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In this article, a novel low-complexity block-processing sparse system estimation method, based on least squares (LS), ℓ1-norm minimization and support shrinkage, is proposed. The proposed method can be seen as a counterpart for the Least Absolute Shrinkage and Selection Operator (LASSO), in the sense that the proposed method aims to find the vector that minimizes its ℓ1-norm subject to a maximum...
This paper presents new dynamic topology adaptation strategies for distributed estimation in smart grids. A dynamic exhaustive search-based topology adaptation algorithm and a dynamic sparsity-inspired topology adaptation algorithm, which can exploit the topology of smart grids with poor-quality links and obtain performance gains, are proposed. An optimized combining rule, named the Hastings rule,...
A novel approach to linearly constrained minimum variance (LCMV) beamforming based on dynamic selection of constraints (DSC) is proposed. The method employs a multiple parallel processors (MPP) framework, where each processor is optimized subject to a particular linear constraint. A selection criterion is employed at the output of the scheme to select the best processor for each time instant. We also...
In this paper, we propose a reduced-rank direction of arrival (DOA) estimation algorithm based on joint and iterative subspace optimization (JISO) with grid search . The reduced-rank scheme includes a rank reduction matrix and an auxiliary reduced-rank parameter vector. They are jointly and iteratively optimized with a recursive least squares algorithm (RLS) to calculate the output power spectrum...
MIMO radar has received significant attention in the past five years. In this paper, we focus on the advantage of MIMO radars in achieving better spatial resolution by employing the colocated antennas and propose a reduced-rank knowledge-aided technique for MIMO radar space-time adaptive processing (STAP) design. The scheme is based on joint iterative optimization of knowledge-aided adaptive filters...
In this paper, we examine blind adaptive and iterative decision-feedback (DF) receivers for direct-sequence code-division multiple-access systems in frequency-selective channels. Code-constrained minimum variance and constant modulus design criteria for DF receivers based on constrained optimization techniques are investigated for scenarios subject to multipath. Computationally efficient blind adaptive...
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