Abstract—In this paper, a compensation estimation algorithm is developed for Multiple-Input–Multiple-Output (MIMO) Orthogonal Frequency-Division-Multiplexing (OFDM) systems operating in a fast fading environment. In order to satisfy the constraint frequency mask, the pulse signal spectrum must be limited in the mask band. We investigate a channel estimator that exploit channel sparsity in the time and/or Doppler domain, where the channel is described by a limited number of paths, each characterized by a delay, Doppler scale, and attenuation factor, and derive the exact inter-carrier-interference pattern. The algorithm works with channel sparsity by jointly estimating the sparse coefficients vector and by reconstructing dynamic mathematical model of pulse wave functions. The proposed method exploits the intrinsic relationship between the sparse channels and the mathematical model. A dynamic mathematical model of pulse wave functions is used to construct the sparse channels. The dynamic mathematical model reconstruction is used to update the sensing matrix. The pulse signal which is band and time concentrated distribution, is conducive to optimization design of sparse MIMO-OFDM channel. The simulation results show that the proposed channel estimator can provide a considerable performance improvement in estimating doubly selective channels with few pilots and computational complexity.
Index Terms—Compressed sensing, sparse channel, channel estimation, fast fading
Cite: Xiaoping. Zhou, Zhongxiao. Zhao, Li. Li, and Si. Li, "Compensation Estimation Method for Fast Fading MIMO-OFDM Channels Based on Compressed Sensing," Journal of Communications, vol. 10, no. 7, pp. 466-473, 2015. Doi: 10.12720/jcm.10.7.466-473
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