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: "fronthaul constrained cloud radio access networks insights and challenges"
  Abstract: As a promising paradigm for fifth generation wireless communication systems, cloud radio access networks (C-RANs) have been shown to reduce both capital and operating expenditures, as well as to provide high spectral efficiency (SE) and energy efficiency (EE). The fronthaul in such networks, defined as the transmission link between the baseband unit and the remote radio head, requires a high capacity, but is often constrained. This article comprehensively surveys recent advances in fronthaul-constrained CRANs, including system architectures and key techniques. Particularly, major issues relating to the impact of the constrained fronthaul on SE/EE and quality of service for users, including compression and quantization, large-scale coordinated processing and clustering, and resource allocation optimization, are discussed together with corresponding potential solutions. Open issues in terms of software-defined networking, network function virtualization, and partial centralization are also identified.

Connected through hyperedge HE-1 (induced by source paper "on the capacity regions of cloud radio access networks with limited orthogonal fronthaul"):
  with members:
    - "integer forcing architectures for uplink cloud radio access networks"
    - "generalized compression strategy for the downlink cloud radio access network"
    - "the capacity of the relay channel solution to cover s problem in the gaussian case"
    - "on the capacity of cloud radio access networks with oblivious relaying"
    - "lossy compression for compute and forward in limited backhaul uplink multicell processing"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "an uplink downlink duality for cloud radio access network"
    - "on achievability for downlink cloud radio access networks with base station cooperation"

Connected through hyperedge HE-2 (induced by source paper "interference mitigation via rate splitting and common message decoding in cloud radio access networks"):
  with members:
    - "energy efficiency of rate splitting multiple access and performance benefits over sdma and noma"
    - "rate splitting for multi antenna non orthogonal unicast and multicast transmission"
    - "cross layer design for downlink multihop cloud radio access networks with network coding"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "optimality of treating interference as noise a combinatorial perspective"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "cloud radio access networks with coded caching"
    - "what will 5g be"

Connected through hyperedge HE-3 (induced by source paper "joint uplink and downlink transmissions in user centric ofdma cloud ran"):
  with members:
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "fronthaul limited uplink ofdma in ultra dense cran with hybrid decoding"
    - "joint millimeter wave fronthaul and ofdma resource allocation in ultra dense cran"
    - "green ofdma resource allocation in cache enabled cran"
    - "why to decouple the uplink and downlink in cellular networks and how to do it"
    - "coordinated scheduling for the downlink of cloud radio access networks"
    - "what will 5g be"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"

Connected through hyperedge HE-4 (induced by source paper "robust network function virtualization"):
  with members:
    - "integrated nfv sdn architectures a systematic literature review"
    - "a scalable approach for service chain mapping with multiple sc instances in a wide area network"
    - "shortest path and maximum flow problems under service function chaining constraints"
    - "service function chaining resource allocation a survey"
    - "an approximation algorithm for path computation and function placement in sdns"
    - "service chain and virtual network embeddings approximations using randomized rounding"
    - "network function virtualization state of the art and research challenges"
    - "lp rounding algorithms for facility location problems"

Connected through hyperedge HE-5 (induced by source paper "interference management in noma based fog radio access networks via joint scheduling and power adaptation"):
  with members:
    - "resource allocation in noma based fog radio access networks"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "fog computing based radio access networks issues and challenges"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

Connected through hyperedge HE-6 (induced by source paper "achieving vanishing rate loss in decentralized network mimo"):
  with members:
    - "on the degrees of freedom of the k user distributed broadcast channel"
    - "fundamental limits of caching"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-7 (induced by source paper "application of machine learning in wireless networks key techniques and open issues"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "learning to optimize training deep neural networks for interference management"
    - "deep reinforcement learning for resource management in network slicing"
    - "optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning"
    - "deep learning for radio resource allocation in multi cell networks"
    - "multi tenant cross slice resource orchestration a deep reinforcement learning approach"
    - "deep reinforcement learning based mode selection and resource management for green fog radio access networks"
    - "deep learning in mobile and wireless networking a survey"

Connected through hyperedge HE-8 (induced by source paper "two level transmission scheme for cache enabled fog radio access networks"):
  with members:
    - "distributed optimization for coordinated beamforming in multicell multigroup multicast systems power minimization and sinr balancing"
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "cache enabled physical layer security for video streaming in backhaul limited cellular networks"
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"
    - "distributed optimization of hierarchical small cell networks a gnep framework"
    - "collaborative mobile edge computing in 5g networks new paradigms scenarios and challenges"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"

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)