human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "the one bit null space learning algorithm and its convergence"):
  Abstract: This paper proposes a new algorithm for MIMO cognitive radio secondary users (SU) to learn the null space of the interference channel to the primary user (PU) without burdening the PU with any knowledge or explicit cooperation with the SU. The knowledge of this null space enables the SU to transmit in the same band simultaneously with the PU by utilizing separate spatial dimensions than the PU. Specifically, the SU transmits in the null space of the interference channel to the PU. We present a new algorithm, called the one-bit null space learning algorithm (OBNSLA), in which the SU learns the PU's null space by observing a binary function that indicates whether the interference it inflicts on the PU has increased or decreased in comparison to the SU's previous transmitted signal. This function is obtained by listening to the PU transmitted signal or control channel and extracting information from it about whether the PU's signal-to-interference-plus-noise power ratio (SINR) has increased or decreased. The OBNSLA is shown to have a linear convergence rate and an asymptotic quadratic convergence rate. Finally, we derive bounds on the interference that the SU inflicts on the PU as a function of a parameter determined by the SU. This lets the SU control the maximum level of interference, which enables it to protect the PU completely blindly with minimum complexity. The asymptotic analysis and the derived bounds also apply to the recently proposed blind null space learning algorithm.

Includes members:
  Member "interference mitigation for cognitive radio mimo systems based on practical precoding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a practical spectrum sharing scheme for cognitive radio networks design and experiments")
  Member "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "algorithm hardware co optimization of the memristor based framework for solving socp and homogeneous qcqp problems")
  Member "on active learning and supervised transmission of spectrum sharing based cognitive radios by exploiting hidden primary radio feedback":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal spectrum sharing with arq based legacy users via chain decoding")
  Member "design of learning based mimo cognitive radio systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "primary channel gain estimation for spectrum sharing in cognitive radio networks")
  Member "exploiting multi antennas for opportunistic spectrum sharing in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal precoder designs for sum utility maximization in swipt enabled multi user mimo cognitive radio networks")
  Member "cognitive mimo radio":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "cognitive beamforming made practical effective interference channel and learning throughput tradeoff":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a practical spectrum sharing scheme for cognitive radio networks design and experiments")

Question: Please tell me which class the source paper 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)