Throughput optimization in multi-hop wireless networks with reconfigurable antennas

In multi-hop wireless networks (MWNs), interference and connectivity are two key factors that affect end-to-end network throughput. Traditional omni-directional antennas and directional antennas either generate significant interference or provide poor network connectivity. Reconfigurable antenna (RA) is an emerging antenna technology that can agilely switch among many different antenna states including radiation patterns, so as to suppress interference and maintain high connectivity at the same time. In this work, we systematically exploit the pattern diversity and fast reconfigurability of RAs to enhance the throughput of MWNs. We first propose a novel link-layer model that captures the dynamic relations between antenna pattern, link coverage and interference. Based on our model, a throughput optimization framework is proposed by jointly considering pattern selection and link scheduling. Our problem is formulated as a mixed integer non-linear programming problem. The superiority of reconfigurable antennas compared with traditional omni-directional and directional antennas is both theoretically proven, and validated through extensive simulations.