A noncooperative power control game in multi-access fading channels with quality of service (QoS) constraints

2010 ◽  
Vol 3 (2) ◽  
pp. 97-104 ◽  
Author(s):  
Deli Qiao ◽  
Mustafa Cenk Gursoy ◽  
Senem Velipasalar
Keyword(s):  
Quality Of Service ◽  
Power Control ◽  
Fading Channels ◽  
Multi Access

Evaluating QoS in a Multi-Access Wireless Network

2010 ◽  
pp. 1-30
Author(s):  
Ronan Skehill ◽  
William Kent ◽  
Dorel Picovici ◽  
Michael Barry ◽  
Sean McGrath
Keyword(s):  
Quality Of Service ◽  
Admission Control ◽  
Control Strategies ◽  
End User ◽  
Ieee 802.11B ◽  
Test Platform ◽  
Tightly Coupled ◽  
Multi Access ◽  
The Impact

This chapter introduces quality of service in multi-access wireless networks. Specifically it demonstrates how QoS is implemented in IEEE 802.11 and UMTS. The chapter explains how these complementary technologies, when coupled together, provide a network that is greater than its individual parts. Combining these networks brings new network management challenges. To this end, the impact of joint admission control strategies on quality of service is evaluated. The evaluation is performed on an advanced test platform that replicates an integrated Release 4 UMTS network and standard IEEE 802.11b network. The results show that when UMTS and WLAN are tightly coupled, the end user enjoys a higher level of quality of service.

scholarly journals R-learning-based team game model for Internet of things quality-of-service control scheme

2017 ◽  
Vol 13 (1) ◽  
pp. 155014771668755 ◽  
Author(s):  
Sungwook Kim
Keyword(s):  
Quality Of Service ◽  
Internet Of Things ◽  
Power Control ◽  
Service Management ◽  
Simulation Analysis ◽  
Learning Algorithm ◽  
Control Approach ◽  
Management Scheme ◽  
Internet Of Things Technology

In modern times, it has been observed that Internet of things technology makes it possible for connecting various smart objects together through the Internet. For the effective Internet of things management, it is necessary to design and develop service models that ensure appropriate level of quality-of-service. Therefore, the design of quality-of-service management schemes has been a hot research issue. In this work, we formulate a new quality-of-service management scheme based on the IoT system power control algorithm. Using the emerging and largely unexplored concept of the R-learning algorithm and docitive paradigm, system agents can teach other agents how to adjust their power levels while reducing computation complexity and speeding up the learning process. Therefore, our proposed power control approach can provide the ability to practically respond to current Internet of things system conditions and suitable for real wireless communication operations. Finally, we validate the introduced concept and confirm the effectiveness of the proposed scheme in comparison with the existing schemes through extensive simulation analysis.

Sign in / Sign up

Export Citation Format

Share Document