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— Waterfilling and mercury/waterfilling power allocation policies maximize the mutual information of independent parallel Gaussian-noise channels under an average power constraint for Gaussian signals and for practical discrete constellations respectively. In this paper, the same criterion is considered for joint power allocation and bit loading in more(More)
—This paper introduces a joint bit loading and power allocation algorithm for systems combining bit-interleaved coded modulation (BICM) with multicarrier transmission. The proposed algorithm maximizes the mutual information, so it can be regarded as a generalization of mercury/waterfilling policy that incorporates bit loading. The followed approach relies(More)
In this paper we propose a low complexity adaptive algorithm for lossless compressive sampling and reconstruction of sparse signals. Consider a sparse non-negative real signal x containing only í µí±˜ << í µí±› non-zero values. The sampling process obtains í µí±š measurements by a linear projection y = Ax and, in order to minimize the complexity, we(More)
—We study the behavior of a new family of non-linear graph-based codes, previously introduced for compression of asymmetric binary memoryless sources, for the joint source-channel coding scenario in which the codewords are transmitted through an additive white Gaussian noise channel. We focus on low entropy sources (with high redundancy) and compression(More)
—In this paper, a new power allocation and bit loading policy is defined for those systems working with a pre-selected binary channel code and specific bit error rate (BER) requirements. It consists on the maximization of the spectral efficiency with a constraint on the average mutual information per coded bit (bit MI), exploiting the relationship of the(More)
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