Channel Estimation

Implementation of Greedy Algorithms for LTE Sparse Channel Estimation

Sparsity in the impulse response of wireless channels can be exploited to de-noise the estimate and thus improve the performance of wireless links. Three algorithms developed in the compressive sensing framework were implemented in ASICs to perform this denoising operation: Matching pursuit (MP), gradient pursuit (GP), and orthogonal matching pursuit (OMP).

Authors: Patrick Maechler, Pierre Greisen, Benjamin Sporrer, Sebastian Steiner, Norbert Felber, and Andreas Burg.

Abstract: 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.

The paper is:

P. Maechler, P. Greisen, B. Sporrer, S. Steiner, N. Felber, and A. Burg: Implementation of greedy algorithms for LTE sparse channel estimation, Proc. 44th Asilomar Conf. Signals, Systems and Computers, Nov. 2010, 400-405

An earlier paper focusing on matching pursuit is:

P. Maechler, P. Greisen, N. Felber, and A. Burg: Matching Pursuit: Evaluation and Implementation for LTE Channel Estimation, Proc. ISCAS, May 2010, 589-592