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학술지 An Evaluation Methodology for Spectrum Usage in LTE-A Networks: Traffic Volume and Resource Utilization Perspective
Cited 18 time in scopus Download 9 time Share share facebook twitter linkedin kakaostory
저자
박승근, Mamta Agiwal, 권혜연, 허진
발행일
201906
출처
IEEE Access, v.7, pp.67863-67873
ISSN
2169-3536
출판사
IEEE
DOI
https://dx.doi.org/10.1109/ACCESS.2019.2918646
협약과제
19HR1500, 전파자원 선순환을 위한 주파수 분석 기술 개발, 박승근
초록
Rising popularity of online gaming and video streaming applications are making tremendous data demands on cellular networks. With higher resolutions, novel multimedia services, and ubiquitous video streaming, the objective to fulfill the quality constraints becomes critical and challenging. It is important that a network operator is able to optimize its resource usage while being able to guarantee the quality of service (QoS) to its subscribers. To this regard, we first propose a methodology to evaluate the upper limits on the traffic volume and the usage of resource blocks for a single cell to ensure seamless video streaming in dense urban environments. By applying these upper limits to the cells distributed in a large area, we subsequently investigate if the deployed spectrum of a network operator is sufficient to address the traffic demands without compromising the QoS. In particular, the upper limits are evaluated by considering practical resource usage pattern of video streaming along with the spectral efficiency analysis. Our statistical study is based on real time, in-field measurements from live LTE-A systems in Seoul, South Korea. Moreover, using system level simulations we forecast the average spectral efficiency of a cell which can be utilized to predict the cell traffic volume per hour. The understanding of current practical resource usage in LTE-A systems along with the methodology proposed in this paper can help network operators for efficient future spectrum deployments.
KSP 제안 키워드
Cellular networks, Dense urban, In-field measurements, LTE-A networks, Long term evolution-advanced(LTE-A), Multimedia Service, Network operator, Online gaming, Real-Time, Resource Block(RB), Resource usage pattern