In this paper, we study channel-aware decision fusion (DF) in a wireless sensor network (WSN), where the sensors transmit their decisions simultaneously for spectral efficiency purposes and the DF center (DFC) is equipped with multiple antennas. Also, each sensor-DFC channel is described via a Rician model. As opposed to the existing literature, in order to account for stringent energy constraints in the WSN, only statistical channel information is assumed for the non-line-of-sight (scattered) fading terms. For such a scenario, suboptimal fusion rules are developed in order to deal with the exponential complexity of the likelihood ratio test (LRT) and impractical (complete) system knowledge. Furthermore, the considered model is extended to the case of (partially unknown) jamming-originated interference. Then, the obtained fusion rules are modified with the use of composite hypothesis testing framework and generalized LRT. Coincidence and statistical equivalence among them are also investigated under some relevant simplified scenarios. Numerical results compare the proposed rules and highlight their jamming-suppression capability.
Rician MIMO Channel- and Jamming-Aware Decision Fusion / Ciuonzo, Domenico; Aubry, Augusto; Carotenuto, Vincenzo. - In: IEEE TRANSACTIONS ON SIGNAL PROCESSING. - ISSN 1053-587X. - 65:15(2017), pp. 3866-3880. [10.1109/TSP.2017.2686375]
Rician MIMO Channel- and Jamming-Aware Decision Fusion
Ciuonzo, Domenico;Aubry, Augusto;Carotenuto, Vincenzo
2017
Abstract
In this paper, we study channel-aware decision fusion (DF) in a wireless sensor network (WSN), where the sensors transmit their decisions simultaneously for spectral efficiency purposes and the DF center (DFC) is equipped with multiple antennas. Also, each sensor-DFC channel is described via a Rician model. As opposed to the existing literature, in order to account for stringent energy constraints in the WSN, only statistical channel information is assumed for the non-line-of-sight (scattered) fading terms. For such a scenario, suboptimal fusion rules are developed in order to deal with the exponential complexity of the likelihood ratio test (LRT) and impractical (complete) system knowledge. Furthermore, the considered model is extended to the case of (partially unknown) jamming-originated interference. Then, the obtained fusion rules are modified with the use of composite hypothesis testing framework and generalized LRT. Coincidence and statistical equivalence among them are also investigated under some relevant simplified scenarios. Numerical results compare the proposed rules and highlight their jamming-suppression capability.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.