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5G , NR , LTE , mmWave , Speed Test and Throughput Dataset

If you use this dataset and code or any herein modified part of it in any publication, please cite the papers:

A. Thantharate, C. Beard and S. Marupaduga, "An Approach to Optimize Device Power Performance Towards Energy Efficient Next Generation 5G Networks," 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2019, pp. 0749-0754, doi: 10.1109/UEMCON47517.2019.8993067.

A. Thantharate, C. Beard and S. Marupaduga, "A Thermal Aware Approach to Enhance 5G Device Performance and Reliability in mmWave Networks," 2020 International Symposium on Networks, Computers and Communications (ISNCC), 2020, pp. 1-5, doi: 10.1109/ISNCC49221.2020.9297313.

An Approach to Optimize Device Power Performance Towards Energy Efficient Next Generation 5G Networks https://ieeexplore.ieee.org/abstract/document/8993067

In Fifth Generation (5G), wireless cellular networks, smartphone battery efficiency, and optimal utilization of power have become a matter of utmost importance. Battery and power are an area of significant challenges considering smartphones these days are equipped with advanced technological network features and systems. These features require much simultaneous power to make decisions and to transfer information between devices and network to provide best the user experience. Furthermore, to meet the demands of increased data capacity, data rate, and to provide the best quality of service, there is a need to adopt energy-efficient architectures. This paper presents system-level architectural changes on both User Equipment (UE) and Network elements along with a proposal to modify control signaling as part of Radio Resource Control messages using smartphone battery level. Additionally, we presented real-world 5G mmWave field results, showing impacts on device battery life in varying RF conditions and proposed methods to allocate optimal network resources and improve the energy efficiency by modifying radio layer parameters between devices and base stations. Without these proposed architecture level and system-level algorithm changes, realizing optimal and consistent 5G speeds will be near impossible.

A Thermal Aware Approach to Enhance 5G Device Performance and Reliability in mmWave Networks https://ieeexplore.ieee.org/abstract/document/9297313

5G NR (New Radio) mmWave networks are creating novel avenues of numerous possibilities and improving mobile broadband in terms of capacity, throughput, and performance, driven by the insatiable demand for faster and better user experience. However, one of the critical problem areas for User Equipment (UE) in mmWave networks is the fast depletion of UE battery power, increase in thermal levels caused by limited coverage and lot of overhead signaling due to rapid radio frequency (RF) and environment changes. With the growing inclusion of advanced functionality on mobile devices, power consumption is growing in parallel, which causes devices to increase thermal temperature, causing an impact on overall system performance. This paper presents system-level change proposal on control signaling between UE and network elements along with changes in UE thermal algorithms based on device battery levels and the coverage of the 5G mmWave networks to deliver the best device performance and user experience. Furthermore, we present real-world field results captured on mmWave networks showing impacts on UE performance with respect to thermal generation in different RF conditions. Our proposal will allocate optimal network resources by modifying the system selection on both UE and base stations. Without the proposed model, realizing the benefits of the 5G NR system along with achieving seamless cellular user experience would be near impossible.

5G , NR , LTE , mmWave , Smartphone , Battery , Power Optimization , Energy Efficiency , Network Efficiency, 5G NR , mmWave , Smartphone , Thermal , Device Temperature , User Equipment , Battery , Network Efficiency , Load Balancing , 3GPP , Power Efficiency , Green Energy

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5G NR Throughput Dataset, 6G Dataset, Wireless Network Dataset

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