Abstract
In MIMO detection, the signals transmitted by multiple antennas can be detected jointly based on the ML principle for optimal performance. However, its complexity is prohibitively high for a large number of transmit antennas and a higher order modulation method. There are suboptimal approaches of low complexity. Unfortunately, they cannot exploit a full receive diversity gain, which results in the performance gap between the ML and suboptimal approaches (e.g., linear MMSE detection). This gap usually increases with SNR. Therefore, it is desirable to find some new detection methods that can provide near ML performance with low complexity which is comparable to that of linear detectors. In this chapter, we introduce two key ingredients: list decoding and lattice (basis) reduction, which can be used to develop different computationally efficient algorithms with reasonably good performance.
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© 2012 Springer Science+Business Media, LLC
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Bai, L., Choi, J. (2012). List and Lattice Reduction-Based Methods. In: Low Complexity MIMO Detection. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8583-5_3
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DOI: https://doi.org/10.1007/978-1-4419-8583-5_3
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Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-8582-8
Online ISBN: 978-1-4419-8583-5
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