Jordi Mongay Batalla
ABSTRACT
The Regulatory Authority monitors and regulates the telecom market at a national-wide range. One of its main tasks is to put spectrum at disposal of the Mobile Network Operators (MNO) for serving the increase number of users and services. For this scope, the Regulator needs to have an independent estimation of the usage of the radio resources by the operators, so that it may anticipate future needs and to initiate actions (e.g., liberation of frequency bands) directed to fulfill the demands of the market. This paper presents a methodology for Regulator-triggered monitoring of 5G radio resources allocation. The requirements of the methodology are: (1) monitoring measurements must be external to the network, (2) information from the MNO is limited to the data of the radio infrastructure, such as localization and technical data of the antennas, and (3) any measurements need to be cost-effective since it is supposed that the Regulator will make extended test campaigns through the whole national territory. Our results of 5G measurements validate the methodology and show the limitations of the estimation of radio resource allocation.
- A. Narayanan et al., "A Comparative Measurement Study of Commercial 5G mmWave Deployments," IEEE INFOCOM 2022 - IEEE Conference on Computer Communications, 2022, pp. 800--809, doi: 10.1109/INFOCOM48880.2022.9796693Google Scholar
Digital Library
- ETSI TS 138 214, ''Physical layer procedures for data', Release 17. May 2022Google Scholar
- ETSI TS 123 502, Procedures for the 5G System, Release 15, June 2018Google Scholar
- A. Gupta and R. K. Jha, "A Survey of 5G Network: Architecture and Emerging Technologies," in IEEE Access, vol. 3, pp. 1206--1232, 2015, doi: 10.1109/ACCESS.2015.2461602Google ScholarCross Ref
- ETSI TS 138 314, 5G NR Layer 2 Measurements, Release 16, July 2020Google Scholar
- C. -X. Wang, J. Bian, J. Sun, W. Zhang and M. Zhang, "A Survey of 5G Channel Measurements and Models," in IEEE Communications Surveys & Tutorials, 20(4) 3142--3168, 2018, doi: 10.1109/COMST.2018.2862141Google ScholarDigital Library
- Y. Kim et al., "Full dimension mimo (FD-MIMO): the next evolution of MIMO in LTE systems," in IEEE Wireless Communications, vol. 21, no. 2, pp. 26--33, April 2014, doi: 10.1109/MWC.2014.6812288.Google ScholarCross Ref
- T. Lu, Z. Fan, Y. Lei, Y. Shang and C. Wang, "The Edge Computing Cloud Architecture Based on 5G Network for Industrial Vision Detection," 2021 IEEE 6th International Conference on Big Data Analytics (ICBDA), 2021, pp. 328--332, doi: 10.1109/ICBDA51983.2021.9402999Google Scholar
- A. Tikhomirov, E. Omelyanchuk and A. Semenova, "Recommended 5G frequency bands evaluation," 2018 Systems of Signals Generating and Processing in the Field of on Board Communications, 2018, pp. 1--5, doi: 10.1109/SOSG.2018.8350639Google Scholar
- Tahir, MN, Katz, M. Performance evaluation of IEEE 802.11p, LTE and 5G in connected vehicles for cooperative awareness. Engineering Reports. 2022; 4( 4):e12467. doi:10.1002/eng2.12467Google Scholar
- A. Morton, Active and Passive Metrics and Methods, RFC7799, 2016Google Scholar
- Dunhao Zhong and Azzedine Boukerche. 2019. Traffic Signal Control Using Deep Reinforcement Learning with Multiple Resources of Rewards. In Proceedings of the 16th ACM International Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN '19). Association for Computing Machinery, New York, NY, USA, 23--28. https://doi.org/10.1145/3345860.3361522Google ScholarDigital Library
- J. Mongay Batalla, M. Moshin, C. X. Mavromoustakis, K. Wesolowski, G. Mastorakis and K. Krzykowska-Piotrowska, On deploying the Internet of Energy with 5G Open RAN technology including beamforming mechanism, Energies 2022, 15, 2429. DOI: 10.3390/en15072429Google Scholar
- J. Mongay Batalla, On analyzing video transmission over wireless WiFi and 5G C-band in harsh IIoT environments. IEEE Access, vol. 8, pp. 118534--118541, 2020. DOI: 10.1109/ACCESS.2020.3005641Google ScholarCross Ref
- Xu, Dongzhu et al., Understanding Operational 5G: A First Measurement Study on Its Coverage, Performance and Energy Consumption, SIGCOMM '20, Virtual Event, USA, 2020. DOI: 10.1145/3387514.3405882Google ScholarDigital Library
- Marcelo S. Alencar. 2020. Epidemic Interference in a Cellular System. In Proceedings of the 17th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN '20). Association for Computing Machinery, New York, NY, USA, 81--84. https://doi.org/10.1145/3416011.3424748Google ScholarDigital Library
- ETSI TS 128 533, 5G, Management and orchestration, Architecture framework, Release 15, Oct. 2018Google Scholar
- J. Mongay Batalla, Advanced Multimedia Service Provisioning based on efficient interoperability of adaptive streaming protocol and High Efficient Video Coding. Springer Journal of Real-Time Image Processing. 2016. DOI: 10.1007/s11554-015-0496--4Google ScholarCross Ref
- Tito Raúl Vargas, Juan Carlos Guerri, and Pau Arce. 2021. Study on the Impact of DASH Streaming Services using Energy Efficient Ethernet. In Proceedings of the 18th ACM Symposium on Performance Evaluation of Wireless Ad Hoc, Sensor, & Ubiquitous Networks (PE-WASUN '21). Association for Computing Machinery, New York, NY, USA, 89--94. DOI: 10.1145/3479240.3488527Google ScholarDigital Library
- J. Mongay Batalla, E. Andrukiewicz, G. Peinado Gomez, P. Sapiecha, C. X. Mavromoustakis, G. Mastorakis, J. Zurek, M. Imran, Security Risk Assessment for 5G networks - national perspective. IEEE Wireless communications, vol. 27, no. 4, pp. 16--22, Aug. 2020. DOI: 10.1109/MWC.001.1900524Google Scholar
Index Terms
- Cost-effective Measurements of 5G Radio Resources Allocation for Telecom Market Regulator's Monitoring
Recommendations
On studying active radio measurements estimating the mobile network quality of service for the Regulatory Authority's purposes
AbstractThe Regulatory Authority monitors and regulates the telecom market at a national-wide range. One of its main tasks is to put spectrum at the disposal of the Mobile Network Operators (MNOs) for serving the increasing number of users and services. ...
An uplink resource allocation scheme for OFDMA-based cognitive radio networks
Cognitive radio makes it possible for an unlicensed user to access a spectrum unoccupied by licensed users. In cognitive radio networks, extra constraints on interference temperature need to be introduced into radio resource allocation. In this paper, ...
Radio Resource Allocation for Overlapping MBS Zones
MWS '09: Proceedings of the 2009 IEEE Mobile WiMAX SymposiumMulticast and broadcast service (MBS) is one of the important services for next generation wireless systems. In WiMAX, the radio resource unit (i.e., time, frequency, code, etc.) for MBS is centralized allocated by a network device named Anchor ASN-GW. ...
Comments