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 "the price of certainty waterslide curves and the gap to capacity"):
  Abstract: The classical problem of reliable point-to-point digital communication is to achieve a low probability of error while keeping the rate high and the total power consumption small. Traditional information-theoretic analysis uses `waterfall' curves to convey the revolutionary idea that unboundedly low probabilities of bit-error are attainable using only finite transmit power. However, practitioners have long observed that the decoder complexity, and hence the total power consumption, goes up when attempting to use sophisticated codes that operate close to the waterfall curve. #R##N#This paper gives an explicit model for power consumption at an idealized decoder that allows for extreme parallelism in implementation. The decoder architecture is in the spirit of message passing and iterative decoding for sparse-graph codes. Generalized sphere-packing arguments are used to derive lower bounds on the decoding power needed for any possible code given only the gap from the Shannon limit and the desired probability of error. As the gap goes to zero, the energy per bit spent in decoding is shown to go to infinity. This suggests that to optimize total power, the transmitter should operate at a power that is strictly above the minimum demanded by the Shannon capacity. #R##N#The lower bound is plotted to show an unavoidable tradeoff between the average bit-error probability and the total power used in transmission and decoding. In the spirit of conventional waterfall curves, we call these `waterslide' curves.

Includes members:
  Member "a channel that heats up":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "low snr capacity of noncoherent fading channels")
  Member "a hot channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multipath channels of bounded capacity")
  Member "accumulate repeat accumulate codes capacity achieving ensembles of systematic codes for the erasure channel with bounded complexity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "log logarithmic time pruned polar coding")
  Member "optimal memoryless encoding for low power off chip data buses":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cooling codes thermal management coding for high performance interconnects")
  Member "capacity achieving codes with bounded graphical complexity on noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on universal properties of capacity approaching ldpc code ensembles")
  Member "capacity achieving ensembles for the binary erasure channel with bounded complexity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "log logarithmic time pruned polar 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)