Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/102478
Title: Dynamic service selection and bandwidth allocation in IEEE 802.16m mobile relay networks
Authors: Zhu, Kun
Niyato, Dusit
Wang, Ping
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Zhu, K., Niyato, D., & Wang, P. (2012). Dynamic service selection and bandwidth allocation in IEEE 802.16m mobile relay networks. IEEE journal on selected areas in communications, 30(9), 1798-1805.
Series/Report no.: IEEE journal on selected areas in communications
Abstract: Cooperative relay network will be supported in IEEE 802.16m to improve the coverage and performance of mobile broadband wireless access service. In this paper, we jointly consider the problem of dynamic service selection and bandwidth allocation in IEEE 802.16m mobile relay networks. Specifically, the advanced mobile stations (AMSs) perform the selection of advanced base station (ABS) and transmission mode (i.e., direct transmission or relay-cooperation transmission) for a better service quality. The ABSs allocate the bandwidth for different transmission modes to maintain the desired queue level at base stations and user distribution for satisfying performance requirements. This problem is challenging when the strategies of both ABSs and AMSs influence each other and the decisions are made dynamically. To address this problem, a two-level dynamic game framework based on an evolutionary game and a differential game is developed. Since the mobile stations can adapt their strategies according to the received service quality, the dynamic service selection is modeled as an evolutionary game at the lower level. At the upper level, a differential game is formulated for a dynamic bandwidth allocation of base stations and a closed-loop Nash equilibrium is obtained as the solution. Viewing the fluctuation of traffic flow rate as disturbance, the robust bandwidth allocation strategy design is performed. Both stochastic optimal control and H_∞ optimal control approaches are adopted for average performance and worst-case performance design, respectively.
URI: https://hdl.handle.net/10356/102478
http://hdl.handle.net/10220/16385
DOI: http://dx.doi.org/10.1109/JSAC.2012.121025
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.