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 "optimizing transmission lengths for limited feedback with non binary ldpc examples"):
  Abstract: This paper presents a general approach for optimizing the number of symbols in increments (packets of incremental redundancy) in a feedback communication system with a limited number of increments. This approach is based on a tight normal approximation on the rate for successful decoding. Applying this approach to a variety of feedback systems using non-binary (NB) low-density parity-check (LDPC) codes shows that greater than 90% of capacity can be achieved with average blocklengths fewer than 500 transmitted bits. One result is that the performance with ten increments closely approaches the performance with an infinite number of increments. The paper focuses on binary- input additive-white Gaussian noise (BI-AWGN) channels but also demonstrates that the normal approximation works well on examples of fading channels as well as high-SNR AWGN channels that require larger QAM constellations. The paper explores both variable-length feedback codes with termination (VLFT) and the more practical variable length feedback (VLF) codes without termination that require no assumption of noiseless transmitter confirmation. For VLF we consider both a two-phase scheme and CRC-based scheme.

Includes members:
  Member "isn t hybrid arq sufficient":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "status updates through multicast networks")
  Member "protograph based raptor like ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "low density majority codes and the problem of graceful degradation")
  Member "reliability output decoding of tail biting convolutional codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "efficient error correcting codes in the short blocklength regime")
  Member "a hybrid arq scheme based on polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "design of polar codes in 5g new radio")
  Member "feedback communication systems with limitations on incremental redundancy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards massive ultra reliable and low latency wireless the art of sending short packets")
  Member "polar coded harq scheme with chase combining":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "throughput based design for polar coded modulation")
  Member "a rate compatible sphere packing analysis of feedback coding with limited retransmissions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy latency tradeoff in ultra reliable low latency communication with retransmissions")

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)