### Abstract

This paper considers low-complexity implementation of energy-efficient cooperative transmission in wireless sensor networks. In particular, an optimization framework is considered which, for a given configuration of the source, destination and relay nodes, performs optimal relay selection and power allocation subject to signal-to-noise ratio constraints. While the proposed framework gives the optimal solution, considering simple platforms of sensing nodes, solving the corresponding mixed-integer linear programming problem is computationally complex. To overcome this hurdle, an explicit solution to the optimization problem at hand is presented by invoking the theory of multi-parametric programming. This technique provides the solution as a function of measurable parameters in an off-line manner. The piecewise-constant values in such a solution can be stored in a memory chip and the online computational tasks are reduced to finding the parameters and evaluating simple functions to obtain the optimal solution.

Original language | English |
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Title of host publication | 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013 |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 4146-4151 |

Number of pages | 6 |

ISBN (Print) | 9781467357173 |

DOIs | |

Publication status | Published - 2013 |

Externally published | Yes |

Event | 52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy Duration: 10 Dec 2013 → 13 Dec 2013 |

### Other

Other | 52nd IEEE Conference on Decision and Control, CDC 2013 |
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Country | Italy |

City | Florence |

Period | 10/12/13 → 13/12/13 |

### Fingerprint

### ASJC Scopus subject areas

- Control and Systems Engineering
- Modelling and Simulation
- Control and Optimization

### Cite this

*2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013*(pp. 4146-4151). [6760525] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2013.6760525

**An explicit solution for the energy-efficient cooperative transmission problem in wireless sensor networks.** / Habibi, Jalal; Ghrayeb, Ali; Aghdam, Amir G.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013.*, 6760525, Institute of Electrical and Electronics Engineers Inc., pp. 4146-4151, 52nd IEEE Conference on Decision and Control, CDC 2013, Florence, Italy, 10/12/13. https://doi.org/10.1109/CDC.2013.6760525

}

TY - GEN

T1 - An explicit solution for the energy-efficient cooperative transmission problem in wireless sensor networks

AU - Habibi, Jalal

AU - Ghrayeb, Ali

AU - Aghdam, Amir G.

PY - 2013

Y1 - 2013

N2 - This paper considers low-complexity implementation of energy-efficient cooperative transmission in wireless sensor networks. In particular, an optimization framework is considered which, for a given configuration of the source, destination and relay nodes, performs optimal relay selection and power allocation subject to signal-to-noise ratio constraints. While the proposed framework gives the optimal solution, considering simple platforms of sensing nodes, solving the corresponding mixed-integer linear programming problem is computationally complex. To overcome this hurdle, an explicit solution to the optimization problem at hand is presented by invoking the theory of multi-parametric programming. This technique provides the solution as a function of measurable parameters in an off-line manner. The piecewise-constant values in such a solution can be stored in a memory chip and the online computational tasks are reduced to finding the parameters and evaluating simple functions to obtain the optimal solution.

AB - This paper considers low-complexity implementation of energy-efficient cooperative transmission in wireless sensor networks. In particular, an optimization framework is considered which, for a given configuration of the source, destination and relay nodes, performs optimal relay selection and power allocation subject to signal-to-noise ratio constraints. While the proposed framework gives the optimal solution, considering simple platforms of sensing nodes, solving the corresponding mixed-integer linear programming problem is computationally complex. To overcome this hurdle, an explicit solution to the optimization problem at hand is presented by invoking the theory of multi-parametric programming. This technique provides the solution as a function of measurable parameters in an off-line manner. The piecewise-constant values in such a solution can be stored in a memory chip and the online computational tasks are reduced to finding the parameters and evaluating simple functions to obtain the optimal solution.

UR - http://www.scopus.com/inward/record.url?scp=84902310501&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84902310501&partnerID=8YFLogxK

U2 - 10.1109/CDC.2013.6760525

DO - 10.1109/CDC.2013.6760525

M3 - Conference contribution

SN - 9781467357173

SP - 4146

EP - 4151

BT - 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013

PB - Institute of Electrical and Electronics Engineers Inc.

ER -