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- W3013142897 abstract "We introduce a new channel matrix estimation algorithm for Massive MIMO systems to reduce the required pilot symbols. The proposed method is based on Maximum A Posteriori estimation where the density of QAM transmission symbols are approximated with continuous uniform pdf. Under this simplification, joint channel source estimation problem can be posed as an optimization problem whose objective is quadratic in each channel and source symbol matrices, separately. Also, the source symbols are constrained to lie in an ℓ <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>∞</sub> -norm ball. The resulting framework serves as the channel estimation counterpart of the recently introduced compressed training based adaptive equalization framework. Numerical examples demonstrate that the proposed approach significantly reduces the required pilot length to achieve desired bit error rate performance." @default.
- W3013142897 created "2020-04-03" @default.
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- W3013142897 date "2019-11-01" @default.
- W3013142897 modified "2023-10-16" @default.
- W3013142897 title "Channel Estimation for Massive MIMO: A Semiblind Algorithm Exploiting QAM Structure" @default.
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- W3013142897 doi "https://doi.org/10.1109/ieeeconf44664.2019.9048774" @default.
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