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 "max min sinr in large scale single cell mu mimo asymptotic analysis and low complexity transceivers"):
  Abstract: This work focuses on the downlink and uplink of large-scale single-cell multiuser multiple-input multiple-output systems in which the base station (BS) endowed with M antennas communicates with K single-antenna user equipments (TIEs). Particularly, we aim at reducing the complexity of the linear precoder and receiver that maximize the minimum signal-to-interference-plus-noise ratio (SINR) subject to a given power constraint. To this end, we consider the asymptotic regime in which M and K grow large with a given ratio. Tools from random matrix theory (RMT) are then used to compute, in closed form, accurate approximations for the parameters of the optimal precoder and receiver, when imperfect channel state information (modeled by the generic Gauss- Markov formulation form) is available at the BS. The asymptotic analysis allows us to derive the asymptotically optimal linear precoder and receiver that are characterized by a lower complexity (due to the dependence on the large scale components of the channel) and, possibly, by a better resilience to imperfect channel state information. However, the implementation of both is still challenging as it requires fast inversions of large matrices in every coherence period. To overcome this issue, we apply the truncated polynomial expansion (TPE) technique to the precoding and receiving vector of each TIE and make use of RMT to determine the optimal weighting coefficients on a per-TIE basis that asymptotically solve the max-min SINR problem. Numerical results are used to validate the asymptotic analysis in the finite system regime and to show that the proposed TPE transceivers efficiently mimic the optimal ones, while requiring much lower computational complexity.

Includes members:
  Member "large system analysis of the energy consumption distribution in multi user mimo systems with mobility":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "large system analysis of power normalization techniques in massive mimo")
  Member "large system analysis of base station cooperation for power minimization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rate splitting for multi antenna downlink precoder design and practical implementation")
  Member "optimal multiuser transmit beamforming a difficult problem with a simple solution structure":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "massive mimo has unlimited capacity")
  Member "linear precoding based on polynomial expansion large scale multi cell mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "asymptotic analysis of rzf over double scattering channels with mmse estimation")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "joint beamforming and power control in coordinated multicell max min duality effective network and large system transition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "covariance aided csi acquisition with non orthogonal pilots in massive mimo a large system performance analysis")

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)