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Big Data Analytics in RF - LTE - 4G Environments


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Big Data Analysis in RF and LTE environments

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Big Data Analytics in RF - LTE - 4G Environments

  1. 1. Big Data Analytics in Radio Frequency Systems Presented by Dr. Edwin Hernandez 7/13/2017 – @edwinhm
  2. 2. Who am I? Dr. Edwin Hernandez has a PhD in Computer Engineering from the University of Florida with 10 issued patents and publications. His expertise is on wireless communications, media, and emulation/simulation. He has been working on Mobile Computing since 1999 and in simulations that include the NS-2 and the RAMON emulator both generation massive amounts of data. His experience in Big data spans from the days prior to the conception of the name and distributed computing was used to solve the same problem 2
  3. 3. Powered by Stadson Tech Introduction •The Radio Frequency Problem (RF) •Mobile CDS – Simulation Platform for RF •Multidimensional Problem • Databases are not necessarily RDBMS • Geo-referencing • Geocoding (Latitude and Longitue) – GPS • RF signal being propagagted •Big data analysis
  4. 4. The RF Propagation Problem They suffer path loss due to trees, Buildings, cars, our hands Some other signals, Reflect Signals propagate, some diffract
  5. 5. Proliferation of Devices and Devices and more… Proper dimensioning of networks, devices, is key RF is more complex with 4G and Even more with 5G Millions of iPhones, Androids, iOT
  6. 6. RF Simulator - MobileCDS
  7. 7. Solution: RF Simulator Database of buildings, depends on physical coordinates Needs to manage, physical properties of an RF Signal wave. Needs to handle, thousands, if not millions of independent rays
  8. 8. Mobile CDS – The Software Software and Source Code in C/C++ - Visual Studio Ray Tracing and Simulation Models. 6 -PTX 1 watt (+30 dBm) -Fc 5.0 GHz -TX ants. Half-wave dipole -HTXd 0.75 meters (on the roof of the vehicle) -RX ant. Half wave dipole -HRX 0.5 meters -Area Outdoor/indoor PRX (dBm)
  9. 9. 9 OUR BACKGROUND Mobile CDS or Mobile Computer Deterministic Simulator is an RF Propagation and Simulation Environment that was created after many years of R&D in the areas of electromagnetics and mobile communications. Mobile CDS is a copyright software package created by S.O.L Wireless, LLC and now represented by EGLA COMMUNICATIONS. This tools is the result of several years of R&D conducted by S.O.L Engineers. EGLA COMMUNICATIONS uses Mobile CDS, provides hosting in its cloud environment, and integrates its simulation RF paremeters with MobileCAD. MobileCAD is a wireless emulation patented tool (7231330) that generates LTE / Smart Cities Simulation environments with base stations and mobile phones with RF Characterization created by MobileCDS
  10. 10. Mobile-CDS includes a state of the art 3D databases toolbox. It allows the user to perform the following operations: o Import 3D databases in one of the following formats; Facet, KML and TIN. o Combine terrain and 3D objects (buildings, vehicles, trees, etc.). o Crop a section of the 3D databases. o Assign different electrical properties to different objects included in the databases. o Delete specific objects. o Duplicate databases 3D Databases
  11. 11. Propagation in 3D Database 11 Vehicles on the street Propagating rays
  12. 12. Keyhole Markup Language (KML) is an XML notation for expressing geographic annotation and visualization within Internet-based, two-dimensional maps and three-dimensional Earth browsers. KML was developed for use with Google Earth, which was originally named Keyhole Earth Viewer. KML
  13. 13. Unstructured Database 13 o Polygons for all buildings o Rays created from all the antennas in multiple directions o Database of results of the simulation o Receivers located at x,y,z positons for a the rays to hit
  14. 14. Database of all signals in all directions o X,Y,X coordinates and power o Simulate antenna and antenna propagation o Unstructured Database Signal Database
  15. 15. Models o Inaccurate o Useless for 3D o High Error Propagation Models are 2D/Probabilistic
  16. 16. WiFi and IOT – Same Situation
  17. 17. MultiDimensionality Models o Positons, Polygons, Materials : Builidngs o Electromagnetic fields: Energy, speed, delay, direction, pathloss, defracted, reflected o Receiver and LTE Protocol: Bit rate, Signal Level, Error, Delay
  18. 18. Big DATA – First Analysis Analysis of multiple trends, Receivers and millions of results Big Data, needs to aggregate values from all Antennas. MapReduce signals per sector, Hadoop, massivley distributed cluster Generates signaling and average power received Output file Lat, Long or X,Y with PathLoss, RMS Delay, Number of Rays
  19. 19. Methods and Algorithms
  21. 21. Parameter Value Wireless Protocol LTE TX frequency (MHz) 2110 TX total average power (dBm) 44.8 Htx (meters) 15 TX antenna pattern 18.0 dBi, 4-sectorS 60 degrees pattern TX Losses 6.0 dB Hrx (meters) 2.0 RX antenna pattern Ideal half-wave dipole RX antenna efficiency (%) 50 Diversity gain (dB) 3 Propagation Environment Heavily populated urban LTE Throughput Simulation Parameters Note: The simulation is representative of the coverage generated by a single base station. Co-Channel interference is not included in the simulation results.Receivers On Horizontal Plane 3D Buildings LTE Protocol Specifications Mehtods and Algorithms : LTE Simulation Sample
  22. 22. Big Data : Extraction Transformation, Loading, Massive CSV files with RF
  23. 23. • Tools • Visual Studio C/C++ for RayTracing Simulation • Python • Hadoop – Parallel Cluster • MapReduce – Could be done in AMAZON WEB SERVICES • OpenCL (GPU is better for ray simulation) – Like a video game • “Open Computing Language (OpenCL) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators. Big Data Analysis Required Observations • Simulations can be done at multiple frequencies from 100MHz to 100GHz or higher depending on CPUs/GPUs
  24. 24. RF : Parallelize with Hadoop/OpenCL Big Data, required to parallelize, extract transform and create Data for each field on the map, x,y,z determine from all the rays RSSI value or Signal Strengh, RMS Delay, Field, etc for all antennas In the simulation All the Rays contain metadata, Electric Field, direction, Intersection with Polygon KML database (Buildings)
  25. 25. Parallelize with Hadoop • Tools • Python-based Tools • Process the TXT/SV files • Windows C/C++ OpenCL
  26. 26. Parallelize with Hadoop/Analysis of the Protocol Analyse a huge matrix of <AntennaiD, x,y,z,RSSI, RMS Delay, BER, etc> All points in the map then need to map to a certain protocol 4G/LTE
  27. 27. Parallelize with Hadoop/GlusterFS • Tools • Python-based Tools • GlusterFS insteadl HDFS • Process the TXT/CSV files
  28. 28. Parameter Value Delay Spread (ns) 1185.0 Coherence BW (MHz) 0.84 Doppler Spread (Hz) 98 Coherence Time (ms) 10.3 28 Radar Simulation Parameters Note: Results in the Value column represent the 50%. More DATA: MONO-STATIC RADAR SIMULATION RESULTS
  29. 29. Advanced Simulations - mmW
  30. 30. Advanced Simulations - In Building
  31. 31. OLTP Transactional aspects of intersections and aggregations All the schema generated for the simulation Propagation Modelling, Insert, Update , Delete,
  32. 32. OLAP Best signal locations in the map Bit rate at different positons Propagation report, RSSI, RMS Delay Report,
  33. 33. Areas to Improve Machine Learning Data mining, filling gaps from real drive test Use it for better handover protocols
  34. 34. Contact Us | | 561.869.4446 © 2017 – All rights reserved – Patents : 9,071,957, 9,338,629 Thanks for your attention, Q&A @edwinhm | Mobile CDS is a software created by S.O.L Wireless, LLC