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We examine the problem of determining which nodes are neighbors of a givenone in a wireless network. We consider an unsupervised network operating on afrequency-flat Gaussian channel, where $K+1$ nodes associate their identitiesto nonorthogonal signatures, transmitted at random times, synchronously, andindependently. A number of neighbor-discovery algorithms, based on differentoptimization criteria, are introduced and analyzed. Numerical results show howreduced-complexity algorithms can achieve a satisfactory performance.

Neighbor Discovery in Wireless Networks:A Multiuser-Detection Approach