human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "a capacity achieving coding scheme for the awgn channel with polynomial encoding and decoding complexity"):
  Abstract: A fundamental problem in coding theory is the design of an efficient coding scheme that achieves the capacity of the additive white Gaussian noise (AWGN) channel. In this article, we study a simple capacity-achieving nested lattice coding scheme whose encoding and decoding complexities are polynomial in the blocklength. Specifically, we show that by concatenating an inner nested lattice code with an outer Reed-Solomon code over an appropriate finite field, we can achieve the capacity of the AWGN channel. The main feature of this technique is that the encoding and decoding complexities grow as $O(N^2)$, while the probability of error decays exponentially in $N$, where $N$ denotes the blocklength. Replacing the outer Reed-Solomon code by an expander code helps us further reduce the decoding complexity to $O(N\log^2N)$. We also show that this gives us a recipe to extend a high-complexity nested lattice code for a Gaussian channel to a low-complexity concatenated code without any loss in the asymptotic rate. As examples, we describe polynomial-time coding schemes for the wiretap channel, and the compute-and-forward scheme for computing integer linear combinations of messages.

Includes members:
  Member "a lattice coding scheme for secret key generation from gaussian markov tree sources":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "compressed secret key agreement maximizing multivariate mutual information per bit")
  Member "secure compute and forward in a bidirectional relay":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the polarizing behavior and scaling exponent of polar codes with product kernels")
  Member "construction of capacity achieving lattice codes polar lattices":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sparse regression codes")
  Member "semantically secure lattice codes for the gaussian wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "semantically secure lattice codes for compound mimo channels")
  Member "physical layer network coding tutorial survey and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "random access for massive machine type communications")
  Member "integer forcing linear receivers":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "private information retrieval over gaussian mac")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "private information retrieval over gaussian mac")

Question: Please tell me which class the source paper 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)