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: "the equivalence of semidefinite relaxation mimo detectors for higher order qam"
  Abstract: In multi-input multi-output (MIMO) detection, semidefinite relaxation (SDR) has been shown to be an efficient high-performance approach. For BPSK and QPSK, it has been found that SDR can provide near-optimal bit error probability performance. This has stimulated a number of recent research endeavors that aim to apply SDR to the high-order QAM cases. These independently developed SDRs are different in concept, structure and complexity, and presently no serious analysis has been given to compare these methods. This paper analyzes the relationship of three such SDR methods, namely the polynomial-inspired SDR (PI-SDR) by Wiesel , the bound-constrained SDR (BC-SDR) by Sidiropoulos and Luo, and the virtually-antipodal SDR (VA-SDR) by Mao Rather unexpectedly, we prove that the three SDRs are equivalent in the following sense: The three SDRs yield the same optimal objective values, and their optimal solutions have strong correspondences. Specifically, we establish this solution equivalence between BC-SDR and VA-SDR for any 4q -QAM constellations, and that between BC-SDR and PI-SDR for 16-QAM and 64-QAM. Moreover, the equivalence result holds for any channel, problem size, and signal-to-noise ratio. Our theoretical findings are confirmed by simulations, where the three SDRs offer identical symbol error probabilities. Additional simulation results are also provided to demonstrate the effectiveness of SDR compared to some other MIMO detectors, in terms of complexity and symbol error performance.

Connected through hyperedge HE-1 (induced by source paper "on the equivalence of semidifinite relaxations for mimo detection with general constellations"):
  with members:
    - "optimal estimation of sensor biases for asynchronous multi sensor data fusion"
    - "fifty years of mimo detection the road to large scale mimos"
    - "the diversity order of the semidefinite relaxation detector"
    - "a near maximum likelihood decoding algorithm for mimo systems based on semi definite programming"

Connected through hyperedge HE-2 (induced by source paper "joint turbo receiver for ldpc coded mimo systems based on semi definite relaxation"):
  with members:
    - "phase noise compensation using limited reference symbols in 3gpp lte downlink"

Connected through hyperedge HE-3 (induced by source paper "data detection in large multi antenna wireless systems via approximate semidefinite relaxation"):
  with members:
    - "optimality of large mimo detection via approximate message passing"
    - "optimal non coherent data detection for massive simo wireless systems with general constellations a polynomial complexity solution"
    - "a low complexity gaussian message passing iterative detector for massive mu mimo systems"
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "conjugate gradient based soft output detection and precoding in massive mimo systems"
    - "a field guide to forward backward splitting with a fasta implementation"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"

Connected through hyperedge HE-4 (induced by source paper "fifty years of mimo detection the road to large scale mimos"):
  with members:
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "an esprit based approach for 2 d localization of incoherently distributed sources in massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "approximate bayesian probabilistic data association aided iterative detection for mimo systems using arbitrary m ary modulation"
    - "channel hardening exploiting message passing chemp receiver in large scale mimo systems"
    - "five disruptive technology directions for 5g"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-5 (induced by source paper "mimo detection for high order qam based on a gaussian tree approximation"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "gaussian belief propagation based multiuser detection"
    - "improved message passing for inference in densely connected systems"
    - "belief propagation based multi user detection"

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)