human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "cross layer optimization of two way relaying for statistical qos guarantees"
  Abstract: Two-way relaying promises considerable improvements on spectral efficiency in wireless relay networks. While most existing works focus on physical layer approaches to exploit its capacity gain, the benefits of two-way relaying on upper layers are much less investigated. In this paper, we study the cross-layer design and optimization for delay quality-of-service (QoS) provisioning in two-way relay systems. Our goal is to find the optimal transmission policy to maximize the weighted sum throughput of the two users in the physical layer while guaranteeing the individual statistical delay-QoS requirement for each user in the datalink layer. This statistical delay-QoS requirement is characterized by the QoS exponent. By integrating the concept of effective capacity, the cross-layer optimization problem is equivalent to a weighted sum effective capacity maximization problem. We derive the jointly optimal power and rate adaptation policies for both three-phase and two-phase two-way relay protocols. Numerical results show that the proposed adaptive transmission policies can efficiently provide QoS guarantees and improve the performance. In addition, the throughput gain obtained by the considered three-phase and two-phase protocols over direct transmission is significant when the delay-QoS requirements are loose, but the gain diminishes at tight delay requirements. It is also found that, in the two-phase protocol, the relay node should be placed closer to the source with more stringent delay requirement.

Connected through hyperedge HE-1 (induced by source paper "qos aware transmission policies for ofdm bidirectional decode and forward relaying"):
  with members:
    - "a tutorial on the optimization of amplify and forward mimo relay systems"
    - "optimization framework and graph based approach for relay assisted bidirectional ofdma cellular networks"
    - "physical network coding in two way wireless relay channels"
    - "physical layer network coding"

Connected through hyperedge HE-2 (induced by source paper "spectrum leasing and cooperative resource allocation in cognitive ofdma networks"):
  with members:
    - "resource allocation with subcarrier pairing in ofdma two way relay networks"
    - "optimization framework and graph based approach for relay assisted bidirectional ofdma cellular networks"
    - "broadcast capacity region of two phase bidirectional relaying"
    - "physical network coding in two way wireless relay channels"

Question: Please tell me which class the center node 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)