human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "context aware small cell networks how social metrics improve wireless resource allocation"
  Abstract: In this paper, a novel approach for optimizing and managing resource allocation in wireless small cell networks (SCNs) with device-to-device (D2D) communication is proposed. The proposed approach allows to jointly exploit both the wireless and social context of wireless users for optimizing the overall allocation of resources and improving traffic offload in SCNs. This context-aware resource allocation problem is formulated as a matching game in which user equipments (UEs) and resource blocks (RBs) rank one another, based on utility functions that capture both wireless and social metrics. Due to social interrelations, this game is shown to belong to a class of matching games with peer effects. To solve this game, a novel, selforganizing algorithm is proposed, using which UEs and RBs can interact to decide on their desired allocation. The proposed algorithm is then proven to converge to a two-sided stable matching between UEs and RBs. The properties of the resulting stable outcome are then studied and assessed. Simulation results using real social data show that clustering of socially connected users allows to offload a substantially larger amount of traffic than the conventional context-unaware approach. These results show that exploiting social context has high practical relevance in saving resources on the wireless links and on the backhaul.

Connected through hyperedge HE-1 (induced by source paper "network utility maximization based on incentive mechanism for truthful reporting of local information"):
  with members:
    - "applications of economic and pricing models for wireless network security a survey"
    - "joint scheduling and transmission power control in wireless ad hoc networks"
    - "distributed and fair beaconing rate adaptation for congestion control in vehicular networks"
    - "energy aware traffic offloading for green heterogeneous networks"
    - "propagation path loss models for 5g urban micro and macro cellular scenarios"
    - "distributed pricing based user association for downlink heterogeneous cellular networks"
    - "distributed constrained optimization by consensus based primal dual perturbation method"
    - "energy efficiency and spectral efficiency tradeoff in device to device d2d communications"

Connected through hyperedge HE-2 (induced by source paper "user preference aware lossless data compression at the edge"):
  with members:
    - "deep learning for joint source channel coding of text"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "online edge caching and wireless delivery in fog aided networks with dynamic content popularity"
    - "edge caching wireless networks performance analysis and optimization"

Connected through hyperedge HE-3 (induced by source paper "joint communication computation caching and control in big data multi access edge computing"):
  with members:
    - "deep learning for reliable mobile edge analytics in intelligent transportation systems"
    - "proactive edge computing in latency constrained fog networks"
    - "a survey on mobile edge computing the communication perspective"
    - "an online secretary framework for fog network formation with minimal latency"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "energy efficient resource allocation for cache assisted mobile edge computing"
    - "network slicing for service oriented networks under resource constraints"
    - "artificial neural networks based machine learning for wireless networks a tutorial"

Connected through hyperedge HE-4 (induced by source paper "social community aware content placement in wireless device to device communication networks"):
  with members:
    - "de anonymization of social networks with communities when quantifications meet algorithms"
    - "leveraging social communities for optimizing cellular device to device communications"
    - "cooperative device to device communications with caching"
    - "mean field games for distributed caching in ultra dense small cell networks"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "social data offloading in d2d enhanced cellular networks by network formation games"
    - "cooperative game theoretic solution concepts for top k problems"
    - "a survey on device to device communication in cellular networks"

Connected through hyperedge HE-5 (induced by source paper "human in the loop wireless communications machine learning and brain aware resource management"):
  with members:
    - "dynamic mobility aware interference avoidance for aerial base stations in cognitive radio networks"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "robust deep reinforcement learning for security and safety in autonomous vehicle systems"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "prospect pricing in cognitive radio networks"
    - "context aware computing for the internet of things a survey"

Connected through hyperedge HE-6 (induced by source paper "network decomposed hierarchical cooperation in ad hoc networks with social relationships"):
  with members:
    - "on the effects of subpacketization in content centric mobile networks"
    - "leveraging social communities for optimizing cellular device to device communications"
    - "parallel opportunistic routing in wireless networks"
    - "asymptotic laws for joint content replication and delivery in wireless networks"
    - "improved capacity scaling in wireless networks with infrastructure"
    - "capacity scaling of wireless ad hoc networks shannon meets maxwell"
    - "on capacity scaling in arbitrary wireless networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-7 (induced by source paper "tarco two stage auction for d2d relay aided computation resource allocation in hetnet"):
  with members:
    - "joint optimization of radio and computational resources for multicell mobile edge computing"
    - "a truthful auction based incentive framework for femtocell access"

Connected through hyperedge HE-8 (induced by source paper "spatial motifs for device to device network analysis dna in cellular networks"):
  with members:
    - "spectral and energy efficiency of uplink d2d underlaid massive mimo cellular networks"
    - "fundamentals of cluster centric content placement in cache enabled device to device networks"
    - "modeling and performance analysis of clustered device to device networks"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "a survey on device to device communication in cellular networks"
    - "cognitive and energy harvesting based d2d communication in cellular networks stochastic geometry modeling and analysis"
    - "modeling analysis and optimization of multicast device to device transmissions"
    - "resource management for device to device underlay communication"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)