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Optimal Power Control, Rate Adaptation, and Scheduling for UWB-Based Intravehicular Wireless Sensor Networks

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2 Author(s)
Sadi, Y. ; Dept. of Electr. & Electron. Eng., Koc Univ., Istanbul, Turkey ; Ergen, S.C.

The intravehicular wireless sensor network (IVWSN) is a promising new research area that can provide part cost, assembly, maintenance savings, and fuel efficiency through the elimination of the wires and enables new sensor technologies to be integrated into vehicles, which would otherwise be impossible using wired means such as Intelligent Tire. The close interaction of communication with control systems, strict reliability, energy efficiency, and delay requirements in such a harsh environment that contains a large number of reflectors that operate at extreme temperatures are distinguishing properties of this network. In this paper, we investigate optimal power control, rate adaptation, and scheduling for an ultrawideband-based IVWSN for one-electronic-control-unit (ECU) and multiple-ECU cases. For the one-ECU case, we show that the optimal rate and power allocation is independent of the optimal scheduling algorithm. We prove the NP-hardness of the scheduling problem and formulate the optimal solution as a mixed-integer linear programming (MILP) problem. We then propose a 2-approximation algorithm, which is the smallest period into the shortest subframe first (SSF) algorithm. For the multiple-ECU case, where the concurrent transmission of links is possible, we formulate the optimal power control as a geometric-programming problem and optimal scheduling problem as an MILP problem where the number of variables is exponential in the number of links. We then propose a heuristic algorithm - the maximum-utility-based concurrency allowance algorithm - based on the idea of significantly improving the performance of the SSF algorithm in the existence of multiple ECUs by determining the sets of maximum utility.

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:62 ,  Issue: 1 )

Date of Publication:

Jan. 2013

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