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: "transmitting important bits and sailing high radio waves a decentralized cross layer approach to cooperative video transmission"
  Abstract: We investigate the impact of cooperative relaying on uplink multi-user (MU) wireless video transmissions. We analyze and simplify a MU Markov decision process (MDP), whose objective is to maximize the long-term sum of utilities across the video terminals in a decentralized fashion, by jointly optimizing the packet scheduling and physical layer, under the assumption that some nodes are willing to act as cooperative relays. The resulting MU-MDP is a pricing-based distributed resource allocation algorithm, where the price reflects the expected future congestion in the network. Compared to a non-cooperative setting, we observe that the resource price increases in networks supporting low transmission rates and decreases for high transmission rates. Additionally, cooperation allows users with feeble direct signals to significantly improve their video quality, with a moderate increase in total network energy consumption that is far less than the energy these nodes would require to achieve the same video quality without cooperation.

Connected through hyperedge HE-1 (induced by source paper "convolutive superposition for multicarrier cognitive radio systems"):
  with members:
    - "what will 5g be"
    - "five disruptive technology directions for 5g"
    - "in band full duplex wireless challenges and opportunities"
    - "opportunistic interference alignment in mimo interference channels"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-2 (induced by source paper "wireless video multicast with cooperative and incremental transmission of parity packets"):
  with members:
    - "network coding meets multimedia a review"
    - "sticmac a mac protocol for robust space time coding in cooperative wireless lans"

Connected through hyperedge HE-3 (induced by source paper "interference allocation scheduler for green multimedia delivery"):
  with members:
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"
    - "automated small cell deployment for heterogeneous cellular networks"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "to relay or not to relay learning device to device relaying strategies in cellular networks"):
  with members:
    - "on the complexity of solving markov decision problems"
    - "observation based cooperation enforcement in ad hoc networks"
    - "reinforcement learning a survey"

Connected through hyperedge HE-5 (induced by source paper "fast reinforcement learning for energy efficient wireless communication"):
  with members:
    - "online reinforcement learning for dynamic multimedia systems"

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.MM(Multimedia)