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 "performance analysis of directional modulation with finite quantized rf phase shifters in analog beamforming structure"):
  Abstract: The radio frequency (RF) phase shifter with finite quantization bits in analog beamforming (AB) structure forms quantization error (QE) and causes a performance loss of received signal to interference plus noise ratio (SINR) at the receiver (called Bob). By using the law of large numbers in probability theory, the closed-form expression of SINR performance loss is derived to be inversely proportional to the square of sinc (or sin(x)/x) function. Here, a phase alignment method is applied in directional modulation transmitter with AB structure. Also, the secrecy rate (SR) expression is derived with QE. From numerical simulation results, we find that the SINR performance loss gradually decreases as the number L of quantization bits increases. This loss is less than 0.3dB when L is larger than or equal to 3. As L exceeds 5, the SINR performance loss at Bob can be approximately trivial. Similarly, SR performance loss gradually reduces as L increases. In particular, the SR performance loss is about 0.1 bits/s/Hz for L=3 at signal-to-noise ratio of 15dB.

Includes members:
  Member "robust secure transmission of using main lobe integration based leakage beamforming in directional modulation mu mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient alternating iterative secure structure of maximizing secrecy rate for directional modulation networks")
  Member "artificial noise aided secure multicast precoding for directional modulation systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient alternating iterative secure structure of maximizing secrecy rate for directional modulation networks")
  Member "channel estimation and hybrid precoding for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "spatially sparse precoding in 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 "improving physical layer secrecy using full duplex jamming receivers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "state space adaptive nonlinear self interference cancellation for full duplex communication")
  Member "millimeter wave beamforming for wireless backhaul and access in small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning beam codebooks with neural networks towards environment aware mmwave mimo")
  Member "coding the beams improving beamforming training in mmwave communication system":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sub channel allocation for device to device underlaying full duplex mmwave small cells using coalition formation games")

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)