Cell-Edge Detection via Selective Cooperation and Generalized Canonical Correlation

Improving the uplink quality of service for users located around the boundaries between cells is a key challenge in cellular systems. Existing approaches relying on power control throttle the rates of cell-center users, while multi-user detection requires accurate channel estimates for the cell-edge...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2021-11, Vol.20 (11), p.7431-7444
Main Authors: Ibrahim, Mohamed Salah, Zamzam, Ahmed S., Konar, Aritra, Sidiropoulos, Nicholas D.
Format: Article
Language:English
Subjects:
base station cooperation
Base stations
cell-edge users
cellular networks
Cooperation
Correlation
Correlation analysis
Detectors
Edge detection
Generalized canonical correlation analysis (GCCA)
identifiability
multi-user detection
multiple-input-multiple-output (MIMO)
Multiuser detection
Power control
Signal processing
Signal to noise ratio
Subspaces
uplink detection
Wireless communication
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Summary:Improving the uplink quality of service for users located around the boundaries between cells is a key challenge in cellular systems. Existing approaches relying on power control throttle the rates of cell-center users, while multi-user detection requires accurate channel estimates for the cell-edge users, which is another challenge due to their low received signal-to-noise ratio (SNR). Utilizing the fact that cell-edge user signals are weak but common (received at roughly equal power) at different base stations (BSs), this paper establishes a connection between cell-edge user detection and generalized canonical correlation analysis (GCCA). It puts forth a GCCA-based method that leverages selective BS cooperation to recover the cell-edge user signal subspace even at low SNR. The cell-edge user signals can then be extracted from the resulting mixture via algebraic signal processing techniques. The paper includes theoretical analysis showing why GCCA recovers the correct subspace containing the cell-edge user signals under mild conditions. The proposed method can also identify the number of cell-edge users in the system, i.e., the common subspace dimension. Simulations reveal significant performance improvement relative to various multiuser detection techniques. Cell-edge detection performance is further studied as a function of how many / which BSs are selected, and it is shown that using the closest three BS is always the best choice.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2021.3083685