The energy efficiency of intelligent reflecting surface (IRS) enabled internet of things (IoT) networks is studied in this letter. The energy efficiency is mathematically expressed, respectively, as the number of reflecting elements and the spectral efficiency of the network and is shown to scale in the logarithm of the reflecting elements number in the high regime of transmit power from source node. Furthermore, it is revealed that the energy efficiency scales linearly over the spectral efficiency in the high regime of transmit power, in contrast to conventional studies on energy and spectral efficiency trade-offs in the non-IRS wireless IoT networks. Numerical simulations are carried out to verify the derived results for the IRS enabled IoT networks.

This paper analyzes the impact of directional antennas in improving the transmission capacity, defined as the maximum allowable spatial node density of successful transmissions multiplied by their data rate with a given outage constraint, in wireless networks. We consider the case where the gain Gm for the mainlobe of beamwidth can scale at an arbitrarily large rate. Under the beamwidth scaling model, the transmission capacity is analyzed for all path-loss attenuation regimes for the following two network configurations. In dense networks, in which the spatial node density increases with the antenna gain Gm, the transmission capacity scales as Gm4/α, where α denotes the path-loss exponent. On the other hand, in extended networks of fixed node density, the transmission capacity scales logarithmically in Gm. For comparison, we also show an ideal antenna model where there is no sidelobe beam. In addition, computer simulations are performed, which show trends consistent with our analytical behaviors. Our analysis sheds light on a new understanding of the fundamental limit of outage-constrained ad hoc networks operating in the directional mode.

One of the technological innovations that has enabled the VLSI semiconductor industry to reduce the transistor size, increase the number of transistors per die, and also follow Moore's law year after year is the fact that an equivalent yield and equivalent testing quality have been ensured for the same die size. This has contributed to reducing the economically optimum production cost (production cost per component) as advocated by Moore. In this paper, we will verify Moore's law using actual values from VLSI manufacturing sites while introducing some of the technical progress that occurred from 1970 to 2010.

A one-dimensional ad hoc network with a single active source–destination pair is analyzed in terms of transport capacity, where each node uses multiple antennas. The analysis is based on using a multi-hop opportunistic routing transmission in the presence of fading. Specifically, the lower and upper bounds on the transport capacity are derived and their scaling law is analyzed as the node density, λ, is assumed to be infinitely large. The lower and upper bounds are shown to have the same scaling (ln λ)1/α, where α denotes the path-loss exponent. We also show that using multiple antennas at each node does not fundamentally change the scaling law.

In this paper, it is shown that the bit erasure probability of turbo codes with iterative decoding in the waterfall region is nonlinearly scaled by the information blocklength. This result can be used to predict efficiently the bit erasure probability of the finite-length turbo codes over the binary erasure channel.