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Content Provider | IEEE Xplore Digital Library |
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Author | Boyu Li Ayanoglu, E. |
Copyright Year | 2011 |
Description | Author affiliation: Center for Pervasive Communications and Computing, Department of Electrical Engineering and Computer Science, The Henry Samueli School of Engineering, University of California - Irvine, 92697-2625, USA (Boyu Li; Ayanoglu, E.) |
Abstract | In Multiple-Input Multiple-Output (MIMO) systems, Sphere Decoding (SD) can achieve performance equivalent to full search Maximum Likelihood (ML) decoding with reduced complexity. Several researchers reported techniques that reduce the complexity of SD further. In this paper, a new technique is introduced which decreases the computational complexity of SD substantially, without sacrificing performance. The reduction is accomplished by deconstructing the decoding metric to decrease the number of computations and exploiting the structure of a lattice representation. Simulation results show that this approach achieves substantial gains for the average number of real multiplications and real additions needed to decode one transmitted vector symbol. As an example, for a 4 × 4 MIMO system, the gains in the number of multiplications are 85% with 4-QAM and 90% with 64-QAM, at low SNR. |
Starting Page | 147 |
Ending Page | 151 |
File Size | 703695 |
Page Count | 5 |
File Format | |
ISBN | 9781424495399 |
e-ISBN | 9781424495382 |
DOI | 10.1109/IWCMC.2011.5982522 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-07-04 |
Publisher Place | Turkey |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | SD Lattices Modulation ML Decoding MIMO Complexity theory Low Computational Complexity Maximum likelihood decoding Signal to noise ratio |
Content Type | Text |
Resource Type | Article |
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