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: "sign compute resolve for tree splitting random access"
  Abstract: We present a framework for random access that is based on three elements: physical-layer network coding (PLNC), signature codes and tree splitting. In presence of a collision, physical-layer network coding enables the receiver to decode, i.e. compute, the sum of the packets that were transmitted by the individual users. For each user, the packet consists of the user's signature, as well as the data that the user wants to communicate. As long as no more than K users collide, their identities can be recovered from the sum of their signatures. This framework for creating and transmitting packets can be used as a fundamental building block in random access algorithms, since it helps to deal efficiently with the uncertainty of the set of contending terminals. In this paper we show how to apply the framework in conjunction with a tree-splitting algorithm, which is required to deal with the case that more than K users collide. We demonstrate that our approach achieves throughput that tends to 1 rapidly as K increases. We also present results on net data-rate of the system, showing the impact of the overheads of the constituent elements of the proposed protocol. We compare the performance of our scheme with an upper bound that is obtained under the assumption that the active users are a priori known. Also, we consider an upper bound on the net data-rate for any PLNC based strategy in which one linear equation per slot is decoded. We show that already at modest packet lengths, the net data-rate of our scheme becomes close to the second upper bound, i.e. the overhead of the contention resolution algorithm and the signature codes vanishes.

Connected through hyperedge HE-1 (induced by source paper "efficient scheduling for the massive random access gaussian channel"):
  with members:
    - "a joint graph based coding scheme for the unsourced random access gaussian channel"
    - "a coupled compressive sensing scheme for unsourced multiple access"
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "gaussian multiple access via compute and forward"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "capacity of gaussian many access channels"
    - "code design for short blocks a survey"
    - "massive machine type communications in 5g physical and mac layer solutions"

Connected through hyperedge HE-2 (induced by source paper "on throughput maximization of grant free access with reliability latency constraints"):
  with members:
    - "wireless access in ultra reliable low latency communication urllc"
    - "delay analysis of multichannel parallel contention tree algorithms mp cta"
    - "frameless aloha with reliability latency guarantees"
    - "assessment of lte wireless access for monitoring of energy distribution in the smart grid"

Connected through hyperedge HE-3 (induced by source paper "wireless access in ultra reliable low latency communication urllc"):
  with members:
    - "how reliable and capable is multi connectivity"
    - "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"

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)