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: "fairness in multiuser systems with polymatroid capacity region"
  Abstract: For a wide class of multiuser systems, a subset of capacity region which includes the corner points and the sum-capacity facet has a special structure known as polymatroid. Multiple-access channels with fixed input distributions and multiple-antenna broadcast channels are examples of such systems. Any interior point of the sum-capacity facet can be achieved by time-sharing among corner points or by an alternative method known as rate-splitting. The main purpose of this paper is to find a point on the sum-capacity facet which satisfies a notion of fairness among the active users. This problem is addressed in two cases: (i) where the complexity of achieving interior points is not feasible, and (ii) where the complexity of achieving interior points is feasible. For the first case, the corner point for which the minimum rate of the active users is maximized is desired. A simple greedy algorithm is introduced to find such an optimum corner point. In addition, it is shown for single-antenna Gaussian multiple-access channels, the resulting corner point is leximin maximal with respect to the set of the corner points. For the second case, the properties of the unique leximin maximal rate vector with respect to the polymatroid are reviewed. It is shown that the problems of deriving the time-sharing coefficients or rate-splitting scheme to attain the leximin maximal vector can be solved by decomposing the problem into some lower dimensional subproblems. In addition, a fast algorithm to compute the time-sharing coefficients to attain a general point on the sum-capacity facet is presented.

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"
    - "optimal order of decoding for max min fairness in k user memoryless interference channels"

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:
    - "optimal order of decoding for max min fairness in k user memoryless interference channels"

Connected through hyperedge HE-3 (induced by source paper "robust monotonic optimization framework for multicell miso systems"):
  with members:
    - "non convex utility maximization in gaussian miso broadcast and interference channels"
    - "robust linear precoder design for multi cell downlink transmission"
    - "optimality properties distributed strategies and measurement based evaluation of coordinated multicell ofdma transmission"
    - "optimal beamforming in interference networks with perfect local channel information"
    - "probabilistic sinr constrained robust transmit beamforming a bernstein type inequality based conservative approach"
    - "multi cell mimo downlink with fairness criteria the large system limit"
    - "cooperative interference management with miso beamforming"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"

Connected through hyperedge HE-4 (induced by source paper "beamforming and rate allocation in miso cognitive radio networks"):
  with members:
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "optimal order of decoding for max min fairness in k user memoryless interference channels"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-5 (induced by source paper "optimal order of decoding for max min fairness in k user memoryless interference channels"):
  with members:
    - "characterization of rate region in interference channels with constrained power"

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)