Optimum ML Detection for DF Cooperative Diversity Networks in the Presence of Interference
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Authors
Lu, Tian
Date
2014-07-09
Type
thesis
Language
eng
Keyword
DF , Detection , Interference , ML
Alternative Title
Abstract
Unlike the existing detectors for decode-and-forward (DF) relaying in the ideal case
without interference, this thesis considers a more practical scenario where arbitrary
interference is present. We consider a DF cooperative diversity network consisting of
one source, multiple relays, one destination and multiple interferers affecting the relays
as well as the destination. Under this scenario, for the first time in the literature, we develop the exact closed-form rules for optimum maximum-likelihood (ML) detectors
for DF systems employing any one- or two-dimensional modulations in the presence
of interference. In particular, we derive the optimum ML detection rules for two
transmission schemes: simultaneous transmission and orthogonal transmission. In
each transmission scheme, we derive the detection rules by considering two different
cases of the instantaneous channel state information (CSI): the CSI of the second-hop
is known or unknown at the relays. Numerical results demonstrate that the developed
optimum detectors significantly outperform the conventional detector which simply
ignores the existence of interference.
Description
Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2014-07-09 11:59:42.106
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License
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.