**Author details**

12 Will-be-set-by-IN-TECH

8 12 16 20 24 28

**Figure 4.** Verification of proposed power allocation between the two communication links of a single

Proposed power allocation

Proposed power allocation +10% to best sensor +10% to worst sensor

**Figure 5.** Verification of proposed power allocation between two sensor nodes.

+30% to first link +10% to first link +10% to second link

SNR/dB

11.8 15.8 19.8 23.8 27.8

SNR/dB

In particular, it is shown that the same overall classification probability can be achieved with much lower transmission power, especially for low SNR values, by using an efficient power allocation method. Furthermore, the symbol-error probability of the sensor node with the highest part of the total power is also shown. The classification accuracy is better than the best symbol-error probability for higher SNR values, which affirms the gain of data fusion and illustrates the feasibility of object classification in this kind of distributed sensor networks.

10−5

10−5

10−4

Probability

 of

classification

 error

10−3

10−2

10−1

100

10−4

Probability

sensor node network.

 of

classification

 error

10−3

10−2

10−1

100

Gholamreza Alirezaei, Rudolf Mathar and Daniel Bielefeld

*Institute for Theoretical Information Technology, RWTH Aachen University, D-52056 Aachen, Germany*
