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 "trellis extended codebooks and successive phase adjustment a path from lte advanced to fdd massive mimo systems"):
  Abstract: It is of great interest to develop efficient ways to acquire accurate channel state information (CSI) for frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems for backward compatibility. It is theoretically well known that the codebook size for CSI quantization should be increased as the number of transmit antennas becomes larger, and 3GPP long term evolution (LTE) and LTE-Advanced codebooks also follow this trend. Thus, in massive MIMO, it is hard to apply the conventional approach of using pre-defined vector-quantized codebooks for CSI quantization mainly because of codeword search complexity. In this paper, we propose a trellis-extended codebook (TEC) that can be easily harmonized with current wireless standards such as LTE or LTE-Advanced by extending standardized codebooks designed for 2, 4, or 8 antennas with trellis structures. TEC exploits a Viterbi decoder and convolutional encoder in channel coding as the CSI quantizer and the CSI reconstructer, respectively. By quantizing multiple channel entries simultaneously using standardized codebooks in a state transition of trellis search, TEC can achieve fractional bits per channel entry quantization to have a practical feedback overhead. Thus, TEC can solve both the complexity and the feedback overhead issues of CSI quantization in massive MIMO systems. We also develop trellis-extended successive phase adjustment (TE-SPA) which works as a differential codebook of TEC. This is similar to the dual codebook concept of LTE-Advanced. TE-SPA can reduce CSI quantization error even with lower feedback overhead in temporally correlated channels. Numerical results verify the effectiveness of the proposed schemes in FDD massive MIMO systems.

Includes members:
  Member "pilot beam pattern design for channel estimation in massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "secure massive mimo communication with low resolution dacs")
  Member "bounds on eigenvalues of a spatial correlation matrix":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "intelligent reflecting surface enhanced wireless network two timescale beamforming optimization")
  Member "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "high dimensional stochastic gradient quantization for communication efficient edge learning")
  Member "optimal feedback rate sharing strategy in zero forcing mimo broadcast channels":
    also connected through other hyperedges:
      (none)
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "capacity of a multiple antenna fading channel with a quantized precoding matrix":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on optimizing feedback interval for temporally correlated mimo channels with transmit beamforming and finite rate feedback")
  Member "mimo broadcast channels with finite rate feedback":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dl based csi feedback and cooperative recovery in massive mimo")

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)