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 "outer bounds for the capacity region of a gaussian two way relay channel"):
  Abstract: We consider a three-node half-duplex Gaussian relay network where two nodes (say $a$, $b$) want to communicate with each other and the third node acts as a relay for this twoway communication. Outer bounds and achievable rate regions for the possible rate pairs $(R_a, R_b)$ for two-way communication are investigated. The modes (transmit or receive) of the halfduplex nodes together specify the state of the network. A relaying protocol uses a specific sequence of states and a coding scheme for each state. In this paper, we first obtain an outer bound for the rate region of all achievable $(R_a,R_b)$ based on the half-duplex cut-set bound. This outer bound can be numerically computed by solving a linear program. It is proved that at any point on the boundary of the outer bound only four of the six states of the network are used. We then compare it with achievable rate regions of various known protocols. We consider two kinds of protocols: (1) protocols in which all messages transmitted in a state are decoded with the received signal in the same state, and (2) protocols where information received in one state can also be stored and used as side information to decode messages in future states. Various conclusions are drawn on the importance of using all states, use of side information, and the choice of processing at the relay. Then, two analytical outer bounds (as opposed to an optimization problem formulation) are derived. Using an analytical outer bound, we obtain the symmetric capacity within 0.5 bits for some channel conditions where the direct link between nodes a and b is weak.

Includes members:
  Member "channel coding and decoding in a relay system operated with physical layer network coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning based constellation optimization for physical network coding in two way relay networks")
  Member "physical network coding in two way wireless relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation")

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)