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 "genie tree and degrees of freedom of the symmetric mimo interfering broadcast channel"):
  Abstract: In this paper, we study the information theoretic maximal degrees of freedom (DoF) for the symmetric multi-input-multi-output (MIMO) interfering broadcast channel (IBC) with arbitrary antenna configurations. For the G-cell K-user MXN MIMO-IBC network, we find that the information theoretic maximal DoF per user are related to three DoF bounds: 1) the decomposition DoF bound d^{Decom}=MN/(M+KN), a lower-bound of linear interference alignment (IA) with infinite time/frequency extensions (called asymptotic IA); 2) the proper DoF bound d^{Proper}=(M+N)/(GK+1), an upper-bound of linear IA without time/frequency extensions (called linear IA); and 3) the quantity DoF bound d^{Quan}, a zigzag piecewise linear function of M and N. The whole region of M/N can be divided into two regions, Region I and Region II. Specifically, for most configurations in Region I, the information theoretic maximal DoF are the decomposition DoF bound and can be achieved by the asymptotic IA. For all configurations in Region II, the information theoretic maximal DoF are the quantity DoF bound and can be achieved by the linear IA. To obtain the tight upper-bound, we propose a unified way to construct genies, where the genies help each base station or user resolve the maximal number of interference. According to the feature that the designed genies with the same dimension can derive identical DoF upper-bound, we convert the information theoretic DoF upper-bound problem into a linear algebra problem and obtain the closed-form DoF upper-bound expression. Moreover, we develop a non-iterative linear IA transceiver to achieve the DoF upper-bound for the networks with antenna configurations in Region II, which means that the derived DoF upper-bound is tightest. The basic principles to derive the DoF upper-bound and design the linear IA transceiver to achieve the DoF upper-bound can be extended into general asymmetric networks.

Includes members:
  Member "genie chains exploring outer bounds on the degrees of freedom of mimo interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "achievable dof delay trade offs for the k user mimo interference channel with delayed csit")
  Member "feasibility of interference alignment for the mimo interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the interference channel revisited aligning interference by adjusting receive antenna separation")
  Member "the feasibility conditions for interference alignment in mimo networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "topological interference management with user admission control via riemannian optimization")
  Member "alternating rate profile optimization in single stream mimo interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multiuser wirelessly powered backscatter communications nonlinearity waveform design and sinr energy tradeoff")
  Member "on the feasibility of linear interference alignment for mimo interference broadcast channels with constant coefficients":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "role of interference alignment in wireless cellular network optimization")
  Member "degrees of freedom of mimo cellular networks decomposition and linear beamforming design":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relay aided mimo cellular networks using opposite directional interference alignment")
  Member "on the degrees of freedom achievable through interference alignment in a mimo interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "centralized and decentralized cache aided interference management in heterogeneous parallel channels")
  Member "a feasibility test for linear interference alignment in mimo channels with constant coefficients":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "role of interference alignment in wireless cellular network optimization")

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)