Browsing by Author "Wahdan, Muath Abed Alrauf"

Now showing 1 - 1 of 1

Medium-aware inference for wireless sensor networks
(Izmir Institute of Technology, 2020-12) Wahdan, Muath Abed Alrauf; Altınkaya, Mustafa Aziz
In a wireless sensor network, multilevel quantization is necessary in order to find a compromise between the smallest possible power consumption of the sensors and the detection performance at the fusion center (FC). The general methodology is using distance measures such as J-divergence (JD) and Bhattacharyya distance in this quantization. This thesis proposes a different approach which is based on maximizing the average output entropy of the sensors under both hypotheses of a binary hypothesis test and utilizes it in a Neyman-Pearson (NP) criterion based distributed detection scheme in order to detect a point source. Firstly, a deterministic signal and isotropic propagation model is considered. The receiver operating characteristics of the proposed maximum average entropy (MAE) meth\-od in quantizing sensor outputs was obtained for multilevel quantization both when the sensor outputs are available error-free at the FC and when non-coherent $M$-ary frequency shift keying communication is used for transmitting MAE based multilevel quantized sensor outputs over a Rayleigh fading channel. Secondly, the sequential testing version of the first problem is considered for both unquantized and quantized data transmissions. MAE and maximum JD (MJD) quantization methods for $M$-levels were applied in the sequential probability ratio test of Wald. The average sample number (ASN) required for the target probabilities of detection and a false alarm was the performance criterion: the smaller, the better. The performance of this test improves monotonically with the number of local sensors. Lastly, spatial correlation of the sensors is taken into the account. For this case, a Gaussian isotropic event source was applied. The computational requirements in evaluating multidimensional cumulative densities necessitated proposing a rectangular grid model of sensor deployment and block-diagonal approximations of covariance matrix related to the event signal at the sensors without losing generality. The simulation studies show the success of the MAE both in the cases of fusing error-free sensor outputs and in the case where the effect of the wireless channel is incorporated. As expected the performance gets better as the level of quantization increases and with six-level quantization, it approaches the performance of non-quantized data transmission. In the sequential tests again MAE was more successful compared to MJD resulting in smaller ASNs. It was observed that spatial correlation degrades system performance.