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: "analysis and augmented spatial processing for uplink ofdma mu mimo receiver with transceiver i q imbalance and external interference"
  Abstract: This paper addresses receiver (RX) signal processing in multiuser multiple-input multiple-output (MU-MIMO) systems. We focus on uplink orthogonal frequency-division multiple access (OFDMA)-based MU-MIMO communications under in-phase/quadrature (I/Q) imbalance in the associated radio frequency electronics. It is shown in the existing literature that transceiver I/Q imbalances cause cross-talk of mirror-subcarriers in OFDM systems. As opposed to typically reported single-user studies, we extend the studies to OFDMA-based MU-MIMO communications, with simultaneous user multiplexing in both frequency and spatial domains, and incorporate also external interference from multiple sources at RX input, for modeling challenging conditions in increasingly popular heterogeneous networks. In the signal processing developments, we exploit the augmented subcarrier processing, which processes each subcarrier jointly with its counterpart at the image subcarrier, and jointly across all RX antennas. Furthermore, we derive an optimal augmented linear RX in terms of minimizing the mean-squared error. The novel approach integrates the I/Q imbalance mitigation, external interference suppression, and data stream separation of multiple UEs into a single processing stage, thus avoiding separate transceiver calibration. Extensive analysis and numerical results show the signal-to-interference-plus-noise ratio (SINR) and symbol-error rate (SER) behavior of an arbitrary data stream after RX spatial processing as a function of different system and impairment parameters. Based on the results, the performance of the conventional per-subcarrier processing is heavily limited under transceiver I/Q imbalances, and is particularly sensitive to external interferers, whereas the proposed augmented subcarrier processing provides a high-performance signal processing solution being able to detect the signals of different users as well as suppress the external interference efficiently. Finally, we also extend the studies to massive MIMO framework, with very large antenna systems. It is shown that, despite the huge number of RX antennas, the conventional linear processing methods still suffer heavily from I/Q imbalances while the augmented approach does not have such limitations.

Connected through hyperedge HE-1 (induced by source paper "robust transmission for massive mimo downlink with imperfect csi"):
  with members:
    - "performance analysis of multi user massive mimo downlink under channel non reciprocity and imperfect csi"
    - "on optimizing feedback interval for temporally correlated mimo channels with transmit beamforming and finite rate feedback"
    - "free deterministic equivalents for the analysis of mimo multiple access channel"
    - "pilot reuse for massive mimo transmission over spatially correlated rayleigh fading channels"
    - "multi user linear precoding for multi polarized massive mimo system under imperfect csit"
    - "asymptotic rate analysis of downlink multi user systems with co located and distributed antennas"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "statistical eigenmode transmission over jointly correlated mimo channels"

Connected through hyperedge HE-2 (induced by source paper "widely linear precoding for large scale mimo with iqi algorithms and performance analysis"):
  with members:
    - "i q imbalance aware widely linear receiver for uplink multi cell massive mimo systems design and sum rate analysis"
    - "massive mimo for next generation wireless systems"
    - "generalized design of low complexity block diagonalization type precoding algorithms for multiuser mimo systems"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-3 (induced by source paper "i q imbalance aware widely linear receiver for uplink multi cell massive mimo systems design and sum rate analysis"):
  with members:
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "energy and spectral efficiency of very large multiuser mimo 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)