human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on the uplink transmission of multi user extra large scale massive mimo systems"):
  Abstract: With the inherent benefits, such as, better cell coverage and higher area throughput, extra-large scale massive MIMO has great potential to be one of the key technologies for the next generation wireless communication systems. However, in practice, when the antenna dimensions grow large, spatial non-stationarities occur and users would only see a portion of the base station antenna array, which we call visibility region (VR). To exploit the impact of spatial non-stationarities, in this paper, we investigate the uplink transmission of multi-user extra-large scale massive MIMO systems by considering VRs. In particular, we first propose a subarray-based system architecture for extra-large scale massive MIMO systems. Then, tight closed-form uplink spectral efficiency (SE) approximations with linear receivers are derived.These approximations reveal that users with their VRs covering different subarrays or VRs with less overlap should be scheduled simultaneously under maximum ratio combining receiver, while as many users as possible should be selected under linear minimum mean squared error receiver. With the objective of maximizing the system sum achievable SE, we also propose schemes for the subarray phase coefficient design. In addition, two statistical CSI-based greedy user scheduling algorithms are developed. Our results indicate that statistical CSI-based scheduling algorithms achieve great performance for extra-large scale massive MIMO systems, and it is not necessary to simultaneously turn on all the subarrays and radio frequency chains to serve the users.

Includes members:
  Member "non stationarities in extra large scale massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning based fdd non stationary massive mimo downlink channel reconstruction")
  Member "capacity analysis for spatially non wide sense stationary uplink massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "non stationarities in extra large scale massive mimo")
  Member "towards very large aperture massive mimo a measurement based study":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computation offloading for iot in c ran optimization and deep learning")
  Member "massive mimo performance evaluation based on measured propagation data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "massive mimo asymptotics for ray based propagation channels")
  Member "on the matrix inversion approximation based on neumann series in massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "channel correlation diversity in mu mimo systems analysis and measurements")
  Member "power scaling of uplink massive mimo systems with arbitrary rank channel means":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "spectral efficiency of one bit sigma delta massive mimo")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")

Question: Please tell me which class the source paper 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)