Optimum Power Allocation and Bit Loading for Systems with Suboptimum Receivers

Waterfllling 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 general scenarios where suboptimum receivers introduce a mutual information loss. The proposed approach provides the optimum solution without resorting to greedy algorithms and has nearly the same complexity as the original mercury/waterfilling.