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 in massive mimo based 5g networks opportunities and challenges"):
  Abstract: As we make progress towards the era of fifth generation (5G) communication networks, energy efficiency (EE) becomes an important design criterion because it guarantees sustainable evolution. In this regard, the massive multiple-input multiple-output (MIMO) technology, where the base stations (BSs) are equipped with a large number of antennas so as to achieve multiple orders of spectral and energy efficiency gains, will be a key technology enabler for 5G. In this article, we present a comprehensive discussion on state-of-the-art techniques which further enhance the EE gains offered by massive MIMO (MM). We begin with an overview of MM systems and discuss how realistic power consumption models can be developed for these systems. Thereby, we discuss and identify few shortcomings of some of the most prominent EE-maximization techniques present in the current literature. Then, we discuss "hybrid MM systems" operating in a 5G architecture, where MM operates in conjunction with other potential technology enablers, such as millimetre wave, heterogenous networks, and energy harvesting networks. Multiple opportunities and challenges arise in such a 5G architecture because these technologies benefit mutually from each other and their coexistence introduces several new constraints on the design of energy-efficient systems. Despite clear evidence that hybrid MM systems can achieve significantly higher EE gains than conventional MM systems, several open research problems continue to roadblock system designers from fully harnessing the EE gains offered by hybrid MM systems. Our discussions lead to the conclusion that hybrid MM systems offer a sustainable evolution towards 5G networks and are therefore an important research topic for future work.

Includes members:
  Member "massive mimo performance evaluation based on measured propagation data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "energy efficient antenna selection and power allocation for large scale multiple antenna systems with hybrid energy supply":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficient transmission of hybrid array with non ideal power amplifiers and circuitry")
  Member "massive mimo meets hetnet interference coordination through spatial blanking":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "non coherent detection and bit error rate for an ambient backscatter link in time selective fading")
  Member "optimal design of energy efficient multi user mimo systems is massive mimo the answer":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rate splitting multiple access for multi antenna downlink communication systems spectral and energy efficiency tradeoff")
  Member "massive mimo and small cells improving energy efficiency by optimal soft cell coordination":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a data aided channel estimation scheme for decoupled systems in heterogeneous networks")
  Member "hetnets and massive mimo modeling potential gains and performance analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "user centric interference nulling in downlink multi antenna heterogeneous networks")
  Member "energy efficient optimization for wireless information and power transfer in large scale mimo systems employing energy beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "transmission delay minimization in wireless powered communication systems")

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.NI(Networking and Internet Architecture)