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Rotating cluster mechanism for coordinated heterogeneous MIMO cellular networks
Hakimeh Purmehdi1, Robert C Elliott1, Witold A Krzymień1
11Department of Electrical and Computer Engineering, University of Alberta, T6G 1H9 Edmonton, Alberta, Canada.
EURASIP Journal on Wireless Communications and Networking
|July 2, 2019
Summary
A novel rotating clustering scheme enhances user data rates in coordinated multicell systems. This method improves throughput for edge users by ensuring they are closer to cluster centers, boosting overall network performance.
Area of Science:
- Wireless communication networks
- Mobile computing and networking
Background:
- Multicell multiuser multiple-input multiple-output (MU-MIMO) systems face challenges in providing high data rates for cluster-edge users.
- Coordinated base station operation within clusters is crucial for enhancing system capacity.
Purpose of the Study:
- To propose and analyze a rotating clustering scheme to increase average achievable rates for cluster-edge users.
- To investigate the impact of different rotating patterns and rotation speeds on system performance.
Main Methods:
- A rotating clustering scheme is proposed for coordinated multicell MU-MIMO systems.
- Simulated annealing algorithm for user scheduling and successive zero-forcing dirty paper coding for precoding were employed.
- Performance was evaluated in cellular layouts with three or six macrocells per site.
Main Results:
- The rotating clustering scheme significantly improves throughput for cluster-edge users.
- The scheme offers a slight improvement in the average achievable sum rate for the entire network.
- Higher rotation speeds generally lead to better performance, with diminishing returns beyond a certain point.
Conclusions:
- The proposed rotating clustering scheme is an effective and less complex alternative to fully dynamic clustering.
- The scheme successfully addresses the challenge of low data rates for edge users in multicell MU-MIMO systems.
- Optimizing the speed of rotation is key to maximizing performance gains without unnecessary computational overhead.
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