Energy-Efficient Traffic Offloading for RSMA-Based Hybrid Satellite Terrestrial Networks with Deep Reinforcement Learning

As the demands of massive connections and vast coverage rapidly grow in the next wireless communication networks, rate splitting multiple access(RSMA) is considered to be the new promising access scheme since it can provide higher efficiency with limited spectrum resources. In this paper, combining spectrum splitting with rate splitting, we propose to allocate resources with traffic offloading in hybrid satellite terrestrial networks. A novel deep reinforcement learning method is adopted to solve this challenging non-convex problem. However, the neverending learning process could prohibit its practical implementation. Therefore, we introduce the switch mechanism to avoid unnecessary learning. Additionally, the QoS constraint in the scheme can rule out unsuccessful transmission. The simulation results validates the energy efficiency performance and the convergence speed of the proposed algorithm.

Covert Communication in Integrated High Altitude Platform Station Terrestrial Networks

In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.

Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network

Increasing the coverage and capacity of cellular networks by deploying additional base stations is one of the fundamental objectives of fifth-generation(5G)networks.However,it leads to performance degradation and huge spectral consumption due to the massive densification of connected devices and simultaneous access demand.To meet these access conditions and improve Quality of Service,resource allocation(RA)should be carefully optimized.Traditionally,RA problems are nonconvex optimizations,which are performed using heuristic methods,such as genetic algorithm,particle swarm optimization,and simulated annealing.However,the application of these approaches remains computationally expensive and unattractive for dense cellular networks.Therefore,artificial intelligence algorithms are used to improve traditional RA mechanisms.Deep learning is a promising tool for addressing resource management problems in wireless communication.In this study,we investigate a double deep Q-network-based RA framework that maximizes energy efficiency(EE)and total network throughput in unmanned aerial vehicle(UAV)-assisted terrestrial networks.Specifically,the system is studied under the constraints of interference.However,the optimization problem is formulated as a mixed integer nonlinear program.Within this framework,we evaluated the effect of height and the number of UAVs on EE and throughput.Then,in accordance with the experimental results,we compare the proposed algorithm with several artificial intelligence methods.Simulation results indicate that the proposed approach can increase EE with a considerable throughput.

Double-Edge Intelligent Integrated Satellite Terrestrial Networks

The efficient integration of satellite and terrestrial networks has become an important component for 6 G wireless architectures to provide highly reliable and secure connectivity over a wide geographical area.As the satellite and cellular networks are developed separately these years,the integrated network should synergize the communication,storage,computation capabilities of both sides towards an intelligent system more than mere consideration of coexistence.This has motivated us to develop double-edge intelligent integrated satellite and terrestrial networks(DILIGENT).Leveraging the boost development of multi-access edge computing(MEC)technology and artificial intelligence(AI),the framework is entitled with the systematic learning and adaptive network management of satellite and cellular networks.In this article,we provide a brief review of the state-of-art contributions from the perspective of academic research and standardization.Then we present the overall design of the proposed DILIGENT architecture,where the advantages are discussed and summarized.Strategies of task offloading,content caching and distribution are presented.Numerical results show that the proposed network architecture outperforms the existing integrated networks.

Deep Unfolding for Cooperative Rate Splitting Multiple Access in Hybrid Satellite Terrestrial Networks

Rate splitting multiple access(RSMA)has shown great potentials for the next generation communication systems.In this work,we consider a two-user system in hybrid satellite terrestrial network(HSTN)where one of them is heavily shadowed and the other uses cooperative RSMA to improve the transmission quality.The non-convex weighted sum rate(WSR)problem formulated based on this model is usually optimized by computational burdened weighted minimum mean square error(WMMSE)algorithm.We propose to apply deep unfolding to solve the optimization problem,which maps WMMSE iterations into a layer-wise network and could achieve better performance within limited iterations.We also incorporate momentum accelerated projection gradient descent(PGD)algorithm to circumvent the complicated operations in WMMSE that are not amenable for unfolding and mapping.The momentum and step size in deep unfolding network are selected as trainable parameters for training.As shown in the simulation results,deep unfolding scheme has WSR and convergence speed advantages over original WMMSE algorithm.

Realizing Intelligent Spectrum Management for Integrated Satellite and Terrestrial Networks

Nowadays both satellite and terrestrial networks are expanding rapidly to meet the ever-increasing demands for higher throughput,lower latency,and wider coverage.However,spectrum scarcity places obstacles in the sustainable development.To accommodate the expanding network within a limited spectrum,spectrum sharing is deemed as a promising candidate.Particularly,cognitive radio(CR)has been proposed in the literature to allow satellite and terrestrial networks to share their spectrum dynamically.However,the existing CR-based schemes are found to be impractical and inefficient because they neglect the difficulty in obtaining the accurate and timely environment perception in satellite communications and only focus on link-level coexistence with limited interoperability.In this paper,we propose an intelligent spectrum management framework based on software defined network(SDN)and artificial intelligence(AI).Specifically,SDN transforms the heterogenous satellite and terrestrial networks into an integrated satellite and terrestrial network(ISTN)with reconfigurability and interoperability.AI is further used to make predictive environment perception and to configure the network for optimal resource allocation.Briefly,the proposed framework provides a new paradigm to integrate and exploit the spectrum of satellite and terrestrial networks.

Advances in Multi-Terabit, Long-Haul WDM Transmission for Terrestrial Networks

This paper reviews the recent advances in multi-terabit long-haul transmission technologies for terrestrial optical networks. The use of high performance new fibres, low-noise Raman amplification, optimised modulation formats, and forward error correction is shown to be effective for capacity and distance expansion.

Joint UE Location Energy-Efficient Resource Management in Integrated Satellite and Terrestrial Networks

Integrated satellite and terrestrial networks can be used to solve communication problems in natural disasters,forestry monitoring and control,and military communication.Unlike traditional communication methods,integrated networks are effective solutions because of their advantages in communication,remote sensing,monitoring,navigation,and all-weather seamless coverage.Monitoring,urban management,and other aspects will also have a wide range of applications.This study first builds an integrated network overlay model,and divides the satellite network into two categories:terrestrial network end users and satellite network end users.The energy efficiency,throughput,and signal-to-noise ratio(SINR)are deduced and analyzed.In this paper,we discuss the influence of various factors,such as transmit power,number of users,size of the protected area,and terminal position,on energy efficiency and SINR.A satellite-sharing scheme with a combination of the user location and an exclusion zone with high energy efficiency and anti-jamming capability is proposed to provide better communication quality for end users in integrated satellite and terrestrial networks.

Cooperative Jamming for Physical Layer Security in Hybrid Satellite Terrestrial Relay Networks

To integrate the satellite communications with the LTE/5G services, the concept of Hybrid Satellite Terrestrial Relay Networks(HSTRNs) has been proposed. In this paper, we investigate the secure transmission in a HSTRN where the eavesdropper can wiretap the transmitted messages from both the satellite and the intermediate relays. To effectively protect the message from wiretapping in these two phases, we consider cooperative jamming by the relays, where the jamming signals are optimized to maximize the secrecy rate under the total power constraint of relays. In the first phase, the Maximal Ratio Transmission(MRT) scheme is used to maximize the secrecy rate, while in the second phase, by interpolating between the sub-optimal MRT scheme and the null-space projection scheme, the optimal scheme can be obtained via an efficient one-dimensional searching method. Simulation results show that when the number of cooperative relays is small, the performance of the optimal scheme significantly outperforms that of MRT and null-space projection scheme. When the number of relays increases, the performance of the null-space projection approaches that of the optimal one.

Intelligent Spectrum Management Based on Radio Map for Cloud-Based Satellite and Terrestrial Spectrum Shared Networks

Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite networks,and good communication quality of terrestrial networks.Thanks to the complementary coverage characteristics,any-time and anywhere high-speed communications can be achieved to meet the various needs of users.The scarcity of spectrum resources is a common prob-lem in both satellite and terrestrial networks.In or-der to improve resource utilization,the spectrum is shared not only within each component but also be-tween satellite beams and terrestrial cells,which intro-duces inter-component interferences.To this end,this paper first proposes an analytical framework which considers the inter-component interferences induced by spectrum sharing(SS).An intelligent SS scheme based on radio map(RM)consisting of LSTM-based beam prediction(BP),transfer learning-based spec-trum prediction(SP)and joint non-preemptive prior-ity and preemptive priority(J-NPAP)-based propor-tional fair spectrum allocation is than proposed.The simulation result shows that the spectrum utilization rate of CB-STSSN is improved and user blocking rate and waiting probability are decreased by the proposed scheme.

An overview of multi-antenna technologies for space-ground integrated networks

Multi-antenna technologies have already achieved a series of great successes in the development of information networks. For future space-ground integrated networks(SGINs), the traditional various kinds of separated information networks will converge to a whole fully connected information network to provide more flexible and reliable services on a world scale. Regarding their great successes in existing systems, multiantenna technologies will be of critical importance for the realization of SGINs and multi-antenna technologies are definitely one of the most important enabling technologies for future converged SGINs. In this article, a comprehensive overview on multi-antenna technologies is given. We first investigate multi-antenna technologies from a theoretical viewpoint. It is shown that we can understand multi-antenna technologies in a general and unified point of view. This fact has two-fold meanings. First, the research on multi-antennas can help us understand the relationships between different technologies e.g., OFDMA, CDMA, etc. On the other hand,multi-antenna technologies are easy to integrate into various information systems. Following that, we discuss in depth the potentials and challenges of the multi-antenna technologies on different platforms and in different applications case by case. More specifically, we investigate spaceborne multi-antenna technologies, airborne multi-antenna technologies, shipborne multi-antenna technologies, etc. Moreover, the combinations of multiantenna technologies with other advanced wireless technologies e.g., physical layer network coding, cooperative communication, etc., are also elaborated.