BEM-Assisted Low-Complexity Channel Estimation for AFDM Systems over Doubly Selective Channels

In this paper, we propose a low-complexity channel estimation scheme of affine frequency division multiplexing (AFDM) based on generalized complex exponential basis expansion model (GCE-BEM) over doubly selective channels. The GCE-BEM is used to solve fractional Doppler dispersion while significantly reducing the computational complexity of exhaustive search. Then, the closed-form expression of channel estimation error is derived for the minimum mean square error (MMSE) estimation algorithm. Based on the estimated channel, the MMSE detection is adopt to characterize the impacts of estimated channel on bit error rate (BER) by deriving the theoretical lower bound. Finally, numerical results demonstrate that the proposed scheme effectively mitigates severe inter-Doppler interference (IDoI). Our theoretical performance an alysis can perfectly match the Monte-Carlo results, validating the effectiveness of our proposed channel estimation based on GCE-BEM.

Performance Analysis of BEM-based Channel Estimation for OTFS with Hardware Impairments

This letter studies the low-complexity channel estimation for orthogonal time frequency space (OTFS) in the presence of hardware impairments. Firstly, to tackle the computational complexity of channel estimation, the basis expansion model (BEM) is utilized. Then, the mean square error (MSE) of the estimated channel is theoretically derived, revealing the effects of hardware impairments on channel estimation. Based on the estimated channel, the minimum mean square error (MMSE) detector is adopted to analyze the impacts of imperfect hardware on the bit error rate (BER). Finally, the numerical results validate the correctness of our theoretical analysis of the MSE for channel estimation and lower bound of the BER, and also demonstrate that even minor hardware impairments can significantly degrade the performance of the OTFS system.