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: "networked mimo with fractional joint transmission in energy harvesting systems"
  Abstract: This paper considers two base stations (BSs) powered by renewable energy serving two users cooperatively. With different BS energy arrival rates, a fractional joint transmission (JT) strategy is proposed, which divides each transmission frame into two subframes. In the first subframe, one BS keeps silent to store energy, while the other transmits data, and then, they perform zero-forcing JT (ZF-JT) in the second subframe. We consider the average sum-rate maximization problem by optimizing the energy allocation and the time fraction of ZF-JT separately. First, the sum-rate maximization for given energy budgets in each frame is analyzed. We prove that the optimal transmit power can be derived in closed form, and the optimal time fraction can be found via bi-section search. Second, an approximate dynamic programming algorithm is introduced to determine the energy allocation among frames. We adopt a linear approximation with the features associated with system states and determine the weights of features by simulation. We also operate the approximation several times with random initial policy, named policy exploration, to broaden the policy search range. Numerical results show that the proposed fractional JT greatly improves the performance. In addition, appropriate policy exploration is shown to perform close to the optimal.

Connected through hyperedge HE-1 (induced by source paper "on the total energy efficiency of cell free massive mimo"):
  with members:
    - "energy efficient downlink transmission for multicell massive das with pilot contamination"
    - "cell free massive mimo versus small cells"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "how much do downlink pilots improve cell free massive mimo"
    - "compute and forward in cell free massive mimo great performance with low backhaul load"
    - "deploying dense networks for maximal energy efficiency small cells meet massive mimo"
    - "energy efficiency optimization for mimo distributed antenna systems"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"

Connected through hyperedge HE-2 (induced by source paper "online geographical load balancing for mobile edge computing with energy harvesting"):
  with members:
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"
    - "socially trusted collaborative edge computing in ultra dense networks"
    - "energy harvesting wireless communications a review of recent advances"
    - "a lyapunov optimization approach for green cellular networks with hybrid energy supplies"
    - "cooperation and storage tradeoffs in power grids with renewable energy resources"
    - "optimal power cost management using stored energy in data centers"

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)