MIMO Wireless Technology Seminar report
ABSTRACT
This paper presents measured data at 2.45 GHz from a narrowband multiple-input multiple-output MIMO) channel probe in an indoor office/laboratory environment. The measured transfer matrices are used in a study of the statistical behavior of the channel capacity. The effect of antenna element polarization and array size are highlighted. The data is also used to validate a simple statistically based physical propagation model.
INTRODUCTION
In radio, multiple-input and multiple-output, or MIMO (commonly pronounced my-moh or me-moh), is the use of multiple antennas at both the transmitter and receiver to improve communication performance. It is one of several forms of smart antenna technology.
MIMO technology has attracted attention in wireless communications, because it offers significant increases in data throughput and link range without additional bandwidth or transmit power. It achieves this by higher spectral efficiency (more bits per second per hertz of bandwidth) and link reliability or diversity (reduced fading). Because of these properties, MIMO is a current theme of international wireless research.
The increasing demand for capacity in wireless systems has motivated considerable research aimed at achieving higher throughput on a given bandwidth. One important recent discovery shows that in a multipath environment, the use of space-time coding with multiple antennas on both ends of the link can increase the capacity of the wireless channel.
Assessing the performance of these algorithms requires detailed understanding of multiple-input multiple-output (MIMO) channels as well as models that capture their complex spatial behavior. In this work, we discuss data from an experimental platform designed to measure the transfer matrix for indoor MIMO channels. The data is used to demonstrate the effect of polarization and array size on the achievable capacity for MIMO architectures. A propagation-based statistical model is shown to provide results that match closely with measured observations.
References:
* MIMO Wireless Technology Complete Seminar report
* http://rp.iszf.irk.ru/hawk/URSI2002/URSI-GA/papers/p0471.pdf
* http://en.wikipedia.org/wiki/MIMO
* http://www.ece.ualberta.ca/~HCDC/mimohistory.html
ABSTRACT
This paper presents measured data at 2.45 GHz from a narrowband multiple-input multiple-output MIMO) channel probe in an indoor office/laboratory environment. The measured transfer matrices are used in a study of the statistical behavior of the channel capacity. The effect of antenna element polarization and array size are highlighted. The data is also used to validate a simple statistically based physical propagation model.
INTRODUCTION
In radio, multiple-input and multiple-output, or MIMO (commonly pronounced my-moh or me-moh), is the use of multiple antennas at both the transmitter and receiver to improve communication performance. It is one of several forms of smart antenna technology.
MIMO technology has attracted attention in wireless communications, because it offers significant increases in data throughput and link range without additional bandwidth or transmit power. It achieves this by higher spectral efficiency (more bits per second per hertz of bandwidth) and link reliability or diversity (reduced fading). Because of these properties, MIMO is a current theme of international wireless research.
The increasing demand for capacity in wireless systems has motivated considerable research aimed at achieving higher throughput on a given bandwidth. One important recent discovery shows that in a multipath environment, the use of space-time coding with multiple antennas on both ends of the link can increase the capacity of the wireless channel.
Assessing the performance of these algorithms requires detailed understanding of multiple-input multiple-output (MIMO) channels as well as models that capture their complex spatial behavior. In this work, we discuss data from an experimental platform designed to measure the transfer matrix for indoor MIMO channels. The data is used to demonstrate the effect of polarization and array size on the achievable capacity for MIMO architectures. A propagation-based statistical model is shown to provide results that match closely with measured observations.
References:
* MIMO Wireless Technology Complete Seminar report
* http://rp.iszf.irk.ru/hawk/URSI2002/URSI-GA/papers/p0471.pdf
* http://en.wikipedia.org/wiki/MIMO
* http://www.ece.ualberta.ca/~HCDC/mimohistory.html
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