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 "optimal discrete spatial compression for beamspace massive mimo signals"):
  Abstract: Deploying a massive number of antennas at the base station side can boost the cellular system performance dramatically. This however involves significant additional radio-frequency (RF) front-end complexity, hardware cost, and power consumption. To address this issue, the beamspace-multiple-input-multiple-output (beamspace-MIMO)-based approach is considered as a promising solution. In this paper, we first show that the traditional beamspace-MIMO suffers from spatial power leakage and imperfect channel statistics estimation. A beam combination module is hence proposed, which consists of a small number (compared with the number of antenna elements) of low-resolution (possibly one-bit) digital (discrete) phase shifters after the beamspace transformation module to further compress the beamspace signal dimensionality, such that the number of RF chains can be reduced beyond beamspace transformation and beam selection. The optimum discrete beam combination weights for the uplink are obtained based on the branch-and-bound (BB) approach. The key to the BB-based solution is to solve the embodied subproblem, whose solution is derived in a closed-form. Thereby, a sequential greedy beam combination scheme with linear-complexity (w.r.t. the number of beams in the beamspace) is proposed. Link-level simulation results based on realistic channel models and long-term-evolution parameters are presented which show that the proposed schemes can reduce the number of RF chains by up to   $\text{25}\%$   with a one-bit digital phase-shifter-network.

Includes members:
  Member "a real time millimeter wave phased array mimo channel sounder":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "enable super resolution parameter estimation for mm wave channel sounding")
  Member "branch and bound precoding for multiuser mimo systems with 1 bit quantization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "study of coarse quantization aware block diagonalization algorithms for mimo systems with low resolution")
  Member "spatio temporal waveform design for multiuser massive mimo downlink with 1 bit receivers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "an overview of signal processing techniques for millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "spatial lobes division based low complexity hybrid precoding and diversity combining for mmwave iot systems")
  Member "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "integer forcing architectures for uplink cloud radio access networks")
  Member "quantized precoding for massive mu mimo":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "hybrid beamforming for massive mimo a survey":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "amplitude and phase estimation for absolute calibration of massive mimo front ends")

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)