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 "generalized distributive law for ml decoding of space time block codes"):
  Abstract: The problem of designing good Space-Time Block Codes (STBCs) with low maximum-likelihood (ML) decoding complexity has gathered much attention in the literature. All the known low ML decoding complexity techniques utilize the same approach of exploiting either the multigroup decodable or the fast-decodable (conditionally multigroup decodable) structure of a code. We refer to this well known technique of decoding STBCs as Conditional ML (CML) decoding. In this paper we introduce a new framework to construct ML decoders for STBCs based on the Generalized Distributive Law (GDL) and the Factor-graph based Sum-Product Algorithm. We say that an STBC is fast GDL decodable if the order of GDL decoding complexity of the code is strictly less than M^l, where l is the number of independent symbols in the STBC, and M is the constellation size. We give sufficient conditions for an STBC to admit fast GDL decoding, and show that both multigroup and conditionally multigroup decodable codes are fast GDL decodable. For any STBC, whether fast GDL decodable or not, we show that the GDL decoding complexity is strictly less than the CML decoding complexity. For instance, for any STBC obtained from Cyclic Division Algebras which is not multigroup or conditionally multigroup decodable, the GDL decoder provides about 12 times reduction in complexity compared to the CML decoder. Similarly, for the Golden code, which is conditionally multigroup decodable, the GDL decoder is only half as complex as the CML decoder.

Includes members:
  Member "a family of fast decodable mido codes from crossed product algebras over q":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "revisited design criteria for stbcs with reduced complexity ml decoding")
  Member "four group decodable space time block codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on mimo transmission with discrete input signals technical challenges advances and future trends")
  Member "fast maximum likelihood decoding of the golden code":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on mimo transmission with discrete input signals technical challenges advances and future trends")
  Member "on the search for high rate quasi orthogonal space time block code":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bounds on fast decodability of space time block codes skew hermitian matrices and azumaya algebras")
  Member "on fast decodable space time block codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on mimo transmission with discrete input signals technical challenges advances and future trends")
  Member "quasi orthogonal stbc with minimum decoding complexity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on mimo transmission with discrete input signals technical challenges advances and future trends")

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)