A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems
|
|
- Audra Porter
- 5 years ago
- Views:
Transcription
1 A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems Wei Zhang, Xiang-Gen Xia and P. C. Ching EE Dept., The Chinese University of Hong Kong ECE Dept., University of Delaware A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.1/21
2 Outline Motivation Space-frequency coding High-rate full-diversity SFC design Summary and future work A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.2/21
3 Multiple Antennas System 1 h i, j 1 M M M t M r h i,j, τ i,j : are the multipath gain and delay from the jth Tx to the ith Rx, respectively (j = 1,,M t ; i = 1,,M r ) h i,j = [ h i,j (0) h i,j (1) h i,j (L 1) ] τ i,j = [ τ i,j (0) τ i,j (1) τ i,j (L 1) ] A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.3/21
4 Advantages of MIMO System MIMO increases capacity of communication MIMO uses independent channel fading due to multipath propagation to increase capacity No extra bandwidth is required MIMO gives reliable communication Multiple independent samples of the same signal at the receiver give rise to diversity A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.4/21
5 Multiple Antennas Coding Space-time coding (STC) achieves the diversity gain M t M r is effective in flat-fading channels only ST-OFDM is used for broadband communication where MIMO channel exhibits FSK induced by multipath fading. Its diversity order is M t M r, rather than M t M r L (full). SF-OFDM It encodes the information symbols onto different Tx (space) and OFDM subchannels (frequency bins). It can achieve the potential full diversity M t M r L. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.5/21
6 Advances in SFC Design Lee-Williams (2000), Gong-Letaief (2002), Hong-Hughes (2002) used STC directly as SFC, but without guarantees of full-diversity Bölcskei (2001) organized the columns of FFT matrix into full-diversity SFC, but the symbol rate is only 1 M t L Su-Safar-Olfat-Liu (2003) improved the rate of full-diversity SFC to 1 L by repetition mapping from STC Su-Safar-Liu (2004) achieved the full-rate (rate 1) and full-diversity SFC Our focus is on the design of high-rate (R > 1) full-diversity SFC. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.6/21
7 SF-OFDM System Model OFDM Tx 1 1 OFDM Rx SF Encoder SF Decoder OFDM Tx OFDM Rx M t M r H l (a) Typical MIMO-OFDM system SF Encoder H(e j2 k/n ) SF Decoder (b) Equivalent MIMO system A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.7/21
8 Signal Model Assume a vector S, of which the elements are from the constellation A (QPSK, or QAM), is encoded into C via f : S C where S = [ S 0 S 1 S Ns ] T, C = c (1) 0 c (1) 1 c (1) N 1 c (2) 0 c (2) 1 c (2) N 1 c (M t) 0 c (M t) 1 c (M t) N 1. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.8/21
9 Signal Model (cont.) At the ith receive antenna, after FFT the signal at the kth subchannel, denoted by r (i) k, is given by r (i) k = M t j=1 H i,j (k)c (j) k + n (i) k where H i,j (k) = L 1 l=0 h i,j(l)e j2πkτ i,j(l)/t s and c (j) k is the symbol transmitted from the kth subchannel at the jth Tx. The ML detection at the receiver is given by Ĉ = arg min C M r i=1 N 1 k=0 r (i) k Mt j=1 H i,j (k)c (j) k 2 A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.9/21
10 Pair-wise Error Probability Suppose that the ML detector decides in favor of E wrongly when C is in fact transmitted, the pairwise error probability can be upper bounded by [Bölcskei-Paulraj, 2000] P(C E) ( m i=1 ) Mr ( ) mmr Es λ i 4σn 2 where m is the rank of R(C,E)[R(C,E)] H and {λ 1,,λ m } are the nonzero eigenvalues of R(C,E)[R(C,E)] H. R(C, E) = [D 0 (C E) T, D 1 (C E) T,, D L 1 (C E) T ], and D l = diag{h(l)e j2πkτ(l)/t s } N 1 k=0. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.10/21
11 SFC Design Criteria In the high-snr region, the average error probability for communication over a fading channel usually behave as: P G c SNR G d where G c is referred to as the coding advantage and G d is called the diversity order. Here, G c = ( m i=1 λ i) M r and G d = mm r. The SF code design criteria can be summarized as (rank criteria) Maximize the minimum rank m of R(C, E) (determinant criteria) Maximize the minimum product, m i=1 λ i of R(C,E)[R(C,E)] H for all distinct pairs C and E. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.11/21
12 Full-Diversity SFC Design Assume N M t L, an SFC constructed by f : S Ns 1 C M t N achieves full diversity if and only if R(C,E) has full rank M t L for all C E, where R(C, E) = [D 0 (C E) T, D 1 (C E) T,, D L 1 (C E) T ] Equivalently, (C E) T has full rank M t B i are linearly independent with B j for i j (i,j = 0,1,,L 1), where B i = D i (C E) T A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.12/21
13 High-rate SFC Design N 1 M t S Block S 1 S 2 SFC SFC ~ G ~ G 1 2 Concatenation N M t OFDM T C 1 S J SFC ~ G J OFDM Mt (a) S: Input block of size NM t 1. S i : Sub-block of size KM t 1 for i = 1,,J, where J = N/K and K = 2 log 2 (MtL). G i : Encoded matrix of size K M t for i = 1,,J. C T : SFC given by C T = [ GT 1 G T 2 GT J ]T. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.13/21
14 High-rate SFC Design (cont.) The rate of the proposed SFC is R = N s N = M t Why do we divide the input block in that way? It facilitates the low-complexity decoding at receiver; J is always an integer since K is power of 2; K M t L, so we move to pursue the full rank of K M t L matrix R( G i, Ẽi) rather than R(C,E) Our focus next is to make at least one matrix G i, (1 i J) so that R( G i, Ẽi) achieve full rank when S i Ŝi 0. Equivalently, full-diversity SFC is desired. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.14/21
15 High-rate SFC Design (cont.) SFC KM t 1 KM t 1 K M t K M t S i Precoding X i Reshape G i Hadamard ~ G i (b) (precoding) X i = ΘS i, where Θ =vander( θ 1 θ 2 θ KMt ) and θ k = e j π(4k 3) 2KM t reshaping KM t 1 vector X i into K M t matrix G i (Hadamard) G i = G i ( H a Mt 1 b 1 ), where H a Mt is the first M t columns of the a a Hadamard matrix. a = 2 log 2 M t and b = K a. A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.15/21
16 Example of High-rate SFC For M t = 2, L = 2, and N = 4, the design of rate-2 SFC is shown as the following steps, get K = 4, J = 1, a = 2 and b = 2 construct the 8 8 precoding matrix Θ precoding the data vector S 8 1 with Θ into X = [ x 1 x 2 x 8 ] T after reshaping and Hadamard, we finally get x 1 x 5 C T x 2 x 6 = x 3 x 7 x 4 x 8 A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.16/21
17 Numerical Analysis An SFC denoted by C is a full-diversity if R(C,E) has full rank, i.e. (1) det (R(C,E)) H R(C,E) 0 for all distinct pairs C and E. By exhaustive search in space of (C E), we can numerically prove the full rank of (1) for BPSK, QPSK and 4-PAM, (M t = 2 and L = 2). Dimension of seach space for specific modulation BPSK QPSK 4-PAM ~ S S C E A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.17/21
18 Simulation Results 10 0 Two ray channel model, [0, 0.5] µ s, 2 bits/s/hz Rate 1, QPSK [Su, 2004] Rate 2, BPSK 10 1 Symbol Error Rate SNR (db) Figure 1: Symbol Error Rate, 2 bits/s/hz, τ = [0,0.5]µ s A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.18/21
19 Simulation Results (cont.) 10 0 Two ray channel model, [0, 0.2] µ s, 2 bits/s/hz Rate 1, QPSK [Su, 2004] Rate 2, BPSK 10 1 Symbols Error Rate SNR (db) Figure 2: Symbol Error Rate, 2 bits/s/hz, τ = [0,0.2]µ s A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.19/21
20 Summary and Future Work Proposed a design of high-rate (rate M t ) SFC The proposed SFC was validated to achieve the full-diversity by numerical and simulation results General theory of high-rate full-diversity SFC design are needed (for any number of Tx and Rx, any channel length, and any constellations) Low-complexity decoding (sphere decoding) A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.20/21
21 Thank you! A Design of High-Rate Space-Frequency Codes for MIMO-OFDM Systems p.21/21
Maximum 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 informationSystematic Design of Space-Frequency Codes with Full Rate and Full Diversity
Systematic Design of Space-Frequency Codes with Full Rate and Full Diversity Weifeng Su Department of ECE University of Maryland, College Park, MD 20742, USA Email: weifeng@engumdedu Zoltan Safar Department
More informationHomework 5 Solutions. Problem 1
Homework 5 Solutions Problem 1 (a Closed form Chernoff upper-bound for the uncoded 4-QAM average symbol error rate over Rayleigh flat fading MISO channel with = 4, assuming transmit-mrc The vector channel
More informationA low complexity Soft-Input Soft-Output MIMO detector which combines a Sphere Decoder with a Hopfield Network
A low complexity Soft-Input Soft-Output MIMO detector which combines a Sphere Decoder with a Hopfield Network Daniel J. Louw, Philip R. Botha, B.T. Maharaj Department of Electrical, Electronic and Computer
More informationLimited Feedback in Wireless Communication Systems
Limited Feedback in Wireless Communication Systems - Summary of An Overview of Limited Feedback in Wireless Communication Systems Gwanmo Ku May 14, 17, and 21, 2013 Outline Transmitter Ant. 1 Channel N
More informationConstellation Precoded Beamforming
Constellation Precoded Beamforming Hong Ju Park and Ender Ayanoglu Center for Pervasive Communications and Computing Department of Electrical Engineering and Computer Science University of California,
More informationExploiting Partial Channel Knowledge at the Transmitter in MISO and MIMO Wireless
Exploiting Partial Channel Knowledge at the Transmitter in MISO and MIMO Wireless SPAWC 2003 Rome, Italy June 18, 2003 E. Yoon, M. Vu and Arogyaswami Paulraj Stanford University Page 1 Outline Introduction
More informationLecture 9: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1
: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1 Rayleigh Friday, May 25, 2018 09:00-11:30, Kansliet 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless
More informationLecture 9: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1. Overview. Ragnar Thobaben CommTh/EES/KTH
: Diversity-Multiplexing Tradeoff Theoretical Foundations of Wireless Communications 1 Rayleigh Wednesday, June 1, 2016 09:15-12:00, SIP 1 Textbook: D. Tse and P. Viswanath, Fundamentals of Wireless Communication
More informationLecture 7 MIMO Communica2ons
Wireless Communications Lecture 7 MIMO Communica2ons Prof. Chun-Hung Liu Dept. of Electrical and Computer Engineering National Chiao Tung University Fall 2014 1 Outline MIMO Communications (Chapter 10
More informationApplications of Lattices in Telecommunications
Applications of Lattices in Telecommunications Dept of Electrical and Computer Systems Engineering Monash University amin.sakzad@monash.edu Oct. 2013 1 Sphere Decoder Algorithm Rotated Signal Constellations
More informationELEC E7210: Communication Theory. Lecture 10: MIMO systems
ELEC E7210: Communication Theory Lecture 10: MIMO systems Matrix Definitions, Operations, and Properties (1) NxM matrix a rectangular array of elements a A. an 11 1....... a a 1M. NM B D C E ermitian transpose
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 informationTiming errors in distributed space-time communications
Timing errors in distributed space-time communications Emanuele Viterbo Dipartimento di Elettronica Politecnico di Torino Torino, Italy viterbo@polito.it Yi Hong Institute for Telecom. Research University
More informationOn the Performance of. Golden Space-Time Trellis Coded Modulation over MIMO Block Fading Channels
On the Performance of 1 Golden Space-Time Trellis Coded Modulation over MIMO Block Fading Channels arxiv:0711.1295v1 [cs.it] 8 Nov 2007 Emanuele Viterbo and Yi Hong Abstract The Golden space-time trellis
More informationClosed Form Designs of Complex Orthogonal. Space-Time Block Codes of Rates (k + 1)=(2k) for
Closed Form Designs of Complex Orthogonal Space-Time Block Codes of Rates (k + 1)(k) for k 1 or k Transmit Antennas Kejie Lu, Shengli Fu, Xiang-Gen Xia Abstract In this correspondence, we present a systematic
More informationOmnidirectional Space-Time Block Coding for Common Information Broadcasting in Massive MIMO Systems
Omnidirectional Space-Time Block Coding for Common Information Broadcasting in Massive MIMO Systems Xin Meng, Xiang-Gen Xia, and Xiqi Gao 1 arxiv:1610.07771v1 [cs.it] 25 Oct 2016 Abstract In this paper,
More informationJoint FEC Encoder and Linear Precoder Design for MIMO Systems with Antenna Correlation
Joint FEC Encoder and Linear Precoder Design for MIMO Systems with Antenna Correlation Chongbin Xu, Peng Wang, Zhonghao Zhang, and Li Ping City University of Hong Kong 1 Outline Background Mutual Information
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 informationOn Optimal Quasi-Orthogonal Space-Time. Block Codes with Minimum Decoding Complexity
On Optimal Quasi-Orthogonal Space-Time 1 Block Codes with Minimum Decoding Complexity Haiquan Wang, Dong Wang, and Xiang-Gen Xia Abstract Orthogonal space-time block codes (OSTBC) from orthogonal designs
More informationAdvanced Topics in Digital Communications Spezielle Methoden der digitalen Datenübertragung
Advanced Topics in Digital Communications Spezielle Methoden der digitalen Datenübertragung Dr.-Ing. Carsten Bockelmann Institute for Telecommunications and High-Frequency Techniques Department of Communications
More informationAdvanced Spatial Modulation Techniques for MIMO Systems
Advanced Spatial Modulation Techniques for MIMO Systems Ertugrul Basar Princeton University, Department of Electrical Engineering, Princeton, NJ, USA November 2011 Outline 1 Introduction 2 Spatial Modulation
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 informationConstrained Detection for Multiple-Input Multiple-Output Channels
Constrained Detection for Multiple-Input Multiple-Output Channels Tao Cui, Chintha Tellambura and Yue Wu Department of Electrical and Computer Engineering University of Alberta Edmonton, AB, Canada T6G
More informationSpace-Time Coding for Multi-Antenna Systems
Space-Time Coding for Multi-Antenna Systems ECE 559VV Class Project Sreekanth Annapureddy vannapu2@uiuc.edu Dec 3rd 2007 MIMO: Diversity vs Multiplexing Multiplexing Diversity Pictures taken from lectures
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 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 informationUsing Noncoherent Modulation for Training
EE8510 Project Using Noncoherent Modulation for Training Yingqun Yu May 5, 2005 0-0 Noncoherent Channel Model X = ρt M ΦH + W Rayleigh flat block-fading, T: channel coherence interval Marzetta & Hochwald
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 informationSPACE-TIME CODING FOR MIMO RAYLEIGH FADING SYSTEMS MAO TIANYU
SPACE-TIME CODING FOR MIMO RAYLEIGH FADING SYSTEMS MAO TIANYU (M. Eng.) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF
More informationTitle. Author(s)Tsai, Shang-Ho. Issue Date Doc URL. Type. Note. File Information. Equal Gain Beamforming in Rayleigh Fading Channels
Title Equal Gain Beamforming in Rayleigh Fading Channels Author(s)Tsai, Shang-Ho Proceedings : APSIPA ASC 29 : Asia-Pacific Signal Citationand Conference: 688-691 Issue Date 29-1-4 Doc URL http://hdl.handle.net/2115/39789
More informationA Thesis for the Degree of Master. An Improved LLR Computation Algorithm for QRM-MLD in Coded MIMO Systems
A Thesis for the Degree of Master An Improved LLR Computation Algorithm for QRM-MLD in Coded MIMO Systems Wonjae Shin School of Engineering Information and Communications University 2007 An Improved LLR
More informationEs e j4φ +4N n. 16 KE s /N 0. σ 2ˆφ4 1 γ s. p(φ e )= exp 1 ( 2πσ φ b cos N 2 φ e 0
Problem 6.15 : he received signal-plus-noise vector at the output of the matched filter may be represented as (see (5-2-63) for example) : r n = E s e j(θn φ) + N n where θ n =0,π/2,π,3π/2 for QPSK, and
More informationSpace-Frequency Coded MIMO-OFDM with Variable Multiplexing-Diversity Tradeoff
Space-Frequency Coded MIMO-OFDM with Variable Multiplexing-Diversity Tradeoff Helmut Bölcsei and Moritz Borgmann Communication Technology Laboratory ETH Zurich ETH Zentrum, ETF E122 Sternwartstrasse 7
More informationA Precoding Method for Multiple Antenna System on the Riemannian Manifold
Journal of Communications Vol. 9, No. 2, February 2014 A Precoding Method for Multiple Antenna System on the Riemannian Manifold Lin Zhang1 and S. H. Leung2 1 Department of Electronic Engineering, City
More informationAchieving the Full MIMO Diversity-Multiplexing Frontier with Rotation-Based Space-Time Codes
Achieving the Full MIMO Diversity-Multiplexing Frontier with Rotation-Based Space-Time Codes Huan Yao Lincoln Laboratory Massachusetts Institute of Technology Lexington, MA 02420 yaohuan@ll.mit.edu Gregory
More informationBlind Channel Identification in (2 1) Alamouti Coded Systems Based on Maximizing the Eigenvalue Spread of Cumulant Matrices
Blind Channel Identification in (2 1) Alamouti Coded Systems Based on Maximizing the Eigenvalue Spread of Cumulant Matrices Héctor J. Pérez-Iglesias 1, Daniel Iglesia 1, Adriana Dapena 1, and Vicente Zarzoso
More informationOn Improving the BER Performance of Rate-Adaptive Block Transceivers, with Applications to DMT
On Improving the BER Performance of Rate-Adaptive Block Transceivers, with Applications to DMT Yanwu Ding, Timothy N. Davidson and K. Max Wong Department of Electrical and Computer Engineering, McMaster
More informationTransmitter-Receiver Cooperative Sensing in MIMO Cognitive Network with Limited Feedback
IEEE INFOCOM Workshop On Cognitive & Cooperative Networks Transmitter-Receiver Cooperative Sensing in MIMO Cognitive Network with Limited Feedback Chao Wang, Zhaoyang Zhang, Xiaoming Chen, Yuen Chau. Dept.of
More informationarxiv:cs/ v1 [cs.it] 11 Sep 2006
0 High Date-Rate Single-Symbol ML Decodable Distributed STBCs for Cooperative Networks arxiv:cs/0609054v1 [cs.it] 11 Sep 2006 Zhihang Yi and Il-Min Kim Department of Electrical and Computer Engineering
More informationAdaptive Space-Time Shift Keying Based Multiple-Input Multiple-Output Systems
ACSTSK Adaptive Space-Time Shift Keying Based Multiple-Input Multiple-Output Systems Professor Sheng Chen Electronics and Computer Science University of Southampton Southampton SO7 BJ, UK E-mail: sqc@ecs.soton.ac.uk
More informationOn the Use of Division Algebras for Wireless Communication
On the Use of Division Algebras for Wireless Communication frederique@systems.caltech.edu California Institute of Technology AMS meeting, Davidson, March 3rd 2007 Outline A few wireless coding problems
More informationLecture 4 Capacity of Wireless Channels
Lecture 4 Capacity of Wireless Channels I-Hsiang Wang ihwang@ntu.edu.tw 3/0, 014 What we have learned So far: looked at specific schemes and techniques Lecture : point-to-point wireless channel - Diversity:
More informationNew Coded Modulation for the Frequency Hoping OFDMA System.
New Coded Modulation for the Frequency Hoping OFDMA System. Kreshchuk Alexey Potapov Vladimir Institute for Information Transmission Problems of Russian Academy of Science Thirteenth International Workshop
More informationA Construction of a Space Time Code Based on Number Theory
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 48, NO. 3, MARCH 00 753 A Construction of a Space Time Code Based on Number Theory Mohamed Oussama Damen, Associate Member, IEEE, Ahmed Tewfik, Fellow, IEEE,
More informationLecture 12. Block Diagram
Lecture 12 Goals Be able to encode using a linear block code Be able to decode a linear block code received over a binary symmetric channel or an additive white Gaussian channel XII-1 Block Diagram Data
More informationEE6604 Personal & Mobile Communications. Week 13. Multi-antenna Techniques
EE6604 Personal & Mobile Communications Week 13 Multi-antenna Techniques 1 Diversity Methods Diversity combats fading by providing the receiver with multiple uncorrelated replicas of the same information
More informationELEC546 MIMO Channel Capacity
ELEC546 MIMO Channel Capacity Vincent Lau Simplified Version.0 //2004 MIMO System Model Transmitter with t antennas & receiver with r antennas. X Transmitted Symbol, received symbol Channel Matrix (Flat
More informationThe E8 Lattice and Error Correction in Multi-Level Flash Memory
The E8 Lattice and Error Correction in Multi-Level Flash Memory Brian M Kurkoski University of Electro-Communications Tokyo, Japan kurkoski@iceuecacjp Abstract A construction using the E8 lattice and Reed-Solomon
More information8 PAM BER/SER Monte Carlo Simulation
xercise.1 8 PAM BR/SR Monte Carlo Simulation - Simulate a 8 level PAM communication system and calculate bit and symbol error ratios (BR/SR). - Plot the calculated and simulated SR and BR curves. - Plot
More informationMulti-Branch MMSE Decision Feedback Detection Algorithms. with Error Propagation Mitigation for MIMO Systems
Multi-Branch MMSE Decision Feedback Detection Algorithms with Error Propagation Mitigation for MIMO Systems Rodrigo C. de Lamare Communications Research Group, University of York, UK in collaboration with
More information16.36 Communication Systems Engineering
MIT OpenCourseWare http://ocw.mit.edu 16.36 Communication Systems Engineering Spring 2009 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 16.36: Communication
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 informationMultiple Antennas in Wireless Communications
Multiple Antennas in Wireless Communications Luca Sanguinetti Department of Information Engineering Pisa University luca.sanguinetti@iet.unipi.it April, 2009 Luca Sanguinetti (IET) MIMO April, 2009 1 /
More information2318 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 6, JUNE Mai Vu, Student Member, IEEE, and Arogyaswami Paulraj, Fellow, IEEE
2318 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 54, NO. 6, JUNE 2006 Optimal Linear Precoders for MIMO Wireless Correlated Channels With Nonzero Mean in Space Time Coded Systems Mai Vu, Student Member,
More informationExpectation propagation for symbol detection in large-scale MIMO communications
Expectation propagation for symbol detection in large-scale MIMO communications Pablo M. Olmos olmos@tsc.uc3m.es Joint work with Javier Céspedes (UC3M) Matilde Sánchez-Fernández (UC3M) and Fernando Pérez-Cruz
More informationL interférence dans les réseaux non filaires
L interférence dans les réseaux non filaires Du contrôle de puissance au codage et alignement Jean-Claude Belfiore Télécom ParisTech 7 mars 2013 Séminaire Comelec Parts Part 1 Part 2 Part 3 Part 4 Part
More informationON DECREASING THE COMPLEXITY OF LATTICE-REDUCTION-AIDED K-BEST MIMO DETECTORS.
17th European Signal Processing Conference (EUSIPCO 009) Glasgow, Scotland, August 4-8, 009 ON DECREASING THE COMPLEXITY OF LATTICE-REDUCTION-AIDED K-BEST MIMO DETECTORS. Sandra Roger, Alberto Gonzalez,
More informationIN THE last several years, there has been considerable
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 48, NO. 8, AUGUST 2002 2291 Unitary Signal Constellations Differential Space Time Modulation With Two Transmit Antennas: Parametric Codes, Optimal Designs,
More informationWireless Communications Lecture 10
Wireless Communications Lecture 1 [SNR per symbol and SNR per bit] SNR = P R N B = E s N BT s = E b N BT b For BPSK: T b = T s, E b = E s, and T s = 1/B. Raised cosine pulse shaper for other pulses. T
More informationPrecoded Integer-Forcing Universally Achieves the MIMO Capacity to Within a Constant Gap
Precoded Integer-Forcing Universally Achieves the MIMO Capacity to Within a Constant Gap Or Ordentlich Dept EE-Systems, TAU Tel Aviv, Israel Email: ordent@engtauacil Uri Erez Dept EE-Systems, TAU Tel Aviv,
More informationReliability of Radio-mobile systems considering fading and shadowing channels
Reliability of Radio-mobile systems considering fading and shadowing channels Philippe Mary ETIS UMR 8051 CNRS, ENSEA, Univ. Cergy-Pontoise, 6 avenue du Ponceau, 95014 Cergy, France Philippe Mary 1 / 32
More informationCapacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming
Capacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming Authors: Christian Lameiro, Alfredo Nazábal, Fouad Gholam, Javier Vía and Ignacio Santamaría University of Cantabria,
More informationOptimization of Modulation Constrained Digital Transmission Systems
University of Ottawa Optimization of Modulation Constrained Digital Transmission Systems by Yu Han A thesis submitted in fulfillment for the degree of Master of Applied Science in the Faculty of Engineering
More informationA Coding Strategy for Wireless Networks with no Channel Information
A Coding Strategy for Wireless Networks with no Channel Information Frédérique Oggier and Babak Hassibi Abstract In this paper, we present a coding strategy for wireless relay networks, where we assume
More informationTruncation for Low Complexity MIMO Signal Detection
1 Truncation for Low Complexity MIMO Signal Detection Wen Jiang and Xingxing Yu School of Mathematics Georgia Institute of Technology, Atlanta, Georgia, 3033 Email: wjiang@math.gatech.edu, yu@math.gatech.edu
More informationA Fast-Decodable, Quasi-Orthogonal Space Time Block Code for 4 2 MIMO
Forty-Fifth Annual Allerton Conference Allerton House, UIUC, Illinois, USA September 26-28, 2007 ThC6.4 A Fast-Decodable, Quasi-Orthogonal Space Time Block Code for 4 2 MIMO Ezio Biglieri Universitat Pompeu
More informationDistributed Space-Frequency Coding over Amplify-and-Forward Relay Channels
Distributed Space-Frequency Coding over Amplify-and-Forward Relay Channels Karim G. Seddik and K. J. Ray Liu Department of Electrical and Computer Engineering, and Institute for Systems Research University
More informationCapacity of multiple-input multiple-output (MIMO) systems in wireless communications
15/11/02 Capacity of multiple-input multiple-output (MIMO) systems in wireless communications Bengt Holter Department of Telecommunications Norwegian University of Science and Technology 1 Outline 15/11/02
More informationPOWER ALLOCATION AND OPTIMAL TX/RX STRUCTURES FOR MIMO SYSTEMS
POWER ALLOCATION AND OPTIMAL TX/RX STRUCTURES FOR MIMO SYSTEMS R. Cendrillon, O. Rousseaux and M. Moonen SCD/ESAT, Katholiee Universiteit Leuven, Belgium {raphael.cendrillon, olivier.rousseaux, marc.moonen}@esat.uleuven.ac.be
More informationCapacity of MIMO Systems in Shallow Water Acoustic Channels
Capacity of MIMO Systems in Shallow Water Acoustic Channels Andreja Radosevic, Dario Fertonani, Tolga M. Duman, John G. Proakis, and Milica Stojanovic University of California, San Diego, Dept. of Electrical
More informationSingle-User MIMO systems: Introduction, capacity results, and MIMO beamforming
Single-User MIMO systems: Introduction, capacity results, and MIMO beamforming Master Universitario en Ingeniería de Telecomunicación I. Santamaría Universidad de Cantabria Contents Introduction Multiplexing,
More informationSynchronization in Physical- Layer Network Coding
Synchronization in Physical- Layer Network Coding Soung Liew Institute of Network Coding The Chinese University of Hong Kong Slides in this talk based on partial content in Physical-layer Network Coding:
More informationEE6604 Personal & Mobile Communications. Week 15. OFDM on AWGN and ISI Channels
EE6604 Personal & Mobile Communications Week 15 OFDM on AWGN and ISI Channels 1 { x k } x 0 x 1 x x x N- 2 N- 1 IDFT X X X X 0 1 N- 2 N- 1 { X n } insert guard { g X n } g X I n { } D/A ~ si ( t) X g X
More informationDemixing Radio Waves in MIMO Spatial Multiplexing: Geometry-based Receivers Francisco A. T. B. N. Monteiro
Demixing Radio Waves in MIMO Spatial Multiplexing: Geometry-based Receivers Francisco A. T. B. N. Monteiro 005, it - instituto de telecomunicações. Todos os direitos reservados. Demixing Radio Waves in
More informationPerfect Space-Time Block Codes and Ultra-Wideband
Perfect Space-Time Block Codes and Ultra-Wideband Kei Hao 1 Introduction In this report, we present the techniques for constructing Space-Time Block Codes based on division algebra Even though commutative
More informationModulation & Coding for the Gaussian Channel
Modulation & Coding for the Gaussian Channel Trivandrum School on Communication, Coding & Networking January 27 30, 2017 Lakshmi Prasad Natarajan Dept. of Electrical Engineering Indian Institute of Technology
More informationMulti-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems
Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User
More informationChapter 7: Channel coding:convolutional codes
Chapter 7: : Convolutional codes University of Limoges meghdadi@ensil.unilim.fr Reference : Digital communications by John Proakis; Wireless communication by Andreas Goldsmith Encoder representation Communication
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 informationAlgebraic Multiuser Space Time Block Codes for 2 2 MIMO
Algebraic Multiuser Space Time Bloc Codes for 2 2 MIMO Yi Hong Institute of Advanced Telecom. University of Wales, Swansea, UK y.hong@swansea.ac.u Emanuele Viterbo DEIS - Università della Calabria via
More informationA Fast Decodable Full-Rate STBC with High Coding Gain for 4x2 MIMO Systems
A Fast Decodable Full-Rate STBC with High Coding Gain for 4x2 MIMO Systems Ming Liu, Maryline Hélard, Jean-François Hélard, Matthieu Crussière To cite this version: Ming Liu, Maryline Hélard, Jean-François
More informationErgodic and Outage Capacity of Narrowband MIMO Gaussian Channels
Ergodic and Outage Capacity of Narrowband MIMO Gaussian Channels Yang Wen Liang Department of Electrical and Computer Engineering The University of British Columbia April 19th, 005 Outline of Presentation
More informationMulti-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems
Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User MIMO Systems Multi-Input Multi-Output Systems (MIMO) Channel Model for MIMO MIMO Decoding MIMO Gains Multi-User
More informationComputing Probability of Symbol Error
Computing Probability of Symbol Error I When decision boundaries intersect at right angles, then it is possible to compute the error probability exactly in closed form. I The result will be in terms of
More informationEXPLOITING TRANSMIT CHANNEL SIDE INFORMATION IN MIMO WIRELESS SYSTEMS
EXPLOITING TRANSMIT CHANNEL SIDE INFORMATION IN MIMO WIRELESS SYSTEMS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF ELECTRICAL ENGINEERING AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN
More informationImproved Detected Data Processing for Decision-Directed Tracking of MIMO Channels
Improved Detected Data Processing for Decision-Directed Tracking of MIMO Channels Emna Eitel and Joachim Speidel Institute of Telecommunications, University of Stuttgart, Germany Abstract This paper addresses
More informationModulation Diversity in Fading Channels with Quantized Receiver
011 IEEE International Symposium on Information Theory Proceedings Modulation Diversity in Fading Channels with Quantized Receiver Saif Khan Mohammed, Emanuele Viterbo, Yi Hong, and Ananthanarayanan Chockalingam
More informationA View on Full-Diversity Modulus-Preserving Rate-One Linear Space-Time Block Codes
SIGNAL PROCESSING (TO APPEAR) A View on Full-Diversity Modulus-Preserving Rate-One Linear Space-Time Block Codes Shengli Zhou 1, Xiaoli Ma 2, and Krishna Pattipati 1 Paper Number: SIGPRO-D-05-00038 Associate
More informationOn the Robustness of Algebraic STBCs to Coefficient Quantization
212 Australian Communications Theory Workshop (AusCTW) On the Robustness of Algebraic STBCs to Coefficient Quantization J. Harshan Dept. of Electrical and Computer Systems Engg., Monash University Clayton,
More informationList Decoding: Geometrical Aspects and Performance Bounds
List Decoding: Geometrical Aspects and Performance Bounds Maja Lončar Department of Information Technology Lund University, Sweden Summer Academy: Progress in Mathematics for Communication Systems Bremen,
More informationInterleave Division Multiple Access. Li Ping, Department of Electronic Engineering City University of Hong Kong
Interleave Division Multiple Access Li Ping, Department of Electronic Engineering City University of Hong Kong 1 Outline! Introduction! IDMA! Chip-by-chip multiuser detection! Analysis and optimization!
More informationAnalysis of Receiver Quantization in Wireless Communication Systems
Analysis of Receiver Quantization in Wireless Communication Systems Theory and Implementation Gareth B. Middleton Committee: Dr. Behnaam Aazhang Dr. Ashutosh Sabharwal Dr. Joseph Cavallaro 18 April 2007
More informationCoherentDetectionof OFDM
Telematics Lab IITK p. 1/50 CoherentDetectionof OFDM Indo-UK Advanced Technology Centre Supported by DST-EPSRC K Vasudevan Associate Professor vasu@iitk.ac.in Telematics Lab Department of EE Indian Institute
More informationGolden Space-Time Block Coded Modulation
Golden Space-Time Block Coded Modulation Laura Luzzi Ghaya Rekaya-Ben Othman Jean-Claude Belfiore and Emanuele Viterbo Télécom ParisTech- École Nationale Supérieure des Télécommunications 46 Rue Barrault
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 informationPhysical Layer and Coding
Physical Layer and Coding Muriel Médard Professor EECS Overview A variety of physical media: copper, free space, optical fiber Unified way of addressing signals at the input and the output of these media:
More informationCapacity Pre-log of Noncoherent SIMO Channels via Hironaka s Theorem
Capacity Pre-log of Noncoherent SIMO Channels via Hironaka s Theorem Veniamin I. Morgenshtern 22. May 2012 Joint work with E. Riegler, W. Yang, G. Durisi, S. Lin, B. Sturmfels, and H. Bőlcskei SISO Fading
More informationReceived Signal, Interference and Noise
Optimum Combining Maximum ratio combining (MRC) maximizes the output signal-to-noise ratio (SNR) and is the optimal combining method in a maximum likelihood sense for channels where the additive impairment
More information