Optimizing 5G Cellular Networks through a User Density-Based Soft Frequency Reuse Algorithm.
Soft frequency reuse (SFR) techniques have been widely employed to tackle interference challenges faced by users in cellular networks. However, some of these techniques rely on the assumption of uniformly distributed users, which may not accurately reflect real-world scenarios where user deployments are random. Understanding the impact of random user distribution on SFR-based resource allocation is crucial for designing efficient networks.
This study introduces a novel SFR algorithm termed “User-SFR,” which intelligently adjusts resource allocation parameters based on the load distribution within the network. Comparative analysis with several fixed SFR algorithms reveals that the proposed User-SFR algorithm outperforms them significantly. Specifically, the Signal-to-Interference plus Noise Ratio (SINR) for users at the edge regions exhibits an improvement of approximately 3.2%, and the network capacity experiences a remarkable enhancement of over 202%.
These findings underscore the importance of considering a more realistic approach, accounting for random user distribution within the network, as it leads to a more robust and enhanced cellular network performance.
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