Towards closing the gap between MOE and subspace methods

Abstract

In this paper, we propose a power of R (POR) technique to significantly improve the performance of the minimum output energy (MOE) receiver. The new receiver is shown to asymptotically converge to the MMSE receiver. The convergence is established either under high SNR, or with large exponent raised in the power of the covariance matrix. Connection between the POR method and a subspace method is investigated, and their asymptotic equivalence is also established. However, the POR receiver does not require either a computationally expensive subspace decomposition of a data covariance matrix, or estimation of dimension of either the signal subspace or the noise subspace.