on the maximum stable throughput problem in random networks with directional antennas
We consider the problem of determining rates of growth for the maximum stable throughput achievable in dense wireless networks. We formulate this problem as one of finding maximum flows on random unit-disk graphs. Equipped with the max-flow/min-cut theorem as our basic analysis tool, we obtain rates of growth under three models of communication: (a) omnidirectional transmissions; (b) "simple" directional transmissions, in which sending nodes generate a single beam aimed at a particular receiver; and (c) "complex" directional transmissions, in which sending nodes generate multiple beams aimed at multiple receivers. Our main finding is that an increase of ?log2 n in maximum stable throughput is all that can be achieved by allowing arbitrarily complex signal processing (in the form of generation of directed beams) at the transmitters and receivers. We conclude therefore that neither directional antennas, nor the ability to communicate simultaneously with multiple nodes, can be expected in practice to effectively circumvent the constriction on capacity in dense networks that results from the geometric layout of nodes in space.
maximum stable throughput throughput randomization random networks network directional antennas direct wireless networks flow graph analysis tool model communication generation complexity signal processing practical capacities layout space multicommodity flow network flow random graphs