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Channel estimation for massive MIMO : a semiblind algorithm exploiting QAM structure

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Yılmaz, Baki Berkay

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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(infinity)-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.

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IEEE

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Computer science, Information systems, Engineering, Electrical electronic engineering, Telecommunications

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Conference Record of The 2019 Fifty-Third Asilomar Conference on Signals, Systems and Computers

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10.1109/IEEECONF44664.2019.9048774

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