Ribeiro, Alejandro
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Publication Layers and layer interfaces in wireless networks(2009-04-19) Ribeiro, AlejandroThis paper proposes an optimal architecture for wireless networks based on layers and layer interfaces. In the presence of fading the architecture is shown to be optimal. The result follows from a subgradient descent algorithm on the dual function of a generic wireless networking optimization problem. The fact that these non-convex optimization problems have nonetheless zero duality gap is exploited.Publication Optimal Robust Multihop Routing for Wireless Networks of Mobile Micro Autonomous Systems(2010-10-31) Fink, Jonathan; Ribeiro, Alejandro; Kumar, Vijay; Sadler, Brian M.This paper develops algorithms to ensure that agents of a mobile micro autonomous system (MMAS) maintain integrity of communication flows as they move to accomplish their task. Due to inherent uncertainties in estimation of wireless channels, we advocate a stochastic approach whereby achievable communication rates of point-to-point links are regarded as random variables with known means and variances. To achieve reliable end-to-end communication flows, terminals route their traffic through various alternative paths to reduce the effect of uncertainty in individual link rates. The proposed algorithms are optimal and robust in that routes are obtained as solutions of optimization problems subject to constraints on minimum required rates and maximum acceptable variances. Algorithms are tested in an event-based simulator that uses an accurate data-driven model of radio communications to model both the structure of code running independently on multiple robots as well as the transmission of messages via a real radio. Simulation results corroborate that rates of end-to-end flows are maintained at target levels despite variations in the rates of individual links.Publication Ergodic Stochastic Optimization Algorithms for Wireless Communication and Networking(2010-11-17) Ribeiro, AlejandroErgodic stochastic optimization (ESO) algorithms are proposed to solve resource allocation problems that involve a random state and where optimality criteria are expressed in terms of long term averages. A policy that observes the state and decides on a resource allocation is proposed and shown to almost surely satisfy problem constraints and optimality criteria. Salient features of ESO algorithms are that they do not require access to the state’s probability distribution, that they can handle nonconvex constraints in the resource allocation variables, and that convergence to optimal operating points holds almost surely. The proposed algorithm is applied to determine operating points of an orthogonal frequency division multiplexing broadcast channel that maximize a given rate utility.