Reconfigurable intelligent surfaces (RISs) and millimeter-wave (mmWave) communications have been considered for providing wireless connectivity to mobile robots used in industrial plants and other indoor environments. However, the existing works have not sufficiently studied how the number and deployment locations of RISs should be optimized for serving a mobile robot. In this paper, we study RIS-assisted mmWave communications for a robot moving around fixed obstacles in an indoor industrial environment. For a fixed total number of reflecting elements, we formulate an optimization problem to minimize the transmission energy consumption of the access point (AP) while ensuring the robot’s received signal-to-noise ratio (SNR) above a threshold throughout its journey by jointly optimizing the number, positions and phase shifts of RISs and the beamforming vectors of the AP. To solve the formulated nonconvex optimization problem, we devise an iterative algorithm that decomposes it into two subproblems (i.e., optimizing the phase shifts of RISs and the beamforming vector of the AP, and optimizing the number and locations of RISs) and solves them alternately. Simulation results show that the proposed algorithm converges fast and can obtain the best number and locations of RISs that lead to a transmission energy consumption of the AP much lower than the benchmark schemes.

As offshore industries and the Internet of underwater things (IoUT) continue to expand, air-to-water communication is needed to connect various underwater sensors and things to the outside world. Visible light communication (VLC) has the potential to provide higher data rates and longer transmission distances than radio frequency and other air-to-water communication techniques. This paper presents an air-to-water VLC system where a light emitting diode (LED) transmitter carried by a hovering unmanned aerial vehicle (UAV) transmits data to an underwater receiver. We minimize the UAV energy consumption that includes both LED transmission and UAV propulsion energy consumption by optimizing the LED transmit power while guaranteeing that the average received signal-tonoise ratio (SNR) at the underwater receiver is above the required SNR. Simulation results show that our optimized LED transmit power reduces the total UAV energy consumption by up to 46% as compared to the benchmark schemes without increasing the transmission time for a given data volume.

Decentralized cryptocurrency systems, known as blockchains, have shown promise as an infrastructure for mutually distrustful parties to securely agree on transactions. Nevertheless, blockchain systems are constrained by the CAP Trilemma. Due to performance degradation, it is impossible to address this issue by improving simply the consensus layer or the network layer. To alleviate the CAP constraint in consortium blockchains, we propose a topological construction method to optimize the physical layer based on multi-dimensional hypercubes with excellent partition tolerance in probability. The basic topology has the advantage of solving the mismatch problem between the overlay network and the underlying network. It is further extended to hierarchical recursive topologies with more intermediate links or short links to balance the reliability requirement with the cost of building the physical network. We prove that the proposed hypercube topology has better partition tolerance than the regular rooted tree and ring lattice topologies, and effectively fits the upper-layer protocols at the consensus and network layers. As a result, combined with suitable transmission and consensus protocols that satisfy strong consistency and availability, the proposed topology-constructed blockchain can reach the CAP guarantee bound.