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: "on the role of transmit correlation diversity in multiuser mimo systems"
  Abstract: Correlation across transmit antennas in multiple-input multiple-output (MIMO) systems has been studied in various scenarios and has been shown to be detrimental or provide benefits depending on the particular system and underlying assumptions. In this paper, we investigate the effect of transmit correlation on the capacity of the Gaussian MIMO broadcast channel, with a particular interest in the large-scale array (or massive MIMO) regime. To this end, we introduce a new type of diversity, referred to as  transmit correlation diversity , which captures the fact that the channel vectors of different users may have different channel covariance matrices spanning often nearly mutually orthogonal subspaces. In particular, when taking the cost of downlink training properly into account, transmit correlation diversity can yield significant capacity gains in all regimes of interest. Our analysis shows that the system multiplexing gain can be increased by a factor up to    $\lfloor {M}/{r}\rfloor $   , where    $M$    is the number of antennas and    $r\le M$    is the common rank of the users channel covariance matrices, with respect to standard schemes that are agnostic of the transmit correlation diversity and treat the channels as if they were isotropically distributed. Thus, this new form of diversity reveals itself as a valuable “new resource” in multiuser communications.

Connected through hyperedge HE-1 (induced by source paper "capacity scaling of massive mimo in strong spatial correlation regimes"):
  with members:
    - "massive mimo has unlimited capacity"
    - "massive mimo pilot decontamination and channel interpolation via wideband sparse channel estimation"
    - "on the miso channel with feedback can infinitely massive antennas achieve infinite capacity"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "robust pilot decontamination based on joint angle and power domain discrimination"
    - "hybrid beamforming for massive mimo a survey"
    - "on the high snr capacity of the gaussian interference channel and new capacity bounds"
    - "massive mimo performance evaluation based on measured propagation data"

Connected through hyperedge HE-2 (induced by source paper "uplink analysis of large mu mimo systems with space constrained arrays in ricean fading"):
  with members:
    - "multi user massive mimo communication systems based on irregular antenna arrays"
    - "on the spectral efficiency of space constrained massive mimo with linear receivers"
    - "space constrained massive mimo hitting the wall of favorable propagation"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "massive mimo for next generation wireless systems"
    - "millimeter wave channel modeling and cellular capacity evaluation"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "performance analysis of macrodiversity mimo systems with mmse and zf receivers in flat rayleigh fading"

Connected through hyperedge HE-3 (induced by source paper "on the ergodic rate lower bounds with applications to massive mimo"):
  with members:
    - "channel hardening and favorable propagation in cell free massive mimo with stochastic geometry"
    - "low rank covariance assisted downlink training and channel estimation for fdd massive mimo systems"
    - "no downlink pilots are needed in tdd massive mimo"
    - "cell free massive mimo uniformly great service for everyone"
    - "achieving large multiplexing gain in distributed antenna systems via cooperation with pcell technology"
    - "massive mimo for next generation wireless systems"
    - "massive mu mimo downlink tdd systems with linear precoding and downlink pilots"
    - "joint spatial division and multiplexing for mm wave channels"

Connected through hyperedge HE-4 (induced by source paper "impact of line of sight and unequal spatial correlation on uplink mu mimo systems"):
  with members:
    - "on the spectral efficiency of space constrained massive mimo with linear receivers"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "achievable rates of fdd massive mimo systems with spatial channel correlation"
    - "millimeter wave channel modeling and cellular capacity evaluation"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-5 (induced by source paper "a new approach to user scheduling in massive multi user mimo broadcast channels"):
  with members:
    - "an overview on resource allocation techniques for multi user mimo systems"
    - "two stage beamformer design for massive mimo downlink by trace quotient formulation"
    - "pilot beam pattern design for channel estimation in massive mimo systems"
    - "two tier precoding for fdd multi cell massive mimo time varying interference networks"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "random beamforming with heterogeneous users and selective feedback individual sum rate and individual scaling laws"
    - "joint spatial division and multiplexing opportunistic beamforming and user grouping"

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)