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 "maximum rate of 3 and 4 real symbol ml decodable unitary weight stbcs"):
  Abstract: It has been shown recently that the maximum rate of a 2-real-symbol (single-complex-symbol) maximum likelihood (ML) decodable, square space-time block codes (STBCs) with unitary weight matrices is $\frac{2a}{2^a}$ complex symbols per channel use (cspcu) for $2^a$ number of transmit antennas \cite{KSR}. These STBCs are obtained from Unitary Weight Designs (UWDs). In this paper, we show that the maximum rates for 3- and 4-real-symbol (2-complex-symbol) ML decodable square STBCs from UWDs, for $2^{a}$ transmit antennas, are $\frac{3(a-1)}{2^{a}}$ and $\frac{4(a-1)}{2^{a}}$ cspcu, respectively. STBCs achieving this maximum rate are constructed. A set of sufficient conditions on the signal set, required for these codes to achieve full-diversity are derived along with expressions for their coding gain.

Includes members:
  Member "maximum rate of unitary weight single symbol decodable stbcs":
    also connected through other hyperedges:
      (none)
  Member "multi group ml decodable collocated and distributed space time block codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "construction of block orthogonal stbcs and reducing their sphere decoding complexity")
  Member "high rate multi symbol decodable stbcs from clifford algebras":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "construction of block orthogonal stbcs and reducing their sphere decoding complexity")
  Member "algebraic distributed differential space time codes with low decoding complexity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a belief propagation based framework for soft multiple symbol differential detection")

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)