Advanced Signal Processing in Communications
|
|
- Daisy Shaw
- 6 years ago
- Views:
Transcription
1 Avance Signal Processing in Communications Lecture 2 Morten Jeppesen & Joachim Dahl {mje,ja}@cpk.auc.k DICOM, Aalborg University DICOM 2 p./26
2 Minimum Variance Estimation DICOM 2 p.2/26
3 Problem formulation Recall the linear moel: where is complex white Gaussian. It is critical that has full column rank. We wish to obtain the estimate of as the solution to without any restrictions or prior knowlege of This is a maximumlikelihoo problem. For the linear moel, this coincies with a leastsquares solution. We will follow the leastsquares approach.. DICOM 2 p.3/26
4 $ ' % ( Complex scalar an vector ifferentiation For complex scalar ifferentiation:, we efine complex Vectorifferentiation is efine as: #"!!! With these efinitions it is straightforwar to show that, ' +) &*) & % & % DICOM 2 p.4/26
5 +, + Leastsquares solution : We wish to fin the (global) minimum of, Applying the three rules from before, we get.,! +., + to / / is obtaine by equating The global minimizer zero: 3,2 + DICOM 2 p.5/26
6 ) ) % % ) ; : < < ) :; < EF D C 8, B + = : ) 6 G < +) ) The pseuoinverse Let be an arbitrary matrix with rank seen that only has a solution if If 8. We have., +), then the pseuoinverse (of imensions ) is efine as where the pseuoinverse, the LS solution is!!! 3 >? B!!! 3 >A@. In terms of < % If, +) then the pseuoinverse is given as! 3 ),2 ) DICOM 2 p.6/26
7 Applications to channel estimation DICOM 2 p.7/26
8 L Q PW QXW X B Z 6 Signal moel Recall the FIRfilter moel: I "N IJ"M IJ" IJ" The output of the filter is Q P 6 2Y P 6V R S T U Q P 6O where B Q P 6V Q P 6V for is the known transmitte signal (we assume ) an we wish to estimate. Q P 6 DICOM 2 p.8/26
9 e e a a iii M e e L M N L N a M iii N M iii & Reworke signal moel Put in matrixvector form, we have Ia Ia Ia I [ \^\^\^\^\\]\\^\^\^\\]\\`_ h ff]ff]fff]ff^f^f^ff`g Ia I Ib ff]ff^f^f`g I [ \\]\\^\^\`_ k ff]ff^f^f`g Ia I Ib [ \\]\\^\^\`_ L f^f^f^f^ff]ff^f^f^ff]ff`g [ \\]\\]\\\]\\^\^\^\\`_ Ia Ib Ib Ic Ic b Ic j Ic Ic. The optimum channel estimate is m l or & l, l m l + DICOM 2 p.9/26
10 t s q Example: Measure UMTS channel We have a measure impulse response: real part of channel imaginary part of channel We have npo an we choose rpo. The SNR is 2B. DICOM 2 p./26
11 u u u Importance of probing signal Below we see the powerspectrum of ( ) a binary pseuoranom sequence an ( ) a binary alternating sequence with istinct zeros: powerspectrum [B] ra powerspectrum [B] ra DICOM 2 p./26
12 The estimate impulse response real part of channel real part of channel imaginary part of channel imaginary part of channel (a) Pseuoranom probing signal (b) Alternating probing signal We see a clear avantage of using a pseuoranom probing signal. DICOM 2 p.2/26
13 Applications to econvolution DICOM 2 p.3/26
14 v L c " a e L a a iii iii iii L a e e e N M L iii N M a h a L N M iii L a iii a a iii iii iii Signal moel Again we consier the output of a FIR filter IJ"N k I{ L { IJ" h IJ"M wyx z is I ". Assuming that I " only now is assume known an we wish to estimate only nonzero for, we get IJ" Ia L Ia Ib L Ia I Ib [ \\^\^\^\\]\\\]\\]\\^\^\^\\]\\^\^\^\\]\\\]\`_ Ia Ia L f^f^f^ff]f`g I Ia I Ic [ \^\^\^\\]\`_ ff^f^f^ff]fff]ff]ff^f^f^ff]ff^f^f^ff]fff]f`g Ia I f^f^f^ff]f`g I [ \^\^\^\\]\`_ k f^f^f^ff]f`g [ \^\^\^\\]\`_ Ib L Ib L bk Ic bk Ic Ib L Ib L DICOM 2 p.4/26
15 } j } } } o r s Ÿ Š ˆ ž Zeroforcing equalizer As before the estimate of is &ƒ & ~ }o This is the optimal solution to ŠŒ Ž ˆ ~ }o i.e. without restrictions on owever, if c s s A suboptimal solution to this problem is. the problem is much harer to solve. &š & u o ~œ o This solutions is calle the Zeroforcing equalizer, as it forces the ISI to zero. The rawback is a egraation of the SNR. DICOM 2 p.5/26
16 s Ex: equalization of UMTS channel We use the measure UMTS channel for a burst of bits. We assume that the channel is perfectly known. r o 2 SNR=B 2 SNR=2B imaginary part imaginary part real part real part 2 SNR=3B 2 SNR=4B imaginary part imaginary part real part real part DICOM 2 p.6/26
17 Array application DICOM 2 p.7/26
18 Ê «ª Á Á ¹ Array application Recall the array moel from lecture Á À ÁAË AÀ Omniirectional antenna Linear array Equiistance: Plane waves wih incient angle: Æ Ç È É Å Ä ¹ J ¹ À ºÃ AÀ º ¾ Á AÀ¾ º»½¼ A ²³ ²³µ ± J «ª A Á AÀ Âà Á AÀ  ¾ Á AÀ¾ »½¼ DICOM 2 p.8/26
19 Array application We have 4 equal powere users with 4 istinct electrical angles We now want to use the ZF spatial equalizer to estimate the signals from the 4 users. DICOM 2 p.9/26
20 Array application The array manifol of the ZF exhibits nulls at interferers irrespective of the noise level > Nulling beamformer. 2 Array manifol for user 2 Array manifol for user 2 Power [B] 2 Power [B] Array manifol for user 3 2 Array manifol for user 4 Power [B] 2 Power [B] DICOM 2 p.2/26
21 Array application Scatterplots at SNR=5b (blue) an SNR=25B (re). 2 2 Quarature Quarature Inphase Inphase 2 2 Quarature Quarature Inphase Inphase DICOM 2 p.2/26
22 Extensions of moel to coloure noise DICOM 2 p.22/26
23 Ì = Î Ì Ñ Ñ PÎ Ò Ò Ñ Coloure noise In the linear moel ÍÌ we mae the important assumption that Gaussian noise, i.e. that is white, D Ï 3!!! +ÐÏ Q P Ì Ì If instea Q is coloure Gaussian with covariance for an arbitrary ermitian, we factor it as e.g. with a Cholesky factorization. DICOM 2 p.23/26
24 3 Ò Ó 3 Õ Î Ò PÎ Coloure noise We next transform the signal moel as Ô The covariance of the filtere noise is Q Ò P Ì Ì Q Thus the noise in the moifie signal moel is white, an the results from before now apply. It can be shown, that the LS solution for the moifie moel using a whitening transformation is still optimal. DICOM 2 p.24/26
25 Summary of lecture DICOM 2 p.25/26
26 Summary In this lecture we have seen: ow to obtain the LS solution to complex form. That this solution is optimal when in is analogous. ow it is relate to the pseuoinverse solution. ow to apply this solution to channel estimation. zeroforcing equalization. nulling beamforming. DICOM 2 p.26/26
First generation mobile communication systems (e.g. NMT and AMPS) are based on analog transmission techniques, whereas second generation systems
1 First generation mobile communication systems (e.g. NMT and AMPS) are based on analog transmission techniques, whereas second generation systems (e.g. GSM and D-AMPS) are digital. In digital systems,
More informationTHE SHOPS AT ROSSMOOR NWC St Cloud Drive & Seal Beach Blvd, Seal Beach, CA
THE SHOPS AT ROSSMOOR NWC St Cloud Drive & Seal Beach Blvd, Seal Beach, CA JOIN Restaurant ready space Endcap with great frontage and visibility 3,299 SF 120-208 volt, 3-phase, 4-wire, 600-amp, 3 gas line,
More informationData Flow 4.{1,2}, 3.2
< = = Computer Science Program, The University of Texas, Dallas Data Flow 4.{1,2}, 3.2 Batch Sequential Pipeline Systems Tektronix Case Study: Oscilloscope Formalization of Oscilloscope "systems where
More informationLinear time and frequency domain Turbo equalization
Linear time and frequency domain Turbo equalization Michael Tüchler, Joachim Hagenauer Lehrstuhl für Nachrichtentechnik TU München 80290 München, Germany micha,hag@lnt.ei.tum.de Abstract For coded data
More informationUplink and Downlink Beamforming for Fading Channels. Mats Bengtsson and Björn Ottersten
Uplink and Downlink Beamforming for Fading Channels Mats Bengtsson and Björn Ottersten 999-02-7 In Proceedings of 2nd IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications,
More informationAwareness in Games, Awareness in Logic
Awareness in Games, Awareness in Logic Joseph Halpern Leandro Rêgo Cornell University Awareness in Games, Awareness in Logic p 1/37 Game Theory Standard game theory models assume that the structure of
More informationMULTIPLE antenna systems have attracted considerable attention in the communication community
A Generalized Probabilistic Data Association 1 Detector for Multiple Antenna Systems D. Pham, K.R. Pattipati, P. K. Willett Abstract The Probabilistic Data Association (PDA) method for multiuser detection
More informationAntennas 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 informationBand 10 Bandwidth and Noise Performance
Band 10 Bandwidth and Noise Performance A Preliminary Design Review of Band 10 was held recently. A question was raised which requires input from the Science side. Here is the key section of the report.
More informationA Neural Solution for Signal Detection In Non-Gaussian Noise
1 A Neural Solution for Signal Detection In Non-Gaussian Noise D G Khairnar, S N Merchant, U B Desai SPANN Laboratory Department of Electrical Engineering Indian Institute of Technology, Bombay, Mumbai-400
More informationSecond Year March 2017
Reg. No. :... Code No. 5023 Name :... Second Year March 2017 Time : 2 Hours Cool-off time : 15 Minutes Part III ELECTRONICS Maximum : 60 Scores General Instructions to Candidates : There is a cool-off
More informationFractionally Sampled Linear Detectors for DS-CDMA
Fractionally Sampled Linear Detectors for DS-CDMA DR Brown, DL Anair, and CR Johnson, Jr Cornell University Ithaca, NY 4853 Abstract In this paper we analyze the performance of fractionally chip sampled
More informationClosed-Loop Transmit Diversity for FDD WCDMA Systems
Closed-Loop Transmit Diversity for FDD WCDMA Systems Jyri ämäläinen Nokia Networks, PO Box 319 FN 9051 Oulu, Finl jyrikhamalainen@nokiacom Risto Wichman Nokia Research Center, PO Box 07 FN 0005 NOKA GROUP,
More informationIMPERIAL COLLEGE of SCIENCE, TECHNOLOGY and MEDICINE, DEPARTMENT of ELECTRICAL and ELECTRONIC ENGINEERING.
IMPERIAL COLLEGE of SCIENCE, TECHNOLOGY and MEDICINE, DEPARTMENT of ELECTRICAL and ELECTRONIC ENGINEERING. COMPACT LECTURE NOTES on COMMUNICATION THEORY. Prof. Athanassios Manikas, version Spring 22 Digital
More information&$121,1' $VUHFRUGHGE\'DQLHO+R
ä É ì Ê Ë î Ë Ë µ ö Ë µ ö Ò ¹ ú Ò º Ë º Ê º Ë ½ Õ Ö ½ Ö 4658769-:?@A>
More informationFigure 2. Another example from Teun Spaans Domino Plaza web site.
ISO/IEC JTC1/SC2/WG2 N2760 L2/04-163 2004-05-18 Universal Multiple-Octet Coded Character Set International Organization for Standardization Organisation internationale de normalisation еждународная организация
More informationVacuum Regulator IRV20 Series
! Contact our sales office for delivery dates and prices as this is a special model. Special option P.G.Information (Specialized Product) Vacuum egulator IV20 Series Special options usable for various
More informationMIMO Receiver Design in Impulsive Noise
COPYRIGHT c 007. ALL RIGHTS RESERVED. 1 MIMO Receiver Design in Impulsive Noise Aditya Chopra and Kapil Gulati Final Project Report Advanced Space Time Communications Prof. Robert Heath December 7 th,
More informationMIMO III: Channel Capacity, Interference Alignment
MIMO III: Channel Capacity, Interference Alignment COS 463: Wireless Networks Lecture 18 Kyle Jamieson [Parts adapted from D. Tse] Today 1. MIMO Channel Degrees of Freedom 2. MIMO Channel Capacity 3. Interference
More informationCounting Things. Tom Davis November 14, 2002
Counting Things Tom Davis tomrdavis@earthlink.net http://www.geometer.org/mathcircles November 14, 2002 Abstract We present here various strategies for counting things. Usually, the things are patterns,
More informationBasic Definitions and The Spectral Estimation Problem
Informal Definition of Spectral Estimation Given: A finite record of a signal Basic Definitions and The Spectral Estimation Problem Determine: The distribution of signal power over frequency signal t=1,
More informationTRANSMIT diversity has emerged in the last decade as an
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 3, NO. 5, SEPTEMBER 2004 1369 Performance of Alamouti Transmit Diversity Over Time-Varying Rayleigh-Fading Channels Antony Vielmon, Ye (Geoffrey) Li,
More informationIterative Detection and Channel Estimation for MC-CDMA
Iterative Detection and Estimation for MC-CDMA Thomas Zemen Siemens Austria, PSE PRO RCD Erdbergerlände 26 A-1031 Vienna, Austria E-mail: thomaszemen@siemenscom Joachim Wehinger, Christoph Mecklenbräuker
More informationBeamforming in Combination with Space-Time Diversity for Broadband OFDM Systems
Beamforming in Combination with Space-Time Diversity for Broadband OFDM Systems Armin Dammann, Ronald Raulefs and Stefan Kaiser German Aerospace Center (DLR), Institute of Communications and Navigation
More informationPerformance Evaluation of V-Blast Mimo System in Fading Diversity Using Matched Filter
Performance Evaluation of V-Blast Mimo System in Fading Diversity Using Matched Filter Priya Sharma 1, Prof. Vijay Prakash Singh 2 1 Deptt. of EC, B.E.R.I, BHOPAL 2 HOD, Deptt. of EC, B.E.R.I, BHOPAL Abstract--
More informationCHARACTERIZING IMAGE QUALITY: BLIND ESTIMATION OF THE POINT SPREAD FUNCTION FROM A SINGLE IMAGE
CHARACTERIZING IMAGE QUALITY: BLIND ESTIMATION OF THE POINT SPREAD FUNCTION FROM A SINGLE IMAGE Marc Luxen, Wolfgang Förstner Institute for Photogrammetry, University of Bonn, Germany luxen wf@ipb.uni-bonn.de
More informationPerformance Analysis of MUSIC and LMS Algorithms for Smart Antenna Systems
nternational Journal of Electronics Engineering, 2 (2), 200, pp. 27 275 Performance Analysis of USC and LS Algorithms for Smart Antenna Systems d. Bakhar, Vani R.. and P.V. unagund 2 Department of E and
More informationSpace-Time Block Coded Spatial Modulation Aided mmwave MIMO with Hybrid Precoding
Space-Time Block Coded Spatial Modulation Aided mmwave MIMO with Hybrid Precoding Taissir Y. Elganimi and Ali A. Elghariani Electrical and Electronic Engineering Department, University of Tripoli Tripoli,
More informationOptimal Power Allocation over Fading Channels with Stringent Delay Constraints
1 Optimal Power Allocation over Fading Channels with Stringent Delay Constraints Xiangheng Liu Andrea Goldsmith Dept. of Electrical Engineering, Stanford University Email: liuxh,andrea@wsl.stanford.edu
More informationReuse within a cell interference rejection or multiuser detection?
Reuse within a cell interference rejection or multiuser detection? CLAES TIDESTAV, MIKAEL STERNAD AND ANDERS AHLÉN MAY UPPSALA UNIVERSITY Signals and Systems Abstract We investigate the use of an antenna
More informationOn limits of Wireless Communications in a Fading Environment: a General Parameterization Quantifying Performance in Fading Channel
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol. 2, No. 3, September 2014, pp. 125~131 ISSN: 2089-3272 125 On limits of Wireless Communications in a Fading Environment: a General
More informationE7220: 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 informationRake-based multiuser detection for quasi-synchronous SDMA systems
Title Rake-bed multiuser detection for qui-synchronous SDMA systems Author(s) Ma, S; Zeng, Y; Ng, TS Citation Ieee Transactions On Communications, 2007, v. 55 n. 3, p. 394-397 Issued Date 2007 URL http://hdl.handle.net/10722/57442
More informationPrewhitening. 1. Make the ACF of the time series appear more like a delta function. 2. Make the spectrum appear flat.
Prewhitening What is Prewhitening? Prewhitening is an operation that processes a time series (or some other data sequence) to make it behave statistically like white noise. The pre means that whitening
More informationForwarding Strategies for Gaussian Parallel-Relay Networks
1 Forwarding Strategies or Gaussian arallelrelay Networks vana Maric Member, EEE and Roy D. Yates Member, EEE Abstract This paper investigates reliable and unreliable orwarding strategies in a parallelrelay
More informationCHAPTER 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 informationDesign Methodology for Shunt Active Filters
Design Methodology for Shunt Active Filters Fabio Ronchi, Andrea Tilli Department of Electronics, omputer and System Sciences (DEIS), University of Bologna Viale Risorgimento 2, 4136 Bologna, ITALY phone:
More informationAdvanced Sonar Processing Techniques for Underwater Acoustic Multi-Input Multi-Output Communications
Advanced Sonar Processing Techniques for Underwater Acoustic Multi-Input Multi-Output Communications Brian Stein 1,2, Yang You 1,2, Terry J. Brudner 1, Brian L. Evans 2 1 Applied Research Laboratories,
More information! 1F8B0 " 1F8B1 ARROW POINTING UPWARDS THEN NORTH WEST ARROW POINTING RIGHTWARDS THEN CURVING SOUTH WEST. 18 (M4b)
! 1F8B0 " 1F8B1 ARROW POINTING UPWARDS THEN NORTH WEST ARROW POINTING WARDS THEN CURVING SOUTH WEST 7D # 1FB00 SEXTANT-1 A1 A0, E0 21 (G1) 21 (G1) 21 (G1) 81 $ 1FB01 SEXTANT-2 A2 90, D0 22 (G1) 22 (G1)
More informationReduced Complexity of QRD-M Detection Scheme in MIMO-OFDM Systems
Advanced Science and echnology Letters Vol. (ASP 06), pp.4- http://dx.doi.org/0.457/astl.06..4 Reduced Complexity of QRD-M Detection Scheme in MIMO-OFDM Systems Jong-Kwang Kim, Jae-yun Ro and young-kyu
More informationADAPTIVE 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 informationAsynchronous Space-Time Cooperative Communications in Sensor and Robotic Networks
Proceedings of the IEEE International Conference on Mechatronics & Automation Niagara Falls, Canada July 2005 Asynchronous Space-Time Cooperative Communications in Sensor and Robotic Networks Fan Ng, Juite
More informationRadar Signal Detection In Non-Gaussian Noise Using RBF Neural Network
2 JOURNAL OF COMPUTER, VOL., NO. 1, JANUARY 2008 Radar ignal Detection In Non-Gaussian Noise Using RBF Neural Network D. G. Khairnar,. N. Merchant, U. B. Desai PANN Laboratory Department of Electrical
More informationLow Power Circuits for Multiple Match Resolution and Detection in Ternary CAMs
Low Power Circuits for Multiple Match Resolution and Detection in Ternary CAMs by Wilson W. Fung A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree
More informationFletch Diatonic A Harmonica Tablature Font User s Manual
Fletch Diatonic A Harmonica Tablature Font For an interactive table of contents in Acrobat, enable bookmarks (Window, Bookmarks) Copyright 2004 Winslow Tully Yerxa Fletch, Fletch Diatonic, and Discrete
More informationMIMO 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 informationDigital Audio Signal Processing DASP. Lecture-3: Noise Reduction-II. Fixed Beamforming. Marc Moonen
Digital Auio Signal Processing DASP Lecture-3: Noise Reuction-II Fixe Beamforming arc oonen Dept. E.E./ESAT-STADIUS, KU Leuven marc.moonen@kuleuven.be homes.esat.kuleuven.be/~moonen/ Overview Introuction
More informationRevision of Lecture Twenty-Eight
ELEC64 Advanced Wireless Communications Networks and Systems Revision of Lecture Twenty-Eight MIMO classification: roughly three classes create diversity, increase throughput, support multi-users Some
More informationCOUNTY OF MIDDLESEX 2016 BUDGET
hedule C C B CC V B B 0 06 0 06 0 06 0 06 hage C W diiai 44730 47763 3.4 40730 4963 3.0 7300 90.3 996 9779 443. laig ad Wdl 7037 660.6 7037 660.6 40774 464340 4366 0.4 i eele 43674 4 0. 3304 463 9. 0600
More informationEBDSM-PRM Product Guide
EBDSM-PRM Product Guide Ceiling PIR presence/absence detector Overview The EBDSM-PRM PIR (passive infrared) presence detector provides automatic control of lighting loads with optional manual control.
More informationMartin Salter Centre for Electromagnetic and Time Metrology, National Physical Laboratory
Measuring signals close to the noise floor Martin Salter Centre for Electromagnetic and Time Metrology, National Physical Laboratory 1 Introduction The presence of noise in a microwave measurement receiver
More informationCommunication over MIMO X Channel: Signalling and Performance Analysis
Communication over MIMO X Channel: Signalling and Performance Analysis Mohammad Ali Maddah-Ali, Abolfazl S. Motahari, and Amir K. Khandani Coding & Signal Transmission Laboratory Department of Electrical
More informationSiberian Branch of Russian Academy of Science BUDKER INSTITUTE OF NUCLEAR PHYSICS
Siberian Branch of Russian Academy of Science BUDKER INSTITUTE OF NUCLEAR PHYSICS A.G. Lee, R.A. Lokhtin, E.M. Mandrik, A.S. Medvedko, V.V. Rashenko, E.P. Semenov, Yu.F. Tokarev PULSE MODULATOR FOR A DIAGNOSTIC
More informationGeneralized Transmitted-Reference UWB Systems
eneralized Transmitted-Reference UWB Systems Honglei Zhang and Dennis L. oeckel lectrical and Computer ngineering Department University of Massachusetts 100 Natural Resources Road Amherst, MA 01003-9292
More informationThe Radio Channel. COS 463: Wireless Networks Lecture 14 Kyle Jamieson. [Parts adapted from I. Darwazeh, A. Goldsmith, T. Rappaport, P.
The Radio Channel COS 463: Wireless Networks Lecture 14 Kyle Jamieson [Parts adapted from I. Darwazeh, A. Goldsmith, T. Rappaport, P. Steenkiste] Motivation The radio channel is what limits most radio
More informationDistributed Broadcast Scheduling in Mobile Ad Hoc Networks with Unknown Topologies
Distributed Broadcast Scheduling in Mobile Ad Hoc Networks with Unknown Topologies Guang Tan, Stephen A. Jarvis, James W. J. Xue, and Simon D. Hammond Department of Computer Science, University of Warwick,
More informationSuperfat. Cape Arcona Type Foundry»Where fonts come true«
Cula Superfat Cape Arcona Type Foundry»Where fonts come true« Introduction CA Cula Superfat CA Cula Superfat is a distinctive fatty typeface, mainly intended for display purposes. You will find out that
More informationPAR reduction revisited: an extension to Tellado s method
1 1 6 th International OFDM-Workshop (InOWo) 1, Hamburg 31-1 PAR reduction revisited: an extension to Tellado s method Werner Henkel and Valentin Zrno Telecommunications Research Center Vienna (FTW) Vienna,
More informationAN-1140 APPLICATION NOTE
APPLICATION NOTE One Technology Way P.O. Box 9106 Norwoo, MA 02062-9106, U.S.A. Tel: 781.329.4700 Fax: 781.461.3113 www.analog.com Microphone Array Beamforming by Jera Lewis INTRODUCTION All MEMS microphones
More informationApproaches for Angle of Arrival Estimation. Wenguang Mao
Approaches for Angle of Arrival Estimation Wenguang Mao Angle of Arrival (AoA) Definition: the elevation and azimuth angle of incoming signals Also called direction of arrival (DoA) AoA Estimation Applications:
More informationIN AN MIMO communication system, multiple transmission
3390 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL 55, NO 7, JULY 2007 Precoded FIR and Redundant V-BLAST Systems for Frequency-Selective MIMO Channels Chun-yang Chen, Student Member, IEEE, and P P Vaidyanathan,
More informationFace Registration Using Wearable Active Vision Systems for Augmented Memory
DICTA2002: Digital Image Computing Techniques and Applications, 21 22 January 2002, Melbourne, Australia 1 Face Registration Using Wearable Active Vision Systems for Augmented Memory Takekazu Kato Takeshi
More informationA wireless MIMO CPM system with blind signal separation for incoherent demodulation
Adv. Radio Sci., 6, 101 105, 2008 Author(s) 2008. This work is distributed under the Creative Commons Attribution 3.0 License. Advances in Radio Science A wireless MIMO CPM system with blind signal separation
More informationBER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOCK CODES WITH MMSE CHANNEL ESTIMATION
BER PERFORMANCE AND OPTIMUM TRAINING STRATEGY FOR UNCODED SIMO AND ALAMOUTI SPACE-TIME BLOC CODES WITH MMSE CHANNEL ESTIMATION Lennert Jacobs, Frederik Van Cauter, Frederik Simoens and Marc Moeneclaey
More informationARQ strategies for MIMO eigenmode transmission with adaptive modulation and coding
ARQ strategies for MIMO eigenmode transmission with adaptive modulation and coding Elisabeth de Carvalho and Petar Popovski Aalborg University, Niels Jernes Vej 2 9220 Aalborg, Denmark email: {edc,petarp}@es.aau.dk
More informationService / Training Manual High Speed Combination Oven
R Commercial Service / Training Manual High Speed Combination Oven AXP / MXP - 60 Hz MXP22QT December 2011 16400012 Amana is a Registered Trademark of Maytag Corporation. Brand used under license. 1 Important
More informationeye_eq Program Tutorial
eye_eq Program Tutorial Jungsub Byun When we send transmissions more closely in succession to increase the data transmission rate, interference between them is unavoidable. This phenomenon is called intersymbol
More informationMIMO PERFORMANCE ANALYSIS WITH ALAMOUTI STBC CODE and V-BLAST DETECTION SCHEME
International Journal of Science, Engineering and Technology Research (IJSETR), Volume 4, Issue 1, January 2015 MIMO PERFORMANCE ANALYSIS WITH ALAMOUTI STBC CODE and V-BLAST DETECTION SCHEME Yamini Devlal
More informationAnalysis of LMS and NLMS Adaptive Beamforming Algorithms
Analysis of LMS and NLMS Adaptive Beamforming Algorithms PG Student.Minal. A. Nemade Dept. of Electronics Engg. Asst. Professor D. G. Ganage Dept. of E&TC Engg. Professor & Head M. B. Mali Dept. of E&TC
More informationAdaptive 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 informationMULTIUSER DETECTION FOR SDMA OFDM. Fernando H. Gregorio
MULTIUSER DETECTION FOR SDMA OFDM Fernando H. Gregorio Helsinki University of Technology Signal Processing Laboratory, POB 3000, FIN-0015 HUT, Finland E-mail:Fernando.Gregorio@hut.fi 1. INTRODUCTION Smart
More informationDatong Chen, Albrecht Schmidt, Hans-Werner Gellersen
Datong Chen, Albrecht Schmidt, Hans-Werner Gellersen TecO (Telecooperation Office), University of Karlsruhe Vincenz-Prießnitz-Str.1, 76131 Karlruhe, Germany {charles, albrecht, hwg}@teco.uni-karlsruhe.de
More informationAdaptive Beamforming. Chapter Signal Steering Vectors
Chapter 13 Adaptive Beamforming We have already considered deterministic beamformers for such applications as pencil beam arrays and arrays with controlled sidelobes. Beamformers can also be developed
More informationMMSE Algorithm Based MIMO Transmission Scheme
MMSE Algorithm Based MIMO Transmission Scheme Rashmi Tiwari 1, Agya Mishra 2 12 Department of Electronics and Tele-Communication Engineering, Jabalpur Engineering College, Jabalpur, Madhya Pradesh, India
More informationMultiple 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 informationDelivered at AERA in Chicago, April 1991
SOCIAL GRAVITY JAMES PAUL GEE DEPARTMENT OF CURRICULUM AND INSTRUCTION UNIVERSITY OF WISCONSIN AT MADISON MADISON, WI 53706 jgee@mail.soemadison.wisc.edu Delivered at AERA in Chicago, April 1991 As physical
More informationChannel 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 informationS Laboratory Works in Radiocommunications RECEIVER
Laboratory Works in Radiocommunications RECEIVER 2 FREQUENCY RESPONSES 5 channel ZF equalizer system 5 H(f) [db] 5 5 2.5.5 2 2.5 3 freq Prerequisites: S-72.328 (or S-88.22), knowledge of MALAB. See the
More informationComparison of wavefront sensing using subdivision at the aperture and focal planes
Comparison of wavefront sensing using subivision at the aperture an focal planes Richar M. Clare an Richar G. Lane Department of Electrical an Computer Engineering, University of Canterbury, Private Bag
More informationBeamforming in Interference Networks for Uniform Linear Arrays
Beamforming in Interference Networks for Uniform Linear Arrays Rami Mochaourab and Eduard Jorswieck Communications Theory, Communications Laboratory Dresden University of Technology, Dresden, Germany e-mail:
More information30. Signal Space Analysis of BASK, BFSK, BPSK, and QAM
Signal Space Analysis of BASK, BFSK, BPSK, an QAM on Mac 3. Signal Space Analysis of BASK, BFSK, BPSK, an QAM The vector-space representation of signals an the optimum etection process which chooses the
More informationPerformance Evaluation of V-BLAST MIMO System Using Rayleigh & Rician Channels
International Journal of Information & Computation Technology. ISSN 0974-2239 Volume 4, Number 15 (2014), pp. 1549-1558 International Research Publications House http://www. irphouse.com Performance Evaluation
More informationSTORING MESSAGES Note: If [MEMORY] (F5) is unavailable in the function key guide, press [MORE] (F2). An alternate key guide will appear.
ASSISTING YOUR SMOOTH QSO 5 If letters not transmitted yet remain in the text string buffer when [F12] is pressed at step 6, "WAIT" appears on the status bar. When the entire text string is transmitted,
More informationAntennas 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 informationIterative Multiuser Joint Decoding: Optimal Power Allocation and Low-Complexity Implementation
Iterative Multiuser Joint Decoding: Optimal Power Allocation and Low-Complexity Implementation Giuseppe Caire, Ralf Müller Ý and Toshiyuki Tanaka Þ March 12, 2003 Institut Eurecom, 2229 Route des Crétes,
More informationDEMONSTRATION OF SPEED AND POWER ENHANCEMENTS ON AN INDUSTRIAL CIRCUIT THROUGH APPLICATION OF CLOCK SKEW SCHEDULING
Journal of Circuits, Systems, and Computers, Vol. 11, No. 3 (2002) 231 245 c World Scientific Publishing Company DEMONSTRATION OF SPEED AND POWER ENHANCEMENTS ON AN INDUSTRIAL CIRCUIT THROUGH APPLICATION
More informationPerformance of BER Analysis of MIMO System using BPSK Modulation under Different Channel with STBC, ML and MRC
Performance of BER Analysis of MIMO System using BPSK Modulation under Different Channel with STBC, ML and MRC Krishna Kant Dubey 1, D.K. Srivastava 2 P.G. Student, Department of Electronics and Communication
More informationLecture 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 informationNear-Optimal Low Complexity MLSE Equalization
Near-Optimal Low Complexity MLSE Equalization Abstract An iterative Maximum Likelihood Sequence Estimation (MLSE) equalizer (detector) with hard outputs, that has a computational complexity quadratic in
More informationPerformance Analysis and Comparison of ZF and MRT Based Downlink Massive MIMO Systems
Performance Analysis an Comparison of ZF an MRT Base Downlink Massive MIMO Systems Tebe Parfait, Yujun uang, 1,2 ponyo Jerry 1 Mobilelink Lab Univ of Electronic Sci an Tech of China, UESTC Chengu, China
More informationAdaptive Beamforming Applied for Signals Estimated with MUSIC Algorithm
Buletinul Ştiinţific al Universităţii "Politehnica" din Timişoara Seria ELECTRONICĂ şi TELECOMUNICAŢII TRANSACTIONS on ELECTRONICS and COMMUNICATIONS Tom 57(71), Fascicola 2, 2012 Adaptive Beamforming
More informationIEEE C802.16a-02/18. IEEE Broadband Wireless Access Working Group <http://ieee802.org/16>
Project Title Date Submitted IEEE 82.6 Broadband Wireless Access Working Group [Analysis of STFBC-OFDM for BWA in SUI channel] [2--22] Source(s) PanYuh Joo, DaeEop Kang Samsung Electronics
More informationRate Allocation for Serial Concatenated Block Codes
1 Rate Allocation for Serial Concatenated Block Codes Maja Bystrom and Robert A. Coury Abstract While serial concatenated codes were designed to provide good overall performance with reasonable system
More informationSIGNAL MODEL AND PARAMETER ESTIMATION FOR COLOCATED MIMO RADAR
SIGNAL MODEL AND PARAMETER ESTIMATION FOR COLOCATED MIMO RADAR Moein Ahmadi*, Kamal Mohamed-pour K.N. Toosi University of Technology, Iran.*moein@ee.kntu.ac.ir, kmpour@kntu.ac.ir Keywords: Multiple-input
More informationA Review on Beamforming Techniques in Wireless Communication
A Review on Beamforming Techniques in Wireless Communication Hemant Kumar Vijayvergia 1, Garima Saini 2 1Assistant Professor, ECE, Govt. Mahila Engineering College Ajmer, Rajasthan, India 2Assistant Professor,
More informationMultiple Antennas and Space-Time Communications
Chapter 10 Multiple Antennas and Space-Time Communications In this chapter we consider systems with multiple antennas at the transmitter and receiver, which are commonly referred to as multiple input multiple
More informationOptimum Beamforming. ECE 754 Supplemental Notes Kathleen E. Wage. March 31, Background Beampatterns for optimal processors Array gain
Optimum Beamforming ECE 754 Supplemental Notes Kathleen E. Wage March 31, 29 ECE 754 Supplemental Notes: Optimum Beamforming 1/39 Signal and noise models Models Beamformers For this set of notes, we assume
More informationESTIMATION OF CARRIER-FREQUENCY OFFSET AND FREQUENCY-SELECTIVE CHANNELS IN MIMO OFDM SYSTEMS USING A COMMON TRAINING SIGNAL
ESTIMATION OF CARRIER-FREQUENCY OFFSET AND FREQUENCY-SELECTIVE CHANNELS IN MIMO OFDM SYSTEMS USING A COMMON TRAINING SIGNAL Hlaing Minn, Member, IEEE and Naofal Al-Dhahir, Senior Member, IEEE Department
More informationINTERFERENCE REJECTION OF ADAPTIVE ARRAY ANTENNAS BY USING LMS AND SMI ALGORITHMS
INTERFERENCE REJECTION OF ADAPTIVE ARRAY ANTENNAS BY USING LMS AND SMI ALGORITHMS Kerim Guney Bilal Babayigit Ali Akdagli e-mail: kguney@erciyes.edu.tr e-mail: bilalb@erciyes.edu.tr e-mail: akdagli@erciyes.edu.tr
More informationLearning a Gaussian Process Prior for Automatically Generating Music Playlists
Learning a Gaussian Process Prior for Automatically Generating Music Playlists John C. Platt Christopher J. C. Burges Steven Swenson Christopher Weare Alice Zheng Microsoft Corporation 1 Microsoft Way
More information