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: "data detection in large multi antenna wireless systems via approximate semidefinite relaxation"
  Abstract: Practical data detectors for future wireless systems with hundreds of antennas at the base station must achieve high throughput and low error rate at low complexity. Since the complexity of maximum-likelihood (ML) data detection is prohibitive for such large wireless systems, approximate methods are necessary. In this paper, we propose a novel data detection algorithm referred to as Triangular Approximate SEmidefinite Relaxation (TASER), which is suitable for two application scenarios: (i) coherent data detection in large multi-user multiple-input multiple-output (MU-MIMO) wireless systems and (ii) joint channel estimation and data detection in large single-input multiple-output (SIMO) wireless systems. For both scenarios, we show that TASER achieves near-ML error-rate performance at low complexity by relaxing the associated ML-detection problems into a semidefinite program, which we solve approximately using a preconditioned forward-backward splitting procedure. Since the resulting problem is non-convex, we provide convergence guarantees for our algorithm. To demonstrate the efficacy of TASER in practice, we design a systolic architecture that enables our algorithm to achieve high throughput at low hardware complexity, and we develop reference field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) designs for various antenna configurations.

Connected through hyperedge HE-1 (induced by source paper "1 bit massive mu mimo precoding in vlsi"):
  with members:
    - "decentralized baseband processing for massive mu mimo systems"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "massive mu mimo ofdm downlink with one bit dacs and linear precoding"
    - "nonlinear 1 bit precoding for massive mu mimo with higher order modulation"
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "performance of the wideband massive uplink mimo with one bit adcs"
    - "high throughput data detection for massive mu mimo ofdm using coordinate descent"

Connected through hyperedge HE-2 (induced by source paper "vlsi design of a nonparametric equalizer for massive mu mimo"):
  with members:
    - "1 bit massive mu mimo precoding in vlsi"
    - "optimally tuned nonparametric linear equalization for massive mu mimo systems"
    - "on the performance of mismatched data detection in large mimo systems"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "massive mimo how many antennas do we need"

Connected through hyperedge HE-3 (induced by source paper "vlsi designs for joint channel estimation and data detection in large simo wireless systems"):
  with members:
    - "optimally tuned nonparametric linear equalization for massive mu mimo systems"
    - "efficient optimal joint channel estimation and data detection for massive mimo systems"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "joint channel estimation data detection in mimo fbmc oqam systems a tensor based approach"
    - "high throughput data detection for massive mu mimo ofdm using coordinate descent"
    - "optimal non coherent data detection for massive simo wireless systems with general constellations a polynomial complexity solution"
    - "fifty years of mimo detection the road to large scale mimos"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"

Connected through hyperedge HE-4 (induced by source paper "quantized precoding for massive mu mimo"):
  with members:
    - "1 bit massive mu mimo precoding in vlsi"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "massive mu mimo ofdm downlink with one bit dacs and linear precoding"
    - "nonlinear 1 bit precoding for massive mu mimo with higher order modulation"
    - "a remark on channels with transceiver distortion"
    - "no downlink pilots are needed in tdd massive mimo"

Connected through hyperedge HE-5 (induced by source paper "nonlinear 1 bit precoding for massive mu mimo with higher order modulation"):
  with members:
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "performance of the wideband massive uplink mimo with one bit adcs"
    - "quantized precoding for massive mu mimo"
    - "mmse precoder for massive mimo using 1 bit quantization"
    - "one bit massive mimo channel estimation and high order modulations"
    - "quantized massive mu mimo ofdm uplink"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"

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)