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: "distributed energy spectral efficiency optimization for partial full interference alignment in multi user multi relay multi cell mimo systems"
  Abstract: The energy spectral efficiency maximization (ESEM) problem of a multi-user, multi-relay, multi-cell system is considered, where all the network nodes are equipped with multi-antenna transceivers. To deal with the potentially excessive interference originating from a plethora of geographically distributed transmission sources, a pair of transmission protocols based on interference alignment (IA) are conceived. The first, termed the full-IA, avoids all intra-cell interference (ICI) and other-cell interference by finding the perfect interference-nulling receive beamforming matrices (RxBFMs). The second protocol, termed partial-IA, only attempts to null the ICI. Employing the RxBFMs computed by either of these protocols mathematically decomposes the channel into a multiplicity of non-interfering multiple-input–single-output channels, which we term as spatial multiplexing components (SMCs). The problem of finding the optimal SMCs as well as their power control variables for the ESEM problem considered is formally defined and converted into a convex optimization form with carefully selected variable relaxations and transformations. Thus, the optimal SMCs and power control variables can be distributively computed using both the classic dual decomposition and subgradient methods. Our results indicate that indeed, the ESEM algorithm performs better than the baseline equal power allocation algorithm in terms of its ESE. Furthermore, surprisingly the partial-IA outperforms the full-IA in all cases considered, which is because the partial-IA is less restrictive in terms of the number of available transmit dimensions at the transmitters. Given the typical cell sizes considered in this paper, the path-loss sufficiently attenuates the majority of the interference, and thus the full-IA over-compensates, when trying to avoid all possible sources of interference.

Connected through hyperedge HE-1 (induced by source paper "a survey of multi objective optimization in wireless sensor networks metrics algorithms and open problems"):
  with members:
    - "energy efficient ofdma networks maintaining statistical qos guarantees for delay sensitive traffic"
    - "wireless sensor network virtualization a survey"
    - "markov decision processes with applications in wireless sensor networks a survey"
    - "accuracy of homology based coverage hole detection for wireless sensor networks on sphere"
    - "end to end reliability aware scheduling for wireless sensor networks"
    - "multiband spectrum access great promises for future cognitive radio networks"
    - "spectral and energy spectral efficiency optimization of joint transmit and receive beamforming based multi relay mimo ofdma cellular networks"
    - "achieving maximum energy efficiency in multi relay ofdma cellular networks a fractional programming approach"

Connected through hyperedge HE-2 (induced by source paper "iterative distributed minimum total mse approach for secure communications in mimo interference channels"):
  with members:
    - "fifty years of mimo detection the road to large scale mimos"
    - "secure degrees of freedom of one hop wireless networks"
    - "degrees of freedom of the three user rank deficient mimo interference channel"
    - "limited feedback based interference alignment for interfering multi access channels"
    - "enhancing secrecy with multi antenna transmission in wireless ad hoc networks"
    - "filter design with secrecy constraints the mimo gaussian wiretap channel"
    - "interference alignment for secrecy"
    - "cooperative algorithms for mimo interference channels"

Connected through hyperedge HE-3 (induced by source paper "energy efficient ofdma networks maintaining statistical qos guarantees for delay sensitive traffic"):
  with members:
    - "large scale mimo is capable of eliminating power thirsty channel coding for wireless transmission of hevc h 265 video"
    - "spectral and energy spectral efficiency optimization of joint transmit and receive beamforming based multi relay mimo ofdma cellular networks"
    - "maximizing energy efficiency in multi relay ofdma cellular networks"
    - "achieving maximum energy efficiency in multi relay ofdma cellular networks a fractional programming approach"
    - "qos aware base station selections for distributed mimo links in broadband wireless networks"
    - "statistical delay control and qos driven power allocation over two hop wireless relay links"
    - "the impact of qos constraints on the energy efficiency of fixed rate wireless transmissions"

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)