Effective capacity: A wireless link model for support of quality of service

TLDR

Current physical‑layer channel models lack explicit QoS metrics; next‑generation networks require channel models expressed in terms of data rate, delay, and delay‑violation probability to support QoS. The paper proposes a link‑layer channel model called effective capacity (EC). The model represents a wireless link with two EC functions—probability of nonempty buffer and QoS exponent—and uses a simple algorithm to estimate them, validated by simulations that confirm close approximation of actual QoS metrics. The EC model offers easy translation into QoS guarantees, simple implementation, and accurate predictions, as simulations confirm close alignment with actual QoS metrics across diverse conditions.

Abstract

To facilitate the efficient support of quality of service (QoS) in next-generation wireless networks, it is essential to model a wireless channel in terms of connection-level QoS metrics such as data rate, delay, and delay-violation probability. However, the existing wireless channel models, i.e., physical-layer channel models, do not explicitly characterize a wireless channel in terms of these QoS metrics. In this paper, we propose and develop a link-layer channel model termed effective capacity (EC). In this approach, we first model a wireless link by two EC functions, namely, the probability of nonempty buffer, and the QoS exponent of a connection. Then, we propose a simple and efficient algorithm to estimate these EC functions. The physical-layer analogs of these two link-layer EC functions are the marginal distribution (e.g., Rayleigh-Ricean distribution) and the Doppler spectrum, respectively. The key advantages of the EC link-layer modeling and estimation are: 1) ease of translation into QoS guarantees, such as delay bounds; 2) simplicity of implementation; and 3) accuracy, and hence, efficiency in admission control and resource reservation. We illustrate the advantage of our approach with a set of simulation experiments, which show that the actual QoS metric is closely approximated by the QoS metric predicted by the EC link-layer model, under a wide range of conditions.