  We present a new adaptive resource optimization strategy that jointly
allocates the subwindow and transmit power in multi-device terahertz (THz) band
Internet of Things (Tera-IoT) networks. Unlike the prior studies focusing
mostly on maximizing the sum distance, we incorporate both rate and
transmission distance into the objective function of our problem formulation
with key features of THz bands, including the spreading and molecular
absorption losses. More specifically, as a performance metric of Tera-IoT
networks, we adopt the transport capacity (TC), which is defined as the sum of
the rate-distance products over all users. This metric has been widely adopted
in large-scale ad hoc networks, and would also be appropriate for evaluating
the performance of various Tera-IoT applications. We then formulate an
optimization problem that aims at maximizing the TC. Moreover, motivated by the
importance of the transmission distance that is very limited due to the high
path loss in THz bands, our optimization problem is extended to the case of
allocating the subwindow, transmit power, and transmission distance. We show
how to solve our problems via an effective two-stage resource allocation
strategy. We demonstrate the superiority of our adaptive solution over
benchmark methods via intensive numerical evaluations for various environmental
setups of large-scale Tera-IoT networks.
