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 "device to device communications in the millimeter wave band a novel distributed mechanism"):
  Abstract: In spite of its potential advantages, the large-scale implementation of the device-to-device (D2D) communications has yet to be realized, mainly due to severe interference and lack of enough bandwidth in the microwave ($\mu$W) band. Recently, exploiting the millimeter wave (mmW) band for D2D communications has attracted considerable attention as a potential solution to these challenges. However, its severe sensitivity to blockage along with its directional nature make the utilization of the mmW band a challenging task as it requires line-of-sight (LOS) link detection and careful beam alignment between the D2D transceivers. In this paper, we propose a novel distributed mechanism which enables the D2D devices to discover unblocked LOS links for the mmW band communication. Moreover, as such LOS links are not always available, the proposed mechanism allows the D2D devices to switch to the $\mu$W band if necessary. In addition, the proposed mechanism detects the direction of the LOS links to perform the beam alignment. We have used tools from stochastic geometry to evaluate the performance of the proposed mechanism in terms of the signal-to-interference-plus-noise ratio (SINR) coverage probability. The performance of the proposed algorithm is then compared to the one of the single band (i.e., $\mu$W/mmW) communication. The simulation results show that the proposed mechanism considerably outperforms the single band communication.

Includes members:
  Member "joint millimeter wave and microwave resources allocation in cellular networks with dual mode base stations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning for mmwave beam and blockage prediction using sub 6ghz channels")
  Member "context aware d2d peer selection for load distribution in lte networks":
    also connected through other hyperedges:
      (none)
  Member "a survey on device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "simultaneous energy harvesting and information transmission in a mimo full duplex system a machine learning based design")
  Member "cognitive and energy harvesting based d2d communication in cellular networks stochastic geometry modeling and analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  Member "coverage and rate analysis for millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "analysis of blockage effects on urban cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")

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)