Ramey, Ascension Island, and Jicamarca. The results show that the diurnal and seasonal variations of B2botP-new have the same trends as that of B0-obs as well as the B2botP-new values are close to the BO-obs values clearly for all three stations. The electron density diffuses from the equator toward the EIA region (15°N and 15°S) during the period of 14-23 LT. The proposed TEC (TEC-P) are computed using the B2botP-new, and then the ionospheric delay is also computed using the TEC-P. The computed TEC-P and Id-P are close to the TEC-obs and Id-obs, but they should be further studied for a solar cycle (11 years).
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    A Study of Air Pollution Smart Sensors LPWAN via NB-IoT for Thailand Smart Cities 4.0
    (2018-08-06) ;
    Takarn, Aekarong
    ;
    Nujankaew, Rachan
    ;
    The problem of air pollutant has to improve urgently, in particular, approach to smart city in 2024 of Thailand 4.0. This paper presents a development of smart sensors of air pollution to monitor the air quality in smart city. We propose the smart sensors that consist of the particulate matter (PM<inf>10</inf>) or dust sensor, carbon monoxide (CO), carbon dioxide (CO<inf>2</inf>), noise level (dB), and ozone (O<inf>3</inf>) respectively. These sensors are solution of a low power wide area network (LPWAN). In the experiment, the measurement has been investigated in Bangkok metropolitan, and the results show air quality index (AQI) via Norrowband Internet of Things (NB-IoT). The proposed of this paper can help the people know the real-time air quality via IoT as a service.
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    Exploring Ground Reflection Effects on Received Signal Strength Indicator and Path Loss in Far-Field Air-to-Air for Unmanned Aerial Vehicle-Enabled Wireless Communication
    Unmanned aerial vehicle (UAV)-enabled wireless communications are becoming increasingly important in applications such as maritime and forest rescue operations. UAV systems often depend on wireless networking and mobile edge computing (MEC) devices for effective deployment, particularly in swarm UAV-enabled MEC configurations focusing on channel modeling and path loss characteristics for air-to-air (A2A) communications. This paper examines path loss characteristics in far-field (FF) ground reflection scenarios, specifically comparing two environments: FF1 (forest floor) and FF2 (seawater floor). LoRa modules operating at 868 MHz were deployed for communication between a transmitting UAV (Tx-UAV) and a receiving UAV (Rx-UAV) to conduct this study. We investigated the received signal strength indicator (RSSI) and path loss characteristics across channel bandwidths of 125 kHz and 250 kHz and spread factors (SF) of 7, 9, and 12. Experimental results show that ground reflection has minimal impact in the FF1 scenario, whereas, in the FF2 scenario, ground reflection significantly influences communication. Therefore, in the seawater environment, a UAV-enabled LoRa MEC configuration using a 250 kHz bandwidth and an SF of 7 is recommended to minimize the effects of ground reflection.
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    A New Method for Computing Ionogram-Based TEC Based on Digisonde data for Disaster Prevention
    (2020-03-01) ; ; ;
    Srisamoodkham, Worachai
    This paper presents a new approach for calculating the ionogram-based total electron content so as to be applied alternatively for alarming and preventing the disasters, for example, earthquake, tsunami or other space objectives. The proposed ITEC is estimated using the analytical expression of NeQuick model, the autoscaled Digisonde data, and a new variable "m" of 1. The results are show that 1) the proposed B0 is close to the B0-obs of Digisonde compared to the B0-IRI and the B2bot of the NeQuick model, 2) the diurnal variation of B0-Pro is the same as that of B0-obs compared to those of B0-IRI and B2bot, 3) the proposed ITEC is also close to the ITEC of Digisonde and TEC-iri, excluding the observed GPS TEC, and 4) all of the studied TEC values behave similar diurnal variations. Since the proposed ITEC is based on the analytical functions, the improvement of TEC-B0-Pro can be conducted reliably in order to close to the GPS TEC possibly and apply it optionally to correct the positioning errors for GNSS and aviation systems.
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    A study on tourism mobile web application based on big data analysis platform for the South of Thailand
    In this paper, we propose to a study on tourism dashboard on mobile web application by approaching based on big data analysis platform for tourism data in southern of Thailand. A case study of this paper is Chumphon province that is a gateway to southern of Thailand. To satisfy and convenient to support tourism information, our design dashboard information can useful for the tourist to plan their traveling as easily. The proposed system consists of data tourism, data storage, data processing, data visualization, and user interface (UI). Note that the proposed system is based on big data analysis platform. Therefore, this proposed system of tourism dashboard on mobile web application can very useful to promote the tourists of the south of Thailand as a growing fast.
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    A Development on Air Pollution Detection Sensors based on NB-IoT Network for Smart Cities
    (2018-12-24) ;
    Takarn, Aekarong
    ;
    Currently, air pollution is a big problem for people health in cities that suffered from the more factors such as the traffic, industrial, or forest fire or polluted skies. This paper presents a development of air pollution detection sensors and monitoring for smart city, Thailand 4.0. The development is designed by using five standard sensors such as carbon dioxide: CO, ozone: O <inf>3</inf> , particulate matter: PM <inf>10</inf> , nitrogen dioxide: NO <inf>2</inf> , and sulfur dioxide: SO <inf>2</inf> respectively, and web monitor shows the graph of the air quality index (AQI). To monitor the air quality, the data processing is computed by using Arduno MEGA 2560 and Respberri Pi 3 to connect with Narrowband Internet of Things (NB-IoT) module network. Experimental setup, the measurement location is examined at Sai Mai District, Bangkok. As the result, we found that the AQI level of measured location is good air quality. We emphasize that the monitoring of air pollution in smart cities is very important.