Efficient Resource Allocation for Multicell Heterogeneous Cognitive Networks With Varying Spectrum Availability

This paper investigates the problem of designing an efficient spectrum-allocation mechanism in heterogeneous multicell coordinated cognitive radio networks (CRNs) under time-varying channel availabilities and traffic demands across the different cells. The problem is modeled as a utility proportiona...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 65; no. 8; pp. 6628 - 6635
Main Author: Salameh, Haythem Bany
Format: Journal Article
Language:English
Published: New York IEEE 01.08.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Allocations
Availability
Binary linear programming (BLP)
Channel allocation
Demand
Heterogeneity
Linear matrix inequalities
Linear programming
Mathematical models
Networks
Optimization
Resource management
Sensors
spectrum heterogeneity
System performance
total unimodularity
Traffic engineering
Traffic flow
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:This paper investigates the problem of designing an efficient spectrum-allocation mechanism in heterogeneous multicell coordinated cognitive radio networks (CRNs) under time-varying channel availabilities and traffic demands across the different cells. The problem is modeled as a utility proportional fair maximization problem subject to traffic demand, spectrum heterogeneity, and exclusive spectrum sharing constraints. Specifically, the optimization problem is formulated as a binary linear programming (BLP) problem. Due to its integrality properties, the BLP is anticipated to be NP-hard. However, this paper proves that the optimal solution of the formulated BLP can be found in polynomial time using linear programming (LP) because of its total unimodular constraint matrix. The proposed solution is a spectrum-aware allocation design that ensures a fair spectrum sharing among cells based on their current traffic loads while considering the unique characteristics of their radio-frequency (RF) environment. Simulation results reveal that the proposed spectrum-aware proportional weighted fair allocation leads to improved system performance while effectively dealing with spectrum heterogeneity and time-varying traffic demands. The results also indicate that the proposed spectrum-allocation design is quite robust to traffic estimation and spectrum sensing errors.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2015.2477432