human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "energy efficiency and sum rate tradeoffs for massive mimo systems with underlaid device to device communications"):
  with members:
    - "massive mimo ten myths and one critical question"
    - "energy efficiency and sum rate when massive mimo meets device to device communication"
    - "an analytical framework for device to device communication in cellular networks"
    - "energy efficient resource allocation for device to device underlay communication"
    - "design aspects of short range millimeter wave networks a mac layer perspective"
    - "the interplay between massive mimo and underlaid d2d networking"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"
    - "spectrum sharing for device to device communication in cellular networks"

Connected through hyperedge HE-2 (induced by source paper "massive machine type communication with data aggregation and resource scheduling"):
  with members:
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "energy efficient scheduling and grouping for machine type communications over cellular networks"
    - "a delay optimal mac and packet scheduler for heterogeneous m2m uplink"
    - "e 2 mac energy efficient medium access for massive m2m communications"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "random cell association and void probability in poisson distributed cellular networks"

Connected through hyperedge HE-3 (induced by source paper "energy efficient scheduling and grouping for machine type communications over cellular networks"):
  with members:
    - "e 2 mac energy efficient medium access for massive m2m communications"
    - "understanding the iot connectivity landscape a contemporary m2m radio technology roadmap"
    - "aggregation and trunking of m2m traffic via d2d connections"
    - "a survey on device to device communication in cellular networks"
    - "reliable reporting for massive m2m communications with periodic resource pooling"
    - "power efficient system design for cellular based machine to machine communications"

Question: Please tell me which class the center node 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)