研究目的
Investigating the spectral-energy efficiency tradeoff in relay-aided massive MIMO cellular networks with pilot contamination.
研究成果
The paper concludes that relay-aided massive MIMO systems can significantly improve spectral and energy efficiencies, but are strongly influenced by pilot contamination. The proposed optimization methods effectively balance SE and EE, with the 1-D searching method offering better performance and the alternate optimization method providing lower complexity. Future work could explore joint optimization over transmit power, relay station deployment, and number of antennas, along with strategies to mitigate pilot contamination.
研究不足
The study focuses on a single-cell scenario and does not consider the optimal deployment of relay stations (such as number, location) which could be a subject for future work. The impact of pilot contamination is significant, suggesting the need for further research to mitigate its effects.
1：Experimental Design and Method Selection:
The study involves deriving closed-form expressions for spectral efficiency (SE) and energy efficiency (EE) in a downlink single-cell multi-user multi-relay massive MIMO system under pilot contamination. The methodology includes theoretical analysis and simulation validation.
2：Sample Selection and Data Sources:
The simulation scenario includes a cellular cell with a radius of 900 m and relays located at 2/3 radius. Monte Carlo simulations with uniform distribution of users and random small-scale fading are conducted.
3：List of Experimental Equipment and Materials:
MATLAB is used for simulations. The simulation parameters are inspired by prior works in the field.
4：Experimental Procedures and Operational Workflow:
The study involves optimizing the number of antennas at the BS, transmit power at the BS, and transmit power of each RS to maximize EE while satisfying SE requirements. Two optimization methods are proposed: 1-D searching and alternate optimization.
5：Data Analysis Methods:
The analysis includes evaluating the impact of system parameters on SE and EE, and validating the effectiveness of the proposed optimization methods through simulation results.
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