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 "low complexity hybrid precoding and diversity combining based on spatial lobes division for millimeter wave mimo systems"):
  Abstract: In this paper, we focus on the design of low complexity hybrid analog/digital precoding and diversity combining in the millimeter wave multiple-input multiple-output (MIMO) systems. Firstly, by exploiting the sparseness property of the millimeter wave in the angular domain, we propose a spatial lobes division (SLD) to group the total paths of the millimeter wave channel into several spatial lobes, where the paths in each spatial lobe form a low-rank sub-channel matrix. Secondly, based on the SLD operation, we propose a low complexity hybrid precoding scheme, named HYP-SLD. Specifically, for each low-rank sub-channel matrix, we formulate the hybrid precoding design as a sparse reconstruction problem, and decouple the design of the analog and digital precoding matrices to obtain the near-optimal solution. Simulation results demonstrate that, the proposed HYP-SLD scheme reduces by 99% the complexity of the classic orthogonal matching pursuit (OMP) scheme, and achieves similar spectral efficiency and bit error rate (BER) performances compared with the fully digital precoding scheme. Finally, we further propose a maximum ratio combining (MRC) based diversity combining scheme, named HYP-SLD-MRC, to improve the BER performance. Simulation results also show that, the BER performance of the proposed HYP-SLD-MRC scheme outperforms the fully digital precoding scheme.

Includes members:
  Member "an overview of signal processing techniques for millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "cost effective millimeter wave communications with lens antenna array":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatial lobes division based low complexity hybrid precoding and diversity combining for mmwave iot systems")
  Member "dynamic subarrays for hybrid precoding in wideband mmwave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gmd based hybrid beamforming for large reconfigurable intelligent surface assisted millimeter wave massive mimo")
  Member "millimeter wave mimo with lens antenna array a new path division multiplexing paradigm":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multiple antenna technologies for beyond 5g")
  Member "channel estimation and hybrid precoding for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "millimeter wave cellular wireless networks potentials and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "spatially sparse precoding in millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")

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)