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: "power control in two tier femtocell networks"
  Abstract: In a two tier cellular network - comprised of a central macrocell underlaid with shorter range femtocell hotspots - cross-tier interference limits overall capacity with universal frequency reuse. To quantify near-far effects with universal frequency reuse, this paper derives a fundamental relation providing the largest feasible cellular Signal-to-Interference-Plus-Noise Ratio (SINR), given any set of feasible femtocell SINRs. We provide a link budget analysis which enables simple and accurate performance insights in a two-tier network. A distributed utility- based SINR adaptation at femtocells is proposed in order to alleviate cross-tier interference at the macrocell from cochannel femtocells. The Foschini-Miljanic (FM) algorithm is a special case of the adaptation. Each femtocell maximizes their individual utility consisting of a SINR based reward less an incurred cost (interference to the macrocell). Numerical results show greater than 30% improvement in mean femtocell SINRs relative to FM. In the event that cross-tier interference prevents a cellular user from obtaining its SINR target, an algorithm is proposed that reduces transmission powers of the strongest femtocell interferers. The algorithm ensures that a cellular user achieves its SINR target even with 100 femtocells/cell-site (with typical cellular parameters) and requires a worst case SINR reduction of only 16% at femtocells. These results motivate design of power control schemes requiring minimal network overhead in two-tier networks with shared spectrum.

Connected through hyperedge HE-1 (induced by source paper "game theory based joint task offloading and resources allocation algorithm for mobile edge computing"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "joint task offloading scheduling and transmit power allocation for mobile edge computing systems"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "joint computation and communication cooperation for mobile edge computing"
    - "power delay tradeoff in multi user mobile edge computing systems"
    - "decentralized computation offloading game for mobile cloud computing"
    - "cloud offloading for multi radio enabled mobile devices"

Connected through hyperedge HE-2 (induced by source paper "a brief history on the theoretical analysis of dense small cell wireless networks"):
  with members:
    - "optimal base station antenna downtilt in downlink cellular networks"
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "ultra dense networks is there a limit to spatial spectrum reuse"
    - "wireless powered dense cellular networks how many small cells do we need"
    - "inter operator base station coordination in spectrum shared millimeter wave cellular networks"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "modeling infrastructure sharing in mmwave networks with shared spectrum licenses"

Connected through hyperedge HE-3 (induced by source paper "distributed joint offloading decision and resource allocation for multi user mobile edge computing a game theory approach"):
  with members:
    - "a survey on mobile edge computing the communication perspective"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "distributed power control in interference channels with qos constraints and rf energy harvesting a game theoretic approach"
    - "decentralized computation offloading game for mobile cloud computing"
    - "cloud offloading for multi radio enabled mobile devices"
    - "efficient multi user computation offloading for mobile edge cloud computing"
    - "the energy frequency convexity rule modeling and experimental validation on mobile devices"

Connected through hyperedge HE-4 (induced by source paper "reinforcement learning for self organization and power control of two tier heterogeneous networks"):
  with members:
    - "learning to optimize training deep neural networks for interference management"
    - "a machine learning approach for power allocation in hetnets considering qos"
    - "from 4g to 5g self organized network management meets machine learning"
    - "what will 5g be"
    - "distributed cooperative q learning for power allocation in cognitive femtocell networks"
    - "decision theoretic planning structural assumptions and computational leverage"

Connected through hyperedge HE-5 (induced by source paper "a game theoretical approach for qos provisioning in heterogeneous networks"):
  with members:
    - "call admission control based on adaptive bandwidth allocation for wireless networks"
    - "cost effective frequency planning for capacity enhancement of femtocellular networks"
    - "open vs closed access femtocells in the uplink"
    - "uplink capacity and interference avoidance for two tier femtocell networks"

Connected through hyperedge HE-6 (induced by source paper "intelligent wireless communications enabled by cognitive radio and machine learning"):
  with members:
    - "toward intelligent vehicular networks a machine learning framework"
    - "deep learning based channel estimation for beamspace mmwave massive mimo systems"
    - "channel agnostic end to end learning based communication systems with conditional gan"
    - "deep learning based csi feedback approach for time varying massive mimo channels"
    - "an introduction to deep learning for the physical layer"
    - "deep reinforcement learning for resource allocation in v2v communications"
    - "energy efficient user association and power allocation in millimeter wave based ultra dense networks with energy harvesting base stations"
    - "deep learning for wireless physical layer opportunities and challenges"

Connected through hyperedge HE-7 (induced by source paper "downlink power optimization for heterogeneous networks with time reversal based transmission under backhaul limitation"):
  with members:
    - "space time block diagonalization for frequency selective mimo broadcast channels"
    - "a survey of energy efficient techniques for 5g networks and challenges ahead"
    - "5g cellular key enabling technologies and research challenges"
    - "uplink performance of time reversal mrc in massive mimo systems subject to phase noise"
    - "time reversal based transmissions with distributed power allocation for two tier networks"

Connected through hyperedge HE-8 (induced by source paper "energy efficient noncooperative power control in small cell networks"):
  with members:
    - "energy efficient joint resource allocation and power control for d2d communications"
    - "a game theoretic analysis for energy efficient heterogeneous networks"
    - "framework for link level energy efficiency optimization with informed transmitter"
    - "interference and outage in clustered wireless ad hoc networks"

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.NI(Networking and Internet Architecture)