Robust modeling and analysis for wireless data resource management

TL;DR: A model and the chosen QoS index are described, and the proposed index is shown to exhibit solid technical behavior, be physically significant, intuitively appealing, and applicable to a wide variety of physical layer situations.

Abstract: Recent publications recognize that decentralized algorithms useful in wireless data applications can be obtained via microeconomics and game theory In these studies, each agent maximizes, under appropriate rules and constraints, a quality-of-service (QoS) index A key solution is a "Nash equilibrium"; ie, an allocation from which no agent is better off by unilaterally "deviating" The actual maximization may be made by software which may not be directly "controllable" by a human user The model and, especially, the chosen QoS index should be as general as possible, so that the derived results be applicable to a wide variety of channel conditions, modulation schemes, and other physical-layer characteristics Likewise, the chosen index should exhibit predictable and reliable technical behavior, without exacting a high complexity cost This note describes a model, and particularly, a QoS index which can accommodate a wide variety of physical layer situations The proposed index is shown to exhibit solid technical behavior, be physically significant, intuitively appealing, and applicable to a wide variety of physical layer situations A game in which terminals carrying multi-rate traffic seek to maximize this index is analyzed, and closed-form equilibrium conditions and power levels are derived "from first principles" All terminals want the same signal-to-interference ratio (SIR), but some cannot reach the necessary power level At equilibrium, a number of terminals transmit full power, and others achieve the same optimal SIR A basic rationale to search for these equilibria is provided