Neighbor Discovery for Wireless Networks

We examine the problem of determining which nodes are neighbors of a given one in a wireless network. We consider an unsupervised network operating on a frequency- flat Gaussian channel, where K + 1 nodes associate their identities to nonorthogonal signatures, transmitted at random times, synchronously, and independently. A number of neighbor- discovery algorithms, based on different optimization criteria, are introduced and analyzed. Numerical results show how reduced- complexity algorithms can achieve a satisfactory performance.