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 "on the capacity of the peak power constrained vector gaussian channel an estimation theoretic perspective"):
  Abstract: This paper studies the capacity of an $n$-dimensional vector Gaussian noise channel subject to the constraint that an input must lie in the ball of radius $R$ centered at the origin. It is known that in this setting the optimizing input distribution is supported on a finite number of concentric spheres. However, the number, the positions and the probabilities of the spheres are generally unknown. This paper characterizes the necessary and sufficient conditions on the constraint $R$ such that the input distribution supported on a single sphere is optimal. The maximum $\bar{R}_n$, such that using only a single sphere is optimal, is shown to be a solution of an integral equation. Moreover, it is shown that $\bar{R}_n$ scales as $\sqrt{n}$ and the exact limit of $\frac{\bar{R}_n}{\sqrt{n}}$ is found.

Includes members:
  Member "upper and lower bounds on the capacity of amplitude constrained mimo channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the capacity achieving distribution for the amplitude constrained additive gaussian channel an upper bound on the number of mass points")
  Member "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "computable upper bounds on the capacity of finite state channels")
  Member "on the capacity of vector gaussian channels with bounded inputs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finite blocklength analysis of gaussian random coding in awgn channels under covert constraints")
  Member "peak to average power ratio of good codes for gaussian channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels")
  Member "pointwise relations between information and estimation in gaussian noise":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a generalized expression for the gradient of mutual information with the application in multiple access channels")
  Member "mutual information and minimum mean square error in gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")

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)