"Communications in wireless MIMO channels: Channel models, baseband algorithms, and system design"

Size: px
Start display at page:

Download ""Communications in wireless MIMO channels: Channel models, baseband algorithms, and system design""

Transcription

1 Postgraduate course on "Communications in wireless MIMO channels: Channel models, baseband algorithms, and system design" Lectures given by Prof. Markku Juntti, University of Oulu Prof. Tadashi Matsumoto, University of Oulu/ Elektrobit Docent Ian Oppermann, University of Oulu/ Southern Poro Comm. Docent Juha Ylitalo, Nokia/University of Oulu

2 Course description Dates 1. Introduction (2h) --Juha Capacity limits of MIMO channels (4h) Markku 22.10, MIMO radio channel models (4h) Juha/Ian 29.10, Beamforming and diversity (2h) --Juha Adaptive antenna algorithms (4h) --Juha 7.11, Example: BLAST (PARC) approach for MIMO (2h) --Juha Transmit diversity (4h) Matsumoto , Example: Transmit diversity techniques for WCDMA (2h) --Juha Advanced receivers for MIMO: space-time equalisation (4h) Tad 28.11, Future prospects for MIMO/ Panel discussion (2h) --All at 1pm Lectures on Tuesdays and Thursdays Place: Room TL201 (Tutkijantie 2E) Time: 14:15-16 (except lecture 10)

3 Course description, cont'd Exam : Date to be determined. Please remember to register for the exam. Literature: Mainly journal articles (to appear soon) Prerequisites: Necessary: Signals and systems, Digital Filters, Random Signals, Digital Communications I, Digital Communications II, Coding Methods, Radio Communication Channels. Recommended: Statistical Signal Processing. Useful background: Information Theory. Requirements: Final exam and a few homework problems Credit units: To be determined

4 Course description, cont'd As a part of the course an optional homework project will be arranged. To receive extra credit units a student may design and perform a simple study using Matlab. The study may consist of Monte-Carlo simulations for Shannon capacity or design of a simple CDMA transmitterchannel-receiver chain with multiple antennas and its performance evaluation compared to a single antenna transmitter/receiver. A report of the study shall be written. Report could be in a form of a 5-page conference paper.

5 Introduction to the MIMO course Short historical note Advantages of multi-antenna techniques Single signal through "Smart" antennas (=adaptive antennas) correlated channels - Beamforming: spatial focusing of correlated signals - Rx/Tx diversity: combining of decorrelated signals - MIMO: increasing spectral efficiency/ data rates Single signal through decorrelated channels Simple example: SINR improvement Definition of MIMO Spatial correlation matrix Example: Diversity & MIMO in WCDMA Multiple parallel signals through decorrelated channels

6 Historical Note Multiple antenna transmission used by Marconi in 1901 Four 61m high tower antennas (circular array) Morse signal for "S" from England to Signal Hill, St. John, Newfoundland, distance 3425km Submarine sonar during 1910's Acoustic sensor arrays 1910's RF radars 1940's Ultrasonic scanners from 1960's

7 Advantages of Multiple Antenna Techniques Resistivity to fading (quality) Increased coverage Increased capacity Increased data rate Improved spectral efficiency Reduced power consumption Reduced cost of wireless network Some challenges: - RF: Linear power amplifiers, calibration - Complex algorithms: DSP requirements, cost - Network planning & optimisation Demonstration by Lucent with 8 Tx /12 Rx antennas: 1.2 Mbit/s in 30kHz

8 What are Smart Antennas? A smart antenna system consists of several antenna elements, whose signals are processed adaptively in order to exploit the spatial dimension of the mobile radio channel. Weight Adaptation RF IF RF IF + RF IF Baseband processing It is not the antenna that is smart, but the antenna system!

9 Introduction - Beamforming Conventional BTS: radiation pattern covers the whole cell area Smart Antenna BTS: adaptive radiation pattern, "spatial filter" transmission/reception only to/from the desired user direction minimise antenna gain to direction of other users Conventional BTS radiation pattern Smart Antenna BTS

10 Introduction - Beamforming Beamforming = phasing the antenna array elements 0-5 DOA = 0 deg. 1 DOA = 30 deg. 2 M=8 Array Gain [db] Azimuth [deg]

11 Introduction - Beamforming (cnt.) Individual antenna elemens experience small delay differences coherence between elements assumed element spacing ~λ/2 Basic assumptions: plane waves impinging array geometry known ( "spatial reference" ) transceivers calibrated d narrowband signals ( run time over array << inverse of system bandwidth ) kd sin(θ) θ 1 2 Μ 1 Μ Observed phase difference can be used for direction-of-arrival (DOA) estimation Delay difference => phase difference: θ τ = (d sin θ) /c ϕ = k d sin θ k=2π / λ

12 Introduction - RX Diversity Basic Principles: uncorrelated (statistically independent) signals received spatial combining andof polarisation independently diversity fading arrangements signals: Diversity antenna Maximum Ratio Combining (MRC) λ/2 Interference Rejection Combining (IRC) coverage improvement in WCDMA utilisation of GSM footprint for data services RX Beamforming array RX RX RX db 10 Separation in space-wcdmand/or in polarisation domain Transceiver Received signal power -10 SRC Rx diversity Seconds, 3km/h Combined received signal SRC= Smart Radio Concept (4-branch Rx diversity)

13 Introduction - Transmission Diversity Multiple antennas available at the BTS for RX diversity Conventional terminal: only one antenna downlink suffers from lack of diversity RX diversity in MS is not favored due to complexity reasons (cost, power consumption) Downlink: Use TX instead of RX diversity Uncorrelated fading Signal #1 Signal #2 (1) Gain against fading TX diversity gain: Gain against fading Feedback modes: coherent combining ("beamforming") gain (2) Coherent combining gain (only feedback modes) Downlink capacity improvement

14 MIMO Definition Starting point: SISO, SIMO Single-Input, Single-Output channel suffers from fading Single-Input, Multiple-Output channel: receive diversity Data stream Single-Input Single-Output SISO radio channel Data stream Data stream SIMO radio channel Single-Input Multiple-Output Combiner Data stream

15 Definition of MIMO Multiple-Input, Multiple-Output channel Mapping of a data stream to multiple parallel data streams and de-mapping multiple received data streams into a single data stream Aims at high spectral efficiency / high data rate Data stream Serial/ parallel mapping R x x MIMO radio channel R y y Parallel/ serial mapping Data stream Aims at high spectral efficiency Requires rich scattering environment

16 Spectral efficiency: WCDMA Capacity UL Load Factor (N speech users): η E b UL = + / N 0 N a (1 ) W / R i DL Load Factor (N speech users): η DL N ( Eb / N0) j = a j [(1 bj ) + i W / R j= 1 j j ] E b /N 0 = required SINR at the receiver, W= CDMA chip rate, R= user bit rate, α= activity factor, i= intercell interference, b j = orthogonality factor

17 144kbpsCoverage/CapacityinMacro Cells Max. allowed path loss [db] Downlink load curve Better coverag e Coverage is uplink limited Capacity is downlink limited Uplink load curve with RX diversity for kbps Load per sector [kbps]

18 Nokia Smart Radio Concept Phase 1: Increase Uplink Coverage Max. allowed path loss [db] Uplink load curve with SRC db coverage improveme nt with SRC Uplink load curve without SRC Load per sector [kbps]

19 Nokia Smart Radio Concept Phase2:IncreaseDownlinkCapacity Max. allowed path loss [db] Downlink with TX diversity, 20W per branch 160 Downlink 20W no diversity % increase in capacity Load per sector [kbps]

20 Introduction to MIMO concepts Reference: Foschini and Gans, "On limits of wireless communications in a fading environment when using multiple antennas", Wireless Personal Communications, vol. 6, no.3, 1998

21 Introduction to MIMO Maximum Gain: Transmit Diversity s1, s2, s3, s4 a) Maximum Capacity: Parallel channel transmission V1 V2 V3 V4 Same signal on all antennas, i.e. conventional Tx diversity s1 s2 s3 s4 V1 V2 V3 V4 Different signals on Tx antennas. i.e. true MIMO BLAST (PARC) type b) of tranmission scheme is considered as MIMO, whereas STTD is a hybrid, considered as a Tx diversity scheme

22 Channel capacity (Shannon) Represents the maximum error-free bit rate Capacity depends on the specific channel realization, noise, and transmitted signal power. log 1 P C + α 2 2 Single-input single-output (SISO) channel σ n y ( t) = α x( t) + n( t) = 2 Multi-input multi-output (MIMO) channel y ( t) = Hx( t) + n( t) C 1 det + σ n = H log2 I HQH 2 -Qis the covariance matrix of the transmitted vector

23 Power allocation strategies - Uniform power distribution Transmission power has to be properly distributed over the antennas to maximize the capacity For unknown channel uniform power distribution over the antennas can be applied Q = P n T I which gives C det + P / n σ = T H log2 I HH 2 n For fading channel ergodic capacity can be found by Monte-Carlo simulations

24 Power allocation strategies Water-filling For known channel optimum power distribution using the water-filling technique can be applied The water-filling algorithm can be derived after converting the MIMO channel into a set of L parallel channels using a SVD of the channel matrix H = UDV ~ y ( t) = λ ~ x ( t) + n~ ( t) k k k k H 1 k L p k = K σ 2 n λk yielding the following optimum power allocation

25 Capacity results Uncorrelated Rayleigh MIMO channel (I) Capacity CDFs for uncorrelated flat-freq. Rayleigh channels ( db) Probability(capacity>abcisa) SISO MIMO(1,2) Unknow n MIMO(2,1) Know n MIMO(2,1) MIMO(1,4) Unknow n MIMO(4,1) Know n MIMO(4,1) Capacity in bits per second per Hertz

26 Capacity results Uncorrelated Rayleigh MIMO channel (II) 0.99 Capacity CDFs for uncorrelated flat-freq. Rayleigh channels ( db) 1 Probability(capacity>abcisa) SISO Unknow n MIMO(2,2) Know n MIMO(2,2) Unknow n MIMO(2,4) Know n MIMO(2,4) Unknow n MIMO(4,2) Know n MIMO(4,2) Unknow n MIMO(4,4) Know n MIMO(4,4) Capacity in bits per second per Hertz

27 Capacity results Fully correlated Rayleigh MIMO channel (I) Probability(capacity>abcisa) Capacity CDFs for correlated flat-freq. Rayleigh channels ( db) SISO MIMO(1,2) Unknow n MIMO(2,1) Know n MIMO(2,1) MIMO(1,4) Unknow n MIMO(4,1) Know n MIMO(4,1) Capacity in bits per second per Hertz

28 Capacity results Fully correlated Rayleigh MIMO channel (II) 1 Capacity CDFs for correlated flat-freq. Rayleigh channels ( db) Probability(capacity>abcisa) SISO Unknow n MIMO(2,2) Know n MIMO(2,2) Unknow n MIMO(2,4) Know n MIMO(2,4) Unknow n MIMO(4,2) Know n MIMO(4,2) Unknow n MIMO(4,4) Know n MIMO(4,4) Capacity in bits per second per Hertz

29 MIMO versus Rx/Tx Diversity (theoretical) Spectral efficiency of one channel, no diversity: C=log 2 (1+SNR) [b/s/hz] MIMO with N Tx and M Rx antennas, unknown channel: C=Nlog 2 (1+SNR*M/N) [b/s/hz] M=N=>C=Nlog 2 (1+SNR) [b/s/hz] Rx & Tx diversity: N Tx and M Rx antennas, known channel: C=log 2 (1+SNR*M*N) [b/s/hz]

30 MIMO vs. diversity approaches True MIMO has a theoretical potential at high SNRs, while conventional Rx schemes are more attractive at low SNRs

Multiple Antennas. Mats Bengtsson, Björn Ottersten. Basic Transmission Schemes 1 September 8, Presentation Outline

Multiple Antennas. Mats Bengtsson, Björn Ottersten. Basic Transmission Schemes 1 September 8, Presentation Outline Multiple Antennas Capacity and Basic Transmission Schemes Mats Bengtsson, Björn Ottersten Basic Transmission Schemes 1 September 8, 2005 Presentation Outline Channel capacity Some fine details and misconceptions

More information

Channel Modelling ETI 085. Antennas Multiple antenna systems. Antennas in real channels. Lecture no: Important antenna parameters

Channel Modelling ETI 085. Antennas Multiple antenna systems. Antennas in real channels. Lecture no: Important antenna parameters Channel Modelling ETI 085 Lecture no: 8 Antennas Multiple antenna systems Antennas in real channels One important aspect is how the channel and antenna interact The antenna pattern determines what the

More information

Antennas Multiple antenna systems

Antennas 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 information

6 Uplink is from the mobile to the base station.

6 Uplink is from the mobile to the base station. It is well known that by using the directional properties of adaptive arrays, the interference from multiple users operating on the same channel as the desired user in a time division multiple access (TDMA)

More information

Performance Evaluation of the VBLAST Algorithm in W-CDMA Systems

Performance Evaluation of the VBLAST Algorithm in W-CDMA Systems erformance Evaluation of the VBLAST Algorithm in W-CDMA Systems Dragan Samardzija, eter Wolniansky, Jonathan Ling Wireless Research Laboratory, Bell Labs, Lucent Technologies, 79 Holmdel-Keyport Road,

More information

Written Exam Channel Modeling for Wireless Communications - ETIN10

Written Exam Channel Modeling for Wireless Communications - ETIN10 Written Exam Channel Modeling for Wireless Communications - ETIN10 Department of Electrical and Information Technology Lund University 2017-03-13 2.00 PM - 7.00 PM A minimum of 30 out of 60 points are

More information

Use of Multiple-Antenna Technology in Modern Wireless Communication Systems

Use of Multiple-Antenna Technology in Modern Wireless Communication Systems Use of in Modern Wireless Communication Systems Presenter: Engr. Dr. Noor M. Khan Professor Department of Electrical Engineering, Muhammad Ali Jinnah University, Islamabad Campus, Islamabad, PAKISTAN Ph:

More information

Antennas and Propagation. Chapter 6b: Path Models Rayleigh, Rician Fading, MIMO

Antennas and Propagation. Chapter 6b: Path Models Rayleigh, Rician Fading, MIMO Antennas and Propagation b: Path Models Rayleigh, Rician Fading, MIMO Introduction From last lecture How do we model H p? Discrete path model (physical, plane waves) Random matrix models (forget H p and

More information

ADAPTIVE ANTENNAS. TYPES OF BEAMFORMING

ADAPTIVE ANTENNAS. TYPES OF BEAMFORMING ADAPTIVE ANTENNAS TYPES OF BEAMFORMING 1 1- Outlines This chapter will introduce : Essential terminologies for beamforming; BF Demonstrating the function of the complex weights and how the phase and amplitude

More information

CHAPTER 8 MIMO. Xijun Wang

CHAPTER 8 MIMO. Xijun Wang CHAPTER 8 MIMO Xijun Wang WEEKLY READING 1. Goldsmith, Wireless Communications, Chapters 10 2. Tse, Fundamentals of Wireless Communication, Chapter 7-10 2 MIMO 3 BENEFITS OF MIMO n Array gain The increase

More information

Channel Capacity Estimation in MIMO Systems Based on Water-Filling Algorithm

Channel Capacity Estimation in MIMO Systems Based on Water-Filling Algorithm Channel Capacity Estimation in MIMO Systems Based on Water-Filling Algorithm 1 Ch.Srikanth, 2 B.Rajanna 1 PG SCHOLAR, 2 Assistant Professor Vaagdevi college of engineering. (warangal) ABSTRACT power than

More information

Performance of wireless Communication Systems with imperfect CSI

Performance of wireless Communication Systems with imperfect CSI Pedagogy lecture Performance of wireless Communication Systems with imperfect CSI Yogesh Trivedi Associate Prof. Department of Electronics and Communication Engineering Institute of Technology Nirma University

More information

3G Evolution. Outline. Chapter: Multi-antenna configurations. Introduction. Introduction. Multi-antenna techniques. Multiple receiver antennas, SIMO

3G Evolution. Outline. Chapter: Multi-antenna configurations. Introduction. Introduction. Multi-antenna techniques. Multiple receiver antennas, SIMO Chapter: 3G Evolution 6 Outline Introduction Multi-antenna configurations Multi-antenna t techniques Vanja Plicanic vanja.plicanic@eit.lth.se lth Multi-antenna techniques Multiple transmitter antennas,

More information

Diversity. Spring 2017 ELE 492 FUNDAMENTALS OF WIRELESS COMMUNICATIONS 1

Diversity. Spring 2017 ELE 492 FUNDAMENTALS OF WIRELESS COMMUNICATIONS 1 Diversity Spring 2017 ELE 492 FUNDAMENTALS OF WIRELESS COMMUNICATIONS 1 Diversity A fading channel with an average SNR has worse BER performance as compared to that of an AWGN channel with the same SNR!.

More information

Performance of Closely Spaced Multiple Antennas for Terminal Applications

Performance of Closely Spaced Multiple Antennas for Terminal Applications Performance of Closely Spaced Multiple Antennas for Terminal Applications Anders Derneryd, Jonas Fridén, Patrik Persson, Anders Stjernman Ericsson AB, Ericsson Research SE-417 56 Göteborg, Sweden {anders.derneryd,

More information

Mobile Communications: Technology and QoS

Mobile Communications: Technology and QoS Mobile Communications: Technology and QoS Course Overview! Marc Kuhn, Yahia Hassan kuhn@nari.ee.ethz.ch / hassan@nari.ee.ethz.ch Institut für Kommunikationstechnik (IKT) Wireless Communications Group ETH

More information

MIMO I: Spatial Diversity

MIMO I: Spatial Diversity MIMO I: Spatial Diversity COS 463: Wireless Networks Lecture 16 Kyle Jamieson [Parts adapted from D. Halperin et al., T. Rappaport] What is MIMO, and why? Multiple-Input, Multiple-Output (MIMO) communications

More information

Transforming MIMO Test

Transforming 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 information

Multiple Antenna Processing for WiMAX

Multiple 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 information

Low-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems

Low-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems Low-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems Jiangzhou Wang University of Kent 1 / 31 Best Wishes to Professor Fumiyuki Adachi, Father of Wideband CDMA [1]. [1]

More information

ELEC E7210: Communication Theory. Lecture 11: MIMO Systems and Space-time Communications

ELEC E7210: Communication Theory. Lecture 11: MIMO Systems and Space-time Communications ELEC E7210: Communication Theory Lecture 11: MIMO Systems and Space-time Communications Overview of the last lecture MIMO systems -parallel decomposition; - beamforming; - MIMO channel capacity MIMO Key

More information

MU-MIMO with Fixed Beamforming for

MU-MIMO with Fixed Beamforming for MU-MIMO with Fixed Beamforming for FDD Systems Manfred Litzenburger, Thorsten Wild, Michael Ohm Alcatel-Lucent R&I Stuttgart, Germany MU-MIMO - Motivation MU-MIMO Supporting multiple users in a cell on

More information

Advanced Antenna Technology

Advanced Antenna Technology Advanced Antenna Technology Abdus Salam ICTP, February 2004 School on Digital Radio Communications for Research and Training in Developing Countries Ermanno Pietrosemoli Latin American Networking School

More information

Wireless Communication: Concepts, Techniques, and Models. Hongwei Zhang

Wireless Communication: Concepts, Techniques, and Models. Hongwei Zhang Wireless Communication: Concepts, Techniques, and Models Hongwei Zhang http://www.cs.wayne.edu/~hzhang Outline Digital communication over radio channels Channel capacity MIMO: diversity and parallel channels

More information

STUDY OF ENHANCEMENT OF SPECTRAL EFFICIENCY OF WIRELESS FADING CHANNEL USING MIMO TECHNIQUES

STUDY OF ENHANCEMENT OF SPECTRAL EFFICIENCY OF WIRELESS FADING CHANNEL USING MIMO TECHNIQUES STUDY OF ENHANCEMENT OF SPECTRAL EFFICIENCY OF WIRELESS FADING CHANNEL USING MIMO TECHNIQUES Jayanta Paul M.TECH, Electronics and Communication Engineering, Heritage Institute of Technology, (India) ABSTRACT

More information

Diversity Techniques

Diversity Techniques Diversity Techniques Vasileios Papoutsis Wireless Telecommunication Laboratory Department of Electrical and Computer Engineering University of Patras Patras, Greece No.1 Outline Introduction Diversity

More information

Correlation and Calibration Effects on MIMO Capacity Performance

Correlation and Calibration Effects on MIMO Capacity Performance Correlation and Calibration Effects on MIMO Capacity Performance D. ZARBOUTI, G. TSOULOS, D. I. KAKLAMANI Departement of Electrical and Computer Engineering National Technical University of Athens 9, Iroon

More information

CHAPTER 5 DIVERSITY. Xijun Wang

CHAPTER 5 DIVERSITY. Xijun Wang CHAPTER 5 DIVERSITY Xijun Wang WEEKLY READING 1. Goldsmith, Wireless Communications, Chapters 7 2. Tse, Fundamentals of Wireless Communication, Chapter 3 2 FADING HURTS THE RELIABILITY n The detection

More information

EE 5407 Part II: Spatial Based Wireless Communications

EE 5407 Part II: Spatial Based Wireless Communications EE 5407 Part II: Spatial Based Wireless Communications Instructor: Prof. Rui Zhang E-mail: rzhang@i2r.a-star.edu.sg Website: http://www.ece.nus.edu.sg/stfpage/elezhang/ Lecture I: Introduction March 4,

More information

MIMO in 3G STATUS. MIMO for high speed data in 3G systems. Outline. Information theory for wireless channels

MIMO in 3G STATUS. MIMO for high speed data in 3G systems. Outline. Information theory for wireless channels MIMO in G STATUS MIMO for high speed data in G systems Reinaldo Valenzuela Wireless Communications Research Department Bell Laboratories MIMO (multiple antenna technologies) provides higher peak data rates

More information

Performance Studies on LTE Advanced in the Easy-C Project Andreas Weber, Alcatel Lucent Bell Labs

Performance Studies on LTE Advanced in the Easy-C Project Andreas Weber, Alcatel Lucent Bell Labs Performance Studies on LTE Advanced in the Easy-C Project 19.06.2008 Andreas Weber, Alcatel Lucent Bell Labs All Rights Reserved Alcatel-Lucent 2007 Agenda 1. Introduction 2. EASY C 3. LTE System Simulator

More information

CHAPTER 3 FADING & DIVERSITY IN MULTIPLE ANTENNA SYSTEM

CHAPTER 3 FADING & DIVERSITY IN MULTIPLE ANTENNA SYSTEM CHAPTER 3 FADING & DIVERSITY IN MULTIPLE ANTENNA SYSTEM 3.1 Introduction to Fading 37 3.2 Fading in Wireless Environment 38 3.3 Rayleigh Fading Model 39 3.4 Introduction to Diversity 41 3.5 Space Diversity

More information

ADVANCED WIRELESS TECHNOLOGIES. Aditya K. Jagannatham Indian Institute of Technology Kanpur

ADVANCED WIRELESS TECHNOLOGIES. Aditya K. Jagannatham Indian Institute of Technology Kanpur ADVANCED WIRELESS TECHNOLOGIES Aditya K. Jagannatham Indian Institute of Technology Kanpur Wireless Signal Fast Fading The wireless signal can reach the receiver via direct and scattered paths. As a result,

More information

Lecture 5: Antenna Diversity and MIMO Capacity Theoretical Foundations of Wireless Communications 1

Lecture 5: Antenna Diversity and MIMO Capacity Theoretical Foundations of Wireless Communications 1 Antenna, Antenna : Antenna and Theoretical Foundations of Wireless Communications 1 Friday, April 27, 2018 9:30-12:00, Kansliet plan 3 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication

More information

Lecture 4 Diversity and MIMO Communications

Lecture 4 Diversity and MIMO Communications MIMO Communication Systems Lecture 4 Diversity and MIMO Communications Prof. Chun-Hung Liu Dept. of Electrical and Computer Engineering National Chiao Tung University Spring 2017 1 Outline Diversity Techniques

More information

Analysis of RF requirements for Active Antenna System

Analysis of RF requirements for Active Antenna System 212 7th International ICST Conference on Communications and Networking in China (CHINACOM) Analysis of RF requirements for Active Antenna System Rong Zhou Department of Wireless Research Huawei Technology

More information

Antennas and Propagation. Chapter 5c: Array Signal Processing and Parametric Estimation Techniques

Antennas and Propagation. Chapter 5c: Array Signal Processing and Parametric Estimation Techniques Antennas and Propagation : Array Signal Processing and Parametric Estimation Techniques Introduction Time-domain Signal Processing Fourier spectral analysis Identify important frequency-content of signal

More information

Ten Things You Should Know About MIMO

Ten 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 information

Capacity and Coverage Improvements of Adaptive Antennas in CDMA Networks

Capacity and Coverage Improvements of Adaptive Antennas in CDMA Networks Capacity and Coverage Improvements of Adaptive Antennas in CDMA etworks V1.2 Erik Lindskog and Mitchell Trott ArrayComm, Inc. 248. First Street, Suite 2 San Jose, CA 95131-114 USA Tel: +1 (48) 428-98 Fax:

More information

CHAPTER 2 WIRELESS CHANNEL

CHAPTER 2 WIRELESS CHANNEL CHAPTER 2 WIRELESS CHANNEL 2.1 INTRODUCTION In mobile radio channel there is certain fundamental limitation on the performance of wireless communication system. There are many obstructions between transmitter

More information

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks

Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks 1 Decentralized Resource Allocation and Effective CSI Signaling in Dense TDD Networks Antti Tölli with Praneeth Jayasinghe,

More information

Optimizing Multi-Cell Massive MIMO for Spectral Efficiency

Optimizing Multi-Cell Massive MIMO for Spectral Efficiency Optimizing Multi-Cell Massive MIMO for Spectral Efficiency How Many Users Should Be Scheduled? Emil Björnson 1, Erik G. Larsson 1, Mérouane Debbah 2 1 Linköping University, Linköping, Sweden 2 Supélec,

More information

Analysis and Improvements of Linear Multi-user user MIMO Precoding Techniques

Analysis 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 information

Noncoherent Communications with Large Antenna Arrays

Noncoherent Communications with Large Antenna Arrays Noncoherent Communications with Large Antenna Arrays Mainak Chowdhury Joint work with: Alexandros Manolakos, Andrea Goldsmith, Felipe Gomez-Cuba and Elza Erkip Stanford University September 29, 2016 Wireless

More information

MIMO Systems and Applications

MIMO 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 information

Opportunistic Communication in Wireless Networks

Opportunistic Communication in Wireless Networks Opportunistic Communication in Wireless Networks David Tse Department of EECS, U.C. Berkeley October 10, 2001 Networking, Communications and DSP Seminar Communication over Wireless Channels Fundamental

More information

Investigation on Multiple Antenna Transmission Techniques in Evolved UTRA. OFDM-Based Radio Access in Downlink. Features of Evolved UTRA and UTRAN

Investigation 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 information

Adaptive Systems Homework Assignment 3

Adaptive Systems Homework Assignment 3 Signal Processing and Speech Communication Lab Graz University of Technology Adaptive Systems Homework Assignment 3 The analytical part of your homework (your calculation sheets) as well as the MATLAB

More information

Measurement Based Capacity of Distributed MIMO Antenna System in Urban Microcellular Environment at 5.25 GHz

Measurement Based Capacity of Distributed MIMO Antenna System in Urban Microcellular Environment at 5.25 GHz Measurement Based Capacity of Distributed MIMO Antenna System in Urban Microcellular Environment at 5.25 GHz Mikko Alatossava, Student member, IEEE, Attaphongse Taparugssanagorn, Student member, IEEE,

More information

Keywords MISO, BER, SNR, EGT, SDT, MRT & BPSK.

Keywords MISO, BER, SNR, EGT, SDT, MRT & BPSK. Volume 5, Issue 6, June 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Comparison of Beamforming

More information

Lecture 12: Summary Advanced Digital Communications (EQ2410) 1

Lecture 12: Summary Advanced Digital Communications (EQ2410) 1 : Advanced Digital Communications (EQ2410) 1 Monday, Mar. 7, 2016 15:00-17:00, B23 1 Textbook: U. Madhow, Fundamentals of Digital Communications, 2008 1 / 15 Overview 1 2 3 4 2 / 15 Equalization Maximum

More information

1 Overview of MIMO communications

1 Overview of MIMO communications Jerry R Hampton 1 Overview of MIMO communications This chapter lays the foundations for the remainder of the book by presenting an overview of MIMO communications Fundamental concepts and key terminology

More information

Comparative Channel Capacity Analysis of a MIMO Rayleigh Fading Channel with Different Antenna Spacing and Number of Nodes

Comparative Channel Capacity Analysis of a MIMO Rayleigh Fading Channel with Different Antenna Spacing and Number of Nodes Comparative Channel Capacity Analysis of a MIMO Rayleigh Fading Channel with Different Antenna Spacing and Number of Nodes Anand Jain 1, Kapil Kumawat, Harish Maheshwari 3 1 Scholar, M. Tech., Digital

More information

Amplitude and Phase Distortions in MIMO and Diversity Systems

Amplitude and Phase Distortions in MIMO and Diversity Systems Amplitude and Phase Distortions in MIMO and Diversity Systems Christiane Kuhnert, Gerd Saala, Christian Waldschmidt, Werner Wiesbeck Institut für Höchstfrequenztechnik und Elektronik (IHE) Universität

More information

MULTIPLE ANTENNA WIRELESS SYSTEMS AND CHANNEL STATE INFORMATION

MULTIPLE ANTENNA WIRELESS SYSTEMS AND CHANNEL STATE INFORMATION MULTIPLE ANTENNA WIRELESS SYSTEMS AND CHANNEL STATE INFORMATION BY DRAGAN SAMARDZIJA A dissertation submitted to the Graduate School New Brunswick Rutgers, The State University of New Jersey in partial

More information

Antenna Design and Site Planning Considerations for MIMO

Antenna Design and Site Planning Considerations for MIMO Antenna Design and Site Planning Considerations for MIMO Steve Ellingson Mobile & Portable Radio Research Group (MPRG) Dept. of Electrical & Computer Engineering Virginia Polytechnic Institute & State

More information

Multiple Antennas in Wireless Communications

Multiple Antennas in Wireless Communications Multiple Antennas in Wireless Communications Luca Sanguinetti Department of Information Engineering Pisa University lucasanguinetti@ietunipiit April, 2009 Luca Sanguinetti (IET) MIMO April, 2009 1 / 46

More information

A Complete MIMO System Built on a Single RF Communication Ends

A Complete MIMO System Built on a Single RF Communication Ends PIERS ONLINE, VOL. 6, NO. 6, 2010 559 A Complete MIMO System Built on a Single RF Communication Ends Vlasis Barousis, Athanasios G. Kanatas, and George Efthymoglou University of Piraeus, Greece Abstract

More information

Wireless Channel Propagation Model Small-scale Fading

Wireless Channel Propagation Model Small-scale Fading Wireless Channel Propagation Model Small-scale Fading Basic Questions T x What will happen if the transmitter - changes transmit power? - changes frequency? - operates at higher speed? Transmit power,

More information

Modeling Mutual Coupling and OFDM System with Computational Electromagnetics

Modeling Mutual Coupling and OFDM System with Computational Electromagnetics Modeling Mutual Coupling and OFDM System with Computational Electromagnetics Nicholas J. Kirsch Drexel University Wireless Systems Laboratory Telecommunication Seminar October 15, 004 Introduction MIMO

More information

EE360: Lecture 6 Outline MUD/MIMO in Cellular Systems

EE360: Lecture 6 Outline MUD/MIMO in Cellular Systems EE360: Lecture 6 Outline MUD/MIMO in Cellular Systems Announcements Project proposals due today Makeup lecture tomorrow Feb 2, 5-6:15, Gates 100 Multiuser Detection in cellular MIMO in Cellular Multiuser

More information

Diversity[1] Dr. Manjunatha. P. Professor Dept. of ECE. May 11, J.N.N. College of Engineering, Shimoga.

Diversity[1] Dr. Manjunatha. P. Professor Dept. of ECE. May 11, J.N.N. College of Engineering, Shimoga. Diversity[1] Dr. Manjunatha. P manjup.jnnce@gmail.com Professor Dept. of ECE J.N.N. College of Engineering, Shimoga May 11, 2015 Diversity Syllabus Diversity: [1] Slides are prepared to use in class room

More information

E7220: Radio Resource and Spectrum Management. Lecture 4: MIMO

E7220: Radio Resource and Spectrum Management. Lecture 4: MIMO E7220: Radio Resource and Spectrum Management Lecture 4: MIMO 1 Timeline: Radio Resource and Spectrum Management (5cr) L1: Random Access L2: Scheduling and Fairness L3: Energy Efficiency L4: MIMO L5: UDN

More information

Abstract. Marío A. Bedoya-Martinez. He joined Fujitsu Europe Telecom R&D Centre (UK), where he has been working on R&D of Second-and

Abstract. Marío A. Bedoya-Martinez. He joined Fujitsu Europe Telecom R&D Centre (UK), where he has been working on R&D of Second-and Abstract The adaptive antenna array is one of the advanced techniques which could be implemented in the IMT-2 mobile telecommunications systems to achieve high system capacity. In this paper, an integrated

More information

Exam 3 is two weeks from today. Today s is the final lecture that will be included on the exam.

Exam 3 is two weeks from today. Today s is the final lecture that will be included on the exam. ECE 5325/6325: Wireless Communication Systems Lecture Notes, Spring 2010 Lecture 19 Today: (1) Diversity Exam 3 is two weeks from today. Today s is the final lecture that will be included on the exam.

More information

EFFICIENT SMART ANTENNA FOR 4G COMMUNICATIONS

EFFICIENT SMART ANTENNA FOR 4G COMMUNICATIONS http:// EFFICIENT SMART ANTENNA FOR 4G COMMUNICATIONS 1 Saloni Aggarwal, 2 Neha Kaushik, 3 Deeksha Sharma 1,2,3 UG, Department of Electronics and Communication Engineering, Raj Kumar Goel Institute of

More information

Multiple Antenna Systems in WiMAX

Multiple Antenna Systems in WiMAX WHITEPAPER An Introduction to MIMO, SAS and Diversity supported by Airspan s WiMAX Product Line We Make WiMAX Easy Multiple Antenna Systems in WiMAX An Introduction to MIMO, SAS and Diversity supported

More information

Lecture 8 Multi- User MIMO

Lecture 8 Multi- User MIMO Lecture 8 Multi- User MIMO I-Hsiang Wang ihwang@ntu.edu.tw 5/7, 014 Multi- User MIMO System So far we discussed how multiple antennas increase the capacity and reliability in point-to-point channels Question:

More information

Review on Improvement in WIMAX System

Review on Improvement in WIMAX System IJIRST International Journal for Innovative Research in Science & Technology Volume 3 Issue 09 February 2017 ISSN (online): 2349-6010 Review on Improvement in WIMAX System Bhajankaur S. Wassan PG Student

More information

About Homework. The rest parts of the course: focus on popular standards like GSM, WCDMA, etc.

About Homework. The rest parts of the course: focus on popular standards like GSM, WCDMA, etc. About Homework The rest parts of the course: focus on popular standards like GSM, WCDMA, etc. Good news: No complicated mathematics and calculations! Concepts: Understanding and remember! Homework: review

More information

MIMO II: Physical Channel Modeling, Spatial Multiplexing. COS 463: Wireless Networks Lecture 17 Kyle Jamieson

MIMO II: Physical Channel Modeling, Spatial Multiplexing. COS 463: Wireless Networks Lecture 17 Kyle Jamieson MIMO II: Physical Channel Modeling, Spatial Multiplexing COS 463: Wireless Networks Lecture 17 Kyle Jamieson Today 1. Graphical intuition in the I-Q plane 2. Physical modeling of the SIMO channel 3. Physical

More information

Narrow- and wideband channels

Narrow- and wideband channels RADIO SYSTEMS ETIN15 Lecture no: 3 Narrow- and wideband channels Ove Edfors, Department of Electrical and Information technology Ove.Edfors@eit.lth.se 2012-03-19 Ove Edfors - ETIN15 1 Contents Short review

More information

Cellular Network Planning and Optimization Part VI: WCDMA Basics. Jyri Hämäläinen, Communications and Networking Department, TKK, 24.1.

Cellular Network Planning and Optimization Part VI: WCDMA Basics. Jyri Hämäläinen, Communications and Networking Department, TKK, 24.1. Cellular Network Planning and Optimization Part VI: WCDMA Basics Jyri Hämäläinen, Communications and Networking Department, TKK, 24.1.2008 Outline Network elements Physical layer Radio resource management

More information

ENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM

ENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM ENERGY EFFICIENT WATER-FILLING ALGORITHM FOR MIMO- OFDMA CELLULAR SYSTEM Hailu Belay Kassa, Dereje H.Mariam Addis Ababa University, Ethiopia Farzad Moazzami, Yacob Astatke Morgan State University Baltimore,

More information

CHAPTER 10 CONCLUSIONS AND FUTURE WORK 10.1 Conclusions

CHAPTER 10 CONCLUSIONS AND FUTURE WORK 10.1 Conclusions CHAPTER 10 CONCLUSIONS AND FUTURE WORK 10.1 Conclusions This dissertation reported results of an investigation into the performance of antenna arrays that can be mounted on handheld radios. Handheld arrays

More information

On Using Channel Prediction in Adaptive Beamforming Systems

On Using Channel Prediction in Adaptive Beamforming Systems On Using Channel rediction in Adaptive Beamforming Systems T. R. Ramya and Srikrishna Bhashyam Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai - 600 036, India. Email:

More information

Performance Evaluation of Adaptive MIMO Switching in Long Term Evolution

Performance Evaluation of Adaptive MIMO Switching in Long Term Evolution Performance Evaluation of Adaptive MIMO Switching in Long Term Evolution Muhammad Usman Sheikh, Rafał Jagusz,2, Jukka Lempiäinen Department of Communication Engineering, Tampere University of Technology,

More information

MIMO in WCDMA and LTE

MIMO in WCDMA and LTE MIMO in WCDMA and LTE STUDENT BOOK LZT 123 9417 R1A LZT 123 9417 R1A Ericsson 2009-1 - DISCLAIMER This book is a training document and contains simplifications. Therefore, it must not be considered as

More information

Transmission Strategies for Wireless Multi-user, Multiple-Input, Multiple-Output Communication Channels

Transmission Strategies for Wireless Multi-user, Multiple-Input, Multiple-Output Communication Channels Brigham Young University BYU ScholarsArchive All Theses and Dissertations 2004-03-18 Transmission Strategies for Wireless Multi-user, Multiple-Input, Multiple-Output Communication Channels Quentin H. Spencer

More information

Dynamic Fair Channel Allocation for Wideband Systems

Dynamic Fair Channel Allocation for Wideband Systems Outlines Introduction and Motivation Dynamic Fair Channel Allocation for Wideband Systems Department of Mobile Communications Eurecom Institute Sophia Antipolis 19/10/2006 Outline of Part I Outlines Introduction

More information

Channel Modelling for Beamforming in Cellular Systems

Channel Modelling for Beamforming in Cellular Systems Channel Modelling for Beamforming in Cellular Systems Salman Durrani Department of Engineering, The Australian National University, Canberra. Email: salman.durrani@anu.edu.au DERF June 26 Outline Introduction

More information

Supplemental Slides: MIMO Testbed Development at the MPRG Lab

Supplemental Slides: MIMO Testbed Development at the MPRG Lab Supplemental Slides: MIMO Testbed Development at the MPRG Lab Raqibul Mostafa Jeffrey H. Reed Slide 1 Overview Space Time Coding (STC) Overview Virginia Tech Space Time Adaptive Radio (VT-STAR) description:

More information

REALISTIC ANTENNA ELEMENTS AND DIFFERENT ARRAY TOPOLOGIES IN THE DOWNLINK OF UMTS-FDD NETWORKS

REALISTIC ANTENNA ELEMENTS AND DIFFERENT ARRAY TOPOLOGIES IN THE DOWNLINK OF UMTS-FDD NETWORKS REALISTIC ANTENNA ELEMENTS AND DIFFERENT ARRAY TOPOLOGIES IN THE DOWNLINK OF UMTS-FDD NETWORKS S. Bieder, L. Häring, A. Czylwik, P. Paunov Department of Communication Systems University of Duisburg-Essen

More information

Analysis of Massive MIMO With Hardware Impairments and Different Channel Models

Analysis of Massive MIMO With Hardware Impairments and Different Channel Models Analysis of Massive MIMO With Hardware Impairments and Different Channel Models Fredrik Athley, Giuseppe Durisi 2, Ulf Gustavsson Ericsson Research, Ericsson AB, Gothenburg, Sweden 2 Dept. of Signals and

More information

EE359 Discussion Session 8 Beamforming, Diversity-multiplexing tradeoff, MIMO receiver design, Multicarrier modulation

EE359 Discussion Session 8 Beamforming, Diversity-multiplexing tradeoff, MIMO receiver design, Multicarrier modulation EE359 Discussion Session 8 Beamforming, Diversity-multiplexing tradeoff, MIMO receiver design, Multicarrier modulation November 29, 2017 EE359 Discussion 8 November 29, 2017 1 / 33 Outline 1 MIMO concepts

More information

Spring 2017 MIMO Communication Systems Solution of Homework Assignment #5

Spring 2017 MIMO Communication Systems Solution of Homework Assignment #5 Spring 217 MIMO Communication Systems Solution of Homework Assignment #5 Problem 1 (2 points Consider a channel with impulse response h(t α δ(t + α 1 δ(t T 1 + α 3 δ(t T 2. Assume that T 1 1 µsecs and

More information

Uplink and Downlink Rate Analysis of a Full-Duplex C-RAN with Radio Remote Head Association

Uplink and Downlink Rate Analysis of a Full-Duplex C-RAN with Radio Remote Head Association Uplink and Downlink Rate Analysis of a Full-Duplex C-RAN with Radio Remote Head Association Mohammadali Mohammadi 1, Himal A. Suraweera 2, and Chintha Tellambura 3 1 Faculty of Engineering, Shahrekord

More information

Beamforming for 4.9G/5G Networks

Beamforming 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 information

Index. Cambridge University Press Fundamentals of Wireless Communication David Tse and Pramod Viswanath. Index.

Index. Cambridge University Press Fundamentals of Wireless Communication David Tse and Pramod Viswanath. Index. ad hoc network 5 additive white Gaussian noise (AWGN) 29, 30, 166, 241 channel capacity 167 capacity-achieving AWGN channel codes 170, 171 packing spheres 168 72, 168, 169 channel resources 172 bandwidth

More information

Smart antenna technology

Smart antenna technology Smart antenna technology In mobile communication systems, capacity and performance are usually limited by two major impairments. They are multipath and co-channel interference [5]. Multipath is a condition

More information

MIMO Channel Capacity in Co-Channel Interference

MIMO Channel Capacity in Co-Channel Interference MIMO Channel Capacity in Co-Channel Interference Yi Song and Steven D. Blostein Department of Electrical and Computer Engineering Queen s University Kingston, Ontario, Canada, K7L 3N6 E-mail: {songy, sdb}@ee.queensu.ca

More information

Lecture LTE (4G) -Technologies used in 4G and 5G. Spread Spectrum Communications

Lecture 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 information

University of Bristol - Explore Bristol Research. Link to published version (if available): /VTCF

University of Bristol - Explore Bristol Research. Link to published version (if available): /VTCF Bian, Y. Q., & Nix, A. R. (2006). Throughput and coverage analysis of a multi-element broadband fixed wireless access (BFWA) system in the presence of co-channel interference. In IEEE 64th Vehicular Technology

More information

Design of Analog and Digital Beamformer for 60GHz MIMO Frequency Selective Channel through Second Order Cone Programming

Design of Analog and Digital Beamformer for 60GHz MIMO Frequency Selective Channel through Second Order Cone Programming IOSR Journal of VLSI and Signal Processing (IOSR-JVSP) Volume 5, Issue 6, Ver. II (Nov -Dec. 2015), PP 91-97 e-issn: 2319 4200, p-issn No. : 2319 4197 www.iosrjournals.org Design of Analog and Digital

More information

EENG473 Mobile Communications Module 3 : Week # (12) Mobile Radio Propagation: Small-Scale Path Loss

EENG473 Mobile Communications Module 3 : Week # (12) Mobile Radio Propagation: Small-Scale Path Loss EENG473 Mobile Communications Module 3 : Week # (12) Mobile Radio Propagation: Small-Scale Path Loss Introduction Small-scale fading is used to describe the rapid fluctuation of the amplitude of a radio

More information

Optimum Power Allocation in Cooperative Networks

Optimum Power Allocation in Cooperative Networks Optimum Power Allocation in Cooperative Networks Jaime Adeane, Miguel R.D. Rodrigues, and Ian J. Wassell Laboratory for Communication Engineering Department of Engineering University of Cambridge 5 JJ

More information

Long Term Evolution (LTE) and 5th Generation Mobile Networks (5G) CS-539 Mobile Networks and Computing

Long Term Evolution (LTE) and 5th Generation Mobile Networks (5G) CS-539 Mobile Networks and Computing Long Term Evolution (LTE) and 5th Generation Mobile Networks (5G) Long Term Evolution (LTE) What is LTE? LTE is the next generation of Mobile broadband technology Data Rates up to 100Mbps Next level of

More information

Designing Energy Efficient 5G Networks: When Massive Meets Small

Designing 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 information

CHAPTER 4 PERFORMANCE ANALYSIS OF THE ALAMOUTI STBC BASED DS-CDMA SYSTEM

CHAPTER 4 PERFORMANCE ANALYSIS OF THE ALAMOUTI STBC BASED DS-CDMA SYSTEM 89 CHAPTER 4 PERFORMANCE ANALYSIS OF THE ALAMOUTI STBC BASED DS-CDMA SYSTEM 4.1 INTRODUCTION This chapter investigates a technique, which uses antenna diversity to achieve full transmit diversity, using

More information

Impact of Antenna Geometry on Adaptive Switching in MIMO Channels

Impact of Antenna Geometry on Adaptive Switching in MIMO Channels Impact of Antenna Geometry on Adaptive Switching in MIMO Channels Ramya Bhagavatula, Antonio Forenza, Robert W. Heath Jr. he University of exas at Austin University Station, C0803, Austin, exas, 787-040

More information