Convex optimization in wireless CDMA receiver design

The objective of this work is the development of cross-layer network receiver designs for wireless CDMA communications with a special emphasis given to high-dimensional adaptive processing under small sample support (e.g. rapidly-changing environments). In this work, we propose a quadratically-constrained MVDR/MMSE filter in an effort to achieve superior filtering performance under limited sample support adaptations. The quadratically-constrained MVDR/MMSE filter estimator utilizes a parameterized estimate of the input covariance matrix that is given as a convex combination of the sample-average covariance matrix and a scalar multiple of its inverse. Selection methods based on the limited sample support are proposed for both the inverse matrix multiplicative scalar as well as the convex parameter, and they can be applied more generally to other adaptive decision techniques such as selection of the diagonally-loaded MVDR parameter.