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: "joint optimization of user association data delivery rate and precoding for cache enabled f rans"
  Abstract: This paper considers the downlink of a cache-enabled fog radio access network (F-RAN) with limited fronthaul capacity, where user association (UA), data delivery rate (DDR) and signal precoding are jointly optimized. We formulate a mixed-integer nonlinear programming problem in which the weighted difference of network throughput and total power consumption is maximized, subject to the predefined DDR requirements and the maximum transmit power at each eRRH. To address this challenging problem, we first apply the l0-norm approximation and l1-norm minimization techniques to deal with the UA. After this key step, we arrive at an approximated problem that only involves the joint optimization of DDR and precoding. By using the alternating descent method, we further decompose this problem into a convex subproblem for DDR allocation and a nonconvex subproblem for precoding design. While the former is globally solved by the interior-point method, the latter is solved by a specifically tailored successive convex quadratic programming method. Finally, we propose an iterative algorithm for the original joint optimization that is guaranteed to converge. Importantly, each iteration of the developed algorithm only involves solving simple convex problems. Numerical examples demonstrate that the proposed design significantly improves both throughput and power performances, especially in practical F-RANs with limited fronthaul capacity. Compared to the sole precoder design for a given cache placement, our joint design is shown to improve the throughput by 50% while saving at least half of the total power consumption in the considered examples.

Connected through hyperedge HE-1 (induced by source paper "hybrid precoder design for cache enabled millimeter wave radio access networks"):
  with members:
    - "hybrid beamforming based on implicit channel state information for millimeter wave links"
    - "two level transmission scheme for cache enabled fog radio access networks"
    - "optimized base station cache allocation for cloud radio access network with multicast backhaul"
    - "spatial and frequency wideband effects in millimeter wave massive mimo systems"
    - "joint precoding and rrh selection for user centric green mimo c ran"
    - "energy efficient transceiver design for hybrid sub array architecture mimo systems"
    - "joint design of digital and analog processing for downlink c ran with large scale antenna arrays"
    - "codebook based hybrid precoding for millimeter wave multiuser systems"

Connected through hyperedge HE-2 (induced by source paper "joint fronthaul multicast and cooperative beamforming for cache enabled cloud based small cell networks an mds codes aided approach"):
  with members:
    - "joint long term cache allocation and short term content delivery in green cloud small cell networks"
    - "layered group sparse beamforming for cache enabled green wireless networks"
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "optimizing mds coded caching in wireless networks with device to device communication"
    - "coded multicast fronthauling and edge caching for multi connectivity transmission in fog radio access networks"
    - "delivery time minimization in edge caching synergistic benefits of subspace alignment and zero forcing"
    - "fronthauling for 5g lte u ultra dense cloud small cell networks"
    - "content centric sparse multicast beamforming for cache enabled cloud 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)