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Iterative Soft Decision Based Complex K-best MIMO Decoder
Mehnaz Rahman, Gwan S. Choi
Pages - 54 - 65 | Revised - 31-10-2015 | Published - 30-11-2015
Published in Signal Processing: An International Journal (SPIJ)
MORE INFORMATION
KEYWORDS
Complex K-best Algorithm, MIMO, Lattice Reduction, Iterative Soft Decoding, SE Enumeration.
ABSTRACT
This paper presents an iterative soft decision based complex multiple input multiple output (MIMO) decoding algorithm, which reduces the complexity of Maximum Likelihood (ML) detector. We develop a novel iterative complex K-best decoder exploiting the techniques of lattice reduction for 8×8 MIMO. Besides list size, a new adjustable variable has been introduced in order to control the on-demand child expansion. Following this method, we obtain 6.9 to 8.0 dB improvement over real domain K-best decoder and 1.4 to 2.5 dB better performance compared to iterative conventional complex decoder for 4th iteration and 64-QAM modulation scheme. We also demonstrate the significance of new parameter on bit error rate. The proposed decoder not only increases the performance, but also reduces the computational complexity to a certain level.
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Mr. Mehnaz Rahman
Texas A&M University - United States of America
mehnaz@tamu.edu
Dr. Gwan S. Choi
Department of ECE Texas A&M University College Station, Tx- 77840, USA - United States of America
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