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: "multiobjective signal processing optimization the way to balance conflicting metrics in 5g systems"
  Abstract: The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream; first by delivering wireless access to voice communications, then by providing wireless data services, and recently by delivering a Wi-Fi-like experience with wide-area coverage and user mobility management. The support for high data rates has been the main objective in recent years [1], as seen from the academic focus on sum-rate optimization and the efforts from standardization bodies to meet the peak rate requirements specified in IMT-Advanced. In contrast, a variety of metrics/objectives are put forward in the technological preparations for fifth-generation (5G) networks: higher peak rates, improved coverage with uniform user experience, higher reliability and lower latency, better energy efficiency (EE), lower-cost user devices and services, better scalability with number of devices, etc. These multiple objectives are coupled, often in a conflicting manner such that improvements in one objective lead to degradation in the other objectives. Hence, the design of future networks calls for new optimization tools that properly handle the existence of multiple objectives and tradeoffs between them.

Connected through hyperedge HE-1 (induced by source paper "joint dynamic pricing and radio resource allocation framework for iot services"):
  with members:
    - "adaptive and resilient revenue maximizing dynamic resource allocation and pricing for cloud enabled iot systems"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"
    - "toward hierarchical mobile edge computing an auction based profit maximization approach"
    - "market model and optimal pricing scheme of big data and internet of things iot"
    - "mobile data transactions in device to device communication networks pricing and auction"
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"

Connected through hyperedge HE-2 (induced by source paper "coded caching in fog ran b matching approach"):
  with members:
    - "fog networking an overview on research opportunities"
    - "large scale convex optimization for ultra dense cloud ran"
    - "fundamental limits of caching in wireless d2d networks"
    - "fundamental limits of caching"
    - "a survey on network codes for distributed storage"

Connected through hyperedge HE-3 (induced by source paper "energy efficiency optimization a new trade off between fairness and total system performance"):
  with members:
    - "a framework for weighted sum energy efficiency maximization in wireless networks"
    - "energy efficient power control a look at 5g wireless technologies"
    - "energy efficient scheduling and power allocation in downlink ofdma networks with base station coordination"

Connected through hyperedge HE-4 (induced by source paper "joint unicast and multi group multicast transmission in massive mimo systems"):
  with members:
    - "large system analysis of power normalization techniques in massive mimo"
    - "hybrid precoding for multi group physical layer multicasting"
    - "max min fair transmit precoding for multi group multicasting in massive mimo"
    - "multigroup multicast precoding in massive mimo"
    - "reducing the computational complexity of multicasting in large scale antenna systems"
    - "joint beamforming and broadcasting in massive mimo"
    - "hybrid precoding for physical layer multicasting"
    - "on the spectral efficiency and security enhancements of noma assisted multicast unicast streaming"

Connected through hyperedge HE-5 (induced by source paper "enhanced max min sinr for uplink cell free massive mimo systems"):
  with members:
    - "cell free massive mimo with limited backhaul"
    - "cooperative access networks optimum fronthaul quantization in distributed massive mimo and cloud ran"
    - "max min sinr in large scale single cell mu mimo asymptotic analysis and low complexity transceivers"
    - "energy efficient power control a look at 5g wireless technologies"
    - "cell free massive mimo versus small cells"

Connected through hyperedge HE-6 (induced by source paper "cell free massive mimo with limited backhaul"):
  with members:
    - "cooperative access networks optimum fronthaul quantization in distributed massive mimo and cloud ran"
    - "enhanced max min sinr for uplink cell free massive mimo systems"
    - "energy efficient power control a look at 5g wireless technologies"
    - "cell free massive mimo versus small cells"

Connected through hyperedge HE-7 (induced by source paper "an overview on resource allocation techniques for multi user mimo systems"):
  with members:
    - "low complexity downlink user selection for massive mimo systems"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "user association in 5g networks a survey and an outlook"
    - "cell free massive mimo versus small cells"
    - "mu mimo mac protocols for wireless local area networks a survey"
    - "on the number of rf chains and phase shifters and scheduling design with hybrid analog digital beamforming"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"

Connected through hyperedge HE-8 (induced by source paper "optimal pilot and payload power control in single cell massive mimo systems"):
  with members:
    - "massive mimo with multi cell mmse processing exploiting all pilots for interference suppression"
    - "uplink pilot and data power control for single cell massive mimo systems with mrc"
    - "massive mimo performance evaluation based on measured propagation data"
    - "massive mimo with optimal power and training duration allocation"
    - "joint optimization of power allocation and training duration for uplink multiuser mimo communications"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "massive mimo for maximal spectral efficiency how many users and pilots should be allocated"
    - "scaling up mimo opportunities and challenges with very large arrays"

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)