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: "cellular broadcast service convergence through caching for comp cloud rans"
  Abstract: Cellular and Broadcast services have been traditionally treated independently due to the different market requirements, thus resulting in different business models and orthogonal frequency allocations. However, with the advent of cheap memory and smart caching, this traditional paradigm can converge into a single system which can provide both services in an efficient manner. This paper focuses on multimedia delivery through an integrated network, including both a cellular (also known as unicast or broadband) and a broadcast last mile operating over shared spectrum. The subscribers of the network are equipped with a cache which can effectively create zero perceived latency for multimedia delivery, assuming that the content has been proactively and intelligently cached. The main objective of this work is to establish analytically the optimal content popularity threshold, based on a intuitive cost function. In other words, the aim is to derive which content should be broadcasted and which content should be unicasted. To facilitate this, Cooperative Multi- Point (CoMP) joint processing algorithms are employed for the uni and broad-cast PHY transmissions. To practically implement this, the integrated network controller is assumed to have access to traffic statistics in terms of content popularity. Simulation results are provided to assess the gain in terms of total spectral efficiency. A conventional system, where the two networks operate independently, is used as benchmark.

Connected through hyperedge HE-1 (induced by source paper "symbol level and multicast precoding for multiuser multiantenna downlink a survey classification and challenges"):
  with members:
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "an overview on resource allocation techniques for multi user mimo systems"
    - "spatio temporal waveform design for multiuser massive mimo downlink with 1 bit receivers"
    - "joint beamforming and broadcasting in massive mimo"
    - "coordinate update algorithms for robust power loading for the mu miso downlink with outage constraints"
    - "energy efficient symbol level precoding in multiuser miso based on relaxed detection region"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "adaptive pilot clustering in heterogeneous massive mimo networks"

Connected through hyperedge HE-2 (induced by source paper "content centric sparse multicast beamforming for cache enabled cloud ran"):
  with members:
    - "rank two beamforming and power allocation in multicasting relay networks"
    - "content centric multicast beamforming in cache enabled cloud radio access networks"
    - "on content centric wireless delivery networks"
    - "backhaul limited asymmetric cooperation for mimo cellular networks via semidefinite relaxation"
    - "caching eliminates the wireless bottleneck in video aware wireless networks"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"
    - "living on the edge the role of proactive caching in 5g wireless networks"
    - "sparse beamforming and user centric clustering for downlink cloud radio access network"

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)