title: A cross-layer adaptation scheme for improving IEEE 802.11e QoS by learning.
abstract: In this letter, we propose a cross-layer adaptation scheme which improves IEEE 802.11e quality of service (QoS) by online adapting multidimensional medium access control (MAC)-layer parameters depending on the application-layer QoS requirements and physical layer (PHY) channel conditions. Our solution is based on an optimization approach which utilizes neural networks (NNs) to learn the cross-layer function. Simulations results demonstrate the effectiveness of our adaptation scheme.
authors.forename: Chiapin
authors.initials: C
authors.lastname: Wang
authors.forename: Po-Chiang
authors.initials: PC
authors.lastname: Lin
authors.forename: Tsungnan
authors.initials: T
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D003195:Computer Communication Networks; D016247:Information Storage and Retrieval / Q000379:methods* / Q000592:standards; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D011786:Quality Control; D012815:Signal Processing, Computer-Assisted; D014481:United States