Emmanouel T. Michailidis Athanasios G. Kanatas
|
|
- Matthew Watkins
- 6 years ago
- Views:
Transcription
1 Emmanouel T. Michailidis George Efthymoglou gr) Athanasios G. Kanatas University of Piraeus Department of Digital Systems Wireless Communications Laboratory
2 Introduction The 3-D Land Mobile HAP-MIMO Channel Model Space-Time Correlation Functions Numerical Results Conclusions 2
3 High Altitude Platforms (HAPs) are an alternative or complement to terrestrial and satellite infrastructure for providing narrowband and broadband wireless access. The ITU has licensed 48/47 GHz for the world wide 4G communications systems, 31/28 GHz for Asians countries and 2 GHz for 3G communications systems through h HAPs. HAPs typically operate in lower stratosphere (approximately 20 km above ground). 3
4 Even though HAPs can provide quasi- stationary communication platforms, winds or pressure variations have to be compensated. In practice, HAPs may move in any direction at a varying speed (6 degrees of freedom). The ITU has specified that a HAP should be kept within a circle of 400m radius, with height variations of ±700m, in order for the services to be available. 4
5 High elevation angles imply the presence of a predominant radio wave path of line-of-sight i (LOS), but also multipath propagation (NLOS) should be considered in urban and indoor areas (2 GHz band) Rain attenuation effects are negligible at this frequency range. 5
6 Traditional Multiple Input-Multiple Output (MIMO) techniques for terrestrial systems exploit effectively the propagation environments with rich scattering. An uncorrelated MIMO channel matrix can enhance the performance of communication systems, provide increased data rates and maximize channel capacity. 6
7 We consider a Stratospheric Base Station (SBS) and a Terrestrial Mobile Station (TMS) that constitute a 2 2 HAP-MIMO system with ULA antennas. Both SBS and TMS are in motion. Previous studies indicated that vertical stratospheric winds are almost insignificant, therefore SBS is considered to move within a circle, instead of a cylinder. 7
8 Definition of Parameters (a) 8
9 Definition of Parameters (b) 9
10 z p R HAP O T q The LOS paths of the 3-D cylinder model for 2 2 HAP-MIMO channels l ψ O R q% y θ T p% γ T u T β HAP O O m% m LOS α Rl θ l% R R γ R ur x 10
11 z p R HAP O T q The NLOS paths of the 3-D cylinder model for 2x2 HAP-MIMO channels ( n) S l ( n) β S ψ O R q% y θ T p% u T γ T ( n) a T ( n) S % m ( n) O O m% a R θ l% R R γ R ur x 11
12 Since the number of local scatterers is infinite, the impulse response of the NLOS component can be modeled as a low pass zero mean complex Gaussian process and therefore its envelope is Rayleigh distributed (due to the central limit theorem) The impulse response of the sub-channel p-l is a superposition of the LOS and NLOS rays: ( ) = ( ) + ( ) h t h t h t pl pl, LOS pl, NLOS 12
13 The impulse responses of the LOS and NLOS components are, respectively: 2πH π LOS K j j δt cosθt+ δr cos( αrl θr) cosψ LOS LOS sin cos j2 tft,max cos( Rl T ) j2 tfr,max cos( Rl ) pl λ β λ π π α γ + π α γ HAP βhap hpl, LOS ( t) e e e K + 1 pl N 1 1 jϕ ( ) h () t lim a b e e + pl, NLOS p, S S, l K 1 N pl n = 1 N where: a ps, ( n) ( n) j2πt f,max ( Δ sinγ sinαr + cosγ ) + f,max cos αr γ ( ) n T T T R R ( n ) 2π H πδ T cosθ T πδ T Δsin θ T sin αr j j j λ sin β λcosβ λcos β = e e e HAP HAP HAP 2πR π ( n) π ( n) ( n) π ( n) ( n) j j δrsinψ sin βs j δrcosψcosβs cosθrcosαr j δrcosψcosβs sinθrsinαr λ λ λ λ b = e e e e Sl,, 13
14 The Space-Time Correlation function between two sub-channels p-l and q-m is defined as: LoS NLOS ( δ, δ, τ) = ( δ, δ, τ) + ( δ, δ, τ) R R R pl, qm T R pl, qm T R pl, qm T R { }, Using the far-field assumption: δ δ D T R O O the Space-Time Correlation function of the LOS component can be written as: j2π λcosβ max,, K ( T cos T R cos R cos ) pl K δ θ δ θ ψ LOS qm j2πτ ft,max cos T fr,max cos HAP γ γr Rpl, qm ( δt, δr, τ) e e. K + 1 K + 1 pl qm 14
15 Random scatterer s discrete angle of arrival and elevation angle can be replaced with continuous random variables with probability density functions: f 1 α exp[ kcos ( α μ) ], - π α π, R R R 2π I ( ) 0 ( k) Von Mises p.d.f. for non-isotropic environments and: f π π β βs = cos, βs βs π / 2. 4 β S,max 2 β S,max S ( ),max Parson s p.d.f. for scatterer s elevation angle 15
16 The Space-Time Correlation function of the NLOS component can be written as: a + β 4 S,max ( ) ( ) ( ) NLOS 1 1 ae 3 a5 sin βs 2 2 pl, qm δt δr τ = 3βS βs K K I k pl + 1 qm R,, cos a e I a a d, K K I k β where ( ) S,max 2πδ Δ sinθ 2π T T a = j 2 πτ f sin γ j 2 πτ f Δ sin γ + j + j δ cos ψ cos β sin θ + k sin μ, 1 R,max R T,max T R S R λcos β λ 2 a = j2πτ f cos γ + j π δ cosψ cos β cosθ + kcos μ, 2 R,max R R S R λ a = π /2 β, 3 S,max HAP 2πδ cosθ T T a = j j 2 πτ f cos γ, 4 T,max T λcos βhap 2π a = j sin. 5 δ R ψ λ 16
17 In HAP-MISO channels, assuming isotropic scattering, the Spatial Correlation Function is the following: 1 1 R e K K I a { ( )} a4 ( δ ) = + ( Δ θ ) tan. MISO pl, qm T pl qm 0 4 T Kpl + 1 Kqm + 1 In HAP-SIMO channels, assuming isotropic scattering, the Spatial Correlation Function is the following: a5 cosθr + βs,max 1 1 SIMO tanψ cos β a HAP 3 a5 sin β a S 5 Rpl, pm ( δr ) = Kpl Kqme + cos( a3βs ) e I0 cos βs dβs. Kpl + 1 Kqm tanψ β S,max 17
18 60 Kψ0 μo o T θ90 kβ60 β45 R D MAX o R S HAP OO OT, Spatially Correlated 3-D HAP-MIMO Fading Channels Examined Scenario 18
19 Spatial Correlation of a HAP-MISO channel versus normalized antenna element spacing for different amount of local scattering at the TMS k=2 Corre elation k=1 k= k= δ /λ T 19
20 Spatial Correlation of a HAP-SIMO channel for different scatterers' maximum elevation angle values 1 Co orrelation ψ=0 β S,max =π/4 ψ=π/2 β S,max =π/4 ψ=π/2 β S,max =π/9 ψ=π/2 β S,max =π/ δ /λ R 20
21 Spatial Correlation of a 2x2 HAP-MIMO channel with horizontally placed TMS antennas Cor rrelation δ R /λ R δ /λ Τ
22 Spatial Correlation of a 2x2 HAP-MIMO channel with vertically placed TMS antennas Corr rrelation δ R /λ δ T /λ
23 The geometrical model can be used to estimate the required HAP inter-element distance to achieve an uncorrelated HAP-MIMO channel matrix. At 2 GHz, considering an isotropic scattering environment, the SBS antennas require a separation of around 12 meters. MIMO techniques are applicable in a single HAP in a single HAP 23
24 Spatial correlation increases as the scattering becomes more non-isotropic. For a HAP-SIMO channel When TMS antennas are vertically placed, as scatterer s maximum elevation angle increases, the correlations between the two sub-channels reduce dramatically. When TMS antennas are horizontally placed, their correlation is always significantly small. Low correlations can be obtained in a 2 2 system, if we arrange the SBS and TMS antenna element spacing, such that their correlation falls in the valleys of the plots. 24
25
Lecture 6: Modeling of MIMO Channels Theoretical Foundations of Wireless Communications 1. Overview. CommTh/EES/KTH
: Theoretical Foundations of Wireless Communications 1 Wednesday, May 11, 2016 9:00-12:00, Conference Room SIP 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication 1 / 1 Overview
More informationMobile Radio Communications
Course 3: Radio wave propagation Session 3, page 1 Propagation mechanisms free space propagation reflection diffraction scattering LARGE SCALE: average attenuation SMALL SCALE: short-term variations in
More informationLecture 6: Modeling of MIMO Channels Theoretical Foundations of Wireless Communications 1
Fading : Theoretical Foundations of Wireless Communications 1 Thursday, May 3, 2018 9:30-12:00, Conference Room SIP 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication 1 / 23 Overview
More informationECE6604 PERSONAL & MOBILE COMMUNICATIONS. Week 4. Envelope Correlation Space-time Correlation
ECE6604 PERSONAL & MOBILE COMMUNICATIONS Week 4 Envelope Correlation Space-time Correlation 1 Autocorrelation of a Bandpass Random Process Consider again the received band-pass random process r(t) = g
More informationECE6604 PERSONAL & MOBILE COMMUNICATIONS. Week 3. Flat Fading Channels Envelope Distribution Autocorrelation of a Random Process
1 ECE6604 PERSONAL & MOBILE COMMUNICATIONS Week 3 Flat Fading Channels Envelope Distribution Autocorrelation of a Random Process 2 Multipath-Fading Mechanism local scatterers mobile subscriber base station
More informationLecture 2. Fading Channel
1 Lecture 2. Fading Channel Characteristics of Fading Channels Modeling of Fading Channels Discrete-time Input/Output Model 2 Radio Propagation in Free Space Speed: c = 299,792,458 m/s Isotropic Received
More informationMultiple Antennas. Mats Bengtsson, Björn Ottersten. Channel characterization and modeling 1 September 8, Signal KTH Research Focus
Multiple Antennas Channel Characterization and Modeling Mats Bengtsson, Björn Ottersten Channel characterization and modeling 1 September 8, 2005 Signal Processing @ KTH Research Focus Channel modeling
More informationLecture 7: Wireless Channels and Diversity Advanced Digital Communications (EQ2410) 1
Wireless : Wireless Advanced Digital Communications (EQ2410) 1 Thursday, Feb. 11, 2016 10:00-12:00, B24 1 Textbook: U. Madhow, Fundamentals of Digital Communications, 2008 1 / 15 Wireless Lecture 1-6 Equalization
More informationIII. Spherical Waves and Radiation
III. Spherical Waves and Radiation Antennas radiate spherical waves into free space Receiving antennas, reciprocity, path gain and path loss Noise as a limit to reception Ray model for antennas above a
More informationOn the Utility of the Circular Ring Model for Wideband MIMO Channels
On the Utility of the Circular ing Model for Wideband MIMO Channels Zoran Latinovic, Ali Abdi and Yeheskel Bar-Ness Center for Communication and Signal Processing esearch, Dept. of Elec. and Comp. Eng.
More informationCS6956: Wireless and Mobile Networks Lecture Notes: 2/4/2015
CS6956: Wireless and Mobile Networks Lecture Notes: 2/4/2015 [Most of the material for this lecture has been taken from the Wireless Communications & Networks book by Stallings (2 nd edition).] Effective
More informationXI. Influence of Terrain and Vegetation
XI. Influence of Terrain and Vegetation Terrain Diffraction over bare, wedge shaped hills Diffraction of wedge shaped hills with houses Diffraction over rounded hills with houses Vegetation Effective propagation
More informationPROPAGATION PARAMETER ESTIMATION IN MIMO SYSTEMS USING MIXTURE OF ANGULAR DISTRIBUTIONS MODEL
PROPAGATION PARAMETER ESTIMATION IN MIMO SYSTEMS USING MIXTURE OF ANGULAR DISTRIBUTIONS MODEL Cássio B. Ribeiro, Esa Ollila and Visa Koivunen Signal Processing Laboratory, SMARAD CoE Helsinki University
More informationFading Statistical description of the wireless channel
Channel Modelling ETIM10 Lecture no: 3 Fading Statistical description of the wireless channel Fredrik Tufvesson Department of Electrical and Information Technology Lund University, Sweden Fredrik.Tufvesson@eit.lth.se
More informationCommunication Systems Lecture 21, 22. Dong In Kim School of Information & Comm. Eng. Sungkyunkwan University
Communication Systems Lecture 1, Dong In Kim School of Information & Comm. Eng. Sungkyunkwan University 1 Outline Linear Systems with WSS Inputs Noise White noise, Gaussian noise, White Gaussian noise
More informationEE401: Advanced Communication Theory
EE401: Advanced Communication Theory Professor A. Manikas Chair of Communications and Array Processing Imperial College London Multi-Antenna Wireless Communications Part-B: SIMO, MISO and MIMO Prof. A.
More informationOptimum Transmission Scheme for a MISO Wireless System with Partial Channel Knowledge and Infinite K factor
Optimum Transmission Scheme for a MISO Wireless System with Partial Channel Knowledge and Infinite K factor Mai Vu, Arogyaswami Paulraj Information Systems Laboratory, Department of Electrical Engineering
More informationESTIMATION OF VELOCITY IN UNDERWATER WIRELESS CHANNELS
ESTIMATION OF VELOCITY IN UNDERWATER WIRELESS CHANNELS A Thesis Presented to The Academic Faculty by Bryan S. Blankenagel In Partial Fulfillment of the Requirements for the Degree Master of Science in
More informationOn the MIMO Channel Capacity Predicted by Kronecker and Müller Models
1 On the MIMO Channel Capacity Predicted by Kronecker and Müller Models Müge Karaman Çolakoğlu and Mehmet Şafak Abstract This paper presents a comparison between the outage capacity of MIMO channels predicted
More informationEFFECT OF STEERING ERROR VECTOR AND AN- GULAR POWER DISTRIBUTIONS ON BEAMFORMING AND TRANSMIT DIVERSITY SYSTEMS IN CORRE- LATED FADING CHANNEL
Progress In Electromagnetics Research, Vol. 105, 383 40, 010 EFFECT OF STEERING ERROR VECTOR AND AN- GULAR POWER DISTRIBUTIONS ON BEAMFORMING AND TRANSMIT DIVERSITY SYSTEMS IN CORRE- LATED FADING CHANNEL
More informationWireless Communications
NETW701 Wireless Communications Dr. Wassim Alexan Winter 2018 Lecture 2 NETW705 Mobile Communication Networks Dr. Wassim Alexan Winter 2018 Lecture 2 Wassim Alexan 2 Reflection When a radio wave propagating
More informationA Wideband Space-Time MIMO Channel Simulator Based on the Geometrical One-Ring Model
A Wideband Space-Time MIMO Channel Simulator Based on the Geometrical One-Ring Model Matthias Pätzold and Bjørn Olav Hogstad Faculty of Engineering and Science Agder University College 4898 Grimstad, Norway
More informationEnvelope PDF in Multipath Fading Channels with Random Number of Paths and Nonuniform Phase Distributions
Envelope PDF in Multipath Fading Channels with andom umber of Paths and onuniform Phase Distributions ALI ABDI AD MOSTAFA KAVEH DEPT. OF ELEC. AD COMP. EG., UIVESITY OF MIESOTA 4-74 EE/CSCI BLDG., UIO
More informationDesign and Simulation of Narrowband Indoor Radio Propagation Channels Under LOS and NLOS Propagation Conditions
Design and Simulation of arrowband Indoor Radio Propagation Channels Under LOS and LOS Propagation Conditions Yuanyuan Ma and Matthias Pätzold University of Agder Servicebox 59, O-4898, Grimstad, orway
More informationAerial Anchors Positioning for Reliable RSS-Based Outdoor Localization in Urban Environments
1 Aerial Anchors Positioning for Reliable RSS-Based Outdoor Localization in Urban Environments Hazem Sallouha, Mohammad Mahdi Azari, Alessandro Chiumento, Sofie Pollin arxiv:1711.06014v2 [cs.ni] 5 Dec
More informationBROADBAND MIMO SONAR SYSTEM: A THEORETICAL AND EXPERIMENTAL APPROACH
BROADBAND MIMO SONAR SYSTM: A THORTICAL AND XPRIMNTAL APPROACH Yan Pailhas a, Yvan Petillot a, Chris Capus a, Keith Brown a a Oceans Systems Lab., School of PS, Heriot Watt University, dinburgh, Scotland,
More informationModeling of Multiple-Input Multiple-Output Radio Propagation Channels
Modeling of Multiple-Input Multiple-Output Radio Propagation Channels Kai Yu TRITA S3 SB-0235 ISSN 1103-8039 ISRN KTH/SB/R - - 02/35 - - SE Signal Processing Department of Signals, Sensors and Systems
More informationPerfect Modeling and Simulation of Measured Spatio-Temporal Wireless Channels
Perfect Modeling and Simulation of Measured Spatio-Temporal Wireless Channels Matthias Pätzold Agder University College Faculty of Engineering and Science N-4876 Grimstad, Norway matthiaspaetzold@hiano
More informationELG7177: MIMO Comunications. Lecture 3
ELG7177: MIMO Comunications Lecture 3 Dr. Sergey Loyka EECS, University of Ottawa S. Loyka Lecture 3, ELG7177: MIMO Comunications 1 / 29 SIMO: Rx antenna array + beamforming single Tx antenna multiple
More informationA VECTOR CHANNEL MODEL WITH STOCHASTIC FADING SIMULATION
A VECTOR CHANNEL MODEL WITH STOCHASTIC FADING SIMULATION Jens Jelitto, Matthias Stege, Michael Löhning, Marcus Bronzel, Gerhard Fettweis Mobile Communications Systems Chair, Dresden University of Technology
More informationThe Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and its Implications
Technical Report 07 The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and its Implications Vutha Va Junil Choi Robert W. Heath Jr. Wireless Networking and Communications Group
More informationDouble-Directional Estimation for MIMO Channels
Master Thesis Double-Directional Estimation for MIMO Channels Vincent Chareyre July 2002 IR-SB-EX-0214 Abstract Space-time processing based on antenna arrays is considered to significantly enhance the
More informationRanging detection algorithm for indoor UWB channels
Ranging detection algorithm for indoor UWB channels Choi Look LAW and Chi XU Positioning and Wireless Technology Centre Nanyang Technological University 1. Measurement Campaign Objectives Obtain a database
More informationLecture 5: Antenna Diversity and MIMO Capacity Theoretical Foundations of Wireless Communications 1. Overview. CommTh/EES/KTH
: Antenna Diversity and Theoretical Foundations of Wireless Communications Wednesday, May 4, 206 9:00-2:00, Conference Room SIP Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication
More informationAPPENDIX 1 NEYMAN PEARSON CRITERIA
54 APPENDIX NEYMAN PEARSON CRITERIA The design approaches for detectors directly follow the theory of hypothesis testing. The primary approaches to hypothesis testing problem are the classical approach
More informationTight Lower Bounds on the Ergodic Capacity of Rayleigh Fading MIMO Channels
Tight Lower Bounds on the Ergodic Capacity of Rayleigh Fading MIMO Channels Özgür Oyman ), Rohit U. Nabar ), Helmut Bölcskei 2), and Arogyaswami J. Paulraj ) ) Information Systems Laboratory, Stanford
More informationThe Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and its Implications
The Impact of Beamwidth on Temporal Channel Variation in Vehicular Channels and its Implications arxiv:5.0937v [cs.it] 9 Nov 05 Vutha Va, Junil Choi, and Robert W. Heath Jr. Abstract Millimeter wave (mmwave)
More informationRate-Optimum Beamforming Transmission in MIMO Rician Fading Channels
Rate-Optimum Beamforming Transmission in MIMO Rician Fading Channels Dimitrios E. Kontaxis National and Kapodistrian University of Athens Department of Informatics and telecommunications Abstract In this
More informationEffective Rate Analysis of MISO Systems over α-µ Fading Channels
Effective Rate Analysis of MISO Systems over α-µ Fading Channels Jiayi Zhang 1,2, Linglong Dai 1, Zhaocheng Wang 1 Derrick Wing Kwan Ng 2,3 and Wolfgang H. Gerstacker 2 1 Tsinghua National Laboratory for
More informationA. Dong, N. Garcia, A.M. Haimovich
A. Dong, N. Garcia, A.M. Haimovich 2 Goal: Localization (geolocation) of unknown RF emitters in multipath environments Challenges: Conventional methods such as TDOA based on line-of-sight (LOS) Non-line-of-sight
More informationOn capacity of multi-antenna wireless channels: Effects of antenna separation and spatial correlation
3rd AusCTW, Canberra, Australia, Feb. 4 5, 22 On capacity of multi-antenna wireless channels: Effects of antenna separation and spatial correlation Thushara D. Abhayapala 1, Rodney A. Kennedy, and Jaunty
More informationA Single-bounce Channel Model for Dense Urban Street Microcell
URSI-F JAPAN MEETING NO. 52 1 A Single-bounce Channel Model for Dense Urban Street Microcell Mir Ghoraishi Jun-ichi Takada Tetsuro Imai Department of International Development Engineering R&D Center Tokyo
More informationA MIMO MOBILE-TO-MOBILE CHANNEL MODEL: PART I THE REFERENCE MODEL
A MIMO MOBILE-O-MOBILE CHANNEL MODEL: PA I HE EFEENCE MODEL Matthias Pätzold 1, Bjørn Olav Hogstad 1, Neji Youssef 2, and Dongwoo Kim 3 1 Faculty of Engineering and Science, Agder University College Grooseveien
More informationParametric Characterization and Estimation of Dispersive Multi-Path Components with SAGE in Radio Propagation Channel
Parametric Characterization and Estimation of Dispersive Multi-Path Components with SAGE in Radio Propagation Channel SIGNAL AND INFORMATION PROCESSING IN COMMUNICATIONS SYSTEMS DEPARTMENT OF COMMUNICATION
More informationA GENERALISED (M, N R ) MIMO RAYLEIGH CHANNEL MODEL FOR NON- ISOTROPIC SCATTERER DISTRIBUTIONS
A GENERALISED (M, N R MIMO RAYLEIGH CHANNEL MODEL FOR NON- ISOTROPIC SCATTERER DISTRIBUTIONS David B. Smith (1, Thushara D. Abhayapala (2, Tim Aubrey (3 (1 Faculty of Engineering (ICT Group, University
More informationEffect of Multipath Propagation on the Noise Performance of Zero Crossing Digital Phase Locked Loop
International Journal of Electronics and Communication Engineering. ISSN 0974-2166 Volume 9, Number 2 (2016), pp. 97-104 International Research Publication House http://www.irphouse.com Effect of Multipath
More informationOutline. 1 Path-Loss, Large-Scale-Fading, Small-Scale Fading. 2 Simplified Models. 3 Multipath Fading Channel
Outline Digital Communiations Leture 11 Wireless Channels Pierluigi SALVO OSSI Department of Industrial and Information Engineering Seond University of Naples Via oma 29, 81031 Aversa CE), Italy homepage:
More informationOn the estimation of the K parameter for the Rice fading distribution
On the estimation of the K parameter for the Rice fading distribution Ali Abdi, Student Member, IEEE, Cihan Tepedelenlioglu, Student Member, IEEE, Mostafa Kaveh, Fellow, IEEE, and Georgios Giannakis, Fellow,
More informationCooperative MIMO Channel Modeling and Multi-Link Spatial Correlation Properties
Cooperative MIMO Channel Modeling and Multi-Link Spatial Correlation Properties Xiang Cheng, Cheng-Xiang Wang 2, Haiming Wang 3, Xiqi Gao 3, Xiao-Hu You 3, Dongfeng Yuan 4, Bo Ai 5, Qiang Huo, Ling-Yang
More informationMATHEMATICAL TOOLS FOR DIGITAL TRANSMISSION ANALYSIS
ch03.qxd 1/9/03 09:14 AM Page 35 CHAPTER 3 MATHEMATICAL TOOLS FOR DIGITAL TRANSMISSION ANALYSIS 3.1 INTRODUCTION The study of digital wireless transmission is in large measure the study of (a) the conversion
More informationComparison of DPSK and MSK bit error rates for K and Rayleigh-lognormal fading distributions
Comparison of DPSK and MSK bit error rates for K and Rayleigh-lognormal fading distributions Ali Abdi and Mostafa Kaveh ABSTRACT The composite Rayleigh-lognormal distribution is mathematically intractable
More informationTHE number of MIMO channel models available in the
IEEE TANSACTIONS ON WIELESS COMMUNICATIONS, VOL. 6, NO. 8, AUGUST 7 759 An Extended One-ing MIMO Channel Model Min Zhang, Peter J. Smith, and Mansoor Shafi Abstract In this paper we develop a Multiple
More informationComparisons of Performance of Various Transmission Schemes of MIMO System Operating under Rician Channel Conditions
Comparisons of Performance of Various ransmission Schemes of MIMO System Operating under ician Channel Conditions Peerapong Uthansakul and Marek E. Bialkowski School of Information echnology and Electrical
More informationMultiple-Input Multiple-Output Systems
Multiple-Input Multiple-Output Systems What is the best way to use antenna arrays? MIMO! This is a totally new approach ( paradigm ) to wireless communications, which has been discovered in 95-96. Performance
More informationA Non-Stationary Mobile-to-Mobile Channel Model Allowing for Velocity and Trajectory Variations of the Mobile Stations
1 A Non-Stationary Mobile-to-Mobile Channel Model Allowing for Velocity and rajectory Variations of the Mobile Stations Wiem Dahech, Matthias Pätzold, Carlos A. Gutiérrez, and Néji Youssef Abstract In
More informationSEAFLOOR MAPPING MODELLING UNDERWATER PROPAGATION RAY ACOUSTICS
3 Underwater propagation 3. Ray acoustics 3.. Relevant mathematics We first consider a plane wave as depicted in figure. As shown in the figure wave fronts are planes. The arrow perpendicular to the wave
More informationPower and Complex Envelope Correlation for Modeling Measured Indoor MIMO Channels: A Beamforming Evaluation
Power and Complex Envelope Correlation for Modeling Measured Indoor MIMO Channels: A Beamforming Evaluation Jon Wallace, Hüseyin Özcelik, Markus Herdin, Ernst Bonek, and Michael Jensen Department of Electrical
More informationModeling Environmental Effects on Directionality in Wireless Networks
Modeling Environmental Effects on Directionality in Wireless Networks Eric Anderson, Caleb Phillips, Douglas Sicker, and Dirk Grunwald eric.anderson@colorado.edu University of Colorado Department of Computer
More informationOn Limits of Multi-Antenna. Wireless Communications in. Spatially Selective Channels
On Limits of Multi-Antenna Wireless Communications in Spatially Selective Channels Tony Steven Pollock B.E.(Hons 1) (Canterbury) B.Sc. (Otago) July 2003 A thesis submitted for the degree of Doctor of Philosophy
More informationImplementation of a Space-Time-Channel-Filter
Implementation of a Space-Time-Channel-Filter Nadja Lohse, Clemens Michalke, Marcus Bronzel and Gerhard Fettweis Dresden University of Technology Mannesmann Mobilfunk Chair for Mobile Communications Systems
More informationDigital Band-pass Modulation PROF. MICHAEL TSAI 2011/11/10
Digital Band-pass Modulation PROF. MICHAEL TSAI 211/11/1 Band-pass Signal Representation a t g t General form: 2πf c t + φ t g t = a t cos 2πf c t + φ t Envelope Phase Envelope is always non-negative,
More informationSIGNALS OF OPPORTUNITY IN MOBILE RADIO POSITIONING. Armin Dammann, Stephan Sand and Ronald Raulefs
20th European Signal Processing Conference (EUSIPCO 2012) Bucharest, Romania, August 27-31, 2012 SIGNALS OF OPPORTUNITY IN MOBILE RADIO POSITIONING Armin Dammann, Stephan Sand and Ronald Raulefs Institute
More informationSolution to Homework 1
Solution to Homework 1 1. Exercise 2.4 in Tse and Viswanath. 1. a) With the given information we can comopute the Doppler shift of the first and second path f 1 fv c cos θ 1, f 2 fv c cos θ 2 as well as
More information10. Scattering from Central Force Potential
University of Rhode Island DigitalCommons@URI Classical Dynamics Physics Course Materials 215 1. Scattering from Central Force Potential Gerhard Müller University of Rhode Island, gmuller@uri.edu Creative
More informationDiversity Combining Techniques
Diversity Combining Techniques When the required signal is a combination of several plane waves (multipath), the total signal amplitude may experience deep fades (Rayleigh fading), over time or space.
More informationDOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Uniform Linear Array with Fewer Sensors than Sources
Progress In Electromagnetics Research M, Vol. 63, 185 193, 218 DOA Estimation of Quasi-Stationary Signals Using a Partly-Calibrated Uniform Linear Array with Fewer Sensors than Sources Kai-Chieh Hsu and
More informationSpatial Array Processing
Spatial Array Processing Signal and Image Processing Seminar Murat Torlak Telecommunications & Information Sys Eng The University of Texas at Austin, Introduction A sensor array is a group of sensors located
More informationSTATISTICAL MODELING OF ASYNCHRONOUS IMPULSIVE NOISE IN POWERLINE COMMUNICATION NETWORKS
STATISTICAL MODELING OF ASYNCHRONOUS IMPULSIVE NOISE IN POWERLINE COMMUNICATION NETWORKS Marcel Nassar, Kapil Gulati, Yousof Mortazavi, and Brian L. Evans Department of Electrical and Computer Engineering
More informationMutual Coupling Effect on Thermal Noise in Multi-Element Antenna Systems
Progress In Electromagnetics Research Symposium 2005, Hangzhou, China, August 22-26 53 Mutual Coupling Effect on Thermal Noise in Multi-Element Antenna Systems Snezana Krusevac 1, Predrag B. Rapajic 1,
More informationAn Efficient Approach to Multivariate Nakagami-m Distribution Using Green s Matrix Approximation
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL 2, NO 5, SEPTEMBER 2003 883 An Efficient Approach to Multivariate Nakagami-m Distribution Using Green s Matrix Approximation George K Karagiannidis, Member,
More informationOn the Multivariate Nakagami-m Distribution With Exponential Correlation
1240 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 51, NO. 8, AUGUST 2003 On the Multivariate Nakagami-m Distribution With Exponential Correlation George K. Karagiannidis, Member, IEEE, Dimitris A. Zogas,
More informationSignals and Systems. Lecture 11 Wednesday 22 nd November 2017 DR TANIA STATHAKI
Signals and Systems Lecture 11 Wednesday 22 nd November 2017 DR TANIA STATHAKI READER (ASSOCIATE PROFFESOR) IN SIGNAL PROCESSING IMPERIAL COLLEGE LONDON Effect on poles and zeros on frequency response
More informationTen years analysis of Tropospheric refractivity variations
ANNALS OF GEOPHYSICS, VOL. 47, N. 4, August 2004 Ten years analysis of Tropospheric refractivity variations Stergios A. Isaakidis and Thomas D. Xenos Department of Electrical and Computer Engineering,
More informationOn the Capacity and Simulation of 3-D MIMO Mobile-to-Mobile Relay Fading Channels
200 I 2st International yposiu on Personal Indoor and Mobile adio Counications On the Capacity and iulation of 3- MIMO Mobile-to-Mobile elay Fading Channels anouel T. Michailidis Panagiotis Theofilakos
More informationTropospheric Effects on GNSS
Tropospheric Effects on GNSS The Atmosphere and its Effect on GNSS Systems 14 to 16 April 008 Santiago, Chile Dr. M. Bakry El-Arini Background 1 of The troposphere contains about 80% of the atmosphere
More informationMassive MIMO Channel Modeling
Massive MIMO Channel Modeling Xin You carolineyou@sina.com Yongchun Wang w yongchun@sina.com Department of Electrical and Information Technology Lund University Advisor: Xiang Gao, Ove Edfors December,
More informationSimulations and Observations of GNSS Ocean Surface Reflections
Simulations and Observations of GNSS Ocean Surface Reflections Per Høeg Hans-Henrik von Benzon Ocean Surface Reflections Figure of the geometry of ocean reflections The presented simulations involve ocean
More informationBeam Based Stochastic Model of the Coverage Probability in 5G Millimeter Wave Systems
Beam Based Stochastic Model of the Coverage Probability in 5G Millimeter Wave Systems Cristian Tatino, Ilaria Malanchini, Danish Aziz, Di Yuan Department of Science and Technology, Linköping University,
More informationResearch Article Geometry-Based Stochastic Modeling for MIMO Channel in High-Speed Mobile Scenario
Antennas and Propagation Volume 202, Article ID 84682, 6 pages doi:0.55/202/84682 Research Article Geometry-Based Stochastic Modeling for MIMO Channel in High-Speed Mobile Scenario Binghao Chen and Zhangdui
More informationA TIME-VARYING MIMO CHANNEL MODEL: THEORY AND MEASUREMENTS
A TIME-VARYING MIMO CHANNEL MODEL: THEORY AND MEASUREMENTS Shuangquan Wang, Ali Abdi New Jersey Institute of Technology Dept. of Electr. & Comput. Eng. University Heights, Newark, NJ 7 Jari Salo, Hassan
More informationASPECTS OF FAVORABLE PROPAGATION IN MASSIVE MIMO Hien Quoc Ngo, Erik G. Larsson, Thomas L. Marzetta
ASPECTS OF FAVORABLE PROPAGATION IN MASSIVE MIMO ien Quoc Ngo, Eri G. Larsson, Thomas L. Marzetta Department of Electrical Engineering (ISY), Linöping University, 58 83 Linöping, Sweden Bell Laboratories,
More informationA DIFFUSION MODEL FOR UWB INDOOR PROPAGATION. Majid A. Nemati and Robert A. Scholtz. University of Southern California Los Angeles, CA
A DIFFUION MODEL FOR UWB INDOOR PROPAGATION Majid A. Nemati and Robert A. choltz nematian@usc.edu scholtz@usc.edu University of outhern California Los Angeles, CA ABTRACT This paper proposes a diffusion
More informationMassive MIMO: Signal Structure, Efficient Processing, and Open Problems II
Massive MIMO: Signal Structure, Efficient Processing, and Open Problems II Mahdi Barzegar Communications and Information Theory Group (CommIT) Technische Universität Berlin Heisenberg Communications and
More informationLecture 8: MIMO Architectures (II) Theoretical Foundations of Wireless Communications 1. Overview. Ragnar Thobaben CommTh/EES/KTH
MIMO : MIMO Theoretical Foundations of Wireless Communications 1 Wednesday, May 25, 2016 09:15-12:00, SIP 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication 1 / 20 Overview MIMO
More informationChapter 2 Propagation Modeling
Chapter 2 Propagation Modeling The design of spectrally efficient wireless communication systems requires a thorough understanding of the radio propagation channel. The characteristics of the radio channel
More informationOn Coding for Orthogonal Frequency Division Multiplexing Systems
On Coding for Orthogonal Frequency Division Multiplexing Systems Alan Clark Department of Electrical and Computer Engineering A thesis presented for the degree of Doctor of Philosophy University of Canterbury
More informationObserver-Sun Angles. ), Solar altitude angle (α s. ) and solar azimuth angle (γ s )). θ z. = 90 o α s
Observer-Sun Angles Direction of Beam Radiation: The geometric relationships between a plane of any particular orientation relative to the earth at any time and the incoming beam solar radiation can be
More information[EN-028] On the use of MIMO in aeronautical communications
ENRI Int. Workshop on ATM/CNS. Tokyo, Japan (EIWAC010) [EN-08] On the use of MIMO in aeronautical communications + B. Holter J. E. Håkegård T. A. Myrvoll Department of Communication Systems SINTEF ICT
More informationSami Alhumaidi, Ph.D. Prince Sultan Advanced Technology Institute King Saud University Radar Symposium, Riyadh December 9, 2014
Anomalous Wave Propagation and its Adverse Effects on Military Operations Sami Alhumaidi, Ph.D. Prince Sultan Advanced Technology Institute King Saud University Radar Symposium, Riyadh December 9, 2014
More informationCHARACTERIZATION AND ANALYSIS OF DOUBLY DISPERSIVE MIMO CHANNELS. Gerald Matz
CHARACTERIZATION AND ANALYSIS OF DOUBLY DISPERSIVE MIMO CHANNELS Gerald Matz Institute of Communications and Radio-Frequency Engineering, Vienna University of Technology Gusshausstrasse 2/389, A-14 Vienna,
More informationStatistical Modeling of Co-Channel Interference
Statistical Modeling of Co-Channel Interference Kapil Gulati, Aditya Chopra, Brian L. Evans and Keith R. Tinsley The University of Texas at Austin, Austin, Texas 7871 Email: gulati,chopra,bevans}@ece.utexas.edu
More informationFree Space Optical (FSO) Communications. Towards the Speeds of Wireline Networks
Free Space Optical (FSO) Communications Towards the Speeds of Wireline Networks FSO Basic Principle Connects using narrow beams two optical wireless transceivers in line-of-sight. Light is transmitted
More informationFree-body diagrams. a. Find the acceleration of mass 2. b. Determine the magnitude of the tension in the string.
Free-body diagrams 1. wo blocks of masses m1 = 5.0 kg and m =.0 kg hang on both sides of an incline, connected through an ideal, massless string that goes through an ideal, massless pulley, as shown below.
More informationIf light travels past a system faster than the time scale for which the system evolves then t I ν = 0 and we have then
6 LECTURE 2 Equation of Radiative Transfer Condition that I ν is constant along rays means that di ν /dt = 0 = t I ν + ck I ν, (29) where ck = di ν /ds is the ray-path derivative. This is equation is the
More informationCopyright license. Exchanging Information with the Stars. The goal. Some challenges
Copyright license Exchanging Information with the Stars David G Messerschmitt Department of Electrical Engineering and Computer Sciences University of California at Berkeley messer@eecs.berkeley.edu Talk
More information1. Propagation Mechanisms
Contents: 1. Propagation Mechanisms The main propagation mechanisms Point sources in free-space Complex representation of waves Polarization Electric field pattern Antenna characteristics Free-space propagation
More informationAperture Antennas 1 Introduction
1 Introduction Very often, we have antennas in aperture forms, for example, the antennas shown below: Pyramidal horn antenna Conical horn antenna 1 Paraboloidal antenna Slot antenna Analysis Method for.1
More information12.4 Known Channel (Water-Filling Solution)
ECEn 665: Antennas and Propagation for Wireless Communications 54 2.4 Known Channel (Water-Filling Solution) The channel scenarios we have looed at above represent special cases for which the capacity
More informationCommunications and Signal Processing Spring 2017 MSE Exam
Communications and Signal Processing Spring 2017 MSE Exam Please obtain your Test ID from the following table. You must write your Test ID and name on each of the pages of this exam. A page with missing
More informationMaximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary. Spatial Correlation
Maximum Achievable Diversity for MIMO-OFDM Systems with Arbitrary Spatial Correlation Ahmed K Sadek, Weifeng Su, and K J Ray Liu Department of Electrical and Computer Engineering, and Institute for Systems
More information