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In MIMO communications, channel estimation is required for signal detection at the receiver.
In the case of large-scale MIMO (with an increased number of antennas), if the channel matrix is derived by inverse matrix operations, the length of the series becomes longer, and the amount of operations increases exponentially with the number of antennas.
When the measured signal is known, LSCE (Least Square Channel Estimation), which is based on the minimization of the mean square error, is used to estimate the channel matrix.
¡æWhen LSCE is used, there is a problem that the throughput is reduced due to overhead preambles.
If the probing signal is not known, LSCE cannot be used.
On the other hand, when the transmitted signal is unknown, signal detection using ICA, a type of BSS, is attracting attention
¡æThis method is useful when the signals are independent of each other, the number of signal sources is less than the number of observed data, and the probability distribution of the signals is not Gaussian.
¡æThe ICA algorithm using the fixed-point iterative method converges quickly.
¡æShort preamble length compared to the preamble length required for conventional channel estimation. |
IEEE/ICACT20230070 Slide.05
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