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 based modulation for noncoherent massive simo systems"):
  Abstract: An uplink system with a single antenna transmitter and a single receiver with a large number of antennas is considered. We propose an energy-detection-based single-shot noncoherent communication scheme which does not use the instantaneous channel state information (CSI), but rather only the knowledge of the channel statistics. The suggested system uses a transmitter that modulates information on the power of the symbols, and a receiver which measures only the average energy across the antennas. We propose constellation designs which are asymptotically optimal with respect to symbol error rate (SER) with an increasing number of antennas, for any finite signal to noise ratio (SNR) at the receiver, under different assumptions on the availability of CSI statistics (exact channel fading distribution or the first few moments of the channel fading distribution). We also consider the case of imperfect knowledge of the channel statistics and describe in detail the case when there is a bounded uncertainty on the moments of the fading distribution. We present numerical results on the SER performance achieved by these designs in typical scenarios and find that they may outperform existing noncoherent constellations, e.g., conventional Amplitude Shift Keying (ASK), and pilot-based schemes, e.g., Pulse Amplitude Modulation (PAM). We also observe that an optimized constellation for a specific channel distribution makes it very sensitive to uncertainties in the channel statistics. In particular, constellation designs based on optimistic channel conditions could lead to significant performance degradation in terms of the achieved symbol error rates.

Includes members:
  Member "an overview of signal processing techniques for millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "channel estimation in massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "super resolution blind channel and signal estimation for massive mimo with one dimensional antenna array")
  Member "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis of quantized uplink massive mimo ofdm with oversampling under adjacent channel interference")
  Member "massive mimo performance evaluation based on measured propagation data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "massive mimo asymptotics for ray based propagation channels")
  Member "channel estimation and hybrid precoding for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits":
    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 "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")

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)