Estimation and Performance Analysis of Wireless Multiple Antenna Communication Channels

• The focus of this thesis is on channel estimation in wireless communication systems that employ multiple antennas.The thesis is divided into two parts, whereof the first part addresses theproblem of parameter estimation of distributed sources. Due to, e.g., localscattering around the transmitter, the source (as seen from the receiver)appears spatially distributed. A characterization of the spatial channel, inparticular mean direction of arrival and spatial spread, is of interest for optimizationand performance prediction of future communication systems. Nonparametricbeamforming-based estimators are derived and analyzed for thelocalization of distributed sources, and it is found that they provide goodestimation performance. Parametric generalized beamformers are also presentedand analyzed. It is found that they also yield competitive performancecompared to existing algorithms.The second part of the thesis deals with Multiple-Input Multiple-Output(MIMO) and Single-Input Single-Output (SISO) channel estimation. A simpleand straightforward way of estimating the unknown channel is to transmitknown training/pilot sequences. In the recent past, a number of publicationshave suggested Superimposed Pilots (SIP) for channel estimation in communicationsystems. However, the performance gain achieved by SIP comparedto conventional (time-multiplexed) training is still questionable. To evaluatethe performance of the various training-based schemes, a lower bound on the mutual information of a general training-based scheme applied to block-wise fading MIMO and SISO channels is derived and maximized. It is found that in certain scenarios it is beneficial to also transmit data during the training mode (i.e., use SIP). The main conclusion though, is that the general SIP-scheme quite often reduces to the conventional time-multiplexed scheme, and, hence, renders the same performance. The theory is also extended to the case when detected data symbols are used as additional training symbols, which significantly improves the channel estimation performance. An improved channel estimate leads to an improvement in the effective Signa-lto-Noise Ratio (SNR), and, thus, a higher coding rate may successfully be applied. The extended scheme shows a performance close to the fundamental capacity of the noncoherent MIMO channel.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Keyword

capacity

Wireless communications

performance bounds

distributed sources

generalized beamforming

channel estimation

MIMO

training

Publication and Content Type

dok (subject category)

vet (subject category)