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 "sense and predict harnessing spatial interference correlation for cognitive radio networks"):
  Abstract: Cognitive radio (CR) is a key enabler realizing future networks to achieve higher spectral efficiency by allowing spectrum sharing between different wireless networks. It is important to explore whether spectrum access opportunities are available, but conventional CR based on transmitter (TX) sensing cannot be used to this end because the paired receiver (RX) may experience different levels of interference, according to the extent of their separation, blockages, and beam directions. To address this problem, this paper proposes a novel form of medium access control (MAC) termed sense-and-predict (SaP), whereby each secondary TX predicts the interference level at the RX based on the sensed interference at the TX; this can be quantified in terms of a spatial interference correlation between the two locations. Using stochastic geometry, the spatial interference correlation can be expressed in the form of a conditional coverage probability, such that the signal-to-interference ratio at the RX is no less than a predetermined threshold given the sensed interference at the TX, defined as an opportunistic probability (OP). The secondary TX randomly accesses the spectrum depending on OP. We optimize the SaP framework to maximize the area spectral efficiencies (ASEs) of secondary networks while guaranteeing the service quality of the primary networks. The testbed experiments using universal software radio peripheral (USRP) and MATLAB simulations show that SaP affords higher ASEs compared with CR without prediction.

Includes members:
  Member "ultra reliable and low latency communications in 5g downlink physical layer aspects":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards reliable uav swarm communication in d2d enhanced cellular network")
  Member "millimeter wave interference avoidance via building aware associations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "lte and millimeter waves for v2i communications an end to end performance comparison")
  Member "the connectivity of millimeter wave networks in urban environments modeled using random lattices":
    also connected through other hyperedges:
      (none)
  Member "macro diversity in cellular networks with random blockages":
    also connected through other hyperedges:
      (none)
  Member "sense and predict opportunistic mac based on spatial interference correlation for cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "opportunism in dynamic spectrum access for 5g a concept and its application to duplexing")
  Member "downlink and uplink cell association with traditional macrocells and millimeter wave small cells":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "intelligent uav base station selection in urban environments a supervised learning approach")
  Member "spatio temporal interference correlation and joint coverage in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "handover probability in drone cellular networks")
  Member "design and analysis of initial access in millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "periodic analog channel estimation aided beamforming for massive mimo systems")

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)