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Adaptive Multichannel Sequential Lattice Prediction Filtering Method for Range Estimation in Cognitive Radios
(IEEE, 2014)
A range estimation method 14 cognitive MIMO-OFDM radio systems is considered in this presentation. The range estimation problem is formulated as time delay estimation problem, and then adapted as multiple channel estimation ...
Adaptive V-BLAST Type Channel Equalizer Design for Cognitive MIMO-OFDM Radios
(IEEE, 2013)
A channel shortening equalizer design for cognitive Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) communication systems is considered in this presentation. The proposed receiver ...
Sequential Combinations of Multiple Adaptive Lattice Filters in Cognitive Radio Channel Identification
(IEEE, 2017)
Sequential convex combinations of multiple adaptive lattice filters using different exponential weighting factors in cognitive radio channel identification framework have been considered in this presentation. First, the ...
Adaptive Multichannel Sequential Lattice Prediction Filtering Method For Cognitive Radio Spectrum Sensing in Subbands
(IEEE, 2012)
A multichannel characterization for autoregressive moving average(ARMA) spectrum estimation in subbands with applications to cognitive radio spectrum sensing is considered in this presentation. The fullband ARMA spectrum ...
Combination of Approximate l(0)-Norm Regularized Multiple Adaptive Lattice Filters in Sparse Cogntive Radio Coannel Identification
(IEEE, 2020)
A priori recursive least squares (RLS) lattice algorithm has been regularized by adding an approximation of 10-norm constraint penalty term to the cost function so as to introduce sparsity awareness to the prenously proposed ...
Combinations of Multiple Adaptive Lattice Filters in Sparse Cognitive Radio Channel Identification
(IEEE, 2019)
Sparsity awareness feature has been introduced into the a priori recursive least squares (RLS) lattice algorithm by regularizing the RLS cost function with the addition of l(1)-norm constraint penalty term. The newly ...