Software Design Analysis and Implementation of OFDMA and Its Computing Architecture Analysis for 5G/4G eNodeB

Dessai, Sanket N.; Patidar, Hemant

doi:10.1007/s11277-023-10335-1

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…Technological advancements over the years have led to the integration of numerous Internet of Things (IoT) technologies, resulting in more advanced and sophisticated systems such as online monitoring [1][2][3][4] embedded hardware-software [5][6][7][8] and intelligent system [9][10][11]. As has been noted, the increasing prominence of these IoT technologies provides greater advantages to enhance the efficacy of conventional processes or approaches; as a result, these technologies have been extensively investigated and deployed in various sectors, including the food and agriculture industry, including bee farming.…”

Section: Introductionmentioning

confidence: 99%

Real-Time IoT-Blynk Application for Log Hive Weight Monitoring in Stingless Bees

Jani,

Hairuddin,

Ja’afar

et al. 2024

I2M

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The paper aims to develop a weight-sensing system and monitoring platform to track the activity patterns of a stingless bee colony using a weight-sensing system that consists of an Arduino Mega, a NodeMCU ESP8266, and load cell as weight sensors with a Real-Time Clock (RTC) module. The system was designed with an improved weight sensor that includes triangle or delta positioning and placement for greater stability on the log hive. It also featured real-time mobile monitoring via the Blynk application, which sends weight measurements continuously via Wi-Fi. It shows that the weight fluctuations indicate that the stingless bees are most active in their foraging activities between 9:00 and 13:00, with occasional activity between 21:00 and 22:00, gathering food sources to produce honey or beebread. Consequently, analysing the daily pattern of weight measurements using a correlation analysis throughout a week enable beekeepers to observe their diverse foraging patterns. These patterns can be strongly linked to the movements of active bees, human interference, or environmental errors when the correlation value approaches one. The findings of this research can assist beekeepers in understanding routine activities by observing the foraging patterns of stingless bees, which could reveal valuable insights regarding bee health and honey production levels and help detect a decline in the bee colony. This can be achieved by utilising Internet of Things (IoT) technology to enhance hive management practices.

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Section: Introductionmentioning

confidence: 99%

Real-Time IoT-Blynk Application for Log Hive Weight Monitoring in Stingless Bees

Jani,

Hairuddin,

Ja’afar

et al. 2024

I2M

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Performance analysis of wireless compressed-image transmission over DST-based OFDMA systems

Al‐Ashwal

Soufy

Al-Kamali

et al. 2023

J Wireless Com Network

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Multimedia data, like images, consumes significant bandwidth when transmitted over wireless systems. Therefore, compressing transmitted images becomes crucial to reduce the required bandwidth and improve energy efficiency. This work aims to analyze the performance of transmitting wireless compressed images over a recent Discrete Sine Transform (DST)-Based Orthogonal Frequency Division Multiple Access (DST-OFDMA) system. It investigates the effectiveness of several image compression methods by determining the minimum Signal-to-Noise Ratio (SNR) required for each method to achieve error-free image recovery at the receiver. This work considers different modulation schemes including 16QAM and QPSK, as well as different subcarrier mapping schemes (localized and interleaved) over vehicular A, SUI3, and uniform channels. Nine standard compression methods are used for analyzing the performance of the DST-OFDMA system and compared it with that of the conventional Discrete Fourier Transform (DFT)-based OFDMA (DFT-OFDMA) system. The results show that the performance of DST-OFDMA outperforms that of DFT-OFDMA, especially when QPSK modulation is used. Simulation results demonstrate that the interleaved DST-OFDMA (DST-IOFDMA) system, employing the SPIHT_3D compression method and QPSK modulation (over the SUI3 channel model), achieves the lowest SNR value required for compressed image recovery, approximately 18 dB. This indicates that the SPIHT_3D compression method exhibits lower power consumption compared to other methods as well as high bandwidth efficiency.

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Software Design Analysis and Implementation of OFDMA and Its Computing Architecture Analysis for 5G/4G eNodeB

Cited by 2 publications

References 13 publications

Real-Time IoT-Blynk Application for Log Hive Weight Monitoring in Stingless Bees

Real-Time IoT-Blynk Application for Log Hive Weight Monitoring in Stingless Bees

Performance analysis of wireless compressed-image transmission over DST-based OFDMA systems

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