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Full-duplex (FD) systems have emerged as an essential enabling technology to further increase the data rate of wireless communication systems. The key idea of FD is to serve multiple users over the same bandwidth with a base station (BS) that can simultaneously transmit and receive the signals. The most challenging issue in designing an FD system is to address both the harmful effects of residual self-interference caused by the transmit-to-receive antennas at the BS as well as the cochannel interference from an uplink user (ULU) to a downlink user (DLU). An efficient solution to these problems is to assign the ULUs/DLUs in different groups/slots, with each user served in multiple groups. Hence, this paper studies the joint design of transmit beamformers, ULUs/DLUs group assignment, and time allocation for each group. The specific aim is to maximize the sum rate under the ULU/DLU minimum throughput constraints. The utility function of interest is a difficult nonconcave problem, and the involved constraints are also nonconvex, and so this is a computationally troublesome problem. To solve this optimization problem, we propose a new path-following algorithm for computational solutions to arrive at least the local optima. Each iteration involves only a simple convex quadratic program. We prove that the proposed algorithm iteratively improves the objective while guaranteeing convergence. Simulation results confirm the fast convergence of the proposed algorithm with substantial performance improvements over existing approaches.Index Terms-Full-duplex radios, full-duplex self-interference, multiuser transmission, nonconvex programming, spectral efficiency, transmit beamforming, user grouping.

Accurate characterization of marsh elevation and landcover evolution is important for coastal management and conservation. This research proposes a novel unsupervised clustering method specifically developed for segmenting dense terrestrial laser scanning (TLS) data in coastal marsh environments. The framework implements unsupervised clustering with the well-known K-means algorithm by applying an optimization to determine the "k" clusters. The fundamental idea behind this novel framework is the application of multi-scale voxel representation of 3D space to create a set of features that characterizes the local complexity and geometry of the terrain. A combination of point-and voxel-generated features are utilized to segment 3D point clouds into homogenous groups in order to study surface changes and vegetation cover. Results suggest that the combination of point and voxel features represent the dataset well. The developed method compresses millions of 3D points representing the complex marsh environment into eight distinct clusters representing different landcover: tidal flat, mangrove, low marsh to high marsh, upland, and power lines. A quantitative assessment of the automated delineation of the tidal flat areas shows acceptable results considering the proposed method is unsupervised with no training data. Clustering results based on K-means are also compared to results based on the Self Organizing Map (SOM) clustering algorithm. Results demonstrate that the developed multi-scale voxelization approach and representative feature set are transferrable to other clustering algorithms, thereby providing an unsupervised framework for intelligent scene segmentation of TLS point cloud data in marshes.

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Recent years have witnessed a growing interest in Internet access from space assisted by low earth orbit (LEO) satellite networks. In the domain of the last-mile access for the Internet of Vehicles (IoV), hybrid free-space optical (FSO)/radio-frequency (RF) communication has recently attracted worldwide research efforts. While the transmission control protocol (TCP) is the most widely deployed transport protocol on the Internet, its performance in the error-prone environment of LEO satellite-assisted hybrid FSO/RF vehicular networks is not well understood. This paper develops a comprehensive analytical model based on the cross-layer approach for TCP performance, considering the FSO and RF satellite fading channels, modeled by the Gamma-Gamma and Nakagami-m distributions, respectively. The error-control solutions, including the Reed-Solomon (RS) code and Selective repeat automatic repeat request (SR-ARQ), are also employed. Numerical results quantitatively demonstrate the impact of transmission errors at lastmile links and different parameters/settings of error-control solutions on the TCP performance. The paper also supports the selection of proper TCP variants for the considered networks.INDEX TERMS Satellite networks, hybrid FSO/RF last-mile, Internet of vehicles, Transmission control protocols, Error-control solutions.

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