human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "joint transmit and circuit power minimization in massive mimo with downlink sinr constraints when to turn on massive mimo"):
  with members:
    - "employing antenna selection to improve energy efficiency in massive mimo systems"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "massive mimo ten myths and one critical question"
    - "energy efficiency of massive mimo coping with daily load variation"
    - "massive mimo performance evaluation based on measured propagation data"
    - "impact of transceiver power consumption on the energy efficiency of zero forcing detector in massive mimo systems"
    - "what will 5g be"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"

Connected through hyperedge HE-2 (induced by source paper "discussions on signal uncertainty principle in shannon channel capacity equation and research on breaking shannon limit method"):
  with members:
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "a survey on low latency towards 5g ran core network and caching solutions"
    - "mixed adc massive mimo"
    - "index modulation techniques for 5g wireless networks"
    - "a survey of energy efficient techniques for 5g networks and challenges ahead"

Connected through hyperedge HE-3 (induced by source paper "mimo underlay cognitive radio optimized power allocation effective number of transmit antennas and harvest transmit tradeoff"):
  with members:
    - "rf based energy harvesting in decode and forward relaying systems ergodic and outage capacities"
    - "jointly optimal spatial channel assignment and power allocation for mimo swipt systems"
    - "optimal power allocation and active interference mitigation for spatial multiplexed mimo cognitive systems"
    - "simultaneous spectrum sensing and data reception for cognitive spatial multiplexing distributed systems"
    - "full duplex mimo small cell networks with interference cancellation"
    - "practical non linear energy harvesting model and resource allocation for swipt systems"
    - "full duplex wireless powered relay with self energy recycling"
    - "on green energy powered cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "energy efficiency of mmwave massive mimo precoding with low resolution dacs"):
  with members:
    - "hybrid analog digital precoding revisited under realistic rf modeling"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs"
    - "achievable rate and energy efficiency of hybrid and digital beamforming receivers with low resolution adc"
    - "quantized precoding for massive mu mimo"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "hybrid mimo architectures for millimeter wave communications phase shifters or switches"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-5 (induced by source paper "downlink user association and uplink scheduling for energy harvesting users in software defined mobile networks"):
  with members:
    - "user association in massive mimo hetnets"
    - "energy efficient precoding design for swipt in mimo two way relay networks"
    - "greendelivery proactive content caching and push with energy harvesting based small cells"
    - "software defined and virtualized future mobile and wireless networks a survey"

Connected through hyperedge HE-6 (induced by source paper "low dimensionality of noise free rss and its application in distributed massive mimo"):
  with members:
    - "cell free massive mimo versus small cells"
    - "fingerprinting based positioning in distributed massive mimo systems"
    - "gaussian processes for nonlinear signal processing an overview of recent advances"

Question: Please tell me which class the center node 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)