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 "study of structured root ldpc codes and peg techniques for block fading channels"):
  Abstract: In this work, we propose structured Root-Low-Density Parity-Check (LDPC) codes and design techniques for block-fading channels. In particular, Quasi-Cyclic Root-LDPC codes, Irregular repeat-accumulate Root-LDPC codes and Controlled Doping Root-LDPC codes based on Progressive Edge Growth (PEG) techniques for block-fading channels are proposed. The proposed Root-LDPC codes are both suitable for channels under $F = 2, 3$ and $4$ independent fading per codeword. The performance of the proposed codes is investigated in terms of Frame Error Rate (FER). The proposed Root-LDPC codes are capable of achieving the channel diversity and outperform standard LDPC codes. For block-fading channel with $F = 2$ our proposed PEG-based Root-LDPC codes outperform PEG-based LDPC codes by $7.5$dB at a FER close to $10^{-3}$.

Includes members:
  Member "iterative detection and decoding algorithms for mimo systems in block fading channels using ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "study of coarse quantization aware block diagonalization algorithms for mimo systems with low resolution")
  Member "massive mimo systems signal processing challenges and research trends":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "uplink downlink rate balancing and throughput scaling in fdd massive mimo systems")
  Member "adaptive distributed space time coding based on adjustable code matrices for cooperative mimo relaying systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "study of cloud aided multi way multiple antenna relaying with best user link selection and joint ml 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)