MIMO Systems: Principles, Iterative Techniques, and advanced Polarization

International audienceThis chapter considers the principles of multiple-input multiple-output (MIMO) wireless communication systems as well as some recent accomplishments concerning their implementation. By employing multiple antennas at both transmitter and receiver, very high data rates can be achieved under the condition of deployment in a rich-scattering propagation medium. This interesting property of MIMO systems suggests their use in the future high-rate and high-quality wireless communication systems. Several concepts in MIMO systems are reviewed in this chapter. We first consider MIMO channel models and recall the basic principles of MIMO structures and channel modeling. We next study the MIMO channel capacity and present the early developments in these systems concerning the information theory aspect. Iterative signal detection is considered next; it considers iterative techniques for space-time decoding. As the capacity is inversely proportional to the spatial channel correlation, MIMO antennas should be sufficiently separated, usually by several wavelengths. In order to minimize antennas' deployment, we present advanced polarization diversity techniques for MIMO systems and explain how they can help to reduce the spatial correlation in order to achieve high transmission rates. We end the chapter by considering the application of MIMO systems in local area networks, as well as their potential in enhancing range, localization, and power efficiency of sensor networks

Advanced MIMO Techniques: Polarization Diversity and Antenna Selection

International audienceThis chapter is attempted to provide a survey of the advanced concepts and related issues involved in Multiple Input Multiple Output (MIMO) systems. MIMO system technology has been considered as a really significant foundation on which to build the next and future generations of wireless networks. The chapter addresses advanced MIMO techniques such as polarization diversity and antenna selection. We gradually provide an overview of the MIMO features from basic to more advanced topics. The first sections of this chapter start by introducing the key aspects of theMIMO theory. TheMIMO systemmodel is first presented in a genericway. Then, we proceed to describe diversity schemes used in MIMO systems. MIMO technology could exploit several diversity techniques beyond the spatial diversity. These techniques essentially cover frequency diversity, time diversity and polarization diversity. We further provide the reader with a geometrically based models for MIMO systems. The virtue of this channel modeling is to adopt realisticmethods for modeling the spatio-temporal channel statistics from a physical wave-propagation viewpoint. Two classes for MIMO channel modeling will be described. These models involve the Geometry-based Stochastic ChannelModels (GSCM) and the Stochastic channel models. Besides the listedMIMO channel models already described, we derive and discuss capacity formulas for transmission over MIMO systems. The achieved MIMO capacities highlight the potential of spatial diversity for improving the spectral efficiency of MIMO channels. When Channel State Information (CSI) is available at both ends of the transmission link, the MIMO system capacity is optimally derived by using adaptive power allocation based on water-filling technique. The chapter continues by examining the combining techniques for multiple antenna systems. Combining techniques are motivated for MIMO systems since they enable the signal to noise ratio (SNR) maximization at the combiner output. The fundamental combing techniques are the Maximal Ratio Combining (MRC), the Selection Combining (SC) and the Equal Gain Combining(EGC). Once the combining techniques are analyzed, the reader is introduced to the beamforming processing as an optimal strategy for combining. The use of multiple antennas significantly improves the channel spectral efficiency. Nevertheless, this induces higher system complexity of the communication system and the communication system performance is effected due to correlation between antennas that need to be deployed at the same terminal. As such, the antenna selection algorithm for MIMO systems is presented. To elaborate on this point, we introduce Space time coding techniques for MIMO systems and we evaluate by simulation the performance of the communication system. Next, we emphasis on multi polarization techniques for MIMO systems. As a background, we presume that the reader has a thorough understanding of antenna theory. We recall the basic antenna theory and concepts that are used throughout the rest of the chapter. We rigorously introduce the 3D channel model over the Non-Line of Sight (NLOS) propagation channel for MIMO system with polarized antennas. We treat the depolarization phenomena and we study its effect on MIMO system capacity. The last section of the chapter provides a scenario for collaborative sensor nodes performing distributed MIMO system model which is devoted to sensor node localization in Wireless Sensor Networks. The localization algorithm is based on beamforming processing and was tested by simulation. Our chapter provides the reader by simulation examples for almost all the topics that have been treated for MIMO system development and key issues affecting achieved performance

Modélisation et étude de la capacité du canal pour un système multi-antennes avancé exploitant la diversité de polarisation

At present, there is a high demand for an increasing data rate transmission over wireless communication systems, in order to serve a recent development of multimedia applications on terminals. In 1996, one important technique was proposed by Bell laboratory researchers in order to improve data throughput and quality without increasing additional bandwidth and power of transmission. The basic aim of this technique is to create the independent sub-channels by using multiple antennas at the transmitter and receiver sides (MIMO). However, MIMO systems suffer from the correlation between the sub-channels that might occur, especially, when the distance between antennas is limited and when the angular spread is narrow. This incident affects the performance of MIMO systems. Therefore, the main objective of this thesis is to implement a MIMO system with polarization diversity so as to reduce the correlation between the sub-channels under physical limitation of antenna array size. The research presented in this thesis is composed of three main parts. First of all, a three dimensional modelling of the MIMO transmission channel is proposed. In order to accurate the channel, was taken into account the characteristic of the antenna polarization. Secondly, the channel capacity for the multiple antenna systems employing single polarized antennas is examined. Finally, we extend our study by focusing on the multiple antenna systems with the polarization diversity such as MIMO systems with double polarization, triple polarization and sextuple polarization.Depuis quelques années, il y a une exigence accrue quant à la rapidité de transferts d'information, notamment, en raison de la généralisation des applications multimédia sur le système de communication sans fil. Pour y remédier, les chercheurs du laboratoire Bell en 1996 ont proposé une technique d'emploi simultané de réseaux d'antennes en émission et en réception (MIMO). Le canal MIMO est alors constitué par un ensemble de sous-canaux. Grâce à cette technique, le débit et la qualité de transmission peuvent être améliorés sans augmenter la puissance de transmission et la bande passante supplémentaires. Cependant, les gains obtenus par ce système peuvent se diminuer en raison de la corrélation entre les sous-canaux du canal MIMO, en particulier, si la séparation entre antennes est limitée et l'étalement angulaire est étroit. Donc, l'objectif des travaux réalisés dans le cadre de cette thèse est de proposer un système MIMO à diversité de polarisation qui permet de réduire la corrélation entre les sous-canaux et en même temps de miniaturiser la taille des réseaux d'antennes. Le travail présenté dans cette thèse est d'abord consacré à la caractérisation et à la modélisation du canal de transmission compte tenu des diverses composantes de polarisation des antennes à trois dimensions. Est traitée également l'étude comparative de la capacité de deux types de systèmes de communication multi-antennes. D'une part, il s'agit du système de communication multi-antennes à polarisation unique : dans ce système, sont exploités des antennes ayant les mêmes polarisations. D'autre part, sont examinés les systèmes à polarisation multiple, à savoir, les systèmes MIMO à double polarisation, à triple polarisation et à sextuple polarisation

Modélisation et étude de la capacité du canal pour un système multi-antennes avancé exploitant la diversité de polarisation

Depuis quelques années, il y a une exigence accrue quant à la rapidité de transferts d'information, notamment, en raison de la généralisation des applications multimédia sur le système de communication sans fil. Pour y remédier, les chercheurs du laboratoire Bell en 1996 ont proposé une technique d'emploi simultané de réseaux d'antennes en émission et en réception (MIMO). Le canal MIMO est alors constitué par un ensemble de sous-canaux. Grâce à cette technique, le débit et la qualité de transmission peuvent être améliore s sans augmenter la puissance de transmission et la bande passante supplémentaires. Cependant, les gains obtenus par ce système peuvent se diminuer en raison de la corrélation entre les sous-canaux du canal MIMO, en particulier, si la séparation entre antennes est limitée et l'étalement angulaire est étroit. Donc, l'objectif des travaux réalisés dans le cadre de cette thèse est de proposer un système MIMO à diversité de polarisation qui permet de réduire la corrélation entre les sous-canaux et en même temps de miniaturiser la taille des réseaux d'antennes. Le travail présenté dans cette thèse est d'abord consacré à la caractérisation et à la modélisation du canal de transmission compte tenu des diverses composantes de polarisation des antennes à trois dimensions. Est traitée également l'étude comparative de la capacité de deux types de systèmes de communication multi-antennes. D'une part, il s'agit du système de communication multi-antennes à polarisation unique : dans ce système, sont exploités des antennes ayant les mêmes polarisations. D'autre part, sont examinés les systèmes à polarisation multiple, à savoir, les systèmes MIMO à double polarisation, à triple polarisation et à sextuple polarisation.At present, there is a high demand for an increasing data rate transmission over wireless communication systems, in order to serve a recent development of multimedia applications on terminals. In 1996, one important technique was proposed by Bell laboratory researchers in order to improve data throughput and quality without increasing additional bandwidth and power of transmission. The basic aim of this technique is to create the independent sub-channels by using multiple antennas at the transmitter and receiver sides (MIMO). However, MIMO systems suffer from the correlation between the sub-channels that might occur, especially, when the distance between antennas is limited and when the angular spread is narrow. This incident affects the performance of MIMO systems. Therefore, the main objective of this thesis is to implement a MIMO system with polarization diversity so as to reduce the correlation between the sub-channels under physical limitation of antenna array size. The research presented in this thesis is composed of three main parts. First of all, a three dimensional modelling of the MIMO transmission channel is proposed. In order to accurate the channel, was taken into account the characteristic of the antenna polarization. Secondly, the channel capacity for the multiple antenna systems employing single polarized antennas is examined. Finally, we extend our study by focusing on the multiple antenna systems with the polarization diversity such as MIMO systems with double polarization, triple polarization and sextuple polarization.GRENOBLE1-BU Sciences (384212103) / SudocSudocFranceF

On Capacity of Multi-Element Dual Polarized Antenna Systems

This chapter considers the principles of multiple-input multiple-output (MIMO) wireless communication systems. The pioneering idea of MIMO systems is that multiple transmit antennas are used to combat fading without expanding the bandwidth of the transmitted signal while multiple receive antennas are used to increase the signal-to-noise ratio at the receiver. These systems increase the reliability of system transmission, called diversity gain. However, Many authors proposed the use of multiple antennas at both transmitter and receiver in order to increase the data rate by creating multiple spatial channels. In particular, with N transmitting and N receiving antennas, it is possible to achieve an N-times capacity of single transmitting and single receiving antenna (SISO) systems, multiplexing gain. However, from many experimental campaigns, the MIMO multiplexing and/or diversity gain cannot be effectively achieved because the antenna correlation appears at transmitter or/and receiver sides due to a limited number of physical parameters such as antenna array configuration and propagation channel characteristics. Thus, the use of co-located orthogonally-polarized antennas allows reducing the antenna space and the effective cost. It can give better offer when the co-polar polarized channels are highly correlated. We carry out the basic MIMO system in order to understand the general principle of MIMO wireless communication. Then two MIMO channel models are developed for the multi-polarized MIMO channels. The general information theory for MIMO systems is briefly discussed. Finally, the dual-polarized MIMO gain in accordance with the single-polar MIMO systems and the upper capacity bound are also developed

Capacity of Multiple Antenna Systems in Rayleigh Fading Channels

In this chapter, we start from some introduction of the information theory which make it possible to characterize the capacity of multi-antenna systems. Different structures of multi- antenna systems will be studied such as the systems employing multiple antennas at reception, the systems employing multiple antennas at transmission et the systems employing multiple antennas at both transmitter and receiver sides. Two classic MIMO systems will be exami- ned : spatial multiplexing systems and space-time coding systems. The capacity of these MIMO systems is investigated in the case that the MIMO channel is perfectly known at receiver but known or unknown at transmitter

Impact of Depolarization Phenomena on Polarized MIMO Channel Performances

International audienceThe performance and capacity of multiple-input multiple-output (MIMO) wireless channels are limited by the spatial fading correlation between antenna elements. This limitation is due to the use of mono polarized antennas at receiver and transmitter sides. In this paper, in order to reduce the antenna correlation, the polarization diversity technique is employed. Although the spatial antenna correlation is attenuated for multipolarization configurations, the cross-polar components appear. This paper highlights the impact of depolarization effect on the MIMO channel capacity for a 4×4 uniform linear antenna array. We assume that the channel is unknown at the transmitter and perfectly known at the receiver so that equal power is distributed to each of the transmit antennas. The numerical results illustrate that for low depolarization and spatial correlation, the capacity of single-polarization configuration behaves better than that of multipolarization configuration

Impact of depolarization effects on MIMO polarized wireless configuration

International audienceOn wireless communication systems, multiple-input multiple-output (MIMO) systems have dramatically the potential to improve the reliability and the performance. However, the MIMO wireless channel performance is generally affected by the antenna array configuration and environment characteristic. This paper highlights the impact of angle spread and depolarization effects on the MIMO channel capacity with a focus on 4×4 uniform linear multi-polarized antenna array. We employ a geometric scattering model based on a three-dimensional double bouncing model that takes into account the antenna configurations. We investigate the use of multi-polarization configurations that can provide capacity improvement over conventional single-polarization configurations. The single-polarization configuration is dependent on the depolarization phenomena. It is found that when low depolarization and spatial corre-lation effects, the capacity of single-polarization con-figuration behaves better than that of multi-polarization configuration

Antenna Selection for MIMO Systems in Correlated Channels with diversity technique

International audienceIn recent years, due to the increasing demand of the data transmission rate, a lot of research based on Multiple-Input Multiple-Output (MIMO) system is established. MIMO systems can increase the system capacity and improve transmission reliability. However, the multiple RF chains associated with multiple antennas are costly in terms of size, power and hardware. Antenna selection techniques have been applied in MIMO system design to reduce the system complexity and cost. In this paper, we consider two schemes of antenna selection in correlated Rayleigh channels i.e. the maximal ratio transmission and Orthogonal Space-Time Block Code technique. The simulation results illustrate that; the new antenna selection scheme can obtain performance close to the optimum selection with low computational complexity