Interference Cancellation Information Geometry Approach for Massive MIMO Channel Estimation
<|reference_start|>Interference Cancellation Information Geometry Approach for Massive MIMO Channel Estimation: In this paper, the interference cancellation information geometry approaches (IC-IGAs) for massive MIMO channel estimation are proposed. The proposed algorithms are low-complexity approximations of the minimum mean square error (MMSE) estimation. To illustrate the proposed algorithms, a unified framework of the information geometry approach for channel estimation and its geometric explanation are described first. Then, a modified form that has the same mean as the MMSE estimation is constructed. Based on this, the IC-IGA algorithm and the interference cancellation simplified information geometry approach (IC-SIGA) are derived by applying the information geometry framework. The a posteriori means on the equilibrium of the proposed algorithms are proved to be equal to the mean of MMSE estimation, and the complexity of the IC-SIGA algorithm in practical massive MIMO systems is further reduced by considering the beam-based statistical channel model (BSCM) and fast Fourier transform (FFT). Simulation results show that the proposed methods achieve similar performance as the existing information geometry approach (IGA) with lower complexity.<|reference_end|>
@article{lu2024interference,
    title={Interference Cancellation Information Geometry Approach for Massive MIMO
  Channel Estimation},
    author={An-An Lu, Bingyan Liu, Xiqi Gao},
    journal={arXiv preprint arXiv:2406.19583},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.19583},
    primaryClass={cs.IT math.IT}
}