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 "millimeter wave massive mimo systems relying on generalized sub array connected hybrid precoding"):
  Abstract: In this paper, we consider a generalized sub-array-connected (GSAC) architecture for arbitrary radio frequency (RF) chain and antenna configurations, where the number of RF chains connected to a sub-array and the number of antennas in each sub-array can be arbitrary. Our design objective is to improve the energy-efficiency of the hybrid precoder of millimeter-wave massive multiple input multiple output (MIMO) systems. We firstly propose a successive interference cancellation based hybrid precoding algorithm to maximize the achievable rate for any given RF chain and antenna configuration. This algorithm firstly decomposes the total achievable rate optimization problem into multiple sub-rate optimization problems, then it successively maximizes these sub-rates. Since the number of RF chains is limited, we can afford using an exhaustive search scheme to evaluate all configurations and identify the one having the best energy efficiency. Moreover, to rely on an attractive limited feedback, we also propose a beamsteering codebook for our hybrid precoding aided GSAC architecture. Our simulation results demonstrate that the proposed scheme achieves a similar rate as the corresponding optimal unconstrained precoder. Furthermore, we show that the energy-efficiency of the proposed scheme is better than that of the existing schemes in the fully-connected and sub-array-connected architectures.

Includes members:
  Member "spatial lobes division based low complexity hybrid precoding and diversity combining for mmwave iot systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient extended sub connected architecture for hybrid precoding in millimeter wave massive mimo systems")
  Member "non uniform quantization codebook based hybrid precoding to reduce feedback overhead in millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient extended sub connected architecture for hybrid precoding in millimeter wave massive mimo systems")
  Member "on the energy efficiency of mimo hybrid beamforming for millimeter wave systems with nonlinear power amplifiers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fully partially connected hybrid beamforming architectures for mmwave mu mimo")
  Member "stepwise transmit antenna selection in downlink massive multiuser mimo":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "robustness of low complexity massive mimo architectures against passive eavesdropping")
  Member "downlink precoding with mixed statistical and imperfect instantaneous csi for massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "spectral efficiency analysis of cell free massive mimo systems with zero forcing detector")
  Member "pilot power allocation through user grouping in multi cell massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spectral efficiency analysis of cell free massive mimo systems with zero forcing detector")
  Member "codebook based hybrid precoding for millimeter wave multiuser systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hybrid precoder design for cache enabled millimeter wave radio access networks")
  Member "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "beamforming design for large scale antenna arrays using deep 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)