Fundamental Implications for Location Accuracy in Ultra-Dense 5G Cellular Networks

At the threshold of 5G, much is promised based on the predicate of hyper-accurate location-aware communications. Although the unique spectral real estate associated with 5G implies the possibility of such a persistent localization scheme, we submit that precision range based localization is not a generational inevitability but rather achievable only under the correct architectural philosophy. To show this, we consider a fundamental component that limits or enables any positioning system: the underlying infrastructure geometry. The significance of this research follows from several significant results. First, cell ultra densification, although the primary catalyst of Long Term Evolution (LTE)/LTE-Advanced capacity improvement and a major disruptive technology in 5G networks, will not alone provide for more accurate user positioning. To show this, we derive a closed-form solution to the Cramér–Rao lower bound specific to 5G networks given that infrastructure is distributed via the Poisson point process (PPP). This result is used to justify a positioning services architecture that fundamentally embraces a variable number of supporting access points. In fact, we show that without this architecture, a foundational decline in positioning performance may inadvertently be realized. Finally, by numerically comparing our results with other point processes common in cellular network modeling, we present justification for the PPP as an appropriate model for analyzing positioning performance in ultra dense 5G infrastructures.

[1]  Mohamed-Slim Alouini,et al.  Base Station Ordering for Emergency Call Localization in Ultra-Dense Cellular Networks , 2018, IEEE Access.

[2]  John C. McEachen,et al.  On Location Privacy in LTE Networks , 2017, IEEE Transactions on Information Forensics and Security.

[3]  Shuo Zhang,et al.  Gossip based distributed power control algorithm for 5G ultra dense networks , 2018, 2018 IEEE Wireless Communications and Networking Conference (WCNC).

[4]  Lajos Hanzo,et al.  User-Centric C-RAN Architecture for Ultra-Dense 5G Networks: Challenges and Methodologies , 2017, IEEE Communications Magazine.

[5]  Xiaofeng Tao,et al.  Dense Small Cell Networks: From Noise-Limited to Dense Interference-Limited , 2017, IEEE Transactions on Vehicular Technology.

[6]  Song Guo,et al.  Achieve Sustainable Ultra-Dense Heterogeneous Networks for 5G , 2017, ArXiv.

[7]  Fredrik Tufvesson,et al.  5G mmWave Positioning for Vehicular Networks , 2017, IEEE Wireless Communications.

[8]  Ronald Raulefs,et al.  Survey of Cellular Mobile Radio Localization Methods: From 1G to 5G , 2018, IEEE Communications Surveys & Tutorials.

[9]  Martin Haenggi,et al.  Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[10]  John C. McEachen,et al.  Efficient System Geolocation Architecture in Next-Generation Cellular Networks , 2018, IEEE Systems Journal.

[11]  Lingyang Song,et al.  Load Balancing for 5G Ultra-Dense Networks Using Device-to-Device Communications , 2018, IEEE Transactions on Wireless Communications.

[12]  Mikko Valkama,et al.  High-Efficiency Device Positioning and Location-Aware Communications in Dense 5G Networks , 2016, IEEE Communications Magazine.

[13]  Carlo Fischione,et al.  A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation , 2018, IEEE Communications Surveys & Tutorials.

[14]  Mikko Valkama,et al.  Continuous high-accuracy radio positioning of cars in ultra-dense 5G networks , 2017, 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC).

[15]  Tommy Svensson,et al.  Location-Aware Communications for 5G Networks: How location information can improve scalability, latency, and robustness of 5G , 2014, IEEE Signal Processing Magazine.

[16]  Theodore S. Rappaport,et al.  Millimeter Wave Mobile Communications for 5G Cellular: It Will Work! , 2013, IEEE Access.

[17]  Xiaohu Ge,et al.  Energy Efficiency of Multiuser Multiantenna Random Cellular Networks With Minimum Distance Constraints , 2017, IEEE Transactions on Vehicular Technology.

[18]  Zhao Sun,et al.  Cross-Tier Handover Decision Optimization with Stochastic Based Analytical Results for 5G Heterogeneous Ultra-Dense Networks , 2018, 2018 IEEE International Conference on Communications Workshops (ICC Workshops).

[19]  Xiangyun Zhou,et al.  Coverage and Throughput Analysis with a Non-Uniform Small Cell Deployment , 2013, IEEE Transactions on Wireless Communications.

[20]  Lajos Hanzo,et al.  Connectivity-Based Centroid Localization Using Distributed Dense Reference Nodes , 2018, IEEE Transactions on Vehicular Technology.

[21]  A.H. Sayed,et al.  Network-based wireless location: challenges faced in developing techniques for accurate wireless location information , 2005, IEEE Signal Processing Magazine.

[22]  Navrati Saxena,et al.  Next Generation 5G Wireless Networks: A Comprehensive Survey , 2016, IEEE Communications Surveys & Tutorials.

[23]  Jeffrey G. Andrews,et al.  Modeling and Analysis of K-Tier Downlink Heterogeneous Cellular Networks , 2011, IEEE Journal on Selected Areas in Communications.

[24]  Ismail Güvenç,et al.  A Survey on TOA Based Wireless Localization and NLOS Mitigation Techniques , 2009, IEEE Communications Surveys & Tutorials.

[25]  Jeffrey G. Andrews,et al.  Seven ways that HetNets are a cellular paradigm shift , 2013, IEEE Communications Magazine.

[26]  Jeffrey G. Andrews,et al.  A Tractable Approach to Coverage and Rate in Cellular Networks , 2010, IEEE Transactions on Communications.

[27]  Ying Liu,et al.  Prospective Positioning Architecture and Technologies in 5G Networks , 2017, IEEE Network.

[28]  Cheng-Xiang Wang,et al.  5G Ultra-Dense Cellular Networks , 2015, IEEE Wireless Communications.

[29]  Mohsen Guizani,et al.  5G wireless backhaul networks: challenges and research advances , 2014, IEEE Network.

[30]  Xiaohu Ge,et al.  Vehicular Communications for 5G Cooperative Small-Cell Networks , 2016, IEEE Transactions on Vehicular Technology.

[31]  Qianbin Chen,et al.  An Interference Contribution Rate Based Small Cells On/Off Switching Algorithm for 5G Dense Heterogeneous Networks , 2018, IEEE Access.

[32]  Amr M. Youssef,et al.  Ultra-Dense Networks: A Survey , 2016, IEEE Communications Surveys & Tutorials.

[33]  Jeffrey G. Andrews,et al.  Heterogeneous cellular networks: From theory to practice , 2012, IEEE Communications Magazine.