Resource Allocation in Space Multiaccess Systems

Du, Jun; Jiang, Chunxiao; Wang, Jian; Ren, Yong; Yu, Shui; Han, Zhu

doi:10.1109/taes.2017.2651598

Cited by 86 publications

(25 citation statements)

References 35 publications

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“…2) Backhaul Uplink: The computation tasks of HAPs may be also offloaded to the LEO satellite via the backhaul uplink due to the placement of enhanced MEC server at the LEO satellite. Different form the G2A and A2A LOS communication links, the air-to-space (A2S) backhaul uplink is determined by a Rician fading channel model with the AWGN [10], [11]. Specifically, the channel fading coefficient between HAP j and the LEO satellite is modeled as a circularly symmetric complex Gaussian random variable, i.e., h j = X 1 +X 2 i, where…”

Section: B Communication Modelmentioning

confidence: 99%

Satellite-Aerial Integrated Computing in Disasters: User Association and Offloading Decision

Zhang¹,

Zhang²,

Guo³

et al. 2020

Preprint

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In this paper, a satellite-aerial integrated computing (SAIC) architecture in disasters is proposed, where the computation tasks from two-tier users, i.e., ground/aerial user equipments, are either locally executed at the high-altitude platforms (HAPs), or offloaded to and computed by the Low Earth Orbit (LEO) satellite. With the SAIC architecture, we study the problem of joint two-tier user association and offloading decision aiming at the maximization of the sum rate. The problem is formulated as a 0-1 integer linear programming problem which is NP-complete. A weighted 3-uniform hypergraph model is obtained to solve this problem by capturing the 3D mapping relation for two-tier users, HAPs, and the LEO satellite. Then, a 3D hypergraph matching algorithm using the local search is developed to find a maximum-weight subset of vertex-disjoint hyperedges. Simulation results show that the proposed algorithm has improved the sum rate when compared with the conventional greedy algorithm.

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Section: B Communication Modelmentioning

confidence: 99%

Satellite-Aerial Integrated Computing in Disasters: User Association and Offloading Decision

Zhang¹,

Zhang²,

Guo³

et al. 2020

Preprint

Self Cite

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show abstract

“…Consider a satellite-based SIN system operating in slotted time t ∈ T = {1, 2, ...} [25]. The length of a time slot is denoted as τ .…”

Section: A Network Modelmentioning

confidence: 99%

Multi-Resource Coordinate Scheduling for Earth Observation in Space Information Networks

Wang

Sheng

Zhuang

et al. 2018

IEEE J. Select. Areas Commun.

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Space information network (SIN) is an innovative networking architecture to achieve near-realtime mass data observation, processing and transmission over the globe. In the SIN environment, it is essential to coordinate multi-dimensional heterogeneous resources (i.e., observation resource, computation resource and transmission resource) to improve network performance. However, the time varying property of both the observation resource and transmission resource is not fully exploited in existing studies. Dynamic resource management according to instantaneous channel conditions has a potential to enhance network performance. To this end, in this paper, we study the multi-resource dynamic management problem, considering stochastic observation and transmission channel conditions in SINs.Specifically, we develop an aggregate optimization framework for observation scheduling, compression ratio selection and transmission scheduling, and formulate a flow optimization problem based on extended time expanded graph (ETEG) to maximize the sum network utility. Then, we equivalently transform the flow optimization problem on ETEG as a queue stability-related stochastic optimization problem. An online algorithm is proposed to solve the problem in a slot-by-slot manner by exploiting the Lyapunov optimization technique. Performance analysis shows that the proposed algorithm achieves close-to-optimal network utility while guaranteeing bounded queue occupancy. Extensive simulation results further validate the efficiency of the proposed algorithm and evaluate the impacts of various network parameters on the algorithm performance.

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“…In addition, like other distributed space systems, the cluster flight spacecraft is a resource-sharing and energylimited system. erefore, how to allocate nodal transmit power efficiently and optimize the performance of the cluster flight spacecraft is an important issue needs to be solved [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Transmit Power Allocation with Connectivity Probability for Multi-QoS in Cluster Flight Spacecraft Network

Yan

et al. 2020

Wireless Communications and Mobile Computing

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In this paper, we investigate the transmit power allocation problem to minimize the average packet error rate at the access point in the cluster flight spacecraft network, which adopts the CSMA/CA channel access mechanism. First, the node mobility, nodal distance distribution, and probabilistic adjacency matrix were formulated for cluster flight spacecraft network based on twinsatellite mode. en, the optimization-theoretic model described the optimized transmit power allocation strategy and its implementation algorithm was proposed. And the problem of minimizing the packet error rate of the cluster flight spacecraft network system can be converted into maximizing the expectation of the binary probabilistic adjacency matrix, i.e., maximizing the sum of the nondiagonal elements in the probabilistic adjacency matrix. Due to discreteness of nodal distance distribution, Monte Carlo method was applied to solve the transmit power allocation problem. Yet importantly, the influence of node transmit power on the QoS performance of cluster flight spacecraft network was simulated and analyzed under the assumption of finite overall network transmit power and low traffic load. Finally, the results show that the pocket error rate increases with the provided traffic load, but the pocket error rate hardly changes with the same traffic load in different sequential time slots of any orbital hyperperiod or in the same time slot of different orbital hyperperiods, and by maximizing the sum of the nondiagonal elements in the probabilistic adjacency matrix, the pocket error rate minimum is achieved for a given total network transmit power at any time slot for cluster flight spacecraft network.

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Resource Allocation in Space Multiaccess Systems

Cited by 86 publications

References 35 publications

Satellite-Aerial Integrated Computing in Disasters: User Association and Offloading Decision

Satellite-Aerial Integrated Computing in Disasters: User Association and Offloading Decision

Multi-Resource Coordinate Scheduling for Earth Observation in Space Information Networks

Transmit Power Allocation with Connectivity Probability for Multi-QoS in Cluster Flight Spacecraft Network

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