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: "a generalized zero forcing precoder with successive dirty paper coding in miso broadcast channels"
  Abstract: In this paper, we consider precoder designs for multiuser multiple-input-single-output broadcasting channels. Instead of using a traditional linear zero-forcing (ZF) precoder, we propose a generalized ZF (GZF) precoder in conjunction with successive dirty-paper coding (DPC) for data transmissions, namely, the GZF-DP precoder, where the suffix “DP” stands for “dirty-paper.” The GZF-DP precoder is designed to generate a band-shaped and lower triangular effective channel    ${F}$   , such that only the entries along the main diagonal and the    $\nu $    first lower-diagonals can take non-zero values. Utilizing the successive DPC, the known non-causal inter-user interferences from the other (up to)    $\nu $    users are canceled through successive encoding. We analyze optimal GZF-DP precoder designs both for sum-rate and minimum user-rate maximizations. Utilizing Lagrange multipliers, the optimal precoders for both cases are solved in closed-forms in relation to optimal power allocations. For the sum-rate maximization, the optimal power allocation can be found through water filling, but with modified water levels depending on the parameter    $\nu $   , while for the minimum user-rate maximization that measures the quality of the service, the optimal power allocation is directly solved in closed-form, which also depends on    $\nu $   . Moreover, we propose two low-complexity user-ordering algorithms for the GZF-DP precoder designs for both maximizations, respectively. We show, through numerical results, that the proposed GZF-DP precoder with a small    $\nu $    value (≤ 3) renders significant rate increments compared with the previous precoder designs, such as the linear ZF and the user-grouping-based DPC precoders.

Connected through hyperedge HE-1 (induced by source paper "achieving large sum rate and good fairness in miso broadcast communication"):
  with members:
    - "improving the performance of the zero forcing multiuser miso downlink precoder through user grouping"
    - "a low complexity channel shortening receiver with diversity support for evolved 2g device"
    - "an alternative proof for the capacity region of the degraded gaussian mimo broadcast channel"
    - "an axiomatic theory of fairness in network resource allocation"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-2 (induced by source paper "a high diversity transceiver design for k user miso broadcast channels"):
  with members:
    - "beam design and user scheduling for nonorthogonal multiple access with multiple antennas based on pareto optimality"
    - "rate splitting multiple access for downlink communication systems bridging generalizing and outperforming sdma and noma"
    - "a minorization maximization method for optimizing sum rate in the downlink of non orthogonal multiple access systems"
    - "non orthogonal multiple access noma for downlink multiuser mimo systems user clustering beamforming and power allocation"
    - "the application of mimo to non orthogonal multiple access"
    - "a new approach to user scheduling in massive multi user mimo broadcast channels"
    - "transmit optimization with improper gaussian signaling for interference channels"
    - "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling"

Connected through hyperedge HE-3 (induced by source paper "beyond massive mimo the potential of data transmission with large intelligent surfaces"):
  with members:
    - "the potential of using large antenna arrays on intelligent surfaces"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "a low complexity channel shortening receiver with diversity support for evolved 2g device"
    - "massive mimo performance evaluation based on measured propagation data"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "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)