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: "large scale convex optimization for ultra dense cloud ran"
  Abstract: The heterogeneous cloud radio access network (Cloud-RAN) provides a revolutionary way to densify radio access networks. It enables centralized coordination and signal processing for efficient interference management and flexible network adaptation. Thus, it can resolve the main challenges for next-generation wireless networks, including higher energy efficiency and spectral efficiency, higher cost efficiency, scalable connectivity, and low latency. In this article, we shall provide an algorithmic thinking on the new design challenges for the dense heterogeneous Cloud-RAN based on convex optimization. As problem sizes scale up with the network size, we will demonstrate that it is critical to take unique structures of design problems and inherent characteristics of wireless channels into consideration, while convex optimization will serve as a powerful tool for such purposes. Network power minimization and channel state information acquisition will be used as two typical examples to demonstrate the effectiveness of convex optimization methods. We will then present a two-stage framework to solve general large-scale convex optimization problems, which is amenable to parallel implementation in the cloud data center.

Connected through hyperedge HE-1 (induced by source paper "power efficient resource allocation in c rans with sinr constraints and deadlines"):
  with members:
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "base station on off switching in 5g wireless networks approaches and challenges"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "joint optimization of cloud and edge processing for fog radio access networks"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "energy efficient resource assignment and power allocation in heterogeneous cloud radio access networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"

Connected through hyperedge HE-2 (induced by source paper "the roadmap to 6g ai empowered wireless networks"):
  with members:
    - "6g the next frontier"
    - "a speculative study on 6g"
    - "optimizing space air ground integrated networks by artificial intelligence"
    - "a hardware efficient analog network structure for hybrid precoding in millimeter wave systems"
    - "learning to communicate in uav aided wireless networks map based approaches"
    - "applications of deep reinforcement learning in communications and networking a survey"
    - "data shuffling in wireless distributed computing via low rank optimization"
    - "propagation measurement system and approach at 140 ghz moving to 6g and above 100 ghz"

Connected through hyperedge HE-3 (induced by source paper "coded caching in fog ran b matching approach"):
  with members:
    - "fog networking an overview on research opportunities"
    - "multiobjective signal processing optimization the way to balance conflicting metrics in 5g systems"
    - "fundamental limits of caching in wireless d2d networks"
    - "fundamental limits of caching"
    - "a survey on network codes for distributed storage"

Connected through hyperedge HE-4 (induced by source paper "blind demixing for low latency communication"):
  with members:
    - "nonconvex demixing from bilinear measurements"
    - "regularized gradient descent a nonconvex recipe for fast joint blind deconvolution and demixing"
    - "painless breakups efficient demixing of low rank matrices"
    - "blind deconvolution by a steepest descent algorithm on a quotient manifold"
    - "a survey on low latency towards 5g ran core network and caching solutions"
    - "no spurious local minima in nonconvex low rank problems a unified geometric analysis"
    - "low rank matrix completion for topological interference management by riemannian pursuit"
    - "blind deconvolution meets blind demixing algorithms and performance bounds"

Connected through hyperedge HE-5 (induced by source paper "group sparse precoding for cloud ran with multiple user antennas"):
  with members:
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "a survey of sparse representation algorithms and applications"
    - "robust group sparse beamforming for multicast green cloud ran with imperfect csi"
    - "a comparative study of downlink mimo cellular networks with co located and distributed base station antennas"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"
    - "group sparse beamforming for green cloud ran"
    - "asymptotic rate analysis of downlink multi user systems with co located and distributed antennas"

Connected through hyperedge HE-6 (induced by source paper "load balancing user association in millimeter wave mimo networks"):
  with members:
    - "time fractional user association in millimeter wave mimo networks"
    - "downlink cell association and load balancing for joint millimeter wave microwave cellular networks"
    - "a survey of millimeter wave mmwave communications for 5g opportunities and challenges"
    - "probabilistic omnidirectional path loss models for millimeter wave outdoor communications"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "optimal user cell association for massive mimo wireless networks"
    - "distributed linear precoder optimization and base station selection for an uplink heterogeneous network"
    - "millimeter wave channel modeling and cellular capacity evaluation"

Connected through hyperedge HE-7 (induced by source paper "enhanced group sparse beamforming for green cloud ran a random matrix approach"):
  with members:
    - "layered group sparse beamforming for cache enabled green wireless networks"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "wireless communications in the era of big data"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "large scale convex optimization for dense wireless cooperative networks"
    - "heterogeneous cellular networks using wireless backhaul fast admission control and large system analysis"
    - "robust group sparse beamforming for multicast green cloud ran with imperfect csi"

Connected through hyperedge HE-8 (induced by source paper "joint millimeter wave fronthaul and ofdma resource allocation in ultra dense cran"):
  with members:
    - "locally orthogonal training design for cloud rans based on graph coloring"
    - "millimeter wave wireless communications new results for rural connectivity"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "wireless communications in the era of big data"
    - "5g ultra dense cellular networks"
    - "optimized uplink transmission in multi antenna c ran with spatial compression and forward"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "dynamic nested clustering for parallel phy layer processing in cloud rans"

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)