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 "nonuniform probability modulation for reducing energy consumption of remote sensors"):
  Abstract: One of the main goals of 5G wireless telecommunication technology is improving energy efficiency, especially of remote sensors which should be able for example to transmit on average 1bit/s for 10 years from a single AAA battery. There will be discussed using modulation with nonuniform probability distribution of symbols for improving energy efficiency of transmission at cost of reduced throughput. While the zero-signal (silence) has zero energy cost to emit, it can carry information if used alongside other symbols. If used more frequently than others, for example for majority of time slots or OFDM subcarriers, the number of bits transmitted per energy unit can be significantly increased. For example for hexagonal modulation and zero noise, this amount of bits per energy unit can be doubled by reducing throughput 2.7 times, thanks to using the zero-signal with probability $\approx$ 0.84. There will be discussed models and methods for such nonuniform probability modulations (NPM).

Includes members:
  Member "asymmetric numeral systems entropy coding combining speed of huffman coding with compression rate of arithmetic coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on optimally partitioning variable byte codes")
  Member "embedding grayscale halftone pictures in qr codes using correction trees":
    also connected through other hyperedges:
      (none)
  Member "correction trees as an alternative to turbo codes and low density parity check codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "embedding grayscale halftone pictures in qr codes using correction trees")
  Member "optimal encoding on discrete lattice with translational invariant constrains using statistical algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "asymmetric numeral systems entropy coding combining speed of huffman coding with compression rate of arithmetic coding")

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)