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 active learning and supervised transmission of spectrum sharing based cognitive radios by exploiting hidden primary radio feedback"
  Abstract: This paper studies the wireless spectrum sharing between a pair of distributed primary radio (PR) and cognitive radio (CR) links. Assuming that the PR link adapts its transmit power and/or rate upon receiving an interference signal from the CR and such transmit adaptations are observable by the CR, this results in a new form of feedback from the PR to CR, refereed to as hidden PR feedback, whereby the CR learns the PR's strategy for transmit adaptations without the need of a dedicated feedback channel from the PR. In this paper, we exploit the hidden PR feedback to design new learning and transmission schemes for spectrum sharing based CRs, namely active learning and supervised transmission. For active learning, the CR initiatively sends a probing signal to interfere with the PR, and from the observed PR transmit adaptations the CR estimates the channel gain from its transmitter to the PR receiver, which is essential for the CR to control its interference to the PR during the subsequent data transmission. This paper proposes a new transmission protocol for the CR to implement the active learning and the solutions to deal with various practical issues for implementation, such as time synchronization, rate estimation granularity, power measurement noise, and channel variation. Furthermore, with the acquired knowledge from active learning, the CR designs a supervised data transmission by effectively controlling the interference powers both to and from the PR, so as to achieve the optimum performance tradeoffs for the PR and CR links. Numerical results are provided to evaluate the effectiveness of the proposed schemes for CRs under different system setups.

Connected through hyperedge HE-1 (induced by source paper "optimal spectrum sharing with arq based legacy users via chain decoding"):
  with members:
    - "deep neural network architectures for modulation classification"
    - "on stable throughput of cognitive radio networks with cooperating secondary users"
    - "cross layer estimation and control for cognitive radio exploiting sparse network dynamics"
    - "cognitive access policies under a primary arq process via forward backward interference cancellation"
    - "blind known interference cancellation"
    - "cognitive interference management in retransmission based wireless networks"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-2 (induced by source paper "neural network cognitive engine for autonomous and distributed underlay dynamic spectrum access"):
  with members:
    - "energy efficient noma enabled heterogeneous cloud radio access networks"
    - "distributed anomaly detection using autoencoder neural networks in wsn for iot"
    - "adaptive modulation and coding and cooperative arq in a cognitive radio system"
    - "deep reinforcement learning multiple access for heterogeneous wireless networks"

Connected through hyperedge HE-3 (induced by source paper "learning based coexistence in two tier heterogeneous networks with cognitive small cells"):
  with members:
    - "user association in 5g networks a survey and an outlook"
    - "efficient scheduling and power allocation for d2d assisted wireless caching networks"
    - "what will 5g be"
    - "successive interference cancellation in heterogeneous cellular networks"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-4 (induced by source paper "primary channel gain estimation for spectrum sharing in cognitive radio networks"):
  with members:
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "design of learning based mimo cognitive radio systems"
    - "cognitive beamforming made practical effective interference channel and learning throughput tradeoff"

Connected through hyperedge HE-5 (induced by source paper "estimating the distance between macro base station and users in heterogeneous networks"):
  with members:
    - "user association in 5g networks a survey and an outlook"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-6 (induced by source paper "feedback bits allocation for interference minimization in cognitive radio communications"):
  with members:
    - "adaptive mode selection in multiuser miso cognitive networks with limited cooperation and feedback"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-7 (induced by source paper "proactive eavesdropping via cognitive jamming in fading channels"):
  with members:
    - "cyclical multiple access in uav aided communications a throughput delay tradeoff"
    - "surveillance and intervention of infrastructure free mobile communications a new wireless security paradigm"
    - "wireless information surveillance via proactive eavesdropping with spoofing relay"
    - "a survey on wireless security technical challenges recent advances and future trends"
    - "fundamental rate limits of physical layer spoofing"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "proactive eavesdropping via jamming for rate maximization over rayleigh fading channels"
    - "physical layer security for massive mimo an overview on passive eavesdropping and active attacks"

Connected through hyperedge HE-8 (induced by source paper "the one bit null space learning algorithm and its convergence"):
  with members:
    - "interference mitigation for cognitive radio mimo systems based on practical precoding"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "design of learning based mimo cognitive radio systems"
    - "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks"
    - "cognitive mimo radio"
    - "cognitive beamforming made practical effective interference channel and learning throughput tradeoff"

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)