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Obviously, this is not the best strategy since the distortion vector contains information about the transmitted signal and is not useless noise.
where f D is the pdf of the distortion vector D, which by definition, can be easily seen to be Gaussian circularly symmetric with variance σ D 2 = 1 ρ Ha − 1 Ha − 1 H.
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Also, H ij is the channel matrix of the cooperative MIMO setup, and N j is the additive noise-plus-distortion vector added at the receive nodes.
The noise-plus-distortion vector consists of two parts, namely the thermal noise (Z), and the quantization distortion (D) N j = Z j + D j. (15).
The diamond encoding scheme promises that the distortion of vector is no more than k after embedding a secret digit.
W[l] = [W i 1[l]W i 2[l] ⋯ W i N [l]] T is an N × 1 nonlinear distortion noise vector (out-of-band distortion) due to HPA and it is obtained by taking the DFT of w(t).
where c = ΩC is the peak-canceling signal in the time domain and C = [C0, C1, …, CN - 1] T is the avoid signal distortion; the data vector X and the peak reduction vector C lie in disjoint frequency domains, and X and C are not allowed to be non-zero on the same subcarriers, that is X n + C n = X n, n ∈ R C, C n, n ∈ R, (4).
The purpose of the generated code book is to provide a set of vectors which generate minimal distortion between the original vector and the quantized vector.
The performance of a 64-stage 16 × 16 EC-RRVQ at 0.175 bits per pixel is 23.75 dB with 96 vector distortion calculations per source vector, while the number for previously proposed large-dimensional entropy-constrained residual VQ (EC-RVQ) designed under the same specifications is 21.17 dB with 1212 vector distortion calculations per source vector.
This paper presents an evolution-based tabu search approach (ETSA) to design codebooks with smaller distortion values in vector quantization.
In this paper, we first consider the general distortion analysis of vector quantizers with transformed codebooks.
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