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 "energy efficiency optimization in hardware constrained large scale mimo systems"):
  Abstract: Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.

Includes members:
  Member "impact of residual transmit rf impairments on training based mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "massive mu mimo ofdm uplink with hardware impairments modeling and analysis")
  Member "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the pilot contamination attack in multi cell multiuser massive mimo networks")
  Member "on the mimo capacity with residual transceiver hardware impairments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "toward a realistic assessment of multiple antenna hcns residual additive transceiver hardware impairments and channel aging")
  Member "optimal design of energy efficient multi user mimo systems is massive mimo the answer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "rate splitting multiple access for multi antenna downlink communication systems spectral and energy efficiency tradeoff")
  Member "capacity limits and multiplexing gains of mimo channels with transceiver impairments":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "nuts and bolts of a realistic stochastic geometric analysis of mmwave hetnets hardware impairments and channel aging")
  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")
  Member "mimo transmission with residual transmit rf impairments":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "nuts and bolts of a realistic stochastic geometric analysis of mmwave hetnets hardware impairments and channel aging")

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)