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: "ergodic capacity analysis of remote radio head associations in cloud radio access networks"
  Abstract: Characterizing user to remote radio head (RRH) association strategies in cloud radio access networks (C-RANs) is critical for performance optimization. In this letter, the single nearest and N-nearest RRH association strategies are presented, and the corresponding impact on the ergodic capacity of C-RANs is analyzed, where RRHs are distributed according to a stationary point process. Closed-form expressions for the ergodic capacity of the proposed RRH association strategies are derived. Simulation results demonstrate that the derived uplink closed-form capacity expressions are accurate. Furthermore, the analysis and simulation results show that the ergodic capacity gain is not linear with either the RRH density or the number of antennas per RRH. The ergodic capacity gain from the RRH density is larger than that from the number of antennas per RRH, which indicates that the association number of the RRH should not be bigger than 4 to balance the performance gain and the implementation cost.

Connected through hyperedge HE-1 (induced by source paper "channel matrix sparsity with imperfect channel state information in cloud radio access networks"):
  with members:
    - "energy efficient resource allocation optimization for multimedia heterogeneous cloud radio access networks"
    - "cluster content caching an energy efficient approach to improve quality of service in cloud radio access networks"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "large scale convex optimization for dense wireless cooperative networks"
    - "robust group sparse beamforming for multicast green cloud ran with imperfect csi"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "training design and channel estimation in uplink cloud radio access networks"

Connected through hyperedge HE-2 (induced by source paper "joint user selection and energy minimization for ultra dense multi channel c ran with incomplete csi"):
  with members:
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "tradeoff caching strategy of outage probability and fronthaul usage in cloud ran"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "power efficient resource allocation for full duplex radio distributed antenna networks"
    - "5g ultra dense cellular networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "secure and green swipt in distributed antenna networks with limited backhaul capacity"
    - "what will 5g be"

Connected through hyperedge HE-3 (induced by source paper "an evolutionary game for user access mode selection in fog radio access networks"):
  with members:
    - "recent advances in fog radio access networks performance analysis and radio resource allocation"
    - "fog computing based radio access networks issues and challenges"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "user access mode selection in fog computing based radio access networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "analysis on cache enabled wireless heterogeneous networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-4 (induced by source paper "power and rate adaptation improves the effective capacity of c ran for nakagami m fading channels"):
  with members:
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "joint millimeter wave fronthaul and ofdma resource allocation in ultra dense cran"
    - "what will 5g be"
    - "group sparse beamforming for green cloud ran"
    - "on peak versus average interference power constraints for protecting primary users in cognitive radio networks"

Connected through hyperedge HE-5 (induced by source paper "inter tier interference suppression in heterogeneous cloud radio access networks"):
  with members:
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "comp meets smart grid a new communication and energy cooperation paradigm"
    - "joint power and antenna selection optimization in large cloud radio access networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"
    - "multi user linear precoding for multi polarized massive mimo system under imperfect csit"
    - "group sparse beamforming for green cloud ran"

Connected through hyperedge HE-6 (induced by source paper "load aware dynamic spectrum access for small cell networks a graphical game approach"):
  with members:
    - "a game theoretic perspective on self organizing optimization for cognitive small cells"
    - "partially distributed resource allocation in small cell networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "full duplex cloud radio access networks an information theoretic viewpoint"
    - "coalitional games with overlapping coalitions for interference management in small cell networks"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"

Connected through hyperedge HE-7 (induced by source paper "user access mode selection in fog computing based radio access networks"):
  with members:
    - "fog computing based radio access networks issues and challenges"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "joint power and antenna selection optimization in large cloud radio access networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-8 (induced by source paper "uplink and downlink rate analysis of a full duplex c ran with radio remote head association"):
  with members:
    - "full duplex radio for uplink downlink wireless access with spatially random nodes"
    - "joint power and antenna selection optimization in large cloud radio access networks"
    - "passive self interference suppression for full duplex infrastructure nodes"
    - "low complexity end to end performance optimization in mimo full duplex relay systems"
    - "improving physical layer secrecy using full duplex jamming receivers"

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)