human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "green ofdma resource allocation in cache enabled cran"):
  Abstract: Cloud radio access network (CRAN), in which remote radio heads (RRHs) are deployed to serve users in a target area, and connected to a central processor (CP) via limited-capacity links termed the fronthaul, is a promising candidate for the next-generation wireless communication systems. Due to the content-centric nature of future wireless communications, it is desirable to cache popular contents beforehand at the RRHs, to reduce the burden on the fronthaul and achieve energy saving through cooperative transmission. This motivates our study in this paper on the energy efficient transmission in an orthogonal frequency division multiple access (OFDMA)-based CRAN with multiple RRHs and users, where the RRHs can prefetch popular contents. We consider a joint optimization of the user-SC assignment, RRH selection and transmit power allocation over all the SCs to minimize the total transmit power of the RRHs, subject to the RRHs' individual fronthaul capacity constraints and the users' minimum rate constraints, while taking into account the caching status at the RRHs. Although the problem is non-convex, we propose a Lagrange duality based solution, which can be efficiently computed with good accuracy. We compare the minimum transmit power required by the proposed algorithm with different caching strategies against the case without caching by simulations, which show the significant energy saving with caching.

Includes members:
  Member "fronthaul limited uplink ofdma in ultra dense cran with hybrid decoding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint uplink and downlink transmissions in user centric ofdma cloud ran")
  Member "joint millimeter wave fronthaul and ofdma resource allocation in ultra dense cran":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint beamforming and power splitting design for c ran with multicast fronthaul")
  Member "joint optimization of cloud and edge processing for fog radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "power efficient resource allocation in c rans with sinr constraints and deadlines")
  Member "energy efficiency of downlink transmission strategies for cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sparse optimization for green edge ai inference")
  Member "content centric sparse multicast beamforming for cache enabled cloud ran":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")
  Member "wireless communications in the era of big data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "artificial intelligence enabled wireless networking for 5g and beyond recent advances and future challenges")
  Member "cooperative local caching and file sharing under heterogeneous file preferences":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "caching policy optimization for d2d communications by learning user preference")
  Member "group sparse beamforming for green cloud ran":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sparse optimization for green edge ai inference")

Question: Please tell me which class the source paper 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)