Parameter Estimation and Error Reduction for OFDM-Based WLANs
IEEE Transactions on Mobile Computing
An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
IEEE Transactions on Signal Processing - Part II
OFDM channel estimation in the presence of interference
IEEE Transactions on Signal Processing
Iterative Joint Channel Estimation and Multi-User Detection for Multiple-Antenna Aided OFDM Systems
IEEE Transactions on Wireless Communications
Robust LS channel estimation with phase rotation for single frequency network in OFDM
IEEE Transactions on Consumer Electronics
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OFDM modulation combines advantages of high achievable data rates and relatively easy implementation. However, for proper recovery of input, the OFDM receiver needs accurate channel information. Most algorithms proposed in literature perform channel estimation in time domain which increases computational complexity in multi-access situations where the user is only interested in part of the spectrum. In this paper, we propose a frequency domain algorithm for channel estimation in OFDMA systems. The algorithm performs eigenvalue decomposition of channel autocorrelation matrix and approximates channel frequency response seen by each user using the first few dominant eigenvectors. In a time variant environment, we derive a state space model for the evolution of the eigenmodes that help us to track them. This is done using a forward backward Kalman filter. The performance of the algorithm is further improved by employing a data-aided approach (based on expectation maximization).