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: "iterative detection of turbo coded offset qpsk in the presence of frequency and clock offsets and awgn"
  Abstract: The key contribution of this paper is to develop transmitter and receiver algorithms in discrete-time for turbo-coded offset QPSK signals. The procedure for simulating a clock offset between the transmitter and receiver is described. Due to the use of up-sampling, matched filtering and a differential correlation approach at the receiver, the time required for detecting the start of frame (SoF) is just around 500 symbols, which is also the length of the preamble. The initial estimate of the SoF and the frequency offset, obtained using the differential correlation approach, is improved using an iterative process. A novel two-step maximum likelihood (ML) frequency offset estimation is proposed, which significantly reduces the complexity over the conventional ML estimation. The decision-directed carrier and timing recovery algorithms use simple first-order IIR filters to track the carrier phase and clock slip. The proposed synchronization and detection techniques perform effectively at an SNR per bit close to 1.5 dB, in the presence of a frequency offset as large as 30% of the symbol-rate and a clock offset of 25 ppm (parts per million). It is shown via simulations that the performance loss with respect to the bare turbo code is only about 0.5 dB, for a preamble length of 500 and a BER of 10−7. The proposed techniques are well suited for software implementation.

Connected through hyperedge HE-1 (induced by source paper "data detection in single user massive mimo using re transmissions"):
  with members:
    - "near capacity signaling over fading channels using coherent turbo coded ofdm and massive mimo"
    - "doubly massive mmwave mimo systems using very large antenna arrays at both transmitter and receiver"
    - "a multiband ofdma heterogeneous network for millimeter wave 5g wireless applications"
    - "coherent detection of turbo coded ofdm signals transmitted through frequency selective rayleigh fading channels with receiver diversity and increased throughput"
    - "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"

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)