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: "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
  Abstract: Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.

Connected through hyperedge HE-1 (induced by source paper "rate splitting multiple access for multi antenna downlink communication systems spectral and energy efficiency tradeoff"):
  with members:
    - "cooperative rate splitting for miso broadcast channel with user relaying"
    - "cooperative rate splitting for miso broadcast channel with user relaying and performance benefits over cooperative noma"
    - "rate splitting unifying sdma oma noma and multicasting in miso broadcast channel a simple two user rate analysis"
    - "interference mitigation via rate splitting and common message decoding in cloud radio access networks"
    - "energy efficiency fairness for multi pair wireless powered relaying systems"
    - "rate splitting multiple access for coordinated multi point joint transmission"
    - "rate splitting multiple access for downlink communication systems bridging generalizing and outperforming sdma and noma"
    - "rate splitting for multi antenna non orthogonal unicast and multicast transmission spectral and energy efficiency analysis"

Connected through hyperedge HE-2 (induced by source paper "localization efficiency in massive mimo systems"):
  with members:
    - "localization in ultra narrow band iot networks design guidelines and tradeoffs"
    - "massive mimo based localization and mapping exploiting phase information of multipath components"
    - "employing antenna selection to improve energy efficiency in massive mimo systems"
    - "tracking of wideband multipath components in a vehicular communication scenario"
    - "massive mimo in real propagation environments do all antennas contribute equally"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "fundamental limits of wideband localization part i a general framework"

Connected through hyperedge HE-3 (induced by source paper "multiple antenna technologies for beyond 5g"):
  with members:
    - "intelligent reflecting surface versus decode and forward how large surfaces are needed to beat relaying"
    - "robust trajectory and resource allocation design for secure uav aided communications"
    - "a new look at cell free massive mimo making it practical with dynamic cooperation"
    - "scalability aspects of cell free massive mimo"
    - "cascaded channel estimation for large intelligent metasurface assisted massive mimo"
    - "robust and secure wireless communications via intelligent reflecting surfaces"
    - "channel estimation for intelligent reflecting surface assisted multiuser communications framework algorithms and analysis"
    - "resource allocation for secure irs assisted multiuser miso systems"

Connected through hyperedge HE-4 (induced by source paper "edge computing enabled cell free massive mimo systems"):
  with members:
    - "mobile edge computing enabled heterogeneous networks"
    - "fog massive mimo a user centric seamless hot spot architecture"
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "a survey on mobile edge computing the communication perspective"
    - "channel hardening and favorable propagation in cell free massive mimo with stochastic geometry"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "collaborative mobile edge computing in 5g networks new paradigms scenarios and challenges"
    - "power delay tradeoff in multi user mobile edge computing systems"

Connected through hyperedge HE-5 (induced by source paper "neural networks in hybrid precoding for millimeter wave massive mimo systems"):
  with members:
    - "deep learning based channel estimation for beamspace mmwave massive mimo systems"
    - "energy efficiency of mmwave massive mimo precoding with low resolution dacs"
    - "an introduction to deep learning for the physical layer"
    - "energy efficiency challenges of 5g small cell networks"
    - "energy efficiency optimization of 5g radio frequency chain systems"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-6 (induced by source paper "massive mimo forward link analysis for cellular networks"):
  with members:
    - "massive mimo has unlimited capacity"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "the meta distribution of the sir for cellular networks with power control"
    - "ergodic spectral efficiency in mimo cellular networks"
    - "downlink performance of superimposed pilots in massive mimo systems"
    - "wireless network signals with moderately correlated shadowing still appear poisson"
    - "no downlink pilots are needed in tdd massive mimo"
    - "analyzing uplink sinr and rate in massive mimo systems using stochastic geometry"

Connected through hyperedge HE-7 (induced by source paper "balance queueing and retransmission latency optimal massive mimo design"):
  with members:
    - "delay performance of the multiuser miso downlink under imperfect csi and finite length coding"
    - "outage of periodic downlink wireless networks with hard deadlines"
    - "massive mimo has unlimited capacity"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "delay performance of miso wireless communications"
    - "massive mimo ten myths and one critical question"
    - "massive mimo performance evaluation based on measured propagation data"
    - "on noisy arq in block fading channels"

Connected through hyperedge HE-8 (induced by source paper "double sparsity learning based channel and signal estimation in massive mimo with generalized spatial modulation"):
  with members:
    - "bilinear recovery using adaptive vector amp"
    - "super resolution blind channel and signal estimation for massive mimo with arbitrary array geometry"
    - "complete dictionary recovery over the sphere i overview and the geometric picture"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "parametric bilinear generalized approximate message passing"
    - "generalized spatial modulation in large scale multiuser mimo systems"
    - "bilinear generalized approximate message passing part i derivation"
    - "scaling up mimo opportunities and challenges with very large arrays"

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.IT(Information Theory)