Dual Threshold Cooperative Sensing Based Dynamic Spectrum Sharing Algorithm for Integrated Satellite and Terrestrial System

In this paper, cognitive technology is introduced into the integrated satellite terrestrial system to realize the dynamic spectrum sharing of the system and improve the utilization rate of spectrum resources. To overcome the effects of low signal-to-noise ratio (SNR) and noise uncertainty in the channel, a dual-threshold cooperative sensing strategy based on energy detection is introduced. Spectrum sensing is considered as a binary hypothesis problem, but the uncertainty of noise interference in the integrated satellite terrestrial cognitive system will cause the perception to appear ambiguous. Moreover, the noise power varies with time and relative position within a certain range. In the fuzzy state, the perception technology adopts the equal-gain merging algorithm, and derives the voting optimization algorithm to improve the accuracy of decision-making. In addition, taking the minimum error probability as the optimization goal, the optimal adjustment of the adaptive double threshold is realized based on the equal-gain combining algorithm. The simulation results show that the spectrum detection accuracy under low SNR is improved, and the opportunity for terrestrial networks to share spectrum resources is increased

Load Estimation Based Dynamic Access Protocol for Satellite Internet of Things

In recent years, the Internet of Things (IoT) industry has become a research hotspot. With the advancement of satellite technology, the satellite Internet of Things is further developed along with a new generation of information technology and commercial markets. However, existing random access protocols cannot cope with the access of a large number of sensors and short burst transmissions. The current satellite Internet of Things application scenarios are divided into two categories, one has only sensor nodes and no sink nodes, and the other has sink nodes. A time-slot random access protocol based on Walsh code is proposed for the satellite Internet-of-Things scenario with sink nodes. In this paper, the load estimation algorithm is used to reduce the resource occupancy rate in the case of medium and low load, and a dynamic Walsh code slot random access protocol is proposed to select the appropriate Walsh code length and frame length h. The simulation results show that the slotted random access protocol based on Walsh code can effectively improve the throughput of the system under high load. The introduction of load estimation in the case of medium and low load can effectively reduce the resource utilization of the system, and ensure that the performance of the access protocol based on Walsh codes does not deteriorate. However, in the case of high load, a large resource overhead is still required to ensure the access performance of the system

Load Estimation Based Dynamic Access Protocol for Satellite Internet of Things

In recent years, the Internet of Things (IoT) industry has become a research hotspot. With the advancement of satellite technology, the satellite Internet of Things is further developed along with a new generation of information technology and commercial markets. However, existing random access protocols cannot cope with the access of a large number of sensors and short burst transmissions. The current satellite Internet of Things application scenarios are divided into two categories, one has only sensor nodes and no sink nodes, and the other has sink nodes. A time-slot random access protocol based on Walsh code is proposed for the satellite Internet-of-Things scenario with sink nodes. In this paper, the load estimation algorithm is used to reduce the resource occupancy rate in the case of medium and low load, and a dynamic Walsh code slot random access protocol is proposed to select the appropriate Walsh code length and frame length h. The simulation results show that the slotted random access protocol based on Walsh code can effectively improve the throughput of the system under high load. The introduction of load estimation in the case of medium and low load can effectively reduce the resource utilization of the system, and ensure that the performance of the access protocol based on Walsh codes does not deteriorate. However, in the case of high load, a large resource overhead is still required to ensure the access performance of the system

Regularized Zero-Forcing Dirty Paper Precoding in a High-Throughput Satellite Communication System

In order to maximize the available data rate and spectrum utilization efficiency, a high-throughput satellite communication system adopts the full spectrum reuse scheme, which will cause serious co-frequency interference. In this paper, a forward link model, considering the effects of free space loss, rainfall attenuation, and beam gain, is established, and the classical low-complexity of the zero-forcing precoding algorithm is improved in order to solve the serious co-frequency interference. Moreover, the regularized zero-forcing precoding algorithm considering the influence of system noise is studied, and a low complexity regularized zero-forcing dirty paper precoding algorithm is proposed, whose basic principle is to sort users based on the principle of channel maximum norm selection and practical application scenarios. Simulation results show that it can encode users sequentially, according to the channel conditions, to maximize the SINR (signal-to-interference-plus-noise ratio) and increase the throughput of the system

Regularized Zero-Forcing Dirty Paper Precoding in a High-Throughput Satellite Communication System

In order to maximize the available data rate and spectrum utilization efficiency, a high-throughput satellite communication system adopts the full spectrum reuse scheme, which will cause serious co-frequency interference. In this paper, a forward link model, considering the effects of free space loss, rainfall attenuation, and beam gain, is established, and the classical low-complexity of the zero-forcing precoding algorithm is improved in order to solve the serious co-frequency interference. Moreover, the regularized zero-forcing precoding algorithm considering the influence of system noise is studied, and a low complexity regularized zero-forcing dirty paper precoding algorithm is proposed, whose basic principle is to sort users based on the principle of channel maximum norm selection and practical application scenarios. Simulation results show that it can encode users sequentially, according to the channel conditions, to maximize the SINR (signal-to-interference-plus-noise ratio) and increase the throughput of the system