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 "zero outage cellular downlink with fixed rate d2d underlay"):
  Abstract: Two of the emerging trends in wireless cellular systems are Device-to-Device (D2D) and Machine-to-Machine (M2M) communications. D2D enables efficient reuse of the licensed spectrum to support localized transmissions, while M2M connections are often characterized by fixed and low transmission rates. D2D connections can be instrumental in localized aggregation of uplink M2M traffic to a more capable cellular device, before being finally delivered to the Base Station (BS). In this paper we show that a fixed M2M rate is an enabler of efficient Machine-Type D2D underlay operation taking place simultaneously with another \emph{downlink} cellular transmission. In the considered scenario, a BS $B$ transmits to a user $U$, while there are $N_M$ Machine-Type Devices (MTDs) attached to $U$, all sending simultaneously to $U$ and each using the same rate $R_M$. While assuming that $B$ knows the channel $B-U$, but not the interfering channels from the MTDs to $U$, we prove that there is a positive downlink rate that can always be decoded by $U$, leading to zero-outage of the downlink signal. This is a rather surprising consequence of the features of the multiple access channel and the fixed rate $R_M$. We also consider the case of a simpler, single-user decoder at $U$ with successive interference cancellation. However, with single-user decoder, a positive zero-outage rate exists only when $N_M=1$ and is zero when $N_M>1$. This implies that joint decoding is instrumental in enabling fixed-rate underlay operation.

Includes members:
  Member "a survey on device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simultaneous energy harvesting and information transmission in a mimo full duplex system a machine learning based design")
  Member "low rate machine type communication via wireless device to device d2d links":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "applying device to device communication to enhance iot services")
  Member "five disruptive technology directions for 5g":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning enabled optimization of downlink beamforming under per antenna power constraints algorithms and experimental demonstration")
  Member "random deployment of data collectors for serving randomly located sensors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on detection of critical events in a finite forest using randomly deployed wireless sensors")
  Member "iterative spectrum shaping with opportunistic multiuser detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cognitive wireless powered network spectrum sharing models and throughput maximization")
  Member "exploiting opportunistic multiuser detection in decentralized multiuser mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wireless communications in the era of big data")

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)