posted on 2025-05-11, 22:46authored byEng Hwee Ong, Jamil Y. Khan
The widespread use of IEEE 802.11 WLAN and the potential to deliver QoS demanding multimedia contents, with the advent of 802.11n standard, will position itself as one of the introductory de-facto wireless access networks in the emerging cognitive networks. Existing WLANs can be augmented with cognitive functionality by the introduction of cognitive radios. However, the frequency-agile cognitive radio supports dynamic spectrum access to channels, which are heterogeneous and have largely different propagation characteristics, from diverse parts of the available frequency spectrum. Although WLAN supports link adaptation in practice, most of the existing WLANs are DCF-based which will give rise to the well-known rate anomaly problem where the long-term throughput of stations are penalized by the lowest data rate peer under multirate operation. Hence, deploying a WLAN-based cognitive network results in nontrivial radio resource management. In this paper, we introduce the novel concept of load adaptation strategy (LAS) to manage dynamic channel conditions associated with multirate multi-AP multimedia WLAN-based cognitive network in a single unifying QoS framework. Particularly, we show that our distributed LAS arbitrates optimal load distribution by maintaining a QoS-balanced system through QoS-based handovers in an opportunistic yet altruistic manner. Through simulations, we show that rate anomaly in multirate environment can be mitigated, statistical QoS guarantee can be provisioned for multimedia traffic with QoS fairness and system capacity can be maximized.
History
Source title
2nd IFIP Wireless Days (WD) 2009: Proceedings
Name of conference
2nd IFIP Wireless Days (WD) 2009
Location
Paris, France
Start date
2009-12-15
End date
2009-12-17
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Place published
Piscataway, NJ
Language
en, English
College/Research Centre
Faculty of Engineering and Built Environment
School
School of Electrical Engineering and Computer Science