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 "pilot distribution optimization and power control in multi cellular large scale mimo systems"):
  Abstract: Massive MIMO communication systems have been identified as one of the most prominent technologies of the next generation wireless standards, such as 5G, due to the large gains in energy and spectral efficiency that can be achieved. In the asymptotic condition of infinite number of antennas at the base station (BS), the performance bottleneck of these systems is due to the pilot contamination effect, i.e., the directional interference arising from users in adjacent cells that reuse the same set of orthogonal training sequences, and thus the interference seen by each user is determined by the pilot sequence assigned to him. We show in this paper that the system performance can be improved by appropriately assigning the pilot sequences to the users, in the so-called pilot allocation scheme. Depending on the optimization metric adopted, it is more advantageous to a user with certain long- term fading coefficient be assigned to a specific pilot sequence, whose interference can be completely estimated in advance by the BS by only knowing the long term fading coefficients of users in adjacent cells. Besides, if the objective is to maximize the number of users with a target quality of service, we have shown that the pilot allocation schemes can be combined with power control algorithms, resulting in much more improvements for the system. For unitary frequency reuse factor, we have found that the data throughput provided for 95% of the users increases when applying power control algorithm from 134kbps to 1.461Mbps with no pilot allocation, while this performance gain provided by power control changes from 793kbps to 6.743Mbps when pilot allocation is employed. If the reuse factor increases to 3, a 95%-likely data throughput of 17.310Mbps can be assured when pilot allocation and power control are suitably combined.

Includes members:
  Member "power allocation schemes for multicell massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the pilot contamination attack in multi cell multiuser massive mimo networks")
  Member "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "high dimensional stochastic gradient quantization for communication efficient edge learning")
  Member "five disruptive technology directions for 5g":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning enabled optimization of downlink beamforming under per antenna power constraints algorithms and experimental demonstration")
  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 "signal processing in large systems a new paradigm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "enhanced group sparse beamforming for green cloud ran a random matrix approach")
  Member "energy and spectral efficiency of very large multiuser mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")

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)