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Current fifth-generation (5G) networks do not cover maritime areas, causing difficulties in developing maritime Internet of Things (IoT). To tackle this problem, we establish a nearshore network by collaboratively using on-shore terrestrial base stations (TBSs) and tethered unmanned aerial vehicles (UAVs). These TBSs and UAVs form virtual clusters in a usercentric manner. Within each virtual cluster, non-orthogonal multiple access (NOMA) is adopted for agilely including various maritime IoT devices, which are sparsely distributed over the vast ocean. The nearshore network also shares the spectrum with marine satellites. In such a NOMA-based hybrid satellite-UAV-terrestrial network, interference among different network segments, different clusters, and different users occurs. We thereby formulate a joint power allocation problem to maximize the sum rate of the network. Different from existing studies, we use large-scale channel state information (CSI) only for optimization to reduce system overhead. The large-scale CSI is obtained by using the position information of maritime IoT devices. The problem is non-convex with intractable non-linear constraints. We tackle these difficulties by adopting max-min optimization, the auxiliary function method, and the successive convex approximation technique. An iterative power allocation algorithm is accordingly proposed, which is shown to be effective for coverage enhancement by simulations. This shows the potential of NOMA-based hybrid satellite-UAV-terrestrial networks for maritime on-demand coverage.

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The sixth-generation (6G) network is envisioned to integrate communication and sensing functions, so as to improve the spectrum efficiency (SE) and support explosive novel applications. Although the similarities of wireless communication and radio sensing lay the foundation for their combinations, their different requirements for electromagnetic signals make the joint system design a hard task. To simultaneously guarantee sensing accuracy and communication capacity, the multipleinput and multiple-output (MIMO) technique plays an important role, due to its unique capability of spatial beamforming and waveform shaping. However, the configuration of MIMO also brings high hardware cost, high power consumption, and high signal processing complexity. How to efficiently apply MIMO in the joint communication and sensing (JCAS) system is still open. In this survey, we discuss JCAS in the context of MIMO configurations. We first outline the roles of MIMO in the progress of communication and radar sensing. Then, we review current advances in both communication and sensing coexistence and integration in detail. Three novel JCAS MIMO models are subsequently discussed by introducing the promising 6G enablers, i.e., the unmanned aerial vehicle (UAV) and the reconfigurable intelligent surface (RIS). With the aim of building a compatible dual-function system, the benefits and challenges of MIMO in JCAS are summarized in each subsection. Promising solutions are also discussed from the system perspective with simple, intelligent and robust principles. In the end, open issues are outlined to envisage a comprehensive JCAS network in the near future.

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The sixth-generation (6G) network is envisioned to integrate communication and sensing functions, so as to improve the spectrum efficiency (SE) and support explosive novel applications. Although the similarities of wireless communication and radio sensing lay the foundation for their combination, there is still considerable incompatible interest between them. To simultaneously guarantee the communication capacity and the sensing accuracy, the multiple-input and multiple-output (MIMO) technique plays an important role due to its unique capability of spatial beamforming and waveform shaping. However, the configuration of MIMO also brings high hardware cost, high power consumption, and high signal processing complexity. How to efficiently apply MIMO to achieve balanced communication and sensing performance is still open. In this survey, we discuss joint communication and sensing (JCAS) in the context of MIMO. We first outline the roles of MIMO in the process of wireless communication and radar sensing. Then, we present current advances in both communication and sensing coexistence and integration in detail. Three novel JCAS MIMO models are subsequently discussed by combining cutting-edge technologies, i.e., cloud random access networks (C-RANs), unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs). Examined from the practical perspective, the potential and challenges of MIMO in JCAS are summarized, and promising solutions are provided. Motivated by the great potential of the Internet of Things (IoT), we also specify JCAS in IoT scenarios and discuss the uniqueness of applying JCAS to IoT. In the end, open issues are outlined to envisage a ubiquitous, intelligent and secure JCAS network in the near future.

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