Non-Terrestrial Networks (NTNs), as one core infrastructure of the sixth-generation (6G) communication technology, integrate heterogeneous nodes, such as High Earth Orbit (HEO) satellites, to achieve three-dimensional ubiquitous connectivity. However, NTNs face with spectrum scarcity, imposing stringent demands on spectral efficiency and interference management. To address these challenges, we propose a NOMA-oriented spectrum sensing technique for uplink scenarios, where High-Altitude Platforms (HAPs) serve as dynamic aerial nodes for opportunistic transmission within HEO coverage. Specifically, we derive multi-user sensing thresholds to optimize detection accuracy and suppress false alarms. Numerical simulations demonstrate the technique achieves a 33.5% throughput gain over benchmarks at 10 dB and maintains satisfactory performance across PUs’ varying elevation angles and transmission willingness.

Next-generation Internet of Things (IoT) technology is vital for sixth-Generation (6G) communication systems, driving exponential growth in spectrum resource demand. Spectrum sensing, essential for identifying unused spectrum, and Non-Orthogonal Multiple Access (NOMA), which allows efficient frequency band sharing among users, can significantly improve spectrum efficiency. However, current sensing methods do not fully support NOMA, resulting in suboptimal performance. Motivated by such a circumstance, we propose a feature-based spectrum sensing method for uplink communication in power-domain NOMA IoT scenarios with multi-user interference, aiming to maximize both static and dynamic spectrum efficiency. Firstly, we introduce the notion of orbits to represent non-fully occupied spectral holes. Then we elaborate on the sensing criterion as well as workflow and design the two-stage spectrum sensing framework, which proposes the orbit estimation sensing algorithm in the stage 1 and accurate sensing threshold in the stage 2, to mitigate false alarm fluctuations. The closed-form solution for the estimation threshold and accurate threshold configuration are derived thereafter. Simulation results show that our proposed multi-orbit sensing method has stable performance and achieves average 30% system throughput gains compared to the latest NOMA techniques at 5 dB.

With the rapid development of space technology, the role of satellite communications has become progressively significant. Non-terrestrial communication is deemed a critical scenario in the sixth generation (6G) communication systems, which showcases seamless connectivity, minimal geographic constraints and substantial communication capacity. Simultaneously, satellites and terminals spring up, spatial density increases, which further emphasizes the scarcity of spectrum resources. Consequently, to improve spectrum utilization for non-terrestrial communication is a significant concern. Spectrum sensing, which allows dynamic resource reuse, plays an important role in 6G. However, high mobility in non-terrestrial scenarios poses great challenges, such as fast time-varying channels, Doppler effect, etc., which seriously affect sensing accuracy and cannot well support optimal spectrum utilization. Motivated by such circumstances, this paper proposes an elastic sensing method for the downlink non-terrestrial communication scenario. Firstly, we design the system architecture and sensing workflow. To overcome the negative effects raised by high mobility, we propose the elastic sensing criterion and multi-area dividing scheme for the sensing zone. Thresholds affected by the elastic sensing are derived for different areas. Finally, the numerical results show that from -10 dB to -5 dB, the proposed method can improve the total performance by an average of 28.3% while stabilizing the false alarm probability around 0.1 typical level and demonstrating higher constancy compared with traditional technologies from −10 dB to −5 dB.

The upcoming sixth-generation (6G) of ubiquitous connectivity communications systems is driven by the next-generation of Internet of Things (IoT) technology. Accordingly, the demand for spectrum resources is growing exponentially. Spectrum sensing, which dynamically explores spectrum holes, is expected to be crucial in the 6G era. In the meantime, Non-Orthogonal Multi-Access (NOMA), an efficient means of reusing resources, can enable multiple users to share the same frequency band stably. The combination of both technologies holds promise for more effective use of spectrum resources in future commu-nications. In this paper, we present a spectrum sensing method for the uplink communication scenario in NOMA with multi-user interference, which aims to make effective use of both static and dynamic gain on spectrum efficiency. Firstly, the sensing criterion and workflow are outlined. The closed-form solution for the sensing threshold configuration is derived thereafter. The simulation results demonstrate the feasibility of the proposed approach, which can increase the system throughput up to 19.7%, when compared to NOMA without spectrum sensing.

With the rapid development of mobile communication and Internet of Things, the scarcity of spectrum resources is becoming increasingly severe. As a supplement to terrestrial networks, satellite communication can alleviate the pressure of the terrestrial spectrum. Meanwhile, dynamic spectrum utilization plays an important role in alleviating the scarcity of spectrum resources. To integrate the advantages, we propose the multi-level sliced sensing architecture and design the workflow combining satellites and spectrum sensing. The sensing threshold settings are deduced thereafter. According to the theoretical derivation above, the challenge of false alarm floating caused by high mobility of satellites is addressed by studying the relationship among false alarm probability velocity, Doppler frequency and slice number. Numerical results show that under highly dynamic channel conditions, the proposed method can improve detection probability by up to 54% over existing technique while stabilizing the equivalent limitation of Pf.

In order to improve the feasibility of the CSCW systems, we utilizes the methods in organizational semiotics and put forward the organizational model and the organizational state machine (OSM) to describe the norms in the systems. According to the general form of Norm, we classify the Norm into three kinds of rules expressed by the logical predications. Combining with cooperative theory and speech-act theory, we first propose an organizational relationship graph of role. Behavior and Rule of CSCW systems and then a logical predication-based model. This model is referred to as the organizational model which is used to describe the relationship graph. In addition, we present the OSM, which can check the logical conflict among the rules and insure semantic completeness. And the dynamical changes of rules and roles can be delineated exactly by the OSM.