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: "linearly coupled fountain codes"
  Abstract: Network-coded multiple access (NCMA) is a communication scheme for wireless multiple-access networks where physical-layer network coding (PNC) is employed. In NCMA, a user encodes and spreads its message into multiple packets. Time is slotted and multiple users transmit packets (one packet each) simultaneously in each timeslot. A sink node aims to decode the messages of all the users from the sequence of receptions over successive timeslots. For each timeslot, the NCMA receiver recovers multiple linear combinations of the packets transmitted in that timeslot, forming a system of linear equations. Different systems of linear equations are recovered in different timeslots. A message decoder then recovers the original messages of all the users by jointly solving multiple systems of linear equations obtained over different timeslots. We propose a low-complexity digital fountain approach for this coding problem, where each source node encodes its message into a sequence of packets using a fountain code. The aforementioned systems of linear equations recovered by the NCMA receiver effectively couple these fountain codes together. We refer to the coupling of the fountain codes as a linearly-coupled (LC) fountain code. The ordinary belief propagation (BP) decoding algorithm for conventional fountain codes is not optimal for LC fountain codes. We propose a batched BP decoding algorithm and analyze the convergence of the algorithm for general LC fountain codes. We demonstrate how to optimize the degree distributions and show by numerical results that the achievable rate region is nearly optimal. Our approach significantly reduces the decoding complexity compared with the previous NCMA schemes based on Reed-Solomon codes and random linear codes, and hence has the potential to increase throughput and decrease delay in computation-limited NCMA systems.

Connected through hyperedge HE-1 (induced by source paper "coding for network coded slotted aloha"):
  with members:
    - "batched sparse codes"
    - "an algebraic approach to physical layer network coding"
    - "network coded multiple access"
    - "frameless aloha protocol for wireless networks"
    - "high throughput random access via codes on graphs coded slotted aloha"
    - "physical layer network coding tutorial survey and beyond"
    - "channel coding and decoding in a relay system operated with physical layer network coding"
    - "compute and forward harnessing interference through structured codes"

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)