Many-antenna base stations are interesting systems. Lin Zhong
|
|
- Samuel Evans
- 5 years ago
- Views:
Transcription
1 Many-antenna base stations are interesting systems Lin Zhong
2 2
3 How we got started Why many-antenna base station What we have learned What we are doing now 3
4 How we started Why a mobile system guy got interested in massive MIMO 4
5 Wireless consumes a lot of power Power (mw) HTC Wizard October Power profile!=energy profile 5
6 First insight Wi-Fi more efficient than cellular MobiSys 07 6
7 Why is Wi-Fi more efficient? P TX = a*d 2 D 7
8 Horribly wasteful 8
9 Directional transmission! 9
10 Passive directional antenna to save energy (MobiCom 10) No power overhead Fixed bean patterns 10
11 Beamforming to save energy (MobiCom 11) Extra transceivers Steerable beams 11
12 Power by multi-antenna systems (uplink) P Circuit P PA =P TX / η Baseband Signal DAC Filter Mixer Filter PA 1 Frequency Synthesizer N P Shared Baseband Signal DAC Filter Mixer Filter PA N P = P shared + N P Circuit + P TX / η 12
13 Circuit vs. radiation power tradeoff P=P shared + 1 P Circuit + P TX / η Fixed receiver SNR
14 Circuit vs. radiation power tradeoff P=P shared + 2 P Circuit + P TX / η Fixed receiver SNR
15 Circuit vs. radiation power tradeoff P=P shared + 3 P Circuit + P TX / η Fixed receiver SNR
16 Circuit vs. radiation power tradeoff P=P shared + 4 P Circuit + P TX / η Fixed receiver SNR
17 Circuit vs. radiation power tradeoff Optimal number of antennas for efficiency N = a P /P b P
18 Hardware is cheap & getting cheaper P = P shared + N P Circuit + P TX / η Transmitter Power Consumption (mw) SISO 2x2 MIMO Year Sources: IEEE Int. Solid-State Circuits Conferences (ISSCC) and IEEE Journal of Solid-State Circuits (JSSC)
19 Hardware is cheap & getting cheaper P = P shared + N P Circuit + P TX / η Sources: IEEE Int. Solid-State Circuits Conferences (ISSCC) and IEEE Journal of Solid-State Circuits (JSSC)
20 Circuit vs. radiation power tradeoff is increasingly profitable N = a P /P b P The most energy-efficient way is to use all the antennas 20
21 Beyond a single link 21
22 What the carrier wants: Use all your antennas! 22
23 Guiding principles distilled Spectrum is scarce Hardware is cheap, and getting cheaper 23
24 You can t really fit a lot of antennas in a mobile device L 24
25 Got a call from Erran Li, Bell Labs Spring
26 3590 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 11, NOVEMBER 2010 Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas Thomas L. Marzetta 26
27 Clay Shepard went to Bell Labs Summer
28 Why many-antenna base station? 28
29 Omni-directional base station Data 1 Poor spatial reuse; poor power efficiency; high inter-cell interference 29
30 Sectored base station Data 1 Better spatial reuse; better power efficiency; high inter-cell interference 30
31 Single-user beamforming base station Data 1 Data 3 Better spatial reuse; best power efficiency; reduced inter-cell interference 31
32 Multi-user MIMO base station Data 2 Data 1 Data 5 M: # of BS antennas K: # of clients (K M) Best spatial reuse; best power efficiency; reduced inter-cell interference 32
33 Why massive? More antennas è Higher spectral efficiency More antennas è Higher energy efficiency Marzetta s key result Simple baseband technique becomes effective T.L. Marzetta. Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans. on Wireless Comm.,
34 How multi-user MIMO works H M: # of BS antennas K: # of clients M K 34
35 Multi-user MIMO: Precoding s s! = f (s, H) (Kx1 matrix) (M x 1 matrix) H M: # of BS antennas K: # of clients M K 35
36 Linear Precoding s (Kx1 matrix) s! = W s (M x 1 matrix) H M: # of BS antennas K: # of clients M K 36
37 Linear Precoding I: Zero-forcing Beamforming Null Data 1 Null Null 37
38 Zero-forcing Beamforming Data 2 Null Null 38
39 Zero-forcing Beamforming W = c H * (H T H * ) 1 Data 2 Data 1 Data 5 39
40 Zero-forcing does not scale well W = c H * (H T H * ) 1 Inversion of M X M matrix O(M*K 2 ) 40
41 Linear precoding II: Conjugate Beamforming Data 1 41
42 With more antennas Data 1 42
43 With even more antennas Data 1 43
44 Conjugate Multi-user Beamforming W = c H * Data 2 Data 1 Data 5 Conjugate approaches Zeroforcing as M/Kè
45 Conjugate scales very well W = c H * O(K) per antenna Marzetta s key result: Conjugate approaches Zeroforcing as M/Kè 45
46 Many-antenna vs. small cell Capital Expenditure (CAPEX) of Cell Site Major wireless equipment only 35% Just get the site to work: >50% China Mobile White Paper: C-RAN: The Road Towards Green RAN (Oct, 2011) 46
47 Total Cost of Ownership (TCO) Operating & Maintenance (O&M) Operating Expenditure (OPEX) The most effective way to reduce TCO is to decrease the number of sites. China Mobile White Paper: C-RAN: The Road Towards Green RAN (Oct, 2011) 47
48 If you ve got a site, better use as many antennas as you can 48
49 After a summer at Bell Labs 10-antenna prototype in the anechoic chamber at Bell Labs 49
50 ArgosV1 (MobiCom 12) 50
51 Central Controller WARP Modules Argos Interconnects Sync Distribution Argos Hub Clock Distribution Ethernet Switch51
52 What we have learned 52
53 Good news: Linear gains as # of users increases Capacity vs. K, with M = 64 53
54 Linear gains as # of BS antennas increases even as total P TX scaled with 1/M Capacity vs. M, with K = 15 54
55 Disappointment: Conjugate not approaching Zero-forcing up to 64 antennas Capacity vs. M, with K = 15 55
56 Disappointment: Conjugate not approaching Zero-forcing up to 64 antennas Capacity vs. M, with K = 4 Total Capacity (bps/hz) Zero forcing Conjugate Local Conj. SUBF Single Ant Base Station Antennas 56
57 The dirty secret of massive MIMO s s! = f (s, H) (Kx1 matrix) (M x 1 matrix) H M: # of BS antennas K: # of clients M K 57
58 The dirty secret of massive MIMO s s! = f (s, H) (Kx1 matrix) (M x 1 matrix) H M: # of BS antennas K: # of clients M K 58
59 Sounding-feedback does not scale s s! = f (s, H) (Kx1 matrix) (M x 1 matrix) M: # of BS antennas K: # of clients M K 59
60 One must use time-division duplex and client-sent pilot s s! = f (s, H) (Kx1 matrix) (M x 1 matrix) M: # of BS antennas K: # of clients M K 60
61 What happens in a single coherence period Listen to pilot Send data Calculate BF weights Receive data Time Send pilot Receive data Send data Time Within coherence time 61
62 Both theory and our experiments only consider Listen to pilot Send data Calculate BF weights Receive data Time Send pilot Receive data Send data Time 62
63 What if we factor all in? Listen to pilot Send data Calculate BF weights Receive data Time Send pilot Receive data Send data Time The base station can receive during calculation but the opportunity is limited due to downlink/uplink asymmetry 63
64 What if we factor all in? Listen to pilot Send data Calculate BF weights Receive data Time Client mobility Channel coherence time Number of clients Time to listen to pilot Computation hardware on base station Time to calculate BF weights 64
65 M = 64 K = 15 Type S L Inv. Type Sym. Super Infiniband 40 Gbps 1 µs FPGA Cluster 4x10GbE 40 Gbps 20 µs 8xIntel i7 High 2x10GbE 20 Gbps 20 µs 4xIntel i7 Mid 10GbE 10 Gbps 20 µs 2xIntel i7 F Low GbE 1Gbps 20 µs Intel i7 N Zeroforcing with various hardware configurations 65
66 Achieved Capacity (bps/hz) O(K) O(MK 2 ) Zero Forcing Conjugate Number of Users Fixed coherence time of 30 ms with low-end hardware. 66
67 What we have learned Computational resources matter significantly Simplistic Conjugate beamforming works Not in Marzetta s theoretical sense Need adaptive solutions # of clients; client mobility Precoding methods: Conjugate vs. Zero-forcing 67
68 What we are working on 68
69 Going for more antennas ArgosV2 (2013) 12 WARP V3 (48 antennas) per rack Polycarbonate, dado-style shelf Anti-static spray and thermal vent Battery-powered ArgosMobile 69
70 96-antenna configuration
71
72
73 Ongoing Work: ArgosLab Software Framework for Rapid Prototyping Out-of-the-box Functionality Time/Frequency Synchronization Calibration CSI Collection Scheduled frame-based real-time Transmission
74 From Argos to ArgosNet 10 GbE ArgosBS 1 (Outdoor) Inter-cell interference management Pilot contamination Client grouping & scheduling Cloud RAN 10 Server GbE NetFPGA 10 GbE ArgosBS 4 (Indoor) NetFPGA Server 10 GbE NetFPGA Server 10 GbE ArgosCloud 10 GbE 10 GbE ArgosBS 2 (Outdoor) ArgosBS 3 (Outdoor) A network of massive MU-MIMO base stations 74
75 In summary 75
76 More BS antennas + MU-MIMOè Higher efficiency & lower interference Data 2 Data 1 Data 5
77 More BS antennas + MU-MIMOè Higher efficiency & lower interference Data 3 Data 1 Data 6 Data 12 Data 9 Data 10
78 Guiding Principles Spectrum is scarce Hardware is cheap, and getting cheaper 78
79 Acknowledgments 79
Beamforming on mobile devices: A first study
Beamforming on mobile devices: A first study Hang Yu, Lin Zhong, Ashutosh Sabharwal, David Kao http://www.recg.org Two invariants for wireless Spectrum is scarce Hardware is cheap and getting cheaper 2
More informationMassive MIMO Full-duplex: Theory and Experiments
Massive MIMO Full-duplex: Theory and Experiments Ashu Sabharwal Joint work with Evan Everett, Clay Shepard and Prof. Lin Zhong Data Rate Through Generations Gains from Spectrum, Densification & Spectral
More informationArgos: Practical Base Stations for Large-scale Beamforming. Clayton W. Shepard
Argos: Practical Base Stations for Large-scale Beamforming Clayton W. Shepard Collaborators Hang Yu Narendra Anand Erran Li Thomas Marzetta Richard Yang Lin Zhong 2 = Background Beamforming Power Gain
More informationPractical Performance of MU-MIMO Precoding in Many-Antenna Base Stations
Practical Performance of MU-MIMO Precoding in Many-Antenna Base Stations Clayton Shepard, Narendra Anand, and Lin Zhong Rice University, Houston, TX {cws, nanand, lzhong}@rice.edu Equal Contribution ABSTRACT
More information5G: Opportunities and Challenges Kate C.-J. Lin Academia Sinica
5G: Opportunities and Challenges Kate C.-J. Lin Academia Sinica! 2015.05.29 Key Trend (2013-2025) Exponential traffic growth! Wireless traffic dominated by video multimedia! Expectation of ubiquitous broadband
More informationMassive MIMO a overview. Chandrasekaran CEWiT
Massive MIMO a overview Chandrasekaran CEWiT Outline Introduction Ways to Achieve higher spectral efficiency Massive MIMO basics Challenges and expectations from Massive MIMO Network MIMO features Summary
More informationWhat is the Role of MIMO in Future Cellular Networks: Massive? Coordinated? mmwave?
What is the Role of MIMO in Future Cellular Networks: Massive? Coordinated? mmwave? Robert W. Heath Jr. The University of Texas at Austin Wireless Networking and Communications Group www.profheath.org
More informationNR Physical Layer Design: NR MIMO
NR Physical Layer Design: NR MIMO Younsun Kim 3GPP TSG RAN WG1 Vice-Chairman (Samsung) 3GPP 2018 1 Considerations for NR-MIMO Specification Design NR-MIMO Specification Features 3GPP 2018 2 Key Features
More information5G India Demystifying 5G, Massive MIMO and Challenges
Demystifying 5G, Massive MIMO and Challenges 5G India 2017 Ramarao Anil Head Product Support, Development & Applications Rohde & Schwarz India Pvt. Ltd. COMPANY RESTRICTED Agenda ı 5G Vision ı Why Virtualization
More informationS. Mohammad Razavizadeh. Mobile Broadband Network Research Group (MBNRG) Iran University of Science and Technology (IUST)
S. Mohammad Razavizadeh Mobile Broadband Network Research Group (MBNRG) Iran University of Science and Technology (IUST) 2 Evolution of Wireless Networks AMPS GSM GPRS EDGE UMTS HSDPA HSUPA HSPA+ LTE LTE-A
More informationArgosNet: A Multi-Cell Many-Antenna MU-MIMO Platform
ArgosNet: A Multi-Cell Many-Antenna MU-MIMO Platform Clayton Shepard, Rahman Doost-Mohammady, Jian Ding, Ryan E. Guerra, and Lin Zhong Department of Electrical and Computer Engineering, Rice University,
More informationProf. Xinyu Zhang. Dept. of Electrical and Computer Engineering University of Wisconsin-Madison
Prof. Xinyu Zhang Dept. of Electrical and Computer Engineering University of Wisconsin-Madison 1" Overview of MIMO communications Single-user MIMO Multi-user MIMO Network MIMO 3" MIMO (Multiple-Input Multiple-Output)
More informationDesign of mmwave massive MIMO cellular systems
Design of mmwave massive MIMO cellular systems Abbas Kazerouni and Mainak Chowdhury Faculty mentor: Andrea Goldsmith Wireless Systems Lab, Stanford University March 23, 2015 Future cellular networks Higher
More informationBeamforming for 4.9G/5G Networks
Beamforming for 4.9G/5G Networks Exploiting Massive MIMO and Active Antenna Technologies White Paper Contents 1. Executive summary 3 2. Introduction 3 3. Beamforming benefits below 6 GHz 5 4. Field performance
More informationWhat s Behind 5G Wireless Communications?
What s Behind 5G Wireless Communications? Marc Barberis 2015 The MathWorks, Inc. 1 Agenda 5G goals and requirements Modeling and simulating key 5G technologies Release 15: Enhanced Mobile Broadband IoT
More information5G: implementation challenges and solutions
5G: implementation challenges and solutions University of Bristol / Cambridge Wireless 18 th September 2018 Matthew Baker Nokia Bell-Labs Head of Radio Physical Layer & Coexistence Standardisation Higher
More informationControl Channel Design for Many-Antenna MU-MIMO
Control Channel Design for Many-Antenna MU-MIMO Clayton Shepard, Abeer Javed, and Lin Zhong Department of Electrical and Computer Engineering Rice University, Houston, TX {cws, abeer.javed, lzhong}@rice.edu
More informationWireless InSite. Simulation of MIMO Antennas for 5G Telecommunications. Copyright Remcom Inc. All rights reserved.
Wireless InSite Simulation of MIMO Antennas for 5G Telecommunications Overview To keep up with rising demand and new technologies, the wireless industry is researching a wide array of solutions for 5G,
More informationNext Generation Mobile Communication. Michael Liao
Next Generation Mobile Communication Channel State Information (CSI) Acquisition for mmwave MIMO Systems Michael Liao Advisor : Andy Wu Graduate Institute of Electronics Engineering National Taiwan University
More informationPower Consumption by Wireless Communication. Lin Zhong ELEC518, Spring 2011
Power Consumption by Wireless Communication Lin Zhong ELEC518, Spring 2011 Power consumption (SMT5600) Cellular network, 17, 1% Flight mode: Sleep, 3, 0% Lighting: Keyboard, 73, 3% Lighting: Display I,
More informationSystem Performance of Cooperative Massive MIMO Downlink 5G Cellular Systems
IEEE WAMICON 2016 April 11-13, 2016 Clearwater Beach, FL System Performance of Massive MIMO Downlink 5G Cellular Systems Chao He and Richard D. Gitlin Department of Electrical Engineering University of
More informationHybrid Transceivers for Massive MIMO - Some Recent Results
IEEE Globecom, Dec. 2015 for Massive MIMO - Some Recent Results Andreas F. Molisch Wireless Devices and Systems (WiDeS) Group Communication Sciences Institute University of Southern California (USC) 1
More informationMassive MIMO and mmwave
Massive MIMO and mmwave Why 5G is Not 4G++ Technology Insights and Challenges Bob Cutler, Principal Solutions Architect Roger Nichols, 5G Program Manager Keysight Technologies Page What is 5G? Today, 5G
More informationMassive MIMO for the New Radio Overview and Performance
Massive MIMO for the New Radio Overview and Performance Dr. Amitabha Ghosh Nokia Bell Labs IEEE 5G Summit June 5 th, 2017 What is Massive MIMO ANTENNA ARRAYS large number (>>8) of controllable antennas
More information2015 The MathWorks, Inc. 1
2015 The MathWorks, Inc. 1 What s Behind 5G Wireless Communications? 서기환과장 2015 The MathWorks, Inc. 2 Agenda 5G goals and requirements Modeling and simulating key 5G technologies Release 15: Enhanced Mobile
More information802.11ax Design Challenges. Mani Krishnan Venkatachari
802.11ax Design Challenges Mani Krishnan Venkatachari Wi-Fi: An integral part of the wireless landscape At the center of connected home Opening new frontiers for wireless connectivity Wireless Display
More informationMIMO Systems and Applications
MIMO Systems and Applications Mário Marques da Silva marques.silva@ieee.org 1 Outline Introduction System Characterization for MIMO types Space-Time Block Coding (open loop) Selective Transmit Diversity
More informationPrototyping Next-Generation Communication Systems with Software-Defined Radio
Prototyping Next-Generation Communication Systems with Software-Defined Radio Dr. Brian Wee RF & Communications Systems Engineer 1 Agenda 5G System Challenges Why Do We Need SDR? Software Defined Radio
More informationmm Wave Communications J Klutto Milleth CEWiT
mm Wave Communications J Klutto Milleth CEWiT Technology Options for Future Identification of new spectrum LTE extendable up to 60 GHz mm Wave Communications Handling large bandwidths Full duplexing on
More informationMIMO and Beamforming in the 5G Context SBrT 2017
MIMO and Beamforming in the 5G Context SBrT 2017 05/09/2017 Created by Will Sitch Presented by Bruno Duarte A Brief History of Keysight 1939 1998: Hewlett-Packard years A company founded on electronic
More informationLecture LTE (4G) -Technologies used in 4G and 5G. Spread Spectrum Communications
COMM 907: Spread Spectrum Communications Lecture 10 - LTE (4G) -Technologies used in 4G and 5G The Need for LTE Long Term Evolution (LTE) With the growth of mobile data and mobile users, it becomes essential
More informationInterference Mitigation by MIMO Cooperation and Coordination - Theory and Implementation Challenges
Interference Mitigation by MIMO Cooperation and Coordination - Theory and Implementation Challenges Vincent Lau Dept of ECE, Hong Kong University of Science and Technology Background 2 Traditional Interference
More informationOn the Complementary Benefits of Massive MIMO, Small Cells, and TDD
On the Complementary Benefits of Massive MIMO, Small Cells, and TDD Jakob Hoydis (joint work with K. Hosseini, S. ten Brink, M. Debbah) Bell Laboratories, Alcatel-Lucent, Germany Alcatel-Lucent Chair on
More informationHang Yu A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIRMENTS FOR THE DEGREE. Master of Science
RICE UNIVERSITY Beamforming on Mobile Devices: A First Study by Hang Yu A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIRMENTS FOR THE DEGREE Master of Science APPROVED, THESIS COMMITTEE: Lin Zhong,
More informationAnalysis of massive MIMO networks using stochastic geometry
Analysis of massive MIMO networks using stochastic geometry Tianyang Bai and Robert W. Heath Jr. Wireless Networking and Communications Group Department of Electrical and Computer Engineering The University
More informationAnalysis and Improvements of Linear Multi-user user MIMO Precoding Techniques
1 Analysis and Improvements of Linear Multi-user user MIMO Precoding Techniques Bin Song and Martin Haardt Outline 2 Multi-user user MIMO System (main topic in phase I and phase II) critical problem Downlink
More informationTen Things You Should Know About MIMO
Ten Things You Should Know About MIMO 4G World 2009 presented by: David L. Barner www/agilent.com/find/4gworld Copyright 2009 Agilent Technologies, Inc. The Full Agenda Intro System Operation 1: Cellular
More informationMassive MIMO: Ten Myths and One Critical Question. Dr. Emil Björnson. Department of Electrical Engineering Linköping University, Sweden
Massive MIMO: Ten Myths and One Critical Question Dr. Emil Björnson Department of Electrical Engineering Linköping University, Sweden Biography 2007: Master of Science in Engineering Mathematics, Lund,
More informationHype, Myths, Fundamental Limits and New Directions in Wireless Systems
Hype, Myths, Fundamental Limits and New Directions in Wireless Systems Reinaldo A. Valenzuela, Director, Wireless Communications Research Dept., Bell Laboratories Rutgers, December, 2007 Need to greatly
More informationAnalysis of Novel Eigen Beam Forming Scheme with Power Allocation in LSAS
Analysis of Novel Eigen Beam Forming Scheme with Power Allocation in LSAS Saransh Malik, Sangmi Moon, Hun Choi, Cheolhong Kim. Daeijin Kim, and Intae Hwang, Non-Member, IEEE Abstract Massive MIMO (also
More informationMATLAB COMMUNICATION TITLES
MATLAB COMMUNICATION TITLES -2018 ORTHOGONAL FREQUENCY-DIVISION MULTIPLEXING(OFDM) 1 ITCM01 New PTS Schemes For PAPR Reduction Of OFDM Signals Without Side Information 2 ITCM02 Design Space-Time Trellis
More informationReconfigurable antennas for WiFi networks. Daniele Piazza Founder and CTO Adant Technologies Inc
Reconfigurable antennas for WiFi networks Daniele Piazza Founder and CTO Adant Technologies Inc Company Overview Adant Padova, Italy Adant SF Bay Area Adant Taiwan Adant designs, licenses, and manufactures
More informationBeyond 4G: Millimeter Wave Picocellular Wireless Networks
Beyond 4G: Millimeter Wave Picocellular Wireless Networks Sundeep Rangan, NYU-Poly Joint work with Ted Rappaport, Elza Erkip, Mustafa Riza Akdeniz, Yuanpeng Liu Sept 21, 2013 NJ ACS, Hoboken, J 1 Outline
More informationDesigning Energy Efficient 5G Networks: When Massive Meets Small
Designing Energy Efficient 5G Networks: When Massive Meets Small Associate Professor Emil Björnson Department of Electrical Engineering (ISY) Linköping University Sweden Dr. Emil Björnson Associate professor
More informationExperimental evaluation of massive MIMO at 20 GHz band in indoor environment
This article has been accepted and published on J-STAGE in advance of copyediting. Content is final as presented. IEICE Communications Express, Vol., 1 6 Experimental evaluation of massive MIMO at GHz
More informationBringing the Magic of Asymptotic Analysis to Wireless Networks
Massive MIMO Bringing the Magic of Asymptotic Analysis to Wireless Networks Dr. Emil Björnson Department of Electrical Engineering (ISY) Linköping University, Linköping, Sweden International Workshop on
More information5G - The multi antenna advantage. Bo Göransson, PhD Expert, Multi antenna systems Systems & Technology
5G - The multi antenna advantage Bo Göransson, PhD Expert, Multi antenna systems Systems & Technology Content What is 5G? Background (theory) Standardization roadmap 5G trials & testbeds 5G product releases
More informationUnderstanding Real Many-Antenna. MU-MIMO channels.
Understanding Real Many-Antenna MU-MIMO Channels Clayton Shepard, Jian Ding, Ryan E. Guerra, and Lin Zhong Department of Electrical and Computer Engineering Rice University, Houston, TX Skylark Wireless
More information5G Massive MIMO and mmw Design and Test Solution
5G Massive MIMO and mmw Design and Test Solution Jan. 2017 Philip Chang Senior Project Manager 1 Agenda Communications Page 2 Overview of 5G Technologies 5G Key Radio Technologies mmwave Massive MIMO Keysight
More informationMillimeter Wave Communication in 5G Wireless Networks. By: Niloofar Bahadori Advisors: Dr. J.C. Kelly, Dr. B Kelley
Millimeter Wave Communication in 5G Wireless Networks By: Niloofar Bahadori Advisors: Dr. J.C. Kelly, Dr. B Kelley Outline 5G communication Networks Why we need to move to higher frequencies? What are
More informationInterference management Within 3GPP LTE advanced
Interference management Within 3GPP LTE advanced Konstantinos Dimou, PhD Senior Research Engineer, Wireless Access Networks, Ericsson research konstantinos.dimou@ericsson.com 2013-02-20 Outline Introduction
More informationON PILOT CONTAMINATION IN MASSIVE MULTIPLE-INPUT MULTIPLE- OUTPUT SYSTEM WITH LEAST SQUARE METHOD AND ZERO FORCING RECEIVER
ISSN: 2229-6948(ONLINE) ICTACT JOURNAL ON COMMUNICATION TECHNOLOGY, SEPTEM 2017, VOLUME: 08, ISSUE: 03 DOI: 10.21917/ijct.2017.0228 ON PILOT CONTAMINATION IN MASSIVE MULTIPLE-INPUT MULTIPLE- OUTPUT SYSTEM
More informationMIMO: State of the Art, and the Future in Focus Mboli Sechang Julius
MIMO: State of the Art, and the Future in Focus Mboli Sechang Julius Abstract-Antennas of transmitters and receivers have been manipulated to increase the capacity of transmission and reception of signals.
More informationA Method for Analyzing Broadcast Beamforming of Massive MIMO Antenna Array
Progress In Electromagnetics Research Letters, Vol. 65, 15 21, 2017 A Method for Analyzing Broadcast Beamforming of Massive MIMO Antenna Array Hong-Wei Yuan 1, 2, *, Guan-Feng Cui 3, and Jing Fan 4 Abstract
More informationTuning the Receiver Structure and the Pilot-to-Data Power Ratio in Multiple Input Multiple Output Systems
Tuning the Receiver Structure and the Pilot-to-Data Power Ratio in Multiple Input Multiple Output Systems Gabor Fodor Ericsson Research Royal Institute of Technology 5G: Scenarios & Requirements Traffic
More informationMillimeter-Wave Communication and Mobile Relaying in 5G Cellular Networks
Lectio praecursoria Millimeter-Wave Communication and Mobile Relaying in 5G Cellular Networks Author: Junquan Deng Supervisor: Prof. Olav Tirkkonen Department of Communications and Networking Opponent:
More informationWhat s Behind 5G Wireless Communications?
What s Behind 5G Wireless Communications? Tabrez Khan Application Engineering Group 2015 The MathWorks, Inc. 1 Agenda 5G goals and requirements Modeling and simulating key 5G technologies 5G development
More informationmm-wave Transceiver Challenges for the 5G and 60GHz Standards Prof. Emanuel Cohen Technion
mm-wave Transceiver Challenges for the 5G and 60GHz Standards Prof. Emanuel Cohen Technion November 11, 11, 2015 2015 1 mm-wave advantage Why is mm-wave interesting now? Available Spectrum 7 GHz of virtually
More informationMassive MIMO: Signal Structure, Efficient Processing, and Open Problems I
Massive MIMO: Signal Structure, Efficient Processing, and Open Problems I Saeid Haghighatshoar Communications and Information Theory Group (CommIT) Technische Universität Berlin CoSIP Winter Retreat Berlin,
More informationLTE Direct Overview. Sajith Balraj Qualcomm Research
MAY CONTAIN U.S. AND INTERNATIONAL EXPORT CONTROLLED INFORMATION This technical data may be subject to U.S. and international export, re-export, or transfer ( export ) laws. Diversion contrary to U.S.
More informationMIMO in 4G Wireless. Presenter: Iqbal Singh Josan, P.E., PMP Director & Consulting Engineer USPurtek LLC
MIMO in 4G Wireless Presenter: Iqbal Singh Josan, P.E., PMP Director & Consulting Engineer USPurtek LLC About the presenter: Iqbal is the founder of training and consulting firm USPurtek LLC, which specializes
More informationMultiple Antenna Processing for WiMAX
Multiple Antenna Processing for WiMAX Overview Wireless operators face a myriad of obstacles, but fundamental to the performance of any system are the propagation characteristics that restrict delivery
More informationLTE Base Station Equipments Usable with W-CDMA System
LTE Base Station Equipments Usable with W-CDMA System LTE Base Station Equipment W-CDMA/LTE Shared System Special Articles on Xi (Crossy) LTE Service Toward Smart Innovation 1. Introduction LTE Base Station
More informationWideband Channel Tracking for mmwave MIMO System with Hybrid Beamforming Architecture
Wideband Channel Tracking for mmwave MIMO System with Hybrid Beamforming Architecture Han Yan, Shailesh Chaudhari, and Prof. Danijela Cabric Dec. 13 th 2017 Intro: Tracking in mmw MIMO MMW network features
More informationLTE-Advanced research in 3GPP
LTE-Advanced research in 3GPP GIGA seminar 8 4.12.28 Tommi Koivisto tommi.koivisto@nokia.com Outline Background and LTE-Advanced schedule LTE-Advanced requirements set by 3GPP Technologies under investigation
More informationFractional Delay Filter Based Wideband Self- Interference Cancellation
, pp.22-27 http://dx.doi.org/10.14257/astl.2013 Fractional Delay Filter Based Wideband Self- Interference Cancellation Hao Liu The National Communication Lab. The University of Electronic Science and Technology
More informationCompressed-Sensing Based Multi-User Millimeter Wave Systems: How Many Measurements Are Needed?
Compressed-Sensing Based Multi-User Millimeter Wave Systems: How Many Measurements Are Needed? Ahmed Alkhateeb*, Geert Leus #, and Robert W. Heath Jr.* * Wireless Networking and Communications Group, Department
More informationHOW DO MIMO RADIOS WORK? Adaptability of Modern and LTE Technology. By Fanny Mlinarsky 1/12/2014
By Fanny Mlinarsky 1/12/2014 Rev. A 1/2014 Wireless technology has come a long way since mobile phones first emerged in the 1970s. Early radios were all analog. Modern radios include digital signal processing
More informationMassive MIMO Systems: Signal Processing Challenges and Research Trends
Massive MIMO Systems: Signal Processing Challenges and Research Trends Rodrigo C. de Lamare CETUC, PUC-Rio, Brazil Communications Research Group, Department of Electronics, University of York, U.K. delamare@cetuc.puc-rio.br
More informationMU-MIMO in LTE/LTE-A Performance Analysis. Rizwan GHAFFAR, Biljana BADIC
MU-MIMO in LTE/LTE-A Performance Analysis Rizwan GHAFFAR, Biljana BADIC Outline 1 Introduction to Multi-user MIMO Multi-user MIMO in LTE and LTE-A 3 Transceiver Structures for Multi-user MIMO Rizwan GHAFFAR
More informationFrom massive MIMO to C-RAN: the OpenAirInterface 5G testbed
From massive MIMO to C-RAN: the OpenAirInterface 5G testbed Florian Kaltenberger, Xiwen Jiang, Raymond Knopp EURECOM, Campus SophiaTech, 06410 Biot, France firstnamelastname@eurecomfr Abstract 5G will
More informationInvestigation on Multiple Antenna Transmission Techniques in Evolved UTRA. OFDM-Based Radio Access in Downlink. Features of Evolved UTRA and UTRAN
Evolved UTRA and UTRAN Investigation on Multiple Antenna Transmission Techniques in Evolved UTRA Evolved UTRA (E-UTRA) and UTRAN represent long-term evolution (LTE) of technology to maintain continuous
More informationAdaptive Beamforming towards 5G systems. Whitepaper 1
Adaptive Beamforming towards 5G systems Whitepaper 1 Abstract MIMO has been the undisputed candidate for wireless communications. It provides high diversity order and increased data-rate. Beamforming is
More informationChallenges of 5G mmwave RF Module. Ren-Jr Chen M300/ICL/ITRI 2018/06/20
Challenges of 5G mmwave RF Module Ren-Jr Chen rjchen@itri.org.tw M300/ICL/ITRI 2018/06/20 Agenda 5G Vision and Scenarios mmwave RF module considerations mmwave RF module solution for OAI Conclusion 2 5G
More informationA key parameters based vision
A key parameters based vision of trends in Wireless systems Alain Sibille Telecom ParisTech Outline What do we speak about? Tradeoff between key parameters Technology progress From low-end to high-end
More informationAEROHIVE NETWORKS ax DAVID SIMON, SENIOR SYSTEMS ENGINEER Aerohive Networks. All Rights Reserved.
AEROHIVE NETWORKS 802.11ax DAVID SIMON, SENIOR SYSTEMS ENGINEER 1 2018 Aerohive Networks. All Rights Reserved. 2 2018 Aerohive Networks. All Rights Reserved. 8802.11ax 802.11n and 802.11ac 802.11n and
More informationFrequency Reuse How Do I Maximize the Value of My Spectrum?
Frequency Reuse How Do I Maximize the Value of My Spectrum? Eric Wilson VP Systems Management, Vyyo Broadband Wireless Forum, February 20, 2001 Spectrum Reuse Outline Definition / concept Alternatives
More information5G New Radio Design. Fall VTC-2017, Panel September 25 th, Expanding the human possibilities of technology to make our lives better
5G New Radio Design Expanding the human possibilities of technology to make our lives better Fall VTC-2017, Panel September 25 th, 2017 Dr. Amitabha Ghosh Head of Small Cell Research, Nokia Fellow, IEEE
More informationUplink Receiver with V-BLAST and Practical Considerations for Massive MIMO System
Uplink Receiver with V-BLAST and Practical Considerations for Massive MIMO System Li Tian 1 1 Department of Electrical and Computer Engineering, University of Auckland, Auckland, New Zealand Abstract Abstract
More informationMIDU: Enabling MIMO Full Duplex
MIDU: Enabling MIMO Full Duplex Ehsan Aryafar Princeton NEC Labs Karthik Sundaresan NEC Labs Sampath Rangarajan NEC Labs Mung Chiang Princeton ACM MobiCom 2012 Background AP Current wireless radios are
More informationPerformance Analysis of CoMP Using Scheduling and Precoding Techniques in the Heterogeneous Network
International Journal of Information and Electronics Engineering, Vol. 6, No. 3, May 6 Performance Analysis of CoMP Using Scheduling and Precoding Techniques in the Heterogeneous Network Myeonghun Chu,
More informationTransforming MIMO Test
Transforming MIMO Test MIMO channel modeling and emulation test challenges Presented by: Kevin Bertlin PXB Product Engineer Page 1 Outline Wireless Technologies Review Multipath Fading and Antenna Diversity
More informationNI Technical Symposium ni.com
NI Technical Symposium 2016 1 Build 5G Systems Today Avichal Kulshrestha 2 How We Consume Data is Changing 3 Where We Are Today Explosion of wireless data and connected devices Last year s mobile data
More informationEnergy Efficient Multiple Access Scheme for Multi-User System with Improved Gain
Volume 2, Issue 11, November-2015, pp. 739-743 ISSN (O): 2349-7084 International Journal of Computer Engineering In Research Trends Available online at: www.ijcert.org Energy Efficient Multiple Access
More informationHandset MIMO antenna measurement using a Spatial Fading Emulator
Handset MIMO antenna measurement using a Spatial Fading Emulator Atsushi Yamamoto Panasonic Corporation, Japan Panasonic Mobile Communications Corporation, Japan NTT DOCOMO, INC., Japan Aalborg University,
More informationNon-Orthogonal Multiple Access (NOMA) in 5G Cellular Downlink and Uplink: Achievements and Challenges
Non-Orthogonal Multiple Access (NOMA) in 5G Cellular Downlink and Uplink: Achievements and Challenges Presented at: Huazhong University of Science and Technology (HUST), Wuhan, China S.M. Riazul Islam,
More informationPage 1. Overview : Wireless Networks Lecture 9: OFDM, WiMAX, LTE
Overview 18-759: Wireless Networks Lecture 9: OFDM, WiMAX, LTE Dina Papagiannaki & Peter Steenkiste Departments of Computer Science and Electrical and Computer Engineering Spring Semester 2009 http://www.cs.cmu.edu/~prs/wireless09/
More informationAddressing Future Wireless Demand
Addressing Future Wireless Demand Dave Wolter Assistant Vice President Radio Technology and Strategy 1 Building Blocks of Capacity Core Network & Transport # Sectors/Sites Efficiency Spectrum 2 How Do
More informationA Practical Channel Estimation Scheme for Indoor 60GHz Massive MIMO System. Arumugam Nallanathan King s College London
A Practical Channel Estimation Scheme for Indoor 60GHz Massive MIMO System Arumugam Nallanathan King s College London Performance and Efficiency of 5G Performance Requirements 0.1~1Gbps user rates Tens
More informationPerformance Analysis of Massive MIMO Downlink System with Imperfect Channel State Information
International Journal of Research in Engineering and Science (IJRES) ISSN (Online): 2320-9364, ISSN (Print): 2320-9356 Volume 3 Issue 12 ǁ December. 2015 ǁ PP.14-19 Performance Analysis of Massive MIMO
More informationDiscussion Points for HW-CSP Breakout Session. July 19, 2017 Jeyanandh Paramesh, Subhanshu Gupta, Greg LaCaille, Vishal Saxena, Sarah Yost
Discussion Points for HW-CSP Breakout Session July 19, 2017 Jeyanandh Paramesh, Subhanshu Gupta, Greg LaCaille, Vishal Saxena, Sarah Yost Topics for Discussion (Tentative) What are the main issues at the
More informationAntennas Multiple antenna systems
Channel Modelling ETIM10 Lecture no: 8 Antennas Multiple antenna systems Fredrik Tufvesson Department of Electrical and Information Technology Lund University, Sweden Fredrik.Tufvesson@eit.lth.se 2012-02-13
More informationDesign, Simulation & Concept Verification of 4 4, 8 8 MIMO With ZF, MMSE and BF Detection Schemes
ISSN 2255-9159 (online) ISSN 2255-9140 (print) 2017, vol. 13, pp. 69 74 doi: 10.1515/ecce-2017-0010 https://www.degruyter.com/view/j/ecce Design, Simulation & Concept Verification of 4 4, 8 8 MIMO With
More informationNetPoint Pro. 6x2.4, 6x5.8, 3x2.4, 3x5.8. Wi-Fi base Stations Providing Superior Connectivity
NetPoint Pro 6x2.4, 6x5.8, 3x2.4, 3x5.8 Wi-Fi base Stations Providing Superior Connectivity NetPoint Pro is an advanced Wi-Fi base station that provides superior connectivity and greater range. It enables
More informationEfficient and Low Complex Uplink Detection for 5G Massive MIMO Systems
Efficient and Low Complex Uplink Detection for 5G Massive MIMO Systems Robin Chataut Robert Akl Department of Computer Science and Department of Computer Science and Engineering Engineering University
More informationflexicon.ee.columbia.edu Harish Krishnaswamy, Gil Zussman, Jin Zhou, Jelena (Marašević) Diakonikolas, Tolga Dinc, Negar Reiskarimian, Tingjun Chen
Full-Duplex in a Hand-held Device - From Fundamental Physics to Complex Integrated Circuits, Systems and Networks: An Overview of the Columbia FlexICoN project Harish Krishnaswamy, Gil Zussman, Jin Zhou,
More informationBeamforming algorithm for physical layer security of multi user large scale antenna network
, pp.35-40 http://dx.doi.org/10.14257/astl.2016.134.06 Beamforming algorithm for physical layer security of multi user large scale antenna network Zhou Wen-gang, Li Jing, Guo Hui-ling (School of computer
More informationEnergy Harvested and Achievable Rate of Massive MIMO under Channel Reciprocity Error
Energy Harvested and Achievable Rate of Massive MIMO under Channel Reciprocity Error Abhishek Thakur 1 1Student, Dept. of Electronics & Communication Engineering, IIIT Manipur ---------------------------------------------------------------------***---------------------------------------------------------------------
More informationAll Beamforming Solutions Are Not Equal
White Paper All Beamforming Solutions Are Not Equal Executive Summary This white paper compares and contrasts the two major implementations of beamforming found in the market today: Switched array beamforming
More informationFull Duplex Radios. Sachin Katti Kumu Networks & Stanford University 4/17/2014 1
Full Duplex Radios Sachin Katti Kumu Networks & Stanford University 4/17/2014 1 It is generally not possible for radios to receive and transmit on the same frequency band because of the interference that
More information