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: "stable throughput in a cognitive wireless network"
  Abstract: We study, from a network layer perspective, the effect of an Ad-Hoc secondary network with N nodes randomly accessing the spectrum licensed to a primary node during the idle slots of the primary user. If the sensing is perfect, then the secondary nodes do not interfere with the primary node and hence do not affect its stable throughput. In case of imperfect sensing, it is shown that if the primary user's arrival rate is less than some calculated finite value, cognitive nodes can employ any transmission power or probabilities without affecting the primary user's stability; otherwise, the secondary nodes should control their transmission parameters to reduce the interference on the primary. It is also shown that in contrast with the primary's maximum stable throughput which strictly decreases with increased sensing errors, the throughput of the secondary nodes might increase with sensing errors as more transmission opportunities become available to them. Finally, we explore the use of the secondary nodes as relays of the primary node's traffic to compensate for the interference they might cause. We introduce a relaying protocol based on distributed space-time coding that forces all the secondary nodes that are able to decode a primary's unsuccessful packet to relay that packet whenever the primary is idle. In this case, for appropriate modulation scheme and under perfect sensing, it is shown that the more secondary nodes in the system, the better for the primary user in terms of his stable throughput. Meanwhile, the secondary nodes might benefit from relaying by having access to a larger number of idle slots due to the increase of the service rate of the primary. For the case of a single secondary node, the proposed relaying protocol guarantees that either both the primary and the secondary benefit from relaying or none of them does.

Connected through hyperedge HE-1 (induced by source paper "on optimal spectrum access of cognitive relay with finite packet buffer"):
  with members:
    - "cognitive radio networks with probabilistic relaying stable throughput and delay tradeoffs"
    - "on the stable throughput of cooperative cognitive radio networks with finite relaying buffer"
    - "buffer aided relaying with adaptive link selection"

Connected through hyperedge HE-2 (induced by source paper "on the performance of delay aware shared access with priorities"):
  with members:
    - "joint scheduling and power control for delay guarantees in heterogeneous cognitive radios"
    - "throughput optimization in multichannel cognitive radios with hard deadline constraints"
    - "relay assisted multiple access with full duplex multi packet reception"
    - "throughput of a cognitive radio network under congestion constraints a network level study"
    - "what will 5g be"
    - "low rate machine type communication via wireless device to device d2d links"
    - "power control for d2d underlaid cellular networks modeling algorithms and analysis"
    - "optimal utilization of a cognitive shared channel with a rechargeable primary source node"

Connected through hyperedge HE-3 (induced by source paper "on stable throughput of cognitive radio networks with cooperating secondary users"):
  with members:
    - "cognitive radio networks with probabilistic relaying stable throughput and delay tradeoffs"
    - "on the stable throughput of cooperative cognitive radio networks with finite relaying buffer"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-4 (induced by source paper "coded slotted aloha a graph based method for uncoordinated multiple access"):
  with members:
    - "error floor analysis of coded slotted aloha over packet erasure channels"
    - "the throughput of slotted aloha with diversity"
    - "aloha random access that operates as a rateless code"
    - "spatially coupled random access on graphs"
    - "frameless aloha protocol for wireless networks"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "doubly generalized ldpc codes stability bound over the bec"

Connected through hyperedge HE-5 (induced by source paper "sensing decision based cooperative relaying schemes with multi access transmission stability region and average delay characterization"):
  with members:
    - "cooperative access in cognitive radio networks stable throughput and delay tradeoffs"
    - "information theory vs queueing theory for resource allocation in multiple access 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)