Sparse model identification of a 4x4 MIMO channel measurements in 5 GHz band
Document typeBachelor thesis
Rights accessOpen Access
The Least Absolute Shrinkage and Selection Operator has gained attention in the applied mathematics and signal processing communities. The thesis provides us theoretical expressions for solving Compressive Sensing by the LASSO algorithm for Direction of Arrival estimation. The central idea is highlight the fundamental concepts of the complex Least Absolute Shrinkage and Selection Operator (c-LASSO) and give an overview of its application to the Direction Of Arrival estimation.The role of the regularization parameter and suggestions on the selection are exposed. It is found that LASSO can be compared with Conventional beamforming and Least Squares. The presented results in the context of Direction of Arrival (DOA) single snapshot estimation using a 4 antenna linear sensor array.
Channel data measurement and tap estimation with the LASSO estimator/ detector (Least Absolute Shrinkage and Selection Operator).