Full-duplex and compressed sensing based neighbor discovery for wireless ad-hoc network

Neighbor discovery (ND) is an essential step to configure a wireless ad-hoc network, where a quick and accurate ND scheme is very important for subsequent network operations. However, the speeds of current ND schemes are still not quick enough and mainly restricted by the constraints of half-duplex and single packet reception (SPR). To overcome both of these two constraints, we propose a Full-duplex and Compressed sensing based Neighbor Discovery (FCND) scheme, which can complete the ND process in only one slot. Specifically, with the help of the emerging full-duplex technology, each node broadcasts a unique pseudo-random sequence, and receives a superposition of the sequences from its neighbors, simultaneously. Then, based on compressed sensing (CS) theory, each node decodes all its neighbor IDs from the received signal simultaneously, i.e., resolves the challenge of SPR. Mathematical analysis shows that decoding neighbor IDs in FCND scheme is actually a binary CS recovery problem. To further improve the decoding performance, we propose an adaptive thresholding and adjusting (ATA) algorithm. Simulation results show that, compared with existing schemes, the proposed FCND scheme can reduce the signaling overhead by up to 96%, and the proposed ATA algorithm can increase the decoding accuracy by up to 25%.