A large-scale MIMO low-complexity channel estimation method based on weighted kapetyn series expansion
A channel estimation, low-complexity technology, applied in the field of low-complexity channel estimation algorithms, can solve the problems of high complexity, reduced computational complexity, and large estimation error of Kapetyn series expansion, so as to improve accuracy and speed up convergence. Effect
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[0048] The present invention will be further described below in conjunction with the accompanying drawings.
[0049] Concrete steps of the present invention include:
[0050] 1) Let the received signal model be:
[0051] Y=HP+N
[0052] where Y represents the received signal, H represents the MIMO channel matrix under quasi-static flat fading channel conditions, where N r Represents the number of receiving antennas on the base station side, N t represents the number of transmitting antennas, R represents the channel covariance matrix, P represents the pilot signal matrix of the transmitter, N is an additive noise signal that obeys a cyclic symmetric complex Gaussian random distribution.
[0053] To vectorize the received signal, define the form of the pilot matrix as Then the above formula can be transformed into the following vector form:
[0054]
[0055] 2) Using the traditional MMSE channel estimation algorithm, the channel estimation matrix can be derived...
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