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: "from spectrum pooling to space pooling opportunistic interference alignment in mimo cognitive networks"
  Abstract: We describe a noncooperative interference alignment (IA) technique which allows an opportunistic multiple input multiple output (MIMO) link (secondary) to harmlessly coexist with another MIMO link (primary) in the same frequency band. Assuming perfect channel knowledge at the primary receiver and transmitter, capacity is achieved by transmiting along the spatial directions (SD) associated with the singular values of its channel matrix using a water-filling power allocation (PA) scheme. Often, power limitations lead the primary transmitter to leave some of its SD unused. Here, it is shown that the opportunistic link can transmit its own data if it is possible to align the interference produced on the primary link with such unused SDs. We provide both a processing scheme to perform IA and a PA scheme which maximizes the transmission rate of the opportunistic link. The asymptotes of the achievable transmission rates of the opportunistic link are obtained in the regime of large numbers of antennas. Using this result, it is demonstrated that depending on the signal-to-noise ratio and the number of transmit and receive antennas of the primary and opportunistic links, both systems can achieve transmission rates of the same order.

Connected through hyperedge HE-1 (induced by source paper "contextual bandit learning for machine type communications in the null space of multi antenna systems"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "sleeping multi armed bandit learning for fast uplink grant allocation in machine type communications"
    - "a directed information learning framework for event driven m2m traffic prediction"
    - "fast uplink grant for machine type communications challenges and opportunities"
    - "deep learning for signal authentication and security in massive internet of things systems"
    - "massive connectivity with massive mimo part ii achievable rate characterization"
    - "random access schemes in wireless systems with correlated user activity"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"

Connected through hyperedge HE-2 (induced by source paper "modulation and multiple access for 5g networks"):
  with members:
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "non orthogonal multiple access in large scale heterogeneous networks"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "wireless powered communications with non orthogonal multiple access"
    - "nonorthogonal multiple access in large scale underlay cognitive radio networks"
    - "design of massive mimo noma with limited feedback"
    - "optimal joint power and subcarrier allocation for mc noma systems"
    - "relay selection for cooperative noma"

Connected through hyperedge HE-3 (induced by source paper "opportunistic scheduling of machine type communications as underlay to cellular networks"):
  with members:
    - "a primer on 3gpp narrowband internet of things nb iot"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "fundamentals of throughput maximization with random arrivals for m2m communications"
    - "opportunistic interference alignment for mimo interfering multiple access channels"
    - "improving macrocell small cell coexistence through adaptive interference draining"
    - "opportunistic spatial orthogonalization and its application in fading cognitive radio networks"

Connected through hyperedge HE-4 (induced by source paper "cache enabled wireless networks with opportunistic interference alignment"):
  with members:
    - "caching at the wireless edge design aspects challenges and future directions"
    - "cache aided interference channels"
    - "distributed deep q learning"
    - "opportunistic interference alignment in mimo interference channels"

Connected through hyperedge HE-5 (induced by source paper "hybrid analog digital transceiver designs for cognitive large scale antenna array systems"):
  with members:
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "coverage and rate analysis for millimeter wave cellular networks"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "low complexity hybrid precoding in massive multiuser mimo systems"
    - "millimeter wave beamforming for wireless backhaul and access in small cell networks"
    - "an alternating direction algorithm for matrix completion with nonnegative factors"

Connected through hyperedge HE-6 (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-7 (induced by source paper "spatial sensing and cognitive radio communication in the presence of a k user interference primary network"):
  with members:
    - "on the degrees of freedom achievable through interference alignment in a mimo interference channel"
    - "cooperative algorithms for mimo interference channels"
    - "interference alignment with limited feedback"
    - "opportunistic interference alignment in mimo interference channels"
    - "eigenvalue based spectrum sensing algorithms for cognitive radio"

Connected through hyperedge HE-8 (induced by source paper "on the achievable dof and user scaling law of opportunistic interference alignment in 3 transmitter mimo interference channels"):
  with members:
    - "mimo interference alignment over correlated channels with imperfect csi"
    - "cooperative algorithms for mimo interference channels"
    - "sum rates rate allocation and user scheduling for multi user mimo vector perturbation precoding"
    - "interference alignment with analog channel state feedback"
    - "interference alignment under limited feedback for mimo interference channels"
    - "interference alignment with limited feedback"
    - "opportunistic spatial orthogonalization and its application in fading cognitive radio networks"
    - "degrees of freedom of the k user m times n mimo interference channel"

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)