5G Testbed Implementation and Measurement Campaign for Ground and Aerial Coverage

Fjodorov, Aleksei; Masood, Ali; Alam, Muhammad Mahtab; Pärand, Sven

doi:10.1109/bec56180.2022.9935602

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…Ref. [ 27 ] conducted a measurement campaign on a 5G-NR gNB using n78 (60 MHz TDD 4:1) with 4 × 4 MIMO for DL and 2 × 2 MIMO for UL. The results showed that a comparable result achieved without MIMO per RB is 0.8 Mbps for DL and 0.9 Mbps for UL.…”

Section: Subslice Performance Evaluation At Different Subslice Sizesmentioning

confidence: 99%

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning

Kulmar

Müürsepp

Alam

2023

Sensors

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In 5G and beyond, the network slicing is a crucial feature that ensures the fulfillment of service requirements. Nevertheless, the impact of the number of slices and slice size on the radio access network (RAN) slice performance has not yet been studied. This research is needed to understand the effects of creating subslices on slice resources to serve slice users and how the performance of RAN slices is affected by the number and size of these subslices. A slice is divided into numbers of subslices of different sizes, and the slice performance is evaluated based on the slice bandwidth utilization and slice goodput. A proposed subslicing algorithm is compared with k-means UE clustering and equal UE grouping. The MATLAB simulation results show that subslicing can improve slice performance. If the slice contains all UEs with a good block error ratio (BLER), then a slice performance improvement of up to 37% can be achieved, and it comes more from the decrease in bandwidth utilization than the increase in goodput. If a slice contains UEs with a poor BLER, then the slice performance can be improved by up to 84%, and it comes only from the goodput increase. The most important criterion in subslicing is the minimum subslice size in terms of resource blocks (RB), which is 73 for a slice that contains all good-BLER UEs. If a slice contains UEs with poor BLER, then the subslice can be smaller.

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Section: Subslice Performance Evaluation At Different Subslice Sizesmentioning

confidence: 99%

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning

Kulmar

Müürsepp

Alam

2023

Sensors

Self Cite

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“…Once forests usually are large areas of difficult access, and spreading sensors along forests pose several challenges, namely regarding power supply and data transmission. Due to the areas’ dimensions that need to be covered, Low Power Wide Area Network (LPWAN) technologies [ 16 , 17 ], such as Long Range (LoRa) [ 18 , 19 ], SigFox [ 20 , 21 ], Long Term Evolution (LTE), or 5G [ 22 , 23 , 24 , 25 , 26 ], are reasonable solutions [ 27 , 28 ]. However, LoRa technology is earning popularity since it provides efficient communication with good battery lifetime, capacity, range, and cost [ 28 , 29 ].…”

Section: Related Workmentioning

confidence: 99%

Data Acquisition Filtering Focused on Optimizing Transmission in a LoRaWAN Network Applied to the WSN Forest Monitoring System

Brito

Azevedo

Mendes

et al. 2023

Sensors

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Developing innovative systems and operations to monitor forests and send alerts in dangerous situations, such as fires, has become, over the years, a necessary task to protect forests. In this work, a Wireless Sensor Network (WSN) is employed for forest data acquisition to identify abrupt anomalies when a fire ignition starts. Even though a low-power LoRaWAN network is used, each module still needs to save power as much as possible to avoid periodic maintenance since a current consumption peak happens while sending messages. Moreover, considering the LoRaWAN characteristics, each module should use the bandwidth only when essential. Therefore, four algorithms were tested and calibrated along real and monitored events of a wildfire. The first algorithm is based on the Exponential Smoothing method, Moving Averages techniques are used to define the other two algorithms, and the fourth uses the Least Mean Square. When properly combined, the algorithms can perform a pre-filtering data acquisition before each module uses the LoRaWAN network and, consequently, save energy if there is no necessity to send data. After the validations, using Wildfire Simulation Events (WSE), the developed filter achieves an accuracy rate of 0.73 with 0.5 possible false alerts. These rates do not represent a final warning to firefighters, and a possible improvement can be achieved through cloud-based server algorithms. By comparing the current consumption before and after the proposed implementation, the modules can save almost 53% of their batteries when is no demand to send data. At the same time, the modules can maintain the server informed with a minimum interval of 15 min and recognize abrupt changes in 60 s when fire ignition appears.

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5G Campus Network Factory Floor Measurements with Varying Channel and QoS Flow Priorities

Hamidovic,

Hadziaganovic,

Muzaffar

et al. 2023

IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society

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5G Testbed Implementation and Measurement Campaign for Ground and Aerial Coverage

Cited by 5 publications

References 3 publications

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning

Data Acquisition Filtering Focused on Optimizing Transmission in a LoRaWAN Network Applied to the WSN Forest Monitoring System

5G Campus Network Factory Floor Measurements with Varying Channel and QoS Flow Priorities

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