VEHICULAR TECHNOLOGIES: INCREASING CONNECTIVITY Edited by Miguel Almeida Vehicular Technologies: Increasing Connectivity Edited by Miguel Almeida Published by InTech Janeza Trdine 9, 51000 Rijeka, Croatia Copyright © 2011 InTech All chapters are Open Access articles distributed under the Creative Commons Non Commercial Share Alike Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited. After this work has been published by InTech, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published articles. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Katarina Lovrecic Technical Editor Teodora Smiljanic Cover Designer Martina Sirotic Image Copyright ssguy, 2010. Used under license from Shutterstock.com First published March, 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Vehicular Technologies: Increasing Connectivity, Edited by Miguel Almeida p. cm. ISBN 978-953-307-223-4 free online editions of InTech Books and Journals can be found at www.intechopen.com Chapter 1 Chapter 2 Chapter 3 Chapter 4 Chapter 5 Chapter 6 Chapter 7 Chapter 8 Preface IX A Non-Stationary MIMO Vehicle-to-Vehicle Channel Model Derived From the Geometrical T-Junction Model 1 Ali Chelli and Matthias Pätzold Simulation of SISO and MIMO Multipath Fading Channels 11 Antonio Petrolino and Gonçalo Tavares User Scheduling and Partner Selection for Multiplexing-based Distributed MIMO Uplink Transmission 35 Ping-Heng Kuo and Pang-An Ting Resource Allocation for Multi-User OFDMA-Based Wireless Cellular Networks 51 Dimitri Kténas and Emilio Calvanese Strinati From Linear Equalization to Lattice-Reduction-Aided Sphere-Detector as an Answer to the MIMO Detection Problematic in Spatial Multiplexing Systems 71 Sébastien Aubert and Manar Mohaisen DFT Based Channel Estimation Methods for MIMO-OFDM Systems 97 Moussa Diallo,Maryline Hélard, Laurent Cariou and Rodrigue Rabineau Channels and Parameters Acquisition in Cooperative OFDM Systems 115 D. Neves, C. Ribeiro, A. Silva and A. Gameiro Fast Power and Channel Adaptation for Mobile Users in OFDMA Multi-Cell Scenarios 137 L. Reggiani, L. Galati Giordano and L. Dossi Contents Contents VI Statistical Properties of the Capacity of Double Nakagami-m Channels for Applications in V2V Dualhop Communication Systems 153 Gulzaib Rafiq, Bjørn Olav Hogstad and Matthias Pätzoldt Resource Allocation and User Scheduling in Coordinated Multicell MIMO Systems 165 Edgar Souza, Robson Vieira, Mari Kobayashi and Mérouane Debbah Hybrid Evolutionary Algorithm-based Schemes for Subcarrier, Bit, and Power Allocation in Multiuser OFDM Systems 185 Wei-Cheng Pao, Yung-Fang Chen and Yun-Teng Lu Reduced-Complexity PAPR Minimization Schemes for MC-CDMA Systems 205 Mariano García Otero and Luis A. Paredes Hernández Cognitive Radio Communications for Vehicular Technology – Wavelet Applications 223 Murroni Maurizio and Popescu Vlad Multiple Antenna-Aided Spectrum Sensing Using Energy Detectors for Cognitive Radio 239 Seung-Hoon Hwang and Jun-Ho Baek New Method to Generate Balanced 2 n -PSK STTCs 261 P. Viland, G. Zaharia and J F. Hélard Correlation Coefficients of Received Signal I and Q Components in a Domain with Time and Frequency Axes under Multipath Mobile Channel with LOS and NLOS 281 Shigeru Kozono, Kenji Ookubo, Takeshi Kozima and Tomohiro Hamashima Multimodulus Blind Equalization Algorithm Using Oblong QAM Constellations for Fast Carrier Phase Recovery 299 Jenq-Tay Yuan and Tzu-Chao Lin Peak-to-Average Power Ratio Reduction for Wavelet Packet Modulation Schemes via Basis Function Design 315 Ngon Thanh Le, Siva D. Muruganathan and Abu B. Sesay Outage Performance and Symbol Error Rate Analysis of L-Branch Maximal-Ratio Combiner for κ-µ and η-µ Fading 333 Mirza Milišić, Mirza Hamza and Mesud Hadžialić Chapter 9 Chapter 10 Chapter 11 Chapter 12 Chapter 13 Chapter 14 Chapter 15 Chapter 16 Chapter 17 Chapter 18 Chapter 19 Contents VII Technological Issues in the Design of Cost-Efficient Electronic Toll Collection Systems 359 José Santa, Rafael Toledo-Moreo, Benito Úbeda, Miguel A. Zamora-Izquierdo and Antonio F. Gómez-Skarmeta Propagation Aspects in Vehicular Networks 375 Lorenzo Rubio, Juan Reig and Herman Fernández Propagation Path Loss Modelling in Container Terminal Environment 415 Slawomir J. Ambroziak, Ryszard J. Katulski, Jaroslaw Sadowski and Jacek Stefanski Link Budgets: How Much Energy is Really Received 433 Aarne Mämmelä, Adrian Kotelba, Marko Höyhtyä and Desmond P. Taylor Chapter 20 Chapter 21 Chapter 22 Chapter 23 Pref ac e This book covers the most recent advances concerning the ability to overcome connec- tivity limitations and extend the link capacity of vehicular systems. Ranging from the advances on radio access technologies to intelligent mechanisms deployed to enhance cooperative communications, cognitive radio and multiple antenna systems have been given particular highlight. While some contributions do not off er an immediate response to the challenges that appear in some vehicular scenarios, they provide insight and research conclusions, from which Vehicle Networking Design can greatly benefi t. Finding new ways to over- come the limitations of these systems will increase network reachability, service deliv- ery, from infrastructure to vehicles, and the inter-vehicle connectivity. Having this in mind, particular a ention was paid to the propagation issues and channel character- ization models. To overcome the current limitations over these systems, this book is mainly comprised of the following topics: 1. Multiple Antenna Systems, Cognitive Radio and Cooperative Communica- tions: focusing on multiple smart antenna systems, MIMO, OFDM, MC-CDMA sys- tems, cognitive radio advances. 2. Transmission and Propagation: evaluating the propagation aspects of these systems, link layer coding techniques, mobile/radio oriented technologies, channel characterization, channel coding. It is our understanding that advances on vehicular networking technologies can great- ly benefi t from the research studies presented herein. In this book, we tried to summa- rize the areas concerning physical and link layers with contributions that expose the state of the art for vehicular networks. We are thankful to all of those who contributed to this book and who made it possible. Miguel Almeida University of Aveiro Portugal [...]... Williams, 1999) It has been stated in (Sayeed & Jones, 1995) that the Cohen class, although introduced for deterministic signals, can be applied on non-stationary stochastic processes 2 Vehicular Technologies: Increasing Connectivity In this chapter, we present a non-stationary MIMO V2V channel model The AoD and the AoA are supposed to be time dependent This assumption makes our channel model non-stationary... the underlying M T × M R MIMO V2V channel model can be expressed in the present case as M,N ) gkl (r T , r R=∑ cmn e j m =1,n=1 θ mn ( t)+ k T ·r T − k R ·r R − k 0 d mn ( t) m n (1) 4 Vehicular Technologies: Increasing Connectivity The symbols cmn and θmn (t) stand for the the joint gain and the joint phase shift caused by the √ T R scatterers Sm and Sn The joint channel gain can be written as cmn... ) After substituting (2) and (8) in (1), the complex channel gain gkl (t) can be expressed as M,N gkl (t) = T R TR am bn cmn j √ e MN m,n=1 ∑ T R 2π ( f m + f n ) t+ θ mn ( t) (14) 6 Vehicular Technologies: Increasing Connectivity where δT T T am = e jπ λ ( MT −2l +1) cos( α m ( t)−γ T ) R bn =e TR cmn = e jπ δR λ (15) ( M R −2k +1) cos( β R ( t)− γ R) n − j 2π λ (16) T R Dm ( t)+ Dmn+ Dn ( t) (17)... scatterers is set to 20 m We consider the same number of scatterers around the receiver The transmitter and the receiver have a velocity of 70 km/h and a direction of motion determined 8 Vehicular Technologies: Increasing Connectivity Generalized local ACF, | K(t, τ; φ) | by φT = 0 and φR = − π/2, respectively The transmitter and the receiver antenna tilt angles T T γ T and γ R are equal to π/2 The street... the local transmit space CF | ρ12 (t, δT )| 1 0.8 0.6 0.4 0.2 0 0 1 1 2 0.8 0.6 3 0.4 4 δR /λ 5 0.2 0 Time t (s) R Fig 6 Absolute value of the local receive space CF | ρ12 (t, δR )| 10 Vehicular Technologies: Increasing Connectivity the local receive space CF Supported by our analysis, we can conclude that the stationarity assumption is violated for V2V channels, especially if the mobile speed is high... respectively of the i-th path and n (t) is a white Gaussian process 1 Otherwise, when the propagation delays are negligible compared to the signal interval, the channel is said to be flat 12 Vehicular Technologies: Increasing Connectivity modeling thermal noise and noise added by the receiver amplifiers Although in the case of time varying channels N (t) and τi (t) are functions of the time, for the sake of... the expansion coefficients, that is the projections of the process h(t) on the basis functions The representation in (8) is known as the Karhunen-Loève expansion for the process h(t) 14 Vehicular Technologies: Increasing Connectivity (Van Trees, 1968) Since h(t) is a zero-mean complex Gaussian random process and the − − {φl (t)}lL=01 are orthogonal, the {hl }lL=01 are zero-mean, independent complex Gaussian... case the comparison is made between the target and the simulated time ACFs In both cases, perfect preservation of the initial PDF is achieved Finally, Section 6 concludes the chapter 16 Vehicular Technologies: Increasing Connectivity 2 The Metropolis-Hastings algorithm In this Section, we present a computational efficient and accurate method for simulating every type of fading (e.g Nakagami-m, Weibull,... f ( y1 , y2 ) · h ( x1 , x2 ) ( n) ( n) f ( x1 , x2 ) · h ( y1 , y2 ) ( n) ( n) ,1 Note that the higher the product f ( x1 , x2 ) · h(y1 , y2 ), the lower the probability of move 18 Vehicular Technologies: Increasing Connectivity Compared with the standard MH algorithm, this version of the algorithm provides a PDF with a better match with the target distribution This is achieved by observing that... the target density f (·) However, the comparison of figures 3(a) and 3(b) shows that the (low) correlation introduced by the algorithm is completely canceled by the random shuffling 20 Vehicular Technologies: Increasing Connectivity 1.4 0.35 Theory Simulation 1.2 0.25 0.8 0.2 Θ f (θ) 1 fR(ρ) Theory Simulation 0.3 0.6 0.15 0.4 0.1 0.2 0.05 0 0 0.5 1 1.5 ρ 2 2.5 0 −4 3 −3 (a) Envelope PDF −2 −1 0 θ 1 2 . VEHICULAR TECHNOLOGIES: INCREASING CONNECTIVITY Edited by Miguel Almeida Vehicular Technologies: Increasing Connectivity Edited by Miguel Almeida Published. www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Vehicular Technologies: Increasing Connectivity, Edited by Miguel Almeida p. cm. ISBN 978-953-307-223-4 free online. a distance h T 2 (h R 2 ) from the right-hand side seen in moving direction. 2 Vehicular Technologies: Increasing Connectivity Fig. 1. Typical prop agation sc enario for V2V communicatio n s at