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: "reliable physical layer network coding supporting real applications"
  Abstract: This paper presents the first reliable physical-layer network coding (PNC) system that supports real TCP/IP applica- tions for the two-way relay network (TWRN). Theoretically, PNC could boost the throughput of TWRN by a factor of 2 compared with traditional scheduling (TS) in the high signal-to-noise (SNR) regime. Although there have been many theoretical studies on PNC performance, there have been relatively few experimental and implementation efforts. Our earlier PNC prototype, built in 2012, was an offline system that processed signals offline. For a system that supports real applications, signals must be processed online in real-time. Our real-time reliable PNC pro- totype, referred to as RPNC, solves a number of key challenges to enable the support of real TCP/IP applications. The enabling components include: 1) a time-slotted system that achieves s - level synchronization for the PNC system; 2) reduction of PNC signal processing complexity to meet real-time constraints; 3) an ARQ design tailored for PNC to ensure reliable packet delivery; 4) an interface to the application layer. We took on the challenge to implement all the above with general-purpose processors in PC through an SDR platform rather than ASIC or FPGA. With all these components, we have successfully demonstrated image exchange with TCP and two-party video conferencing with UDP over RPNC. Experimental results show that the achieved throughput approaches the PHY-layer data rate at high SNR, demonstrating the high efficiency of the RPNC system. Index Terms—Network coding, physical-layer network coding, two-way relay network, implementation, ARQ, TCP/IP.

Connected through hyperedge HE-1 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation"):
  with members:
    - "noncoherent detection for physical layer network coding"
    - "practical power balanced non orthogonal multiple access"
    - "ultra reliable short packet communications half duplex or full duplex relaying"
    - "complex linear physical layer network coding"
    - "mobile lattice coded physical layer network coding with practical channel alignment"
    - "on the subtleties of q pam linear physical layer network coding"
    - "ultra reliable communication in 5g wireless systems"
    - "physical layer network coding tutorial survey and beyond"

Connected through hyperedge HE-2 (induced by source paper "mobile lattice coded physical layer network coding with practical channel alignment"):
  with members:
    - "phase precoded compute and forward with partial feedback"
    - "asynchronous convolutional coded physical layer network coding"
    - "multilevel coding schemes for compute and forward with flexible decoding"
    - "scalable synchronization and reciprocity calibration for distributed multiuser mimo"
    - "network coded multiple access"
    - "airsync enabling distributed multiuser mimo with full spatial multiplexing"
    - "the degrees of freedom of compute and forward"
    - "physical layer network coding tutorial survey and beyond"

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.NI(Networking and Internet Architecture)