Nonassisted Adaptive Algorithm for Data Fusion in Distributed Detection Systems

In this work we propose a nonassisted adaptive fusion algorithm to perform data detection in distributed systems with a decode-then-fuse (DtF) type of receiver. Different from previously proposed fusion rules, where channel and nodes statistics are needed, the proposed algorithm adapts its weights and decision threshold based only on the received signals, so that time-varying scenarios or inhomogeneous systems are well suited. Computer simulations show that the proposed adaptive fusion strategy exhibits a performance very close to that of the optimal fusion rule.