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: "multiaccess channels with state known to some encoders and independent messages"
  Abstract: We consider a state-dependent multiaccess channel (MAC) with state non-causally known to some encoders. We derive an inner bound for the capacity region in the general discrete memoryless case and specialize to a binary noiseless case. In the case of maximum entropy channel state, we obtain the capacity region for binary noiseless MAC with one informed encoder by deriving a non-trivial outer bound for this case. For a Gaussian state-dependent MAC with one encoder being informed of the channel state, we present an inner bound by applying a slightly generalized dirty paper coding (GDPC) at the informed encoder that allows for partial state cancellation, and a trivial outer bound by providing channel state to the decoder also. The uninformed encoders benefit from the state cancellation in terms of achievable rates, however, appears that GDPC cannot completely eliminate the effect of the channel state on the achievable rate region, in contrast to the case of all encoders being informed. In the case of infinite state variance, we analyze how the uninformed encoder benefits from the informed encoder's actions using the inner bound and also provide a non-trivial outer bound for this case which is better than the trivial outer bound.

Connected through hyperedge HE-1 (induced by source paper "gaussian multiple access via compute and forward"):
  with members:
    - "a joint typicality approach to algebraic network information theory"
    - "asymmetric compute and forward with csit"
    - "successive integer forcing and its sum rate optimality"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "nested lattice codes for gaussian relay networks with interference"
    - "integer forcing linear receivers"
    - "lattice strategies for the dirty multiple access channel"

Connected through hyperedge HE-2 (induced by source paper "state dependent gaussian multiple access channels new outer bounds and capacity results"):
  with members:
    - "the dirty mimo multiple access channel"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "multiple access channels with states causally known at transmitters"
    - "lattice strategies for the dirty multiple access channel"
    - "multiaccess channels with state known to one encoder another case of degraded message sets"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "information embedding and the triple role of control"):
  with members:
    - "coordination using implicit communication"
    - "reliability in source coding with side information"

Connected through hyperedge HE-4 (induced by source paper "on cooperative multiple access channels with delayed csi at transmitters"):
  with members:
    - "capacity results for binary fading interference channels with delayed csit"
    - "multiple access channels with states causally known at transmitters"
    - "secure degrees of freedom of mimo x channels with output feedback and delayed csit"
    - "estimation with a helper who knows the interference"
    - "wyner ziv type versus noisy network coding for a state dependent mac"
    - "on achievable degrees of freedom for mimo x channels"
    - "wireless network information flow a deterministic approach"
    - "the state dependent semideterministic broadcast channel"

Connected through hyperedge HE-5 (induced by source paper "parallel gaussian networks with a common state cognitive helper"):
  with members:
    - "on the achievable rate regions for state dependent gaussian interference channel"
    - "secret key agreement with channel state information at the transmitter"
    - "the state dependent semideterministic broadcast channel"
    - "bounds on the capacity of the relay channel with noncausal state at source"
    - "capacity bounds for multiuser channels with non causal channel state information at the transmitters"
    - "distributed interference cancellation in multiple access channels"
    - "on the capacity of compound state dependent channels with states known at the transmitter"
    - "lattice strategies for the dirty multiple access channel"

Connected through hyperedge HE-6 (induced by source paper "multi layer gelfand pinsker strategies for the generalized multiple access channel"):
  with members:
    - "multiple access channels with states causally known at transmitters"
    - "capacity region of multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "capacity bounds for multiuser channels with non causal channel state information at the transmitters"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "the state dependent multiple access channel with states available at a cribbing encoder"
    - "multiple access channels with cooperative encoders and channel state information"

Connected through hyperedge HE-7 (induced by source paper "multiple access channels with states causally known at transmitters"):
  with members:
    - "a note on multiple access channels with strictly causal state information"
    - "short message quantize forward network coding"
    - "message and state cooperation in multiple access channels"
    - "noisy network coding"
    - "lecture notes on network information theory"
    - "lattice strategies for the dirty multiple access channel"

Connected through hyperedge HE-8 (induced by source paper "capacity region of multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"):
  with members:
    - "multiple access channels with states causally known at transmitters"
    - "a note on multiple access channels with strictly causal state information"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "on the capacity of memoryless finite state multiple access channels with asymmetric state information at the encoders"
    - "the state dependent multiple access channel with states available at a cribbing encoder"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "lecture notes on network information theory"
    - "lattice strategies for the dirty multiple access channel"

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)