By Topic

Impacts of Radio Channel Characteristics, Heterogeneous Traffic Intensity, and Near–Far Effect on Rate Adaptive Scheduling Algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chiung-Jang Chen ; Chunghwa Telecom Labs., Chung-li ; Li-Chun Wang

Applying adaptive modulation combined with scheduling in a shared data channel can substantially improve the spectral efficiency for wireless systems. This performance gain results from the multiuser diversity, which exploited independent channel variations across multiple users. In this paper, we present a cross-layer analysis to integrate physical-layer channel characteristics, media access control (MAC) layer scheduling strategies, and the network layer issue of heterogeneous traffic intensity across near-far users. Specifically, for radio channel characteristics, we take account of path loss, slowly varying log-normal shadowing and fast-varying Nakagami fading. We also evaluate the impact of selective transmit diversity on the throughput and fairness of wireless data networks. Furthermore, we consider three MAC schedulers: random scheduler, greedy scheduler (GS), and a newly proposed queue-length-based scheduler (QS). By applying the proposed cross-layer analytical framework, the following insights can be gained. First, for the three considered schedulers, channel fluctuations induced by Nakagami fading or log-normal shadowing can improve both total throughput and fairness. Second, using selective transmit diversity can improve throughput, but is unfavorable for the fairness performance. Third, the GS and the QS methods can improve throughput at the expense of unfairness to the far users. However, the throughput improvement from using the GS and the QS decreases as the traffic intensity of the far user increases. In summary, this cross-layer analysis can be used to develop new scheduling mechanisms for achieving better tradeoff between the fairness and throughput for wireless data networks

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:55 ,  Issue: 5 )