Wcfq: an opportunistic wireless scheduler with statistical fairness bounds

We present wireless credit-based fair queuing (WCFQ), a new scheduler for wireless packet networks with provable statistical short- and long-term fairness guarantees. WCFQ exploits the fact that users contending for the wireless medium will have different "costs" of transmission depending on their current channel condition. For example, in systems with variable coding, a user with a high-quality channel can exploit its low-cost channel and transmit at a higher data rate. Similarly, a user in a code-division multiple access system with a high-quality channel can use a lower transmission power. Thus, WCFQ provides a mechanism to exploit inherent variations in channel conditions and select low-cost users in order to increase the system's overall performance (e.g., total throughput). However, opportunistic selection of the best user must be balanced with fairness considerations. In WCFQ, we use a credit abstraction and a general "cost function" to address these conflicting objectives. This provides system operators with the flexibility to achieve a range of performance behaviors between perfect fairness of temporal access independent of channel conditions and purely opportunistic scheduling of the best user without consideration of fairness. To quantify the system's fairness characteristics within this range, we develop an analytical model that provides a statistical fairness bound in terms of the cost function and the statistical properties of the channel. An extensive set of simulations indicate that the scheme is able to achieve significant throughput gains while balancing temporal fairness constraints.