Learn More
— 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)
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)
—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)
  • 1