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: "how reliable and capable is multi connectivity"
  Abstract: Multi-connectivity (MCo) is considered to be a key strategy for enabling reliable transmissions and enhanced data rates in fifth-generation mobile networks, as it provides multiple links from source to destination. In this paper, we quantify the communication performance of MCo in terms of outage probability and throughput. For doing so, we establish a simple, yet accurate analytical framework at high signal-to-noise ratio (SNR), in which the number of links, the spectral efficiency, the path loss, and the SNR are incorporated, giving new insights into the potentials of MCo as compared with the single-connectivity (SCo). These are our main contributions: 1) finding the exact coding gain of the outage probability for parallel block-fading channels; 2) quantifying the performance improvement of MCo over SCo in terms of SNR gain; and 3) comparing optimal and suboptimal combining algorithms for MCo at the receiver side, namely joint decoding, selection combining, and maximal-ratio combining, also in terms of SNR gain. In addition, we apply our analytical framework to real field channel measurements and thereby illustrate the potential of MCo to achieve high reliability and high data rates in real cellular networks.

Connected through hyperedge HE-1 (induced by source paper "wireless mesh networking with devices equipped with multi connectivity"):
  with members:
    - "an overview of machine learning approaches in wireless mesh networks"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

Connected through hyperedge HE-2 (induced by source paper "wireless edge computing with latency and reliability guarantees"):
  with members:
    - "distributed federated learning for ultra reliable low latency vehicular communications"
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "a tutorial on beam management for 3gpp nr at mmwave frequencies"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "coded federated computing in wireless networks with straggling devices and imperfect csi"
    - "ultra reliable communication in 5g mmwave networks a risk sensitive approach"
    - "on device federated learning via blockchain and its latency analysis"
    - "mmwave beam prediction with situational awareness a machine learning approach"

Connected through hyperedge HE-3 (induced by source paper "impact of correlated failures in 5g dual connectivity architectures for urllc applications"):
  with members:
    - "improving network availability of ultra reliable and low latency communications with multi connectivity"
    - "business case and technology analysis for 5g low latency applications"
    - "sinr model with best server association for high availability studies of wireless networks"

Connected through hyperedge HE-4 (induced by source paper "wireless access in ultra reliable low latency communication urllc"):
  with members:
    - "wireless channel dynamics and robustness for ultra reliable low latency communications"
    - "improving network availability of ultra reliable and low latency communications with multi connectivity"
    - "packet duplication in dual connectivity enabled 5g wireless networks overview and challenges"
    - "massive mimo for ultra reliable communications with constellations for dual coherent noncoherent detection"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "energy latency tradeoff in ultra reliable low latency communication with retransmissions"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "short packet structure for ultra reliable machine type communication tradeoff between detection and decoding"

Connected through hyperedge HE-5 (induced by source paper "ultra reliable low latency communication urllc using interface diversity"):
  with members:
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "optimized interface diversity for ultra reliable low latency communication urllc"
    - "random access protocols for massive mimo"
    - "latency analysis of systems with multiple interfaces for ultra reliable m2m communication"
    - "5g ultra reliable vehicular communication"
    - "exploiting the power of multiplicity a holistic survey of network layer multipath"
    - "what will 5g be"

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)