With the explosive proliferation of connected devices and mobile users in the Internet-of-things, multiple access techniques are urged to be developed for the next generation wireless communications. Recently, rate-splitting multiple access (RSMA) has been a promising communication technology that holds advantages of strong robustness, low complexity, and high spectral efficiency, which can be integrated with the indoor visible light communication (VLC) broadcast system to compensate for the shortcomings of limited modulation bandwidth of LEDs. However, the research on the RSMA-based VLC systems is still in its infancy and there exist various problems to be explored. To benefit from the RSMA technique, this paper investigates the energy efficiency optimizations for both single-cell and multi-cell RSMA-based VLC broadcast systems. Specifically, these two systems are modeled, where the VLC broadcast channel follows Lambertian radiation model, and the splitting design and successive interference cancellation of RSMA are employed to mitigate the multi-user interference. Especially for multi-cell networks, the zero-forcing approach is adopted to eliminate the inter-cell interference. To maximize the energy efficiency, the precoding and power allocation problems are formulated for single-cell and multi-cell networks while accommodating multiple constraints including dynamic operation ranges of LEDs, QoS requirements, and interference elimination. For solving these non-convex fractional problems, two pieces of successive convex approximation (SCA)-based algorithms are proposed, in which the variable transformation and linear approximation are adopted. Simulation results indicate that the proposed schemes can achieve superior energy efficiency with fast convergence for various network loads and user deployments.

Multiuser multirelay network is a potential scenario to fulfill the transmission requirements of various sources and high-volume traffic for the Internet of Underwater Things. To efficiently complete concurrent transmissions for multiple users, this article investigates the joint relay assignment and power allocation problem for multiuser multirelay networks based on the underwater optical wireless communication (UOWC). Specifically, the multiuser multirelay network for UOWC based on decode-and-forward relaying is modeled, where the absorption, scattering, solar radiation noise, and oceanic turbulence of UOWC are all considered. The joint optimization problem of relay assignment and power allocation is formulated as a mixed-integer programming problem, where the average outage probability is minimized with the constraint of total transmitted power. To solve this joint problem, an alternating optimization method is employed, which alternately optimizes the relay assignment and power allocation subproblems. The relay assignment subproblem is modeled as a weighted bipartite matching problem and solved by an improved Kuhn-Munkres algorithm, whereas the power allocation subproblem is proved to be quasiconvex and solved by an iterative bisection algorithm. The simulation results indicate that the proposed schemes significantly reduce the average outage probability with fast convergence.

Cooperative transmission is a promising technology to expand communication range and improve system performance for underwater optical wireless communications (UOWCs). To adequately exploit the benefits of cooperative UOWCs, the relay selection and power allocation problems require to be explored. This paper investigates the relay selection and power allocation issues for the cooperative UOWC in the presence of solar radiation noise. Specifically, the cooperative UOWC based on amplify-and-forward (AF) relaying is modeled, where the effects of absorption, scattering, and solar radiation noise are all considered. We design two optimization schemes that minimize the energy consumption and maximize the overall signal-to-noise ratio (SNR), respectively. Both schemes are proved to be strictly quasi-convex and solved by Levenberg-Marquardt (LM) algorithm. The effectiveness of the proposed schemes is evaluated in line-of-sight (LOS) links and non-line-of-sight (NLOS) links, and the main factor affecting the relay selection and power allocation are derived for both LOS links and NLOS links.

Adaptive beamforming plays an increasingly vital role in various applications, including radar, sonar, telecommunications, and many other related fields. In this paper, we present an adaptive beamformer (called polarimetric Sparse-Reconstruction beamformer) based on cascaded sparse diversely polarized planar array. The cascaded sparse array consists of multiple parallel sparse linear subarrays, whose difference co-array has no holes. The beamformer is operated in the joint spatial and polarization domain; thus, can potentially suppress the interferences that are close to the desired signal with different polarization states. Two key building blocks of our proposed beamformer are polynomial rooting-based closed-form two-dimensional direction-of-arrival and polarization joint estimation procedures, where the involved polynomial coefficients are also derived. Then, the closed-form power distribution estimation is presented to reconstruct the interference-plus-noise covariance matrix by leveraging the sparsity of the desired signal and interferences in the joint spatial and polarization domain. Thus, the proposed adaptive beamformer is computationally efficient, since all the procedures involved are formatted by closed-form expressions. Finally, a set of simulation examples are given to evaluate the characteristics of the proposed cascaded sparse array as well as the performance and robustness of the proposed beamformer in different scenarios, and compared against several existing approaches.