A Resource Matching Algorithm for Dynamic Multi-Homing Service Environment

T43 paper investigates the matching problem between radio resources and multi-homing services in a dynamic heterogeneous wireless environment. A mobile terminal (MT) with multi-homing service simultaneously transmits data to multiple radio access networks using multiple air interfaces. We develop an...

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Bibliographic Details
Published in2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC) pp. 97 - 102
Main Authors Zhang, Hui, Liu, Shu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2018
Subjects
Bandwidth
composite fading channel
dynamic heterogeneous wireless environment
Dynamic scheduling
energy efficiency
Fading channels
Heuristic algorithms
Interference
joint optimal allocation
multi-homing service
Resource management
resource matching
Wireless communication
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Summary:T43 paper investigates the matching problem between radio resources and multi-homing services in a dynamic heterogeneous wireless environment. A mobile terminal (MT) with multi-homing service simultaneously transmits data to multiple radio access networks using multiple air interfaces. We develop an energy efficient resource matching algorithm for statistically guaranteeing the transmission rate of each MT with the minimum power consumption. Firstly, aided with the resource matching conception and the dynamic characteristics of wireless channels, we propose a matching probability metric to construct resource matching model for maximizing energy efficiency of all MTs subject to statistical guarantee requirements, and simplify the dynamic channels characteristic based on matching theory. Secondly, we propose a two-level distributed matching algorithm (TLDMA), with inner minimum power consumption and outer maximum matching probability, which realizes joint optimal allocation of bandwidth, transmission power and rate. Simulation results show that TLDMA outperforms conventional algorithms in terms of wireless resources management.
DOI:10.1109/IMCEC.2018.8469749