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 "large system analysis of power normalization techniques in massive mimo"):
  Abstract: Linear precoding has been widely studied in the context of massive multiple-input multiple-output (MIMO) together with two common power normalization techniques, namely, matrix normalization (MN) and vector normalization (VN). Despite this, their effect on the performance of massive MIMO systems has not been thoroughly studied yet. The aim of this paper is to fulfill this gap by using large system analysis. Considering a system model that accounts for channel estimation, pilot contamination, arbitrary pathloss, and per-user channel correlation, we compute tight approximations for the signal-to-interference-plus-noise ratio and the rate of each user equipment in the system while employing maximum ratio transmission (MRT), zero forcing (ZF), and regularized ZF precoding under both MN and VN techniques. Such approximations are used to analytically reveal how the choice of power normalization affects the performance of MRT and ZF under uncorrelated fading channels. It turns out that ZF with VN resembles a sum rate maximizer while it provides a notion of fairness under MN. Numerical results are used to validate the accuracy of the asymptotic analysis and to show that in massive MIMO, noncoherent interference and noise, rather than pilot contamination, are often the major limiting factors of the considered precoding schemes.

Includes members:
  Member "massive mimo has unlimited capacity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "reducing the computational complexity of multicasting in large scale antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint unicast and multi group multicast transmission in massive mimo systems")
  Member "energy efficient downlink transmission for multicell massive das with pilot contamination":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "spectral efficiency analysis of cell free massive mimo systems with zero forcing detector")
  Member "joint power allocation and user association optimization for massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint power allocation and load balancing optimization for energy efficient cell free massive mimo networks")
  Member "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generalized approximate message passing for massive mimo mmwave channel estimation with laplacian prior")
  Member "pilot contamination is not a fundamental asymptotic limitation in massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "machine learning for geometrically consistent angular spread function estimation in massive mimo")
  Member "massive mimo ten myths and one critical question":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "performance analysis of massive mimo for cell boundary users":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a retrodirective wireless power transfer scheme for ambient backscatter systems")

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)