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: "on the gaussian many to one x channel"
  Abstract: In this paper, the Gaussian many-to-one X channel (XC), which is a special case of general multiuser XC, is studied. In the Gaussian many-to-one XC, communication links exist between all transmitters and one of the receivers, along with a communication link between each transmitter and its corresponding receiver. As per the XC assumption, transmission of messages is allowed on all the links of the channel. This communication model is different from the corresponding many-to-one interference channel (IC). Transmission strategies, which involve using Gaussian codebooks and treating interference from a subset of transmitters as noise, are formulated for the above channel. Sum-rate is used as the criterion of optimality for evaluating the strategies. Initially, a    $3 \times 3$    many-to-one XC is considered and three transmission strategies are analyzed. The first two strategies are shown to achieve sum-rate capacity under certain channel conditions. For the third strategy, a sum-rate outer bound is derived and the gap between the outer bound and the achieved rate is characterized. These results are later extended to the    $K \times K$    case. Next, a region in which the many-to-one XC can be operated as a many-to-one IC without the loss of sum-rate is identified. Furthermore, in the above region, it is shown that using Gaussian codebooks and treating interference as noise achieve a rate point that is within    $K/2 -1$    bits from the sum-rate capacity. Subsequently, some implications of the above results to the Gaussian many-to-one IC are discussed. Transmission strategies for the many-to-one IC are formulated, and channel conditions under which the strategies achieve sum-rate capacity are obtained. A region where the sum-rate capacity can be characterized to within    $K/2-1$    bits is also identified. Finally, the regions where the derived channel conditions are satisfied for each strategy are illustrated for a    $3 \times 3$    many-to-one XC and the corresponding many-to-one IC.

Connected through hyperedge HE-1 (induced by source paper "channel conditions for the optimality of interference decoding schemes for k user gaussian interference channels"):
  with members:
    - "on the sum capacity of many to one and one to many gaussian interference channels"
    - "capacity bounds for the k user gaussian interference channel"
    - "on the sum capacity of k user cascade gaussian z interference channel"
    - "k user interference channels general outer bound and sum capacity for certain gaussian channels"
    - "capacity bounds for the gaussian interference channel"
    - "new outer bounds on the capacity region of gaussian interference channels"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-2 (induced by source paper "uplink non orthogonal multiple access with finite alphabet inputs"):
  with members:
    - "on non orthogonal multiple access with finite alphabet inputs in z channels"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "joint rate control and power allocation for non orthogonal multiple access systems"
    - "nonorthogonal multiple access in large scale underlay cognitive radio networks"
    - "relay selection for cooperative noma"
    - "quadrature amplitude modulation division for multiuser miso broadcast channels"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"

Connected through hyperedge HE-3 (induced by source paper "on non orthogonal multiple access with finite alphabet inputs in z channels"):
  with members:
    - "nonorthogonal multiple access in large scale underlay cognitive radio networks"
    - "relay selection for cooperative noma"
    - "a survey of downlink non orthogonal multiple access for 5g wireless communication networks"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"
    - "cooperative non orthogonal multiple access with simultaneous wireless information and power transfer"
    - "linear precoding for the mimo multiple access channel with finite alphabet inputs and statistical csi"
    - "what will 5g be"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

Connected through hyperedge HE-4 (induced by source paper "on the sum capacity of many to one and one to many gaussian interference channels"):
  with members:
    - "lattice codes for many to one interference channels with and without cognitive messages"
    - "capacity bounds for the k user gaussian interference channel"
    - "k user interference channels general outer bound and sum capacity for certain gaussian channels"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"
    - "on the capacity of the k user cyclic gaussian interference channel"
    - "interference alignment and a noisy interference regime for many to one interference channels"
    - "capacity bounds for the gaussian interference channel"
    - "new outer bounds on the capacity region of gaussian interference channels"

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)