04-12-2012, 01:03 PM
Investigation of Channel Adaptation and Interference for Multiantenna OFDM
[attachment=42399]
Abstract
The new use of internet through social networks, combined with popular bandwidth consuming
applications, and the need to deliver high data rate connections to highly mobile
users, is the driving force behind the requirements for future wireless networks. In this
context, spectral efficient techniques constitute vital improvements in high data rate services.
The design of robust systems is an essential factor in coping with the random and
dynamic nature of the multipath in the wireless environment.
This thesis focuses on multiantenna Orthogonal Frequency Division Multiplexing
(OFDM) processing applied with the purpose of increasing the signal strength, of boosting
the data rate, and of increasing the reliability of the wireless link. The author investigates
the interaction between different multiantenna processing algorithms and downlink
adaptive transmission, based on link quality information in time-varying channels.
A tradeoff between spatial diversity and multiplexing is offered by the linear dispersion
framework for space-frequency processing. This thesis evaluates the performance
of the unitary trace orthogonal design, along with linear receivers and channel coding,
and its interaction with link adaptation. Although this coding scheme achieves a superior
performance for low rate modes, the inter-stream interference effect on the probability of
error imposes a poor performance for high order modulations.
Introduction
Over the last two decades, wireless communications have been enthusiastically accepted by
the world’s population a large, to become an essential tool in our day-to-day lives. This
is largely due to the Second Generation (2G) wireless systems. Although 2G networks
focused on delivering speech services, the explosion of internet connections in the home,
along with increasing availability of broadband connections has created a considerable
demand for wireless data services. Moreover, bandwidth intensive or high-speed applications,
such as media streaming offered by YouTube and other media sharing sites, are
expected to drive huge demands on wireless networks’ resources, as they become available
in mobile devices. Once the growth in social networks, such as Facebook and MySpace, is
extended to wireless networks, the multimedia sharing experience enters the next level of
anytime and anywhere access to one’s community.
Motivation
Designed to enable the access to broadband connection through a cellular phone, the
Third Generation (3G) was introduced by The Third Generation Partnership Project
(3GPP). This project promised peak data rates to the order of 10 Mbit/s along with
Wideband Code Division Multiple Access (WCDMA) and High-Speed Packet Access
(HSPA) [HT04, HT06]. In parallel, other development groups within the 802 family of the Institute of Electrical and Electronics Engineers (IEEE) standards promote nomadic
broadband wireless data access that have led to the the popular Wireless Local Area
Networks (WLANs), 802.11b/g, and the fixed Worldwide Interoperability for Microwave
Access (WiMAX), known as 802.16d-2004 [IEE04].
MIMO
A MIMO system is defined as a system with multiple antennas at the receiver and transmitter
ends. Traditionally, multiple antennas were employed to shape the radiation diagram
of the antenna pattern, using a technique known as beamforming [App76]. However,
multiple antennas at the transmitter and receiver may be used to exploit array, diversity,
and/or multiplexing gains. In recent years, techniques that transmit over spatially uncorrelated
antennas have received broad attention from the research community due to their
potential to increase the reliability or the data rate of the wireless link.
Spatial diversity and multiplexing are effective techniques to increase robustness and
the data rate in wireless systems requiring low complexity. MIMO transmission schemes
that assume channel knowledge at the receiver, but not at the transmitter, mainly deliver
spatial diversity or multiplexing gains.
Spatial diversity techniques have been proposed to overcome wireless channel impairments
by providing a more reliable transmission link. Spatial diversity can be exploited
at the receiver by employing Maximal Ratio Combining (MRC) which uses the
knowledge of the channel’s coefficients to achieve both array and diversity gains. The
technique designed to encode multiantenna transmissions is referred to as Space-Time
Coding (STC) [PNG03, GSS+03]. STC schemes map the source symbols to the transmit
antennas. These schemes were popularized with the discovery of Space-Time Block
Code (STBC). STBC, introduced by [Ala98, TJC99], is an open-loop transmit diversity
scheme whose diversity gain is achieved without the knowledge of the channel at the
transmitter by employing linear receivers.
Adaptation and Scheduling
Adaptive transmission and channel-aware scheduling are techniques that use channel
knowledge at the transmitter end. On the basis of available channel sounding techniques, it
is fairly common to assume robust channel estimates at the receiver. However, to have the
channel estimates at the transmitter is cumbersome in non-reciprocal channels as in Frequency
Division Duplex (FDD). In such systems, the channel is estimated at the receiver
and a vector with the Channel State Information (CSI) is returned to the transmitter via
the feedback channel. Updating the CSI is liable to imperfections such as channel estimation
errors, quantization errors, and feedback delays [KVC02]. More specifically, in high
mobility scenarios, the rapid channel variation causes the channel information contained
in the feedback to become outdated. The effect of outdated estimates in channel statistics
affects adaptive techniques [Goe99, NAP04].
Challenges and Goals
Although extensive research has been devoted to the topics mentioned in the previous section,
several issues still remain a challenge. In the context of the state-of-the-art advances
mentioned in the previous section, we list some of the challenges facing future wireless
networks.
OFDM poses a broad area of challenges that need to be more efficiently tackled.
These include estimation of the timing phase, timing frequency, and frequency offset.
Moreover, Peak to Average Power Ratio (PAPR) reduction algorithms are required to
obtain enhanced power efficiency. In addition, ICI and ISI effects lead to new issues to
be tackled when using OFDM, combined with other techniques, such as multiantenna
processing.
Multiantenna processing algorithms continue to be developed in several approaches
and present new challenges. In fact, several issues arise in the implementation of MIMOOFDM
systems, such as channel estimation, preamble and packet design, error control
coding, and space-time techniques. Closed-loop MIMO systems such as precoding promise
significant gains in the system. However, these schemes require new approaches with
regard to complexity reduction, and limited feedback.
The design of systems that integrate several advanced adaptive techniques is a prerequisite
in future wireless networks that has not yet been fully addressed. For example,
although adaptive MIMO switching systems have been proposed, a selection of MIMO
that gives due consideration to the reliability of the channel information provided via
feedback is still an open issue. Multiuser scheduling with MIMO is another area that raises
new challenges, such as the scheduling approach in heterogeneous scenarios in which the
terminals use different MIMO techniques.
[attachment=42399]
Abstract
The new use of internet through social networks, combined with popular bandwidth consuming
applications, and the need to deliver high data rate connections to highly mobile
users, is the driving force behind the requirements for future wireless networks. In this
context, spectral efficient techniques constitute vital improvements in high data rate services.
The design of robust systems is an essential factor in coping with the random and
dynamic nature of the multipath in the wireless environment.
This thesis focuses on multiantenna Orthogonal Frequency Division Multiplexing
(OFDM) processing applied with the purpose of increasing the signal strength, of boosting
the data rate, and of increasing the reliability of the wireless link. The author investigates
the interaction between different multiantenna processing algorithms and downlink
adaptive transmission, based on link quality information in time-varying channels.
A tradeoff between spatial diversity and multiplexing is offered by the linear dispersion
framework for space-frequency processing. This thesis evaluates the performance
of the unitary trace orthogonal design, along with linear receivers and channel coding,
and its interaction with link adaptation. Although this coding scheme achieves a superior
performance for low rate modes, the inter-stream interference effect on the probability of
error imposes a poor performance for high order modulations.
Introduction
Over the last two decades, wireless communications have been enthusiastically accepted by
the world’s population a large, to become an essential tool in our day-to-day lives. This
is largely due to the Second Generation (2G) wireless systems. Although 2G networks
focused on delivering speech services, the explosion of internet connections in the home,
along with increasing availability of broadband connections has created a considerable
demand for wireless data services. Moreover, bandwidth intensive or high-speed applications,
such as media streaming offered by YouTube and other media sharing sites, are
expected to drive huge demands on wireless networks’ resources, as they become available
in mobile devices. Once the growth in social networks, such as Facebook and MySpace, is
extended to wireless networks, the multimedia sharing experience enters the next level of
anytime and anywhere access to one’s community.
Motivation
Designed to enable the access to broadband connection through a cellular phone, the
Third Generation (3G) was introduced by The Third Generation Partnership Project
(3GPP). This project promised peak data rates to the order of 10 Mbit/s along with
Wideband Code Division Multiple Access (WCDMA) and High-Speed Packet Access
(HSPA) [HT04, HT06]. In parallel, other development groups within the 802 family of the Institute of Electrical and Electronics Engineers (IEEE) standards promote nomadic
broadband wireless data access that have led to the the popular Wireless Local Area
Networks (WLANs), 802.11b/g, and the fixed Worldwide Interoperability for Microwave
Access (WiMAX), known as 802.16d-2004 [IEE04].
MIMO
A MIMO system is defined as a system with multiple antennas at the receiver and transmitter
ends. Traditionally, multiple antennas were employed to shape the radiation diagram
of the antenna pattern, using a technique known as beamforming [App76]. However,
multiple antennas at the transmitter and receiver may be used to exploit array, diversity,
and/or multiplexing gains. In recent years, techniques that transmit over spatially uncorrelated
antennas have received broad attention from the research community due to their
potential to increase the reliability or the data rate of the wireless link.
Spatial diversity and multiplexing are effective techniques to increase robustness and
the data rate in wireless systems requiring low complexity. MIMO transmission schemes
that assume channel knowledge at the receiver, but not at the transmitter, mainly deliver
spatial diversity or multiplexing gains.
Spatial diversity techniques have been proposed to overcome wireless channel impairments
by providing a more reliable transmission link. Spatial diversity can be exploited
at the receiver by employing Maximal Ratio Combining (MRC) which uses the
knowledge of the channel’s coefficients to achieve both array and diversity gains. The
technique designed to encode multiantenna transmissions is referred to as Space-Time
Coding (STC) [PNG03, GSS+03]. STC schemes map the source symbols to the transmit
antennas. These schemes were popularized with the discovery of Space-Time Block
Code (STBC). STBC, introduced by [Ala98, TJC99], is an open-loop transmit diversity
scheme whose diversity gain is achieved without the knowledge of the channel at the
transmitter by employing linear receivers.
Adaptation and Scheduling
Adaptive transmission and channel-aware scheduling are techniques that use channel
knowledge at the transmitter end. On the basis of available channel sounding techniques, it
is fairly common to assume robust channel estimates at the receiver. However, to have the
channel estimates at the transmitter is cumbersome in non-reciprocal channels as in Frequency
Division Duplex (FDD). In such systems, the channel is estimated at the receiver
and a vector with the Channel State Information (CSI) is returned to the transmitter via
the feedback channel. Updating the CSI is liable to imperfections such as channel estimation
errors, quantization errors, and feedback delays [KVC02]. More specifically, in high
mobility scenarios, the rapid channel variation causes the channel information contained
in the feedback to become outdated. The effect of outdated estimates in channel statistics
affects adaptive techniques [Goe99, NAP04].
Challenges and Goals
Although extensive research has been devoted to the topics mentioned in the previous section,
several issues still remain a challenge. In the context of the state-of-the-art advances
mentioned in the previous section, we list some of the challenges facing future wireless
networks.
OFDM poses a broad area of challenges that need to be more efficiently tackled.
These include estimation of the timing phase, timing frequency, and frequency offset.
Moreover, Peak to Average Power Ratio (PAPR) reduction algorithms are required to
obtain enhanced power efficiency. In addition, ICI and ISI effects lead to new issues to
be tackled when using OFDM, combined with other techniques, such as multiantenna
processing.
Multiantenna processing algorithms continue to be developed in several approaches
and present new challenges. In fact, several issues arise in the implementation of MIMOOFDM
systems, such as channel estimation, preamble and packet design, error control
coding, and space-time techniques. Closed-loop MIMO systems such as precoding promise
significant gains in the system. However, these schemes require new approaches with
regard to complexity reduction, and limited feedback.
The design of systems that integrate several advanced adaptive techniques is a prerequisite
in future wireless networks that has not yet been fully addressed. For example,
although adaptive MIMO switching systems have been proposed, a selection of MIMO
that gives due consideration to the reliability of the channel information provided via
feedback is still an open issue. Multiuser scheduling with MIMO is another area that raises
new challenges, such as the scheduling approach in heterogeneous scenarios in which the
terminals use different MIMO techniques.