Copyright © 2007. All Rights Reserved. MIMO Receiver Design in Impulsive Noise Aditya Chopra and Kapil Gulati.

Slides:

Advertisements

Similar presentations

Multi-carrier CDMA. Outline Introduction System Model Types Applications References.

Advertisements

Underwater Acoustic MIMO Channel Capacity

Detection Theory Chapter 12 Model Change Detection Xiang Gao January 18, 2011.

Modeling and Mitigation of Interference in Multi-Antenna Receivers Aditya Chopra September 16,

Joint Access Point Placement and Channel Assignment for Wireless LANs Xiang Ling School of Communication and Information Engineering University.

VLF ANTENNAS by Evren EKMEKÇİ Middle East Technical University – May 2004.

Design of Interference-Aware Communication Systems Presentation to Freescale Semiconductor Wireless Networking and Communications Group 16 Dec 2010 Prof.

Paper Discussion: “Simultaneous Localization and Environmental Mapping with a Sensor Network”, Marinakis et. al. ICRA 2011.

MIMO-OFDM MIMO MIMO High diversity gain (space-time coding) High diversity gain (space-time coding) High multiplexing gain (BLAST) High multiplexing gain.

Spatial Diversity and Multiuser Diversity in Wireless Communications Bengt Holter Dept. of Electronics and Telecommunications NTNU IKT-2010 seminar, Lillestrøm,

Design of Interference-Aware Communication Systems WNCG “Dallas or Bust” Roadtrip Wireless Networking and Communications Group 24 Mar 2011 Prof. Brian.

Ghadi Sebaali and Brian L. Evans

BROADBAND BEAMFORMING Presented by: Kalpana Seshadrinathan.

MIMO WIRELESS COMMUNICATION SYSTEMS Bhaskar D. Rao University of California, San Diego La Jolla, CA

MULTIPLE INPUT MULTIPLE OUTPUT SYSTEMS (MIMO)

For 3-G Systems Tara Larzelere EE 497A Semester Project.

Design of Interference-Aware Wireless Communication Systems Wireless Networking and Communications Group 2 Dec 2010 Brian L. Evans Lead Graduate Students.

Radio Frequency Interference Sensing and Mitigation in Wireless Receivers Talk at Intel Labs at Hillsboro, Oregon Wireless Networking and Communications.

PhD Defense 13 May 2011 Wireless Networking and Communications Group Radio Frequency Interference Modeling and Mitigation in Wireless Receivers Kapil Gulati.

On the Coded Complex Field Network Coding Scheme for Multiuser Cooperative Communications with Regenerative Relays Caixi Key Lab of Information.

International Technology Alliance In Network & Information Sciences International Technology Alliance In Network & Information Sciences 1 Cooperative Wireless.

Design of Sparse Filters for Channel Shortening Aditya Chopra and Prof. Brian L. Evans Department of Electrical and Computer Engineering The University.

Ilmenau University of Technology Communications Research Laboratory 1  A new multi-dimensional model order selection technique called closed- form PARAFAC.

Doc.: IEEE /0493r1 Submission May 2010 Changsoon Choi, IHP microelectronicsSlide 1 Beamforming training for IEEE ad Date: Authors:

August 4, 2011 Non-Parametric Methods for Mitigating Interference in OFDM Receivers American University of Beirut 1 Prof. Brian L. Evans Department of.

November 1, 2012 Presented by Marwan M. Alkhweldi Co-authors Natalia A. Schmid and Matthew C. Valenti Distributed Estimation of a Parametric Field Using.

A Soft Decision Decoding Scheme for Wireless COFDM with Application to DVB-T Advisor : Yung-An Kao Student : Chi-Ting Wu

 Most previous work that deals with channel tracking assumes that the number K p of pilot subcarriers in each data OFDM symbol is at least as large as.

Ali Al-Saihati ID# Ghassan Linjawi

Overcoming Interference Limitations in Networked Systems Prof. Brian L. Evans The University of Texas at Austin Cockrell School of Engineering Department.

1 A Randomized Space-Time Transmission Scheme for Secret-Key Agreement Xiaohua (Edward) Li 1, Mo Chen 1 and E. Paul Ratazzi 2 1 Department of Electrical.

NTUEE Confidential Toward MIMO MC-CDMA Speaker : Pei-Yun Tsai Advisor : Tzi-Dar Chiueh 2004/10/25.

Space-Time and Space-Frequency Coded Orthogonal Frequency Division Multiplexing Transmitter Diversity Techniques King F. Lee.

Task Description: Increase powerline communication (PLC) data rate for better monitoring/controlling applications for residential and commercial energy.

Estimation of Number of PARAFAC Components

A Factor-Graph Approach to Joint OFDM Channel Estimation and Decoding in Impulsive Noise Channels Philip Schniter The Ohio State University Marcel Nassar,

VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MOBILE & PORTABLE RADIO RESEARCH GROUP MPRG Multiuser Detection with Base Station Diversity IEEE International.

Statistical Modeling of Co-Channel Interference IEEE Globecom 2009 Wireless Networking and Communications Group 1 st December 2009 Kapil Gulati †, Aditya.

Doc.: IEEE /1401r0 Submission November 2014 Slide 1 Shiwen He ， Haiming Wang Quasi-Orthogonal STBC for SC-PHY in IEEE aj (45GHz) Authors/contributors:

Talk at The University of Texas at Austin

STATISTICAL MODELING OF ASYNCHRONOUS IMPULSIVE NOISE IN POWERLINE COMMUNICATION NETWORKS Marcel Nassar, Kapil Gulati, Yousof Mortazavi, and Brian L. Evans.

VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY MOBILE & PORTABLE RADIO RESEARCH GROUP MPRG Combined Multiuser Detection and Channel Decoding with Receiver.

Space Time Codes. 2 Attenuation in Wireless Channels Path loss: Signals attenuate due to distance Shadowing loss : absorption of radio waves by scattering.

Marcel Nassar PhD Defense Committee Members: Prof. Gustavo de Veciana

Improving Wireless Data Transmission Speed and Reliability to Mobile Computing Platforms Texas Wireless Summit, Austin, Texas Wireless Networking and Communications.

Computer Arch. And Embedded Processors Embedded Real-Time Signal Processing Systems Prof. Brian L. Evans The University of Texas at Austin August 26, 2008.

Mitigating Radio Frequency Interference in Embedded Wireless Receivers Wireless Networking and Communications Group 8 January 2016 Prof. Brian L. Evans.

V- BLAST : Speed and Ordering Madhup Khatiwada IEEE New Zealand Wireless Workshop 2004 (M.E. Student) 2 nd September, 2004 University of Canterbury Alan.

Spectrum Sensing In Cognitive Radio Networks

Bandpass Modulation & Demodulation Detection

Wireless Networking and Communications Group Department of Electrical and Computer Engineering Mitigating Computer Platform Radio Frequency Interference.

Radio Frequency Interference Sensing and Mitigation in Wireless Receivers Talk at Intel Labs in Hillsboro, Oregon Wireless Networking and Communications.

November 9th, 2010 Low Complexity EM-based Decoding for OFDM Systems with Impulsive Noise Asilomar Conference on Signals, Systems, and Computers

Amplifier Nonlinearities in OFDM Multiple Antenna Systems FERNANDO GREGORIO Signal Processing Laboratory HUT.

Dr. Ahmed El-MahdySpread Spectrum Communications (1) Performance of LTE uplink over frequency selective fading channel in impulsive noise environment (2)

Talk at Texas Instruments in Dallas, Texas

Impulsive Noise at Wireless Receivers

Wireless Networking and Communications Group Department of Electrical and Computer Engineering Improving Wireless Data Transmission Speed and Reliability.

Trellis-coded Unitary Space-Time Modulation for Multiple-Antenna Scheme under Rayleigh Flat Fading 指導教授 : 王瑞騰老師學生 : 吳委政.

Marcel Nassar(1), Kapil Gulati(1) , Arvind K. Sujeeth(1),

Jinseok Choi, Brian L. Evans and *Alan Gatherer

Phd Proposal Investigation of Primary User Emulation Attack in Cognitive Radio Networks Chao Chen Department of Electrical & Computer Engineering Stevens.

D.Yu. Ignatov, A.N. Filippov, A.D. Ignatov, X. Zhang

Wenqian Shen1, Linglong Dai1, Yi Shi2, Zhen Gao1, and Zhaocheng Wang1

MIMO Receiver Design in the Presence of Radio Frequency Interference

LDPC for MIMO Systems July 8, 2004 Jianuxan Du,

Texas Wireless Summit, Austin, Texas

Talk at the American University of Beirut

Preliminary Results Mitigation of Radio Frequency Interference from the Computer Platform to Improve Wireless Data Communication Prof. Brian L. Evans Graduate.

The University of Texas at Austin

Presentation transcript:

Copyright © All Rights Reserved. MIMO Receiver Design in Impulsive Noise Aditya Chopra and Kapil Gulati

Copyright © All Rights Reserved. Introduction Background Most MIMO systems assume independent Gaussian noise at each receiver Models thermal noise at the receiver Impulsive noise also present in most systems Man-made electromagnetic interference Co channel interference [Yang and Petropulu, 2003] Atmospheric noise Problem Statement Analysis and design of MIMO receivers in impulsive noise Prior Work Noise Modeling Single antenna [Middleton, 1979, 1999] Two receiver antenna [MacDonald and Blum,1997] Performance Analysis [Li, Wang and Zhou,2004] MIMO Receivers in impulsive noise STBC over MIMO channels with impulsive noise [Gao and Tepedelenlioglu,2007]

Copyright © All Rights Reserved. Work Done Noise Modeling Middleton Model for two antennas Extensions to N t x N r difficult Weighted sum of multivariate complex Gaussians Multivariate Symmetric Alpha Stable Model Performance Analysis Error performance of standard MIMO receivers in impulsive noise Receiver Design (2 x 2 MIMO system) MAP receiver Assumes knowledge of noise parameters at the receiver Sub-optimal MAP receiver Noise parameters estimated Reduction in complexity

Copyright © All Rights Reserved. Results Simulation Setup: 2 x 2 MIMO Middleton noise (moderately impulsive) A (impulsive index) = 0.1, Γ (ratio of Gaussian/non-Gaussian energy) = 0.1

Copyright © All Rights Reserved. References [1] Weiyu Xu Anxin Li, Youzheng Wang and Zucheng Zhou, “Performance evaluation of MIMO systems in a mixture of Gaussian noise and impulsive noise”, Proc. 10th Asia Pacific Conference on Communications and 5t h International Symposium on Multi-Dimensional Mobile- Communications, [2] Ping Gao and C. Tepedelenlioglu, ”Space-time coding over mimo channels with impulsive noise”, IEEE Transactions on Wireless Communications, vol 6(1) :220–229, January [3] Marcel Nassar, Kapil Gulati and Brian L. Evans, ”In-platform radio frequency interference mitigation for wireless communications”, Technical report, The University of Texas at Austin, bevans/projects/rfi/reports/RFIReportSpring2007.doc [4] K.F. McDonald and R.S. Blum, ”A physically-based impulsive noise model for array observations”, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems & Computers, 1997, volume 1, pages 448–452, 2-5 Nov [5] D. Middleton, “Non-Gaussian noise models in signal processing for telecommunications: New methods and results for class a and class b noise models”, IEEE Transactions on Information Theory, vol 45(4):1129 – 1149, May [6] A. Spaulding and D. Middleton, ”Optimum reception in an impulsive interference environment-part 1: Coherent detection”, IEEE Transactions on Communications, vol 25(9):910923, [7] Xueshi Yang and A.P. Petropulu, “Co-channel interference modeling and analysis in a Poisson field of interferers in wireless communications”, IEEE Transactions on Signal Processing, vol 51(1), [8] S. M. Zabin and H. V. Poor, “Efficient estimation of class a noise parameters via the EM [Expectation- Maximization] algorithms”, IEEE Transaction on Information Theory, vol 37(1):60–72, Jan 1991.