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 "optimization of massive full dimensional mimo for positioning and communication"):
  Abstract: Massive Full-Dimensional multiple-input multiple-output (FD-MIMO) base stations (BSs) have the potential to bring multiplexing and coverage gains by means of three-dimensional (3D) beamforming. Key technical challenges for their deployment include the presence of limited-resolution front ends and the acquisition of channel state information (CSI) at the BSs. This paper investigates the use of FD-MIMO BSs to provide simultaneously high-rate data communication and mobile 3D positioning in the downlink. The analysis concentrates on the problem of beamforming design by accounting for imperfect CSI acquisition via Time Division Duplex (TDD)-based training and for the finite resolution of analog-to-digital converter (ADC) and digital-to-analog converter (DAC) at the BSs. Both \textit{unstructured beamforming} and a low-complexity \textit{Kronecker beamforming} solution are considered, where for the latter the beamforming vectors are decomposed into separate azimuth and elevation components. The proposed algorithmic solutions are based on Bussgang theorem, rank-relaxation and successive convex approximation (SCA) methods. Comprehensive numerical results demonstrate that the proposed schemes can effectively cater to both data communication and positioning services, providing only minor performance degradations as compared to the more conventional cases in which either function is implemented. Moreover, the proposed low-complexity Kronecker beamforming solutions are seen to guarantee a limited performance loss in the presence of a large number of BS antennas.

Includes members:
  Member "channel estimation and performance analysis of one bit massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance analysis of quantized uplink massive mimo ofdm with oversampling under adjacent channel interference")
  Member "a pessimistic approximation for the fisher information measure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sensitivity analysis for binary sampling systems via quantitative fisher information lower bounds")
  Member "sectoring in multi cell massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on optimal multi user beam alignment in millimeter wave wireless systems")
  Member "layered downlink precoding for c ran systems with full dimensional mimo":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hybrid precoding for massive mimo systems in cloud ran architecture with capacity limited fronthauls")
  Member "positioning for the internet of things a 3gpp perspective":
    also connected through other hyperedges:
      (none)
  Member "downlink achievable rate analysis in massive mimo systems with one bit dacs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "optimal fronthaul quantization for cloud radio positioning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent advances in cloud radio access networks system architectures key techniques and open issues")
  Member "parallel and distributed methods for nonconvex optimization part ii applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint uplink downlink optimization for backhaul limited mobile cloud computing with user scheduling")

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)