1,234 research outputs found
OFDM pilot allocation for sparse channel estimation
In communication systems, efficient use of the spectrum is an indispensable
concern. Recently the use of compressed sensing for the purpose of estimating
Orthogonal Frequency Division Multiplexing (OFDM) sparse multipath channels has
been proposed to decrease the transmitted overhead in form of the pilot
subcarriers which are essential for channel estimation. In this paper, we
investigate the problem of deterministic pilot allocation in OFDM systems. The
method is based on minimizing the coherence of the submatrix of the unitary
Discrete Fourier Transform (DFT) matrix associated with the pilot subcarriers.
Unlike the usual case of equidistant pilot subcarriers, we show that
non-uniform patterns based on cyclic difference sets are optimal. In cases
where there are no difference sets, we perform a greedy search method for
finding a suboptimal solution. We also investigate the performance of the
recovery methods such as Orthogonal Matching Pursuit (OMP) and Iterative Method
with Adaptive Thresholding (IMAT) for estimation of the channel taps
Near-optimal pilot allocation in sparse channel estimation for massive MIMO OFDM systems
Inspired by the success in sparse signal recovery, compressive sensing has already been applied for the pilot-based channel estimation in massive multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. However, little attention has been paid to the pilot design in the massive MIMO system. To obtain the near-optimal pilot placement, two efficient schemes based on the block coherence (BC) of the measurement matrix are introduced. The first scheme searches the pilot pattern with the minimum BC value through the simultaneous perturbation stochastic approximation (SPSA) method. The second scheme combines the BC with probability model and then utilizes the cross-entropy optimization (CEO) method to solve the pilot allocation problem. Simulation results show that both of the methods outperform the equispaced search method, exhausted search method and random search method in terms of mean square error (MSE) of the channel estimate. Moreover, it is demonstrated that SPSA converges much faster than the other methods thus are more efficient, while CEO could provide more accurate channel estimation performance
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