Project Description

Optimal Joint Spectrum Allocation and Scheduling for Cognitive Radio Networks

Researchers

Funding

  • Sponsor: National Science Foundation
  • Amount of Support: $244,808
  • Duration of Support: 2 Years
  • More details […]

Abstract

Cognitive Radio Network is considered as a promising paradigm for the future networks. To significantly improve spectrum utilization, we conduct optimal or near-optimal joint spectrum allocation and scheduling in cognitive radio networks. We address critical and practical challenges for spectrum allocation and scheduling in cognitive radio networks, in particular multi-hop cognitive radio networks, such as dynamic traffic demands and pattern, unpredictable primary user activity, wireless interference, and coexistence. We develop creative models and algorithms in the framework of restless multi-armed bandit where the problem for spectrum allocation and scheduling in cognitive radio networks is formulated as a partially observable Markov decision process. The proposed methodology is novel in that it intelligently combines the networked multi-armed bandit modeling, graph theory, and communication scheduling theories. The developed algorithms, models, and protocols significantly improve spectrum utilization in future wireless communication systems and advance the fundamental knowledge and understanding of cognitive radio networks. The proposed algorithms, protocols, and models enable future wireless systems to design, deploy, and operate much more efficiently than today’s systems, which will result in significant economical, societal, and public safety impacts

Objectives

The objective of this project is to significantly improve spectrum utilization through conducting optimal or near-optimal joint spectrum allocation and scheduling in cognitive radio networks. The PIs address critical and practical challenges for spectrum allocation and scheduling in cognitive radio networks, in particular multi-hop cognitive radio networks, such as dynamic traffic demands and pattern, unpredictable primary user activity, wireless interference, and coexistence. A test-bed will be set up to extensively evaluate the designed algorithms and protocols.

Intellectual Merits

The intellectual merits of this project are: 1) this project develops creative models and algorithms in the framework of restless multi-armed bandit to address the critical challenges for spectrum allocation and scheduling in cognitive radio networks; 2) the proposed methodology is novel in that it intelligently combines the networked multi-armed bandit modeling, graph theory, and communication scheduling theories; 3) this project significantly advances the fundamental knowledge and understanding of cognitive radio networks; and 4) the developed algorithms, models, and protocols significantly improves spectrum utilization in future wireless communication systems.

Broader Impacts

This project significantly improves the design, deployment, and operation of future wireless communication systems. The proposed algorithms, protocols, and models enable future wireless systems to share spectrum much more efficiently than today’s systems, which will result in significant economical, societal, and public safety impacts. In addition, the proposed research is integrated into education and training for both undergraduate and graduate students. This project also significantly broadens the participation of underrepresented minority groups, e.g., the Native Americans in South Dakota.

Publications

Wang, Lixin and Xu, Xiaohua. “Approximation Algorithms for Maximum Weight Independent Set of Links Under the SINR Model,” Ad-hoc \& sensor wireless networks, v.17, 2013, p. 293–311.

Xu, Xiaohua and Li, Xiang-Yang and Song, Min. “Efficient aggregation scheduling in multihop wireless sensor networks with sinr constraints,” Mobile Computing, IEEE Transactions on, v.12, 2013, p. 2518–252.