Energy-efficient precoding in multicell networks with full-duplex base stations

© 2017, The Author(s). This paper considers multi-input multi-output (MIMO) multicell networks, where the base stations (BSs) are full-duplex transceivers, while uplink and downlink users are equipped with multiple antennas and operate in a half-duplex mode. The problem of interest is to design linear precoders for BSs and users to optimize the network’s energy efficiency. Given that the energy efficiency objective is not a ratio of concave and convex functions, the commonly used Dinkelbach-type algorithms are not applicable. We develop a low-complexity path-following algorithm that only invokes one simple convex quadratic program at each iteration, which converges at least to the local optimum. Numerical results demonstrate the performance advantage of our proposed algorithm in terms of energy efficiency

Global optimization for the generalized polynomial sum of ratios problem

Global optimization, Generalized polynomial, Fractional programming, Sum of ratios, Nonisolated optimal solution,

Towards the Geometry of Model Sensitivity: An Illustration

In statistical practice model building, sensitivity and uncertainty are major concerns of the analyst. This paper looks at these issues from an information geometric point of view. Here, we define sensitivity to mean understanding how inference about a problem of interest changes with perturbations of the model. In particular it is an example of what we call computational information geometry. The embedding of simple models in much larger information geometric spaces is shown to illuminate these critically important issues