Implementation of greedy algorithms for LTE sparse channel estimation

Broadband wireless systems often operate under channel conditions that are characterized by a sparse channel impulse response. When the amount of training is given by the standard, compressed sensing channel estimation can exploit this sparsity to improve the quality of the channel estimate. In this paper, we analyze and compare the hardware complexity and denoising performance of three greedy algorithms for the 3GPP LTE system. The complexity/performance trade-off is analyzed using parameterized designs with varying configurations. One configuration of each algorithm is fabricated in a 180nm process and measured.