Linling Kuang

Resource allocation in spectrum-sharing Cloud Based Integrated Terrestrial-Satellite Network

The increasing traffic demand in both ground and satellite communication systems will lead to increasing spectrum demand. Spectrum sharing would become a challenging issue in future between terrestrial and satellite systems with frequency reusing, as well as the interference management. Upon this, we propose the concept of the Cloud Based Integrated Terrestrial-Satellite Network (CTSN), where both base stations of the cellular networks and the satellite are connected to a cloud central unit and the signal processing procedures are executed centrally at the cloud. By utilizing the channel state information (CSI), the interference from the mixed signal can be mitigated. When it comes to the case of imperfect CSI, we propose a resource allocation scheme in respect to subchannel and power to maximize the total capacity of the terrestrial system while limiting the total interference to the satellite. The optimization problem is solved by means of the dual decomposition method. Simulation results are provided to evaluate the effectiveness of the algorithm.

Non-Orthogonal Multiple Access Based Integrated Terrestrial-Satellite Networks

In this paper, we investigate the downlink transmission of a non-orthogonal multiple access (NOMA)-based integrated terrestrial-satellite network, in which the NOMA-based terrestrial networks and the satellite cooperatively provide coverage for ground users while reusing the entire bandwidth. For both terrestrial networks and the satellite network, multi-antennas are equipped and beamforming techniques are utilized to serve multiple users simultaneously. A channel quality-based scheme is proposed to select users for the satellite, and we then formulate the terrestrial user pairing as a max–min problem to maximize the minimum channel correlation between users in one NOMA group. Since the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, which can be decomposed into the designing of beamforming vectors and the power allocation schemes. Then, a joint iteration algorithm is proposed to maximize the total system capacity, where we introduce the interference temperature limit for the satellite since the satellite can cause interference to all base station users. Finally, numerical results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with some other proposed algorithms and existing algorithms.

Information Credibility Modeling in Cooperative Networks: Equilibrium and Mechanism Design

In a cooperative network, the user equipment (UE) shares information for cooperatively achieving a common goal. However, owing to the concerns of privacy or cost, UEs may be reluctant to share genuine information, which raises the information credibility problem addressed. Diverse techniques have been proposed for enhancing the information credibility in various scenarios. However, there is a paucity of information on modeling the UEs’ decision making behavior, namely as to whether they are willing/able to share genuine information, even though this directly affects the information credibility across the network. Hence, we propose a game theoretic framework for the associated information credibility modeling by taking into account the users’ information sharing strategies and utilities. This framework is investigated under both a homogeneous model and a heterogeneous model. The spontaneous information credibility equilibria of both models are derived and analyzed, including the closed-form analysis of the homogeneous model based on a sophisticated evolutionary game model and on the reinforcement learning-based analysis of the heterogeneous model. Moreover, a credit mechanism is designed for encouraging the UEs to share genuine information. Experimental results relying on real-world data traces support our utility function formulation, while our simulation results verify the theoretical analysis and show that all the UEs are encouraged by the proposed algorithm to share genuine information with a probability of one, when a credit mechanism is invoked. The proposed modeling techniques may be applied in diverse cooperative networks, including classic wireless networks, vehicular networks, as well as social networks.

Multimedia multicast beamforming in integrated terrestrial-satellite networks

This paper investigates a multimedia multicast beamforming scheme in the integrated terrestrial-satellite networks, where base stations (BSs) and the satellite work cooperatively provide ubiquitous services for ground users. Due to the contents diversity of multimedia services, users that request the same contents can be served as a group using multicasting. By utilizing multiple transmission antennas, multicast beamforming is performed among groups while reusing the entire bandwidth, which, however, can inevitably cause the co-channel interference among users. Taking both system performance and user fairness into account, we optimize the total system capacity performance under the satellite capacity constraint and derive the optimal power allocation schemes. Numerical results are presented in the end to evaluate the effectiveness of the proposed scheme compared with the greedy and suboptimal searching strategies.

Preemptive dynamic scheduling algorithm for data relay satellite systems

In data relay satellite (DRS) systems, the performance of tasks scheduling is influenced by the variation of task and resources, which degrades the processing capacity of relay satellites. Considering this problem, we investigate the dynamic scheduling in the application of DRS. To achieve the efficient resource utilization and reliable data transfer, the strategies of task preemptive switching and decomposition are designed. Based on the initial scheme, we construct a dynamic scheduling model with multiple objectives, including maximizing the total weight of scheduled tasks, minimizing the change of scheduling scheme and minimizing the number of decomposed subtasks. Meanwhile, a preemptive dynamic scheduling algorithm (PDSA) is designed to solve the proposed model. Explicitly, our simulation results show that PDSA is superior to the whole rescheduling algorithm (WRA) in quantities of completed tasks, rescheduling rate of scheme and processing time, which can efficiently improve the performance of dynamic scheduling in DRS systems.