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: "mse optimal 1 bit precoding for multiuser mimo via branch and bound"
  Abstract: In this paper, we solve the sum mean-squared error (MSE)-optimal 1-bit quantized precoding problem exactly for small-to-moderate sized multiuser multiple-input multiple-output (MU-MIMO) systems via branch and bound. To this end, we reformulate the original NP-hard precoding problem as a tree search and deploy a number of strategies that improve the pruning efficiency without sacrificing optimality. We evaluate the error-rate performance and the complexity of the resulting 1-bit branch-and-bound (BB-1) precoder, and compare its efficacy to that of existing, suboptimal algorithms for 1-bit precoding in MU-MIMO systems.

Connected through hyperedge HE-1 (induced by source paper "optimal precoding for multiuser mimo systems with phase quantization and psk modulation via branch and bound"):
  with members:
    - "quantized constant envelope precoding with psk and qam signaling"
    - "branch and bound precoding for multiuser mimo systems with 1 bit quantization"
    - "minimum ber precoding in 1 bit massive mimo systems"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "per antenna constant envelope precoding for large multi user mimo systems"

Connected through hyperedge HE-2 (induced by source paper "a framework for one bit and constant envelope precoding over multiuser massive miso channels"):
  with members:
    - "one bit massive mimo precoding via a minimum symbol error probability design"
    - "minimum symbol error rate based constant envelope precoding for multiuser massive miso downlink"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "multiuser one bit massive mimo precoding under mpsk signaling"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "accelerated gradient descent escapes saddle points faster than gradient descent"
    - "nonlinear precoding for phase quantized constant envelope massive mu mimo ofdm"
    - "massive mimo downlink 1 bit precoding with linear programming for psk signaling"

Connected through hyperedge HE-3 (induced by source paper "linear precoding with low resolution dacs for massive mu mimo ofdm downlink"):
  with members:
    - "one bit massive mimo precoding via a minimum symbol error probability design"
    - "a framework for one bit and constant envelope precoding over multiuser massive miso channels"
    - "one bit precoding and constellation range design for massive mimo with qam signaling"
    - "can hardware distortion correlation be neglected when analyzing uplink se in massive mimo"
    - "out of band radiation from antenna arrays clarified"
    - "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"

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)