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: "energy efficient adaptive power allocation for incremental mimo systems"
  Abstract: We consider energy-efficient adaptive power allocation for three incremental multiple-input multiple-output (IMIMO) systems employing ARQ, hybrid ARQ (HARQ) with Chase combining (CC), and HARQ with incremental redundancy (IR), to minimize their rate-outage probability (or equivalently packet drop rate) under a constraint on average energy consumption per data packet. We first provide the rate-outage probability expressions for the three IMIMO systems, and then propose methods to convert them into a tractable form and formulate the corresponding non-convex optimization problems that can be solved by an interior-point algorithm for finding a local optimum. To further reduce the solution complexity, using an asymptotically equivalent approximation of the rate-outage probability expressions, we approximate the non-convex optimization problems as a unified geometric programming problem (GPP), for which we derive the closed-form solution. Illustrative results indicate that the proposed power allocation (PPA) offers significant gains in energy savings as compared to the equal-power allocation (EPA), and the simple closed-form GPP solution can provide closer performance to the exact method at lower values of rate-outage probability, for the three IMIMO systems.

Connected through hyperedge HE-1 (induced by source paper "ultra reliable communication via optimum power allocation for harq retransmission schemes"):
  with members:
    - "effective capacity and power allocation for machine type communication"
    - "low latency short packet transmissions fixed length or harq"
    - "on the effective energy efficiency of ultra reliable networks in the finite blocklength regime"
    - "ultra reliable communication via optimum power allocation for type i arq in finite block length"
    - "short packet communications over multiple antenna rayleigh fading channels"
    - "green communication via type i arq finite block length analysis"
    - "finite block length analysis of the incremental redundancy harq"
    - "ultra reliable communication in 5g wireless systems"

Connected through hyperedge HE-2 (induced by source paper "ultra reliable communication via optimum power allocation for type i arq in finite block length"):
  with members:
    - "understanding the iot connectivity landscape a contemporary m2m radio technology roadmap"
    - "green communication via type i arq finite block length analysis"
    - "finite block length analysis of the incremental redundancy harq"
    - "ultra reliable communication in 5g wireless systems"
    - "quasi static multiple antenna fading channels at finite blocklength"

Connected through hyperedge HE-3 (induced by source paper "asymptotic outage analysis of harq ir over time correlated nakagami m fading channels"):
  with members:
    - "green communication via power optimized harq protocols"
    - "outage exponent a unified performance metric for parallel fading channels"
    - "on the bivariate nakagami m cumulative distribution function closed form expression and applications"
    - "performance of hybrid arq in block fading channels a fixed outage probability analysis"

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)