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 "communication using a large scale array of ubiquitous antennas a geometry approach"):
  Abstract: The recent trends of densification and centralized signal processing in radio access networks suggest that future networks may comprise ubiquitous antennas coordinated to form a network-wide gigantic array, referred to as the ubiquitous array (UA). In this paper, the UA communication techniques are designed and analyzed based on a geometric model. Specifically, the UA is modeled as a continuous circular/spherical array enclosing target users and free-space propagation is assumed. First, consider the estimation of multiuser UA channels induced by user locations. Given single pilot symbols, a novel channel estimation scheme is proposed that decomposes training signals into Fourier/Laplace series and thereby translates multiuser channel estimation into peak detection of a derive function of location. The process is shown to suppress noise. Moreover, it is proved that estimation error due to interference diminishes with the increasing minimum user-separation distance following the power law, where the exponent is 1/3 and 1 for the circular and spherical UA, respectively. If orthogonal pilot sequences are used, channel estimation is found to be perfect. Next, consider channel-conjugate data transmission that maximizes received signal power. The power of interference between two users is shown to decay with the increasing user-separation distance sub-linearly and super-linearly for the circular and spherical UA, respectively. Furthermore, a novel multiuser precoding design is proposed by exciting different phase modes of the UA and controlling the mode weight factors to null interference. The number of available degrees of freedom for interference nulling using the UA is proved to be proportional to the minimum user-separation distance.

Includes members:
  Member "performance analysis and location optimization for massive mimo systems with circularly distributed antennas":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spectral efficiency analysis of cell free massive mimo systems with zero forcing detector")
  Member "a comparative study of downlink mimo cellular networks with co located and distributed base station antennas":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "group sparse precoding for cloud ran with multiple user antennas")
  Member "dealing with interference in distributed large scale mimo systems a statistical approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "covariance aided csi acquisition with non orthogonal pilots in massive mimo a large system performance analysis")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "on capacity of large scale mimo multiple access channels with distributed sets of correlated antennas":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non bayesian activity detection large scale fading coefficient estimation and unsourced random access with a massive mimo receiver")
  Member "a coordinated approach to channel estimation in large scale multiple antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the pilot contamination attack in multi cell multiuser massive mimo networks")
  Member "femtocell networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust resource allocation for pd noma based miso heterogeneous networks with comp technology")

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)