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 "accurately accounting for random blockage in device to device mmwave networks"):
  Abstract: Millimeter-wave systems are characterized by the use of highly directional antennas and the presence of blockages, which significantly alter the path-loss and small-scale fading parameters. The received power of each interferer depends on the direction it points and whether it is line-of-sight (LOS), non-LOS (i.e., partially blocked), or completely blocked. While interferers that are sufficiently far away will almost certainly be completely blocked, a finite number of interferers in close proximity will be subject to random partial blockages. Previous attempts to characterize mmWave networks have made the simplifying assumption that all interferers within some radius, called the LOS ball, are unblocked, while interferers beyond that radius are non-LOS. However, compared to simulation results, the LOS ball assumption tends to overestimate outage. In this paper, we present an accurate yet tractable analysis of finite mmWave networks that dispenses with the LOS ball assumption. In the analysis, each interferer has a distribution that is selected randomly from several possibilities, each representing different blockage and directivity states. First, the exact outage probability is found for a finite network with interferers in fixed locations. Then, the spatially averaged outage probability is found by averaging over the interferer locations. While the focus is on device-to-device networks, the analysis is general enough to find applications outside of the present mmWave framework.

Includes members:
  Member "modeling and analyzing millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "analysis of a frequency hopping millimeter wave cellular uplink":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the potential gains of macrodiversity in mmwave cellular networks with correlated blocking")
  Member "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a hybrid model based and data driven approach to spectrum sharing in mmwave cellular networks")
  Member "tractable model for rate in self backhauled millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")
  Member "a direct approach to computing spatially averaged outage probability":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "outage correlation in finite and clustered wireless networks")
  Member "coverage and rate analysis for millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "millimeter wave channel modeling and cellular capacity evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "analysis of blockage effects on urban cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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)