human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the degrees of freedom for opportunistic interference alignment with 1 bit feedback the 3 cell case"):
  Abstract: Opportunistic interference alignment (OIA) exploits channel randomness and multiuser diversity by user selection. For OIA the transmitter needs channel state information (CSI), which is usually measured on the receiver side and sent to the transmitter side via a feedback channel. Lee and Choi show that $d$ degrees of freedom (DoF) per transmitter are achievable in a 3-cell MIMO interference channel assuming perfect real-valued feedback. However, the feedback of a real-valued variable still requires infinite rate. In this paper, we investigate 1-bit quantization for opportunistic interference alignment (OIA) in 3-cell interference channels. We prove that 1-bit feedback is sufficient to achieve the optimal DoF $d$ in 3-cell MIMO interference channels if the number of users per cell is scaled as ${\rm SNR}^{d^2}$. Importantly, the required number of users for OIA with 1-bit feedback remains the same as with real-valued feedback. For a given system configuration, we provide an optimal choice of the 1-bit quantizer, which captures most of the capacity provided by a system with real-valued feedback. Using our new 1-bit feedback scheme for OIA, we compare OIA with IA and show that OIA has a much lower complexity and provides a better rate in the practical operation region of a cellular communication system.

Includes members:
  Member "on the achievable dof and user scaling law of opportunistic interference alignment in 3 transmitter mimo interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "opportunistic downlink interference alignment for multi cell mimo networks")
  Member "opportunistic interference alignment for mimo interfering multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi stream opportunistic network decoupling relay selection and interference management")
  Member "multiuser diversity in interfering broadcast channels achievable degrees of freedom and user scaling law":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "opportunistic downlink interference alignment for multi cell mimo networks")
  Member "interference alignment with quantized grassmannian feedback in the k user constant mimo interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on channel state feedback model and overhead in theoretical and practical views")
  Member "opportunistic interference mitigation achieves optimal degrees of freedom in wireless multi cell uplink networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "opportunistic downlink interference alignment for multi cell mimo networks")
  Member "interference alignment with analog channel state feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the feasibility of interference alignment in compounded mimo broadcast channels with antenna correlation and mixed user classes")
  Member "quantization bounds on grassmann manifolds and applications to mimo communications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "high dimensional stochastic gradient quantization for communication efficient edge learning")

Question: Please tell me which class the source paper 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)