Digital Picture Processing
Orthogonal Transforms for Digital Signal Processing
Orthogonal Transforms for Digital Signal Processing
On the phase sequence set of SLM OFDM scheme for a crest factor reduction
IEEE Transactions on Signal Processing
Hadamard-based image decomposition and compression
IEEE Transactions on Information Technology in Biomedicine
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We present an efficient usage of quantization bits applied to parallel input signals that are correlated each possessing average power varying over a large dynamic range. Our solution utilizes Hadamard-matrix processing (HMP) which consists of decorrelation spreading followed by the Hadamard matrix operation. If the input signals are uncorrelated, the Hadamardmatrix operation transforms the parallel signal sources to have the equivalent average power prior to quantization, thereby effectively minimizing the overall number of quantization bits required to achieve system performance. To insure that the signals are uncorrelated, we implement decorrelation spreading prior to the Hadamard. Different decorrelator methods of varying complexity are examined. We show that the decorrelation methods when used with the Hadamard matrix can influence the immunization of "signal clipping" due to quantization in addition to realizing significant system capacity and/or power gains. We demonstrate the performance of the HMP on the Mobile-User Objective System (MUOS) through simulation by comparing overall G/T degradation for different scenarios.