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: "optimal order of decoding for max min fairness in k user memoryless interference channels"
  Abstract: A K-user memoryless interference channel is considered where each receiver sequentially decodes the data of a subset of transmitters before it decodes the data of the designated transmitter. Therefore, the data rate of each transmitter depends on (i) the subset of receivers which decode the data of that transmitter, (ii) the decoding order, employed at each of these receivers. In this paper, a greedy algorithm is developed to find the users which are decoded at each receiver and the corresponding decoding order such that the minimum rate of the users is maximized. It is proven that the proposed algorithm is optimal.

Connected through hyperedge HE-1 (induced by source paper "optimum transmission through the multiple antenna gaussian multiple access channel"):
  with members:
    - "completion time in multi access channel an information theoretic perspective"
    - "fairness in multiuser systems with polymatroid capacity region"

Connected through hyperedge HE-2 (induced by source paper "to prolong the lifetime of wireless sensor networks the min max fair scheduling in a multi access contra polymatroid"):
  with members:
    - "fairness in multiuser systems with polymatroid capacity region"

Connected through hyperedge HE-3 (induced by source paper "beamforming and rate allocation in miso cognitive radio networks"):
  with members:
    - "fairness in multiuser systems with polymatroid capacity region"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-4 (induced by source paper "to decode the interference or to consider it as noise"):
  with members:
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"
    - "throughput scaling laws for wireless networks with fading channels"
    - "the effect of fading channel inversion and threshold scheduling on ad hoc networks"
    - "joint power control and user scheduling in multicell wireless networks capacity scaling laws"

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)