Channel Estimation and Self-Interference Suppression for MIMO Relaying Systems
Recently, the introduction of relaying nodes in wireless channels has been identified as a promising technique for providing broader coverage, higher transmission rates, and increased reliability. Moreover, when the concept of relaying systems is combined with that of multiple-input multiple-output (MIMO) technology, the
system performance can be further improved by exploiting the spatial dimension.
This thesis investigates efficient channel estimation techniques for amplify-and-forward (AF) relaying systems. Under the deterministic framework, a Least-Squares (LS) based channel estimation algorithm is developed, providing the destination with full knowledge of all channel responses involved in the transmission. The presented analysis is complemented by deriving analytical expressions for the Cramer-Rao lower Bound (CRB) as well as the asymptotic covariance matrix of the resulting channel estimation errors.
Although the deterministic approach can facilitate all mathematical manipulations,
it does not capture the inherently random nature of wireless channels.Under the Bayesian framework, linear minimum mean square error (LMMSE) and expectation-maximization (EM) based maximum a posteriori (MAP) channel estimation algorithms are also developed, that provide the destination with full channel knowledge. The open problem of deriving analytical expressions of the Bayesian Cramer-Rao Bound (BCRB) for MIMO relaying systems is also addressed. A major difficulty in calculating the BCRB is the computation of the expectation of the Fisher Information Matrix (FIM) with respect to the unknown random parameters, since it involves a multi-dimensional integration over these parameters. Despite this inherent difficulties, some novel, explicit expressions of the BCRB are deduced for predicting and evaluating the channel estimation accuracy.
Moreover, by employing a first-order autoregressive (AR) model for characterizing the time-varying nature of the channels to be estimated, we derive an EM-based Kalman filter (KF) that utilizes the received signal at the destination to track the individual channel links. Furthermore, an alternative channel tracking
technique based on the extended KF algorithm is derived and compared with the proposed EM-based KF.
Finally, this thesis studies the feasibility of full-duplex operation by investigating spatial techniques for self-interference suppression in full-duplex MIMO relaying systems. The main goal is to show that full-duplex relays can become a feasible alternative for half-duplex relays whenever the self-interference power is adequately suppressed.
multiple-input multiple-output (MIMO)
Cramer-Rao Bound (CRB)
Kalman filter (KF)
least squares (LS)