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 "typical sumsets of linear codes"):
  Abstract: Given two identical linear codes $\mathcal C$ over $\mathbb F_q$ of length $n$, we independently pick one codeword from each codebook uniformly at random. A $\textit{sumset}$ is formed by adding these two codewords entry-wise as integer vectors and a sumset is called $\textit{typical}$, if the sum falls inside this set with high probability. We ask the question: how large is the typical sumset for most codes? In this paper we characterize the asymptotic size of such typical sumset. We show that when the rate $R$ of the linear code is below a certain threshold $D$, the typical sumset size is roughly $|\mathcal C|^2=2^{2nR}$ for most codes while when $R$ is above this threshold, most codes have a typical sumset whose size is roughly $|\mathcal C|\cdot 2^{nD}=2^{n(R+D)}$ due to the linear structure of the codes. The threshold $D$ depends solely on the alphabet size $q$ and takes value in $[1/2, \log \sqrt{e})$. More generally, we completely characterize the asymptotic size of typical sumsets of two nested linear codes $\mathcal C_1, \mathcal C_2$ with different rates. As an application of the result, we study the communication problem where the integer sum of two codewords is to be decoded through a general two-user multiple-access channel.

Includes members:
  Member "sumset and inverse sumset inequalities for differential entropy and mutual information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "countably infinite multilevel source polarization for non stationary erasure distributions")
  Member "computing sum of sources over an arbitrary multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding")
  Member "compute and forward harnessing interference through structured codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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)