Locally Optimized Scheduling and Power Control Algorithms for Multi-hop Wireless Networks under SINR Interference Models

Joohwan Kim; Xiaojun Lin; Ness B. Shroff

5th International ICST Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks

Research Article

Locally Optimized Scheduling and Power Control Algorithms for Multi-hop Wireless Networks under SINR Interference Models

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1109/WIOPT.2007.4480039,
    author={ Joohwan Kim and  Xiaojun Lin and Ness B. Shroff},
    title={Locally Optimized Scheduling and Power Control Algorithms for Multi-hop Wireless Networks under SINR Interference Models},
    proceedings={5th International ICST Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks},
    publisher={IEEE},
    proceedings_a={WIOPT},
    year={2008},
    month={3},
    keywords={Application software  Interference  Power control  Power system modeling  Processor scheduling  Scheduling algorithm  Signal to noise ratio  Spread spectrum communication  Throughput  Wireless networks},
    doi={10.1109/WIOPT.2007.4480039}
}

Joohwan Kim
Xiaojun Lin
Ness B. Shroff
Year: 2008
Locally Optimized Scheduling and Power Control Algorithms for Multi-hop Wireless Networks under SINR Interference Models
WIOPT
IEEE
DOI: 10.1109/WIOPT.2007.4480039

Joohwan Kim¹^,*, Xiaojun Lin¹^,*, Ness B. Shroff¹^,*

1: Center for Wireless Systems and Applications (CWSA) School of Electrical and Computer Engineering, Purdue University West Lafayette, IN 47907, U.S.A

*Contact email: jhkim@purdue.edu, linx@purdue.edu, shroff@purdue.edu

Abstract

In this paper, we develop locally optimized scheduling and power control algorithms for multi-hop wireless networks under SINR interference models. Our scheme can be implemented in a fully distributed manner and requires only that each node solve a simple local optimization problem. Since, in our algorithms, each node operates independently of other nodes, it needs to predict the behavior of neighboring nodes when carrying out its local optimization. For such prediction, our proposed algorithms exploit the past records of neighboring nodes' scheduling and power control decisions. Through simulations, we show that our algorithms significantly outperform the state-of-the-art.

Keywords: Application software Interference Power control Power system modeling Processor scheduling Scheduling algorithm Signal to noise ratio Spread spectrum communication Throughput Wireless networks

Published: 2008-03-31
Publisher: IEEE
Modified: 2011-07-28

: http://dx.doi.org/10.1109/WIOPT.2007.4480039