Blind sparse channel estimation for Ultra Wide-Band communications based on representative subspace fitting
Lei Yang · Journal of Anhui University · 2007
In this paper,a novel blind channel estimation algorithm is proposed for TH-PPM Ultra Wide-Band communications based on first-order statistics and representative subspace fitting by exploiting the sparsity property of channel impulse response.Firstly,the channel frequency response is derived by exploiting the cyclic convolution property of the receive signal's expectation.Secondly,the representative subspace fitting algorithm is developed to detect the position of the nonzero tap coefficients,and then the least square algorithm is used to estimate the exact value of the nonzero coefficients,so as to improve the performance of the algorithm by avoiding estimating the zero coefficients.The algorithm's complexity is low for using chip-rate sampling and only some overlap-add operations and discrete Fourier transform operations and so on are needed.Simulation results demonstrate that it has better MSE and BER performance than the first-order blind channel estimation which didn't make use of the sparse structure of the channel.