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1 NI Technical Symposium
2 Build 5G Systems Today Avichal Kulshrestha 2
3 How We Consume Data is Changing 3
4 Where We Are Today Explosion of wireless data and connected devices Last year s mobile data traffic was nearly 30 times the size of the ENTIRE global Internet in
5 Global Mobile Data Forecast Source: Cisco VNI Mobile,
6 And the Trend is Just Beginning 1.9 BILLION SMART PHONES 85% EMBEDDED DEVICES TODAY ARE UNCONNECTED 50 BILLION DEVICES CONNECTED BY
7 5G What will it do? Figures via Samsung 5G Vision Document
8 ITU-R Vision for IMT-2020 and Beyond Enhanced Mobile Broadband (embb) Massive Machine Type Communication(mMTC) Ultra Reliable MTC (umtc) Gigabytes In Seconds 3D Video, UHD Smart Home The Cloud Augmented Reality Industry Automation Smart City Mission Critical (ex. Health Care) Autonomous Driving 8
9 ITU-R Vision for IMT-2020 and Beyond 8 Capabilities Peak Data Rate High Med User Experience Data Rate Area Traffic Capacity Low Spectrum Efficiency Network Energy Efficiency Mobility Connection Density Latency embb umtc, UR/LL mmtc Source ITU-R M.[IMT.VISION] 9
10 Candidate 5G Technologies In Need of Prototyping New Modulation New MIMO Tech New Spectrum Higher Density PHY Waveforms Massive MIMO mmwave Densification Explore alternatives to OFDM such as NOMA, GFDM, FBMC, UFMC that can increase PHY flexibility. Dramatically increase spectral efficiency in existing cell bands by increasing antennas at the basestation by orders of magnitude. Explore extremely wide bandwidths at higher frequencies once thought impractical for commercial wireless. Increase access point density across a geography for reduces power, improves spectrum reuse for increased data rates. 28 GHz, 38 GHz, 60 GHz, and 72 GHz 10
11 Prototyping Is Critical for Algorithm Research Experience shows that the real world often breaks some of the assumptions made in theoretical research, so testbeds are an important tool for evaluation under very realistic operating conditions development of a testbed that is able to test radical ideas in a complete, working system is crucial 1 NSF Workshop on Future Wireless Communication Research 11
12 Communications System Architecture (PHY-SISO) TRANSMITTER DAT A CODING CHANNEL/ SOURCE MODULATOR FM/QAM/ PSK MULTIPLE ACCESS OFDMA/ WCDMA DIGITAL TO ANALOG CONVERTER I-Q UPCONVETER RF I-Q MODULATOR DIGITAL UPCONVETER MULTIPLE CODING ANALOG ACCESS CONVERTER CHANNEL/ FM/QAM/ SOURCE OFDMA/ PSK WCDMA 12
13 Communications System Architecture (PHY-SISO) TRANSMITTER DAT A CODING CHANNEL/ SOURCE MODULATOR FM/QAM/ PSK MULTIPLE ACCESS OFDMA/ WCDMA DIGITAL TO ANALOG CONVERTER I-Q UPCONVETER RF DATA DE- CODING CHANNEL/ SOURCE DE- MODULATOR FM/QAM/ PSK MULTIPLE ACCESS OFDMA/ WCDMA ANALOG TO DIGITAL CONVERTER I-Q DOWN CONVETER RF RECEIVER 13
14 What is SDR? TRANSMITTER DAT A CODING SOFTWARE MODULATOR ALGORITHM MULTIPLE ACCESS CHANNEL/ SOURCE FM/QAM/ PSK OFDMA/ WCDMA RUNNING ON A PROCESSOR SOFTWARE DIGITAL TO TUNABLE I-Q ANALOG UPCONVETER CONVERTER RF FRONT END RF CPU FPGA DATA DE- CODING CHANNEL/ SOURCE DE- MODULATOR FM/QAM/ PSK MULTIPLE ACCESS OFDMA/ WCDMA ANALOG TO DIGITAL CONVERTER I-Q DOWN CONVETER RF RECEIVER 14
15 What is SDR? SOFTWARE ALGORITHM RUNNING ON A PROCESSOR SOFTWARE TUNABLE RF FRONT END CPU FPGA Write and run algorithms Give commands to RF front End Run FPGA Algorithms Upconvert Baseband to RF 15
16 Steps for Wireless Prototyping Single, Cohesive Toolchain Algorithm Development System Mapping Design Exploration System Implementation Collaborative Design Team 16
17 Candidate 5G Technologies In Need of Prototyping New Modulation New MIMO Tech New Spectrum Higher Density PHY Waveforms Massive MIMO mmwave Densification Explore alternatives to OFDM such as NOMA, GFDM, FBMC, UFMC that can increase PHY flexibility. Dramatically increase spectral efficiency in existing cell bands by increasing antennas at the basestation by orders of magnitude. Explore extremely wide bandwidths at higher frequencies once thought impractical for commercial wireless. Increase access point density across a geography for reduces power, improves spectrum reuse for increased data rates. 28 GHz, 38 GHz, 60 GHz, and 72 GHz 17
18 New Waveform Research at TU Dresden Dr. Gerhard Fettweis 5G lab and testbed in TUD (Germany) 5G PHY exploration and prototyping First GFDM MIMO prototype (CeBIT 2015) 18
19 LTE Receiver Results with OFDM Interference 19
20 NI USRP RIO Software Defined Radio Coming Early Q2 Applications 5G wireless prototyping High channel count MIMO Wide bandwidth, low latency Features 2 Channel TX/RX, RF options 50 MHz 6 GHz Customizable Xilinx Kintex 7 FPGA, K7410T Optimized RF Performance (400 point characterization) Powered by the LabVIEW RIO Architecture 40 MHz Real-time Bandwidth PCIe x4, 800 MB/s streaming GPS Disciplined Clock option Audience Industry Research Mil/Aero/Gov Academic Research Front Back 20
21 Candidate 5G Technologies In Need of Prototyping New Modulation New MIMO Tech New Spectrum Higher Density PHY Waveforms Massive MIMO mmwave Densification Explore alternatives to OFDM such as NOMA, GFDM, FBMC, UFMC that can increase PHY flexibility. Dramatically increase spectral efficiency in existing cell bands by increasing antennas at the basestation by orders of magnitude. Explore extremely wide bandwidths at higher frequencies once thought impractical for commercial wireless. Increase access point density across a geography for reduces power, improves spectrum reuse for increased data rates. 28 GHz, 38 GHz, 60 GHz, and 72 GHz 21
22 Massive MIMO in Cellular Networks Give basestation a large array of antennas (> 10X higher than current systems) Time-division duplexing (TDD) Excess antennas guarantee good channel with high probability Large number of users can be served simultaneously T. L. Marzetta, Noncooperative cellular wireless with unlimited numbers of base station antennas, IEEE Trans. Wireless Comm., vol. 9, no. 11,
23 Massive MIMO at Lund University, Sweden Goal: Build a 100x10 massive MIMO system to validate theoretical results with real time processing Prof Ove Edfos Prof Fredrik Tufvesson 23
24 Candidate 5G Technologies In Need of Prototyping New Modulation New MIMO Tech New Spectrum Higher Density PHY Waveforms Massive MIMO mmwave Densification Explore alternatives to OFDM such as NOMA, GFDM, FBMC, UFMC that can increase PHY flexibility. Dramatically increase spectral efficiency in existing cell bands by increasing antennas at the basestation by orders of magnitude. Explore extremely wide bandwidths at higher frequencies once thought impractical for commercial wireless. Increase access point density across a geography for reduces power, improves spectrum reuse for increased data rates. 28 GHz, 38 GHz, 60 GHz, and 72 GHz 24
25 mmwave 5G Technology Vision Existing cellular bands are crowded and expensive The next frontier is mmwave frequencies to provide High throughput (> 10 Gb/s) Lower latency (< 1ms) Enables ultra-definition media and tactile applications image from electronicdesign.com 25
26 Receiver Transmitter mmwave Channel Sounding Key Facts NYU mmwave channel measurement campaign uses sliding correlator PN code can be generated on the FPGA and streamed via AT 1120 NI Quicksyn (20GHz) & Quicksyn lite (10GHz) provides LO to IF mixer and mmwave RF Freq doubler module for mmwave RFIC RX Side: NIBaseband NI
27 Cellular Access Point System LabVIEW mmwave User Device (Handset) System LabVIEW Host PC PXI FlexRIO Baseband RF and Antenna 27 RF and Antenna PXI FlexRIO Baseband Host PC
28 Candidate 5G Technologies In Need of Prototyping New Modulation New MIMO Tech New Spectrum Higher Density PHY Waveforms Massive MIMO mmwave Densification Explore alternatives to OFDM such as NOMA, GFDM, FBMC, UFMC that can increase PHY flexibility. Dramatically increase spectral efficiency in existing cell bands by increasing antennas at the basestation by orders of magnitude. Explore extremely wide bandwidths at higher frequencies once thought impractical for commercial wireless. Increase access point density across a geography for reduces power, improves spectrum reuse for increased data rates. 28 GHz, 38 GHz, 60 GHz, and 72 GHz 28
29 5G Networks Design Directions Hyper dense networks Software defined networking (SDN) Cloud radio access network (cran) Cellular/ coexistence and co-ordination Next generation stack 29
30 Architecture for Protocol Stack Explorations LTE MTC IoT Open Source Upper Layer Stack (e.g. ns-3) Ref Design LTE Ref Design PHY/MAC Stack in LabVIEW NI Hardware 30
31 Thank You
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