Non-orthogonal multiple access (NOMA) is regarded as a promising technology in achieving high capacity and massive connectivity. In this paper, the reliable transmission scheme of downlink NOMA systems is investigated. In particular, we divide the disc covered by the base station into several annular areas, where the receivers are randomly located following a uniform distribution. In this way, NOMA pairing is performed by randomly selecting receivers from two different areas. Firstly, we derive the closed-form expressions of bit error rate (BER) with quadrature phase-shift keying (QPSK) modulation, where the channel is modeled as small-scale Rayleigh fading and large-scale path loss. To achieve reliable communications, then, the BER performance of the receiver with the worst channel gain in each area is studied. Finally, an optimal power allocation algorithm is proposed, which obtains the minimum transmission power and optimal power allocation factor with a given BER constraint of all receivers. Extensive simulations demonstrate the accuracy of obtained BER expressions and the effectiveness of the proposed algorithm. These results provide valuable insight into realizing on reliable transmission of NOMA with randomly deployed receivers.

Unmanned aerial vehicles (UAVs) are widely adopted as aerial relays assisting seamless coverage due to flexible deployment and high maneuverability, but their service time is considered as the bottleneck due to the constrained energy. The energy-efficient intelligent reflecting surface (IRS) is adopted in the UAV system for long-term service. In this paper, the cooperative relay-transmission in UAV-IRS based terahertz (THz) networks is studied, where UAVs with IRSs as relays facilitate long-term seamless coverage through THz transmission, and the maximum transmission capacity based on sum rate and energy consumption is formulated as a maximization problem to optimize UAV altitude, relay selection and user association. In the single-user-single-UAV scenario, how relay selection is affected by the IRS element number and UAV transmitting power is analyzed. In the multiple-user-multiple-UAV scenario, the maximization problem is decomposed into three sub-problems and solved by an alternating optimization method: optimizing UAV height using gradient descent and interior point algorithms, solving relay selection as a linear programming problem by continuous variable relaxation, and optimizing user association as a knapsack problem through association matrix transformation. Simulation results demonstrate the effectiveness of the proposed method and indicate that the cooperative relay-transmission scheme achieves quasi-optimal performance when compared with existing schemes.

To mitigate the impact of the dramatic growth of wireless video traffic and provide users with heterogeneous video services, a collaborative caching-transmission method in cache-enabled terahertz (THz) heterogeneous networks is studied in this paper. We propose a novel scalable video coding (SVC)-based two-tier cooperative caching strategy that can provide video services with different perceptual qualities. In addition, we propose a hierarchical hybrid transmission scheme where users obtain the requested layer files through the cooperative cellular multicast-D2D and THz transmissions. A base layer-based multicast group aggregation process is presented to improve resource utilization, while an efficient multicast transmission resource scheduling scheme can make better use of the spatial reusability. We derive the expressions for the average offloading capacity gain and average energy consumption, and formulate an efficiency function optimization problem. The problem is efficiently solved by the greedy strategy-gradient descent based caching solution and long tail distribution based heuristic caching solution. Simulation results validate the two solutions and demonstrate that the proposed caching-transmission method can achieve quasi-optimal performance compared with other contrasting schemes.

With the ongoing expansion of user numbers and the diversity of business types, wireless networks are progressing toward broader spatial dimensions and increased functionality. With respect to coverage, the space–air–ground integrated network (SAGIN) is considered a promising solution for providing seamless global connectivity to emerging services. In terms of functionality, wireless networks are expected to offer not only communication services but also sensing and computing services, which are crucial for certain businesses. However, within SAGIN there is a significant variance in performance among different types of radio access networks (RANs). This necessitates a reconsideration of system architecture and handover selection schemes to meet the quality of service (QoS) requirements of various business applications. The main focus of this article is to explore the integration of sensing and mobile edge computing (MEC) with SAGIN and also to examine the system architecture, selection schemes, and handover procedures. We first provide an overview of SAGIN’s capabilities and highlight its integrated architecture. Subsequently, we introduce several handover selection schemes, followed by an elaboration on the redesigned handover procedure for SAGIN. Finally, we present some simulation results and discuss challenges that need to be addressed in practical implementation.

To meet the requirements of ubiquitous connectivity, the sixth-generation is expected to support higher frequencies such as millimeter waves and terahertz, as well as high-mobility scenarios like unmanned aerial vehicles and vehicular networks. However, communication scenarios under these conditions may suffer from beam misalignment due to high mobility, especially in high-frequency channels with narrow beam characteristics. Integrated sensing and communications (ISAC) enable hardware and spectrum resource sharing between radar sensing and wireless communication, and exhibit great potential in sensing-assisted communication. One pressing problem is that performance metrics for sensing and communication are often contradictory when they share the same hardware or wireless resources. Therefore, how to optimize the performance metrics between both is the key to fulfilling specific requirements. This article focuses on ISAC enabled predictive beamforming, and investigates the technical characteristics, system architecture, and optimization schemes involved in the performance trade-offs. We first provide an overview of the unique characteristics of ISAC and predictive beamforming and highlight the benefits of combining them. We then investigate the design architectures and propose an optimization scheme that can achieve a performance trade-off between sensing and communication to maximize throughput. Finally, we highlight some challenging issues that need to be addressed in practical implementations.

Considering that unmanned aerial vehicles (UAVs) with the advantages of flexible deployment and high maneuverability have the limited energy to provide long-term seamless coverage, a cooperative recharging-transmission strategy is studied in this paper for the powered UAV-aided terahertz (THz) downlink networks, where a UAV-to-user THz sub-band association scheme is proposed for the THz frequency transmission to eliminate interference. Based on this, the minimum requirements of the wireless charging window and THz-transmitting window are derived. A minimization problem of minimum timeslot requirement is formulated to jointly optimize UAV placement and UAV-to-user THz sub-band association. The optimization problem is non-convex, and we propose an alternating optimization solution via iteratively solving placement subproblem and association subproblem. Specifically, we resort to the coalescent method of interior point and gradient descent algorithms to optimize UAV placement. The UAV-to-user THz sub-band association is solved as a knapsack problem by the transformation of association matrix. Simulation results validate the solution and demonstrate that the proposed strategy can achieve quasi-optimal performance compared with other contrasting strategies.