NDLI: Reduced Complexity Decoder for Orthogonal Space-Time Codes When Using QAM Constellations and Multiple Receive Antennas

Content Provider	IEEE Xplore Digital Library
Author	Enescu, A.A. Ciochinǎ, S. Paleologu, C.
Copyright Year	2010
Abstract	Space-time block coding represents a practical and pragmatic method to mitigate the fading effects and to increase the channel capacity, by using spatial diversity. The space-time coding techniques are still preferred in communication systems because of the very simple transmit coding rule and of the relative reduced complexity of the maximum likelihood (ML) receivers with respect to other coding methods (e.g., space-time trellis codes) or other MIMO (Multiple Input Multiple Output) algorithms (e.g., spatial multiplexing). One of the drawbacks when using space-time block codes is the increase in complexity at the ML receiver when increasing the number of transmit antennas and the number of constellation points. This paper deals with this issue and introduces a decoding algorithm applicable only for orthogonal space-time block codes. We show that this decoding algorithm reduces the search space dimension of a regular ML receiver, leading to significant complexity reduction for quadrature amplitude modulation (QAM) constellations. The algorithm is then extended to an arbitrary number of receive antennas, increasing the spatial diversity order.
Starting Page	143
Ending Page	148
File Size	280342
Page Count	6
File Format	PDF
ISBN	9781424472710
e-ISBN	9781424472727
DOI	10.1109/ICDT.2010.34
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-13
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Space time codes Quadrature amplitude modulation Receiving antennas Maximum likelihood decoding Block codes MIMO Fading Channel capacity Convolutional codes Transmitting antennas spatial diversity Alamouti code maximum likelihood (ML) decoding orthogonal space-time codes
Content Type	Text
Resource Type	Article

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