Counting surrounding nodes using DS-SS signals and De Bruijn sequences in blind environment

In recent years the technological development has encouraged several applications based on node to node communications without any fixed infrastructure. This paper presents preliminary evaluation of popular estimating techniques to populate active nodes in the neighborhood using De Bruijn sequences. They have much higher cardinality compared to any other family of binary sequences at a parity of length. This characteristic of De Bruijn sequences can be exploited to identify the presence of an active node in a dense surrounding, to assist the primary node in making intelligent decisions in a blind or foggy environment. The simulation model in this paper evaluates the use of eigenvalue estimation to estimate the spreading sequence among noisy signals, based on eigenvalues analysis techniques. The received signal is divided into windows, from which a covariance matrix is computed; the sequence can be reconstructed from the two first eigenvectors of this matrix, and that useful information, such as the desynchronization time, can be extracted from the eigenvalues.