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A. J. Goldsmith and P. Varaiya, "Capacity of fading channels with channel side information," IEEE Trans.
By modeling the coefficients using the GMM, we calculate the distribution of watermarked noisy coefficients analytically and we design a Maximum Likelihood (ML) watermark detector using channel side information.
Channel side information.
Thus motivated, our first aim is to provide an analysis of optimal throughput scaling with full channel side information (CSI) at the secondary transmitter.
The information about the channel conditions can be obtained from the receiver in the form of channel side information [5 7, 17, 18].
We assume that both the receiver and transmitter have perfect channel side information (CSI) and hence perfectly know the instantaneous realizations of the fading coefficients.
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Intensity stereo is based on coding only the sum signal of the channels, as well as the time envelopes for each channel as side information, given that these envelopes are adequate for synthesizing the spatial image at the decoder.
Finally for calculating image capacity, we consider watermarking as communication channel with side information [2].
In the following, we provide an outline of the achievability for the achievable rate of the system, based on the results in [15] for the broadcast channel with side information [16].
In addition, we proposed a method to calculate the capacity in bits per pixel unit according to the complexity of images by considering image watermarking as a communication channel with side information.
for all S L ⊂I L and S K ⊂I K where (C x) triangleq frac {1}{2} log (1+x)), R j,i denotes the rate achieved from T j,i to T 0, and P j,i denotes the transmit power at node T j,i, i∈I K and j∈I L. The second phase is a broadcast channel with side information [29].
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