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: "performance analysis for massive mimo downlink with low complexity approximate zero forcing precoding"
  Abstract: Zero-forcing (ZF) precoding plays an important role for massive MIMO downlink due to its near optimal performance. However, the high computation cost of the involved matrix inversion hinders its application. In this paper, we adopt the first order Neumann series (NS) for a low-complexity approximation. By introducing a relaxation parameter jointly with one selected user's interference to others into the precondition matrix, we propose the identity-plus-column NS (ICNS) method. By further exploiting the multi-user diversity gain via choosing the user with the largest interference to others, the ordered ICNS method is also proposed. Moreover, the sum-rate approximations of the proposed ICNS method and the competitive existing identity matrix based NS (INS) method are derived in closed-form, based on which the performance loss of ICNS due to inversion approximation compared with ideal ZF and its performance gain over INS are explicitly analyzed for three typical massive MIMO scenarios. Finally, simulations verify our analytical results and also show that the proposed two designs achieve better performance-complexity tradeoff than ideal ZF and existing low-complexity ZF precodings for practical large antenna number, correlated channels and not-so-small loading factor.

Connected through hyperedge HE-1 (induced by source paper "spectral efficiency analysis of cell free massive mimo systems with zero forcing detector"):
  with members:
    - "downlink precoding with mixed statistical and imperfect instantaneous csi for massive mimo systems"
    - "enhanced max min sinr for uplink cell free massive mimo systems"
    - "on the total energy efficiency of cell free massive mimo"
    - "pilot power allocation through user grouping in multi cell massive mimo systems"
    - "energy efficient downlink transmission for multicell massive das with pilot contamination"
    - "energy efficiency in cell free massive mimo with zero forcing precoding design"
    - "cell free massive mimo versus small cells"
    - "how much do downlink pilots improve cell free massive mimo"

Connected through hyperedge HE-2 (induced by source paper "average sep optimal precoding for correlated massive mimo with zf detection an asymptotic analysis"):
  with members:
    - "large scale fading decoding in cellular massive mimo systems with spatially correlated channels"
    - "massive mimo has unlimited capacity"
    - "joint pilot design and uplink power allocation in multi cell massive mimo systems"
    - "the world s first real time testbed for massive mimo design implementation and validation"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "pilot beam pattern design for channel estimation in massive mimo systems"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "massive mimo for next generation wireless systems"

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)