Efficient System Geolocation Architecture in Next-Generation Cellular Networks

• Published in: IEEE systems journal Vol. 12; no. 4; pp. 3414 - 3425
• Main Authors: Roth, John D., Tummala, Murali, McEachen, John C.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Cellular communication; cellular networks; Computer architecture; Electronic devices; geolocation; Geology; global system for mobile telecommunications (GSM); GSM; Infrastructure; Location based services; location-based services (LBS); Long Term Evolution; Long-Term Evolution (LTE); Mobile communication systems; Next generation networking; Parameter estimation; Systems architecture; Traffic management
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2017.2701903

We propose a shift in the cellular positioning system paradigm that enables cellular providers to better meet the location-based services (LBS) needs of cellular users using only existing network infrastructure. Focusing specifically on current 4G and next-generation 5G technology, we outline a novel positioning system architecture, which utilizes the timing advance parameter to generate continuous position estimates with modern accuracy, minimum overhead, and improved latency. We highlight key limitations in existing positioning methods-excessive data overhead in positioning management traffic and poor network infrastructure geometry-through a review of the Third Generation Partnership Project's positioning system architecture evolution. We then present our alternative architecture, and demonstrate how our proposed system methodology mitigates these concerns, by comparing our proposed architecture with the existing ones. Finally, through numerical study, we establish that our methodology is able to meet and exceed federal emergency services standards and, thus, also many common LBS service requests. Our architecture is agnostic to mobile devices' capabilities and has the potential to alleviate computational burden at the mobile device while simultaneously improving data throughput and latency through reduction of control overhead.