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 "interference alignment with partial csi feedback in mimo cellular networks"):
  Abstract: Interference alignment (IA) is a linear precoding strategy that can achieve optimal capacity scaling at high SNR in interference networks. However, most existing IA designs require full channel state information (CSI) at the transmitters, which could lead to significant CSI signaling overhead. There are two techniques, namely CSI quantization and CSI feedback filtering, that reduce CSI feedback overhead. In this paper, we consider IA processing with CSI feedback filtering in MIMO cellular networks. We introduce a novel metric, namely the feedback dimension, to quantify the first order CSI feedback cost associated with the CSI feedback filtering. The CSI feedback filtering poses several important challenges in IA processing. First, there is a hidden partial CSI knowledge constraint in IA precoder design, which cannot be handled using conventional IA design methodology. Furthermore, existing results on the feasibility conditions of IA cannot be applied due to the partial CSI knowledge. Finally, it is very challenging to find out how much CSI feedback is actually needed to support IA processing. We shall address the above challenges and propose a new IA feasibility condition under partial CSIT knowledge in MIMO cellular networks. Based on this, we consider the CSI feedback dimension minimization subject to the degrees of freedom requirements, and further propose an asymptotically optimal solution and derive closed-form trade-off results between the CSI feedback cost and IA performance in MIMO cellular networks.

Includes members:
  Member "the feasibility conditions for interference alignment in mimo networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "topological interference management with user admission control via riemannian optimization")
  Member "on the feasibility of linear interference alignment for mimo interference broadcast channels with constant coefficients":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "role of interference alignment in wireless cellular network optimization")
  Member "limited feedback design for interference alignment on mimo interference networks with heterogeneous path loss and spatial correlations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an overview on resource allocation techniques for multi user mimo systems")
  Member "on the degrees of freedom achievable through interference alignment in a mimo interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "centralized and decentralized cache aided interference management in heterogeneous parallel channels")
  Member "grassmannian differential limited feedback for interference alignment":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online learning models for content popularity prediction in wireless edge caching")
  Member "interference alignment with incomplete csit sharing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generalized degrees of freedom of the 2 user case miso broadcast channel with distributed csit")
  Member "interference alignment for partially connected mimo cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "interference alignment for multicell multiuser mimo uplink channels")
  Member "on feasibility of interference alignment in mimo interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint optimization of signal design and resource allocation in wireless d2d edge computing")

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)