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 "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling"):
  Abstract: We consider the downlink of a multicell system with multiantenna base stations and single-antenna user terminals, arbitrary base station cooperation clusters, distance-dependent propagation pathloss, and general “fairness” requirements. Base stations in the same cooperation cluster employ joint transmission with linear zero-forcing beamforming, subject to sum or per-base station power constraints. Intercluster interference is treated as noise at the user terminals. Analytic expressions for the system spectral efficiency are found in the large-system limit where both the numbers of users and antennas per base station tend to infinity with a given ratio. In particular, for the per-base station power constraint, we find new results in random matrix theory, yielding the squared Frobenius norm of submatrices of the Moore-Penrose pseudo-inverse for the structured non-i.i.d. channel matrix resulting from the cooperation cluster, user distribution, and path-loss coefficients. The analysis is extended to the case of nonideal Channel State Information at the Transmitters obtained through explicit downlink channel training and uplink feedback. Specifically, our results illuminate the trade-off between the benefit of a larger number of cooperating antennas and the cost of estimating higher-dimensional channel vectors. Furthermore, our analysis leads to a new simplified downlink scheduling scheme that preselects the users according to probabilities obtained from the large-system results, depending on the desired fairness criterion. The proposed scheme performs close to the optimal (finite-dimensional) opportunistic user selection while requiring significantly less channel state feedback, since only a small fraction of preselected users must feed back their channel state information.

Includes members:
  Member "multi cell mimo downlink with cell cooperation and fair scheduling a large system limit analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint user selection power allocation and precoding design with imperfect csit for multi cell mu mimo downlink systems")
  Member "multiuser miso transmitter optimization for intercell interference mitigation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the capacity and optimal signaling for gaussian mimo channels under interference constraints full version")
  Member "on the optimal number of cooperative base stations in network mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "achieving massive mimo spectral efficiency with a not so large number of antennas")
  Member "base station cooperation on the downlink large system analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "large scale beamforming for massive mimo via randomized sketching")
  Member "channel state feedback over the mimo mac":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multiuser mimo achievable rates with downlink training and channel state feedback")
  Member "cooperative multi cell block diagonalization with per base station power constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cooperative downlink interference transmission and cancellation for cellular connected uav a divide and conquer approach")
  Member "mimo downlink scheduling with non perfect channel state knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "dynamic resource allocation in co located and cell free massive mimo")
  Member "training and feedback optimization for multiuser mimo downlink":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "artificial noisy mimo systems under correlated scattering rayleigh fading a physical layer security approach")

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)