Book Recommendation: Advanced MIMO Systems

doi:10.4236/ijcns.2010.312122

Paper Menu >>

Journal Menu >>

Int. J. Communications, Network and System Sciences, 2010, 3, 899-900

doi:10.4236/ijcns.2010.312122 Published Online December 2010 (http://www.SciRP.org/journal/ijcns)

899

Book Recommendation: Advanced MIMO Systems

Kosai Raoof and Huaibei Zhou

Scientific Research Publishing, 2009

234 pages

ISBN: 978-1-935068-02-0

Paperback (US$80.00) E-b oo k (US $100.00)

Order online: www.scirp.org/book

Order by email: [email protected]

1. Background

During recent years, MIMO communication systems

become an important research and development subject.

Many papers are already published in the fields of chan-

nel capacity, synchronization, space time coding, etc.

The idea of this book was born during the Wicom

Conference in 2007, where many sessions have dedi-

cated to MIMO systems, dealing with physical channel

layer as well as protocol aware MIMO networks. Speak-

ing with Professor Huaibei Zhou the steering committee

chair of this outstanding international conference and Dr.

Ruoshan Kong the conference organizer, we decided to

edit and publish a book by exploiting the opportunity of

having direct contacts with the authors during the con-

ference. The proposition was to introduce recent ad-

vances in MIMO systems such as polarized MIMO sys-

tems and smart antenna selection systems, to the re-

searchers and graduate students in academic and industry

communities.

2. Introduction of Chapters

This book covers the main fields of MIMO systems with

10 chapters, each chapter covers either base-band signal

processing aspect or application. I will introduce each

chapter with few lines in order to give a global idea to

the reader.

Chapter 1 reviews most known multiple antenna

MIMO techniques for single-user point-to point systems

and multiuser systems, from how multiple antennas help

provide diversity and multiplexing to the detection tech-

niques. The space time – code is also detailed for differ-

ent structures. Finally many performance curves are also

provided to give the reader an idea about the benefits of

MIMO systems.

Chapter 2 deals with the modeling, analysis, and

simulation of multiple-input multiple-output (MIMO)

narrowband fading channels for mobile-to-mobile com-

munications. Using the wave propagation model, the

complex channel gains are derived and their statistical

properties are studied. General analytical solutions are

provided for the three-dimensional (3-D) space-time

cross-correlation function (CCF). The proposed proce-

dure provides an important framework for designers of

future mobile-to-mobile communication systems to ver-

ify new transmission concepts employing MIMO tech-

niques under realistic propagation conditions.

The purpose of chapter 3, is to introduce the capacity

of multiple antenna systems in Rayleigh fading channels.

The information theory is applied to characterize the

capacity of multi-antenna systems. Different structures of

multi-antenna systems are studied such as systems em-

ploying multiple antennas at reception, systems employ-

ing multiple antennas at transmission and systems em-

ploying multiple antennas at both transmitter and re-

ceiver sides. Two classic MIMO systems will be exam-

ined: spatial mu ltiplexing systems and sp ace-time coding

systems. The capacity of these MIMO systems is inves-

tigated in the case that the MIMO channel is perfectly

known at receivers but known or unknown at transmit-

ters.

Chapter 4 has focused on the synchronization frame-

work and algorithms for MIMO systems, especially for

frequency synchronization. Due to the application of

distributed MIMO or separated oscillators at transmit/

receive antennas in MIMO systems, multi-dimensional

frequency offset combined with unknown channel should

be considered with some signal processing approaches.

Maximum likelihood estimation as well as expectation

maximization algorithm provide the current algorithm

development in this area. The receive signal models,

schemes and algorithms along with performances for

synchron ization in MIMO-CDMA , MIMO-UW B, MIMO-

OFDM systems are also introduced.

Chapter 5 presents antenna selection technique in

MIMO systems. Although the performance of a wireless

communication system can be substantially improved by

900 K. RAOOF

implementing multiple antennas, such a system incurs

high hardware complexity. Since antennas are generally

cheaper than electronic devices, antenna selection is a

promising approach to reduce hardware complexity

while maintaining benefits of MIMO systems. In this

chapter, the application of antenna selection in MIMO

systems over fading channels is studied. The perform-

ance analysis of such MIMO system is provided with

simulation results.

Chapter 6 describes the MIMO-OFDM channel esti-

mation in multi-user systems. A generic MIMO-OFDM

channel estimator is developed for which the number of

channel estimation parameters is less dependent on the

maximum delay spread of the multi-path channel. It is

shown that the vectorization of the fading channel model

presents a preferable solution, where the CSI in the

MIMO-OFDM system can be represented in a reduced

parameter sense using an arbitrary basis.

In chapter 7, a successive interference cancellation

(SIC) based signal detector is introduced. The SIC detec-

tor is very effective in signal recovery with a complexity

close to the MMSE for varying channels. In addition, this

approach can be applied to space-frequency block codes,

time-reversal space-time block codes, and V-BLAST.

Chapter 8 presents a new concept for exploiting po-

larization diversity in MIMO systems. This subject is

recently introduced where theoretical results are so

promising to boost channel capacity. In this chapter, we

briefly present spatial multiplexing MIMO communica-

tion systems. Two MIMO channels modeling are pre-

sented for multi-elements dual-polarized MIMO systems.

These models are based on Kronecker and geome-

try-based stochastic channel models. After modeling the

MIMO channel propagation, we then proceed to the

study of the channel capacity in both cases where the

MIMO channel is perfectly known and unknown at

transmitter.

Finally, we proposed a method to determine approxi-

mately which system (uni-polarized or dual-polarized

systems) corresponds better to a propagation environ-

ment. The Cooperative Systems for Sensor Networks is

introduced in chapter 9; this is one of the direct applica-

tions of MIMO systems in the near future.

Cooperative MIMO (C-MIMO) scheme can deploy

the energy-efficiency of MIMO technique which plays

an important role in long range transmission where

transmit energy is dominant in the total consumption. In

various applications, such as area surveillance for mili-

tary operations, monitoring of agriculture related farm

duties or intelligent transportation systems, middle and

long range transmissions are indeed often required be-

cause of the large covered area of the wireless sensor

networks. An illustrative example of this cooperative

principle to MIMO systems with 3 to 8 antennas is pre-

sented, in which, an energy-efficient antenna subset se-

lection is performed followed by an iterative rate selec-

tion algorithm that selects the transmission rate for uni-

form cluster energy consumption.

In the same context, chapter 10 discusses the impact of

using MIMO physical channel on the MAC and network

layers. MIMO Aware Mobile Ad hoc NETwork (MANET)

presents a radical way to improve the performance of

wireless communications. Such systems can be utilized in

wireless ad hoc networks for improved network through-

put. The MIMO-aware MAC layer has also capabilities to

track the directional position of neighboring mobile net-

work elements of MANET and coordinating the neigh-

bors for concurrent transmission and reception to reduce

interference.

Kosai Raoof

Grenoble, France