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Reduction of ML Decoding Complexity for MIMO Sphere Decoding, QOSTBC, and OSTBC
 

Summary: Reduction of ML Decoding Complexity for MIMO
Sphere Decoding, QOSTBC, and OSTBC
Luay Azzam and Ender Ayanoglu
Center for Pervasive Communications and Computing
Department of Electrical Engineering and Computer Science
University of California, Irvine
email: lazzam@uci.edu, ayanoglu@uci.edu
Abstract-- In this paper, we discuss three applications of the
QR decomposition algorithm to decoding in a number of Multi-
Input Multi-Output (MIMO) systems. In the first application,
we propose a new structure for MIMO Sphere Decoding (SD).
We show that the new approach achieves 80% reduction in the
overall complexity compared to conventional SD for a 2 2
system, and almost 50% reduction for the 4 4 and 6 6
cases. In the second application, we propose a low complexity
Maximum Likelihood Decoding (MLD) algorithm for quasi-
orthogonal space-time block codes (QOSTBCs). We show that for
N = 8 transmit antennas and 16-QAM modulation scheme, the
new approach achieves > 97% reduction in the overall complexity
compared to conventional MLD, and > 89% reduction compared

  

Source: Ayanoglu, Ender - Department of Electrical and Computer Engineering, University of California, Irvine

 

Collections: Engineering