human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Cloud-BSS: Joint intra- and inter-Cluster interference cancellation in uplink 5G cellular networks"
  Abstract: Abstract   Coordinated Multi-Point (CoMP) processing is a promising method to cancel the intra-cluster interference, to improve the average Signal-to-Interference-plus-Noise Ratio (SINR), and to increase the system spectral efficiency. Such a method, however, cannot mitigate the inter-cluster interference, which leads to a poor capacity performance for cluster-edge Mobile Stations (MSs). Moreover, the additional overhead and processing required for multiple-site reception/transmission among different Base Stations (BSs) adds delay and limits the cluster size. In this article, we detail the challenges and problems of CoMP and propose an innovative Blind Source Separation (BSS)-aided solution, called  Cloud-BSS , to address those problems. In the proposed solution, we leverage the centralized characteristic of Cloud Radio Access Networks (C-RANs) as well as the complementary advantages of CoMP and BSS to decrease both intra- and inter-cluster interference. Specifically, we study the performance of BSS under different network topologies and show that its performance highly depends on the mixing matrix. Then, we propose to use CoMP to reject the intra-cluster interference so as to make the overall mixing matrix diagonal dominant, which allows to use BSS in order to reject the inter-cluster interference. Thorough Monte Carlo computer simulations, we confirm the validity of our analysis and show the benefits of this novel uplink solution.

Connected through hyperedge HE-1 (induced by source paper "Group Sparse Beamforming for Green Cloud-RAN"):
  with members:
    - "Simultaneous Support Recovery in High Dimensions: Benefits and Perils of Block $\ell _{1}/\ell _{\infty} $ -Regularization"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science