Author_Institution :
Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
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.
Keywords :
Rayleigh channels; Rician channels; channel capacity; delays; quality of service; queueing theory; Doppler spectrum; Rayleigh-Ricean distribution; admission control; connection-level QoS metrics; data rate; delay; delay bounds; delay-violation probability; effective capacity; link-layer channel model; marginal distribution; next-generation wireless networks; nonempty buffer; quality of service; resource reservation; wireless channel; wireless link model; Admission control; Communication system traffic control; Delay estimation; Fading; Next generation networking; Predictive models; Quality of service; Queueing analysis; Traffic control; Wireless networks;