633 research outputs found
Stochastic Geometry-Based Analysis of Cache-Enabled Hybrid Satellite-Aerial-Terrestrial Networks With Non-Orthogonal Multiple Access
Due to the emergence of non-terrestrial platformswith extensive coverage, flexible deployment, and reconfigurablecharacteristics, the hybrid satellite-aerial-terrestrial networks(HSATNs) can accommodate a great variety of wireless accessservices in different applications. To effectively reduce the trans-mission latency and facilitate the frequent update of files withimproved spectrum efficiency, we investigate the performanceof cache-enabled HSATN, where the user retrieves the requiredcontent files from the cache-enabled aerial relay or the satellitewith the non-orthogonal multiple access (NOMA) scheme. If therequired content files of the user are cached in the aerial relay,the cache-enabled relay would serve directly. Otherwise, the userwould retrieve the content file from the satellite system, where thesatellite system seeks opportunities for proactive content pushingto the relay during the user content delivery phase. Specifically,taking into account the uncertainty of the number and locationof aerial relays, along with the channel fading of terrestrialusers, the outage probability and hit probability of the considerednetwork are, respectively, derived based on stochastic geometry.Numerical results unveil the effectiveness of the cache-enabledHSATN with the NOMA scheme and proclaim the influence ofkey factors on the system performance. The realistic, tractable,and expandable framework, as well as associated methodology,provide both useful guidance and a solid foundation for evolvednetworks with advanced configurations in the performance ofcache-enabled HSATN
A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges
Maritime activities represent a major domain of economic growth with several
emerging maritime Internet of Things use cases, such as smart ports, autonomous
navigation, and ocean monitoring systems. The major enabler for this exciting
ecosystem is the provision of broadband, low-delay, and reliable wireless
coverage to the ever-increasing number of vessels, buoys, platforms, sensors,
and actuators. Towards this end, the integration of unmanned aerial vehicles
(UAVs) in maritime communications introduces an aerial dimension to wireless
connectivity going above and beyond current deployments, which are mainly
relying on shore-based base stations with limited coverage and satellite links
with high latency. Considering the potential of UAV-aided wireless
communications, this survey presents the state-of-the-art in UAV-aided maritime
communications, which, in general, are based on both conventional optimization
and machine-learning-aided approaches. More specifically, relevant UAV-based
network architectures are discussed together with the role of their building
blocks. Then, physical-layer, resource management, and cloud/edge computing and
caching UAV-aided solutions in maritime environments are discussed and grouped
based on their performance targets. Moreover, as UAVs are characterized by
flexible deployment with high re-positioning capabilities, studies on UAV
trajectory optimization for maritime applications are thoroughly discussed. In
addition, aiming at shedding light on the current status of real-world
deployments, experimental studies on UAV-aided maritime communications are
presented and implementation details are given. Finally, several important open
issues in the area of UAV-aided maritime communications are given, related to
the integration of sixth generation (6G) advancements
A Survey on Applications of Cache-Aided NOMA
Contrary to orthogonal multiple-access (OMA), non-orthogonal multiple-access (NOMA) schemes can serve a pool of users without exploiting the scarce frequency or time domain resources. This is useful in meeting the future network requirements (5G and beyond systems), such as, low latency, massive connectivity, users' fairness, and high spectral efficiency. On the other hand, content caching restricts duplicate data transmission by storing popular contents in advance at the network edge which reduces data traffic. In this survey, we focus on cache-aided NOMA-based wireless networks which can reap the benefits of both cache and NOMA; switching to NOMA from OMA enables cache-aided networks to push additional files to content servers in parallel and improve the cache hit probability. Beginning with fundamentals of the cache-aided NOMA technology, we summarize the performance goals of cache-aided NOMA systems, present the associated design challenges, and categorize the recent related literature based on their application verticals. Concomitant standardization activities and open research challenges are highlighted as well
Self-Evolving Integrated Vertical Heterogeneous Networks
6G and beyond networks tend towards fully intelligent and adaptive design in
order to provide better operational agility in maintaining universal wireless
access and supporting a wide range of services and use cases while dealing with
network complexity efficiently. Such enhanced network agility will require
developing a self-evolving capability in designing both the network
architecture and resource management to intelligently utilize resources, reduce
operational costs, and achieve the coveted quality of service (QoS). To enable
this capability, the necessity of considering an integrated vertical
heterogeneous network (VHetNet) architecture appears to be inevitable due to
its high inherent agility. Moreover, employing an intelligent framework is
another crucial requirement for self-evolving networks to deal with real-time
network optimization problems. Hence, in this work, to provide a better insight
on network architecture design in support of self-evolving networks, we
highlight the merits of integrated VHetNet architecture while proposing an
intelligent framework for self-evolving integrated vertical heterogeneous
networks (SEI-VHetNets). The impact of the challenges associated with
SEI-VHetNet architecture, on network management is also studied considering a
generalized network model. Furthermore, the current literature on network
management of integrated VHetNets along with the recent advancements in
artificial intelligence (AI)/machine learning (ML) solutions are discussed.
Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are
identified. Finally, the potential future research directions for advancing the
autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table
Hybrid satellite-terrestrial relay network: proposed model and application of power splitting multiple access
The development of hybrid satellite-terrestrial relay networks (HSTRNs) is one of the driving
forces for revolutionizing satellite communications in the modern era. Although there are many unique
features of conventional satellite networks, their evolution pace is much slower than the terrestrial
wireless networks. As a result, it is becoming more important to use HSTRNs for the seamless integration
of terrestrial cellular and satellite communications. With this intent, this paper provides a comprehensive
performance evaluation of HSTRNs employing non-orthogonal multiple access technique. The terrestrial
relay is considered to be wireless-powered and harvests energy from the radio signal of the satellite.
For the sake of comparison, both amplify-and-forward (AF) and decode-and-forward (DF) relaying
protocols are considered. Subsequently, the closed-form expressions of outage probabilities and ergodic
capacities are derived for each relaying protocol. Extensive simulations are performed to verify the
accuracy of the obtained closed-form expressions. The results provided in this work characterize the
outage and capacity performance of such a HSTRN.publishe
SpaceMeta: Global-Scale Massive Multi-User Virtual Interaction over LEO Satellite Constellations
Low latency and high synchronization among users are critical for emerging
multi-user virtual interaction applications. However, the existing ground-based
cloud solutions are naturally limited by the complex ground topology and fiber
speeds, making it difficult to pace with the requirement of multi-user virtual
interaction. The growth of low earth orbit (LEO) satellite constellations
becomes a promising alternative to ground solutions. To fully exploit the
potential of the LEO satellite, in this paper, we study the satellite server
selection problem for global-scale multi-user interaction applications over LEO
constellations. We propose an effective server selection framework, called
SpaceMeta, that jointly selects the ingress satellite servers and relay servers
on the communication path to minimize latency and latency discrepancy among
users. Extensive experiments using real-world Starlink topology demonstrate
that SpaceMeta reduces the latency by 6.72% and the interquartile range (IQR)
of user latency by 39.50% compared with state-of-the-art methods.Comment: Accepted by IEEE Satellite'2
Dynamic Resource Management in Integrated NOMA Terrestrial-Satellite Networks using Multi-Agent Reinforcement Learning
This study introduces a resource allocation framework for integrated
satellite-terrestrial networks to address these challenges. The framework
leverages local cache pool deployments and non-orthogonal multiple access
(NOMA) to reduce time delays and improve energy efficiency. Our proposed
approach utilizes a multi-agent enabled deep deterministic policy gradient
algorithm (MADDPG) to optimize user association, cache design, and transmission
power control, resulting in enhanced energy efficiency. The approach comprises
two phases: User Association and Power Control, where users are treated as
agents, and Cache Optimization, where the satellite (Bs) is considered the
agent. Through extensive simulations, we demonstrate that our approach
surpasses conventional single-agent deep reinforcement learning algorithms in
addressing cache design and resource allocation challenges in integrated
terrestrial-satellite networks. Specifically, our proposed approach achieves
significantly higher energy efficiency and reduced time delays compared to
existing methods.Comment: 16, 1
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