Leveraging User Distribution for Enhanced Interference Mitigation

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Abstract:

Device-to-Device (D2D) communication, an essential feature in Fifth Generation (5G) cellular networks, enables direct communication between devices in close proximity without involving the Base Station (BS). This technology offers numerous advantages, such as data traffic offloading, location-awareness services, social networking, and smart city applications. However, the implementation of D2D Communication Networks faces significant challenges, notably Interference Management, which severely impacts communication quality.

To enhance D2D Communication performance and maximize its potential, researchers have explored various approaches to mitigate interference. One such approach is soft frequency reuse (SFR) through fair bandwidth allocation. Under the SFR scheme, cellular network users are divided into two categories: Center Users and Edge Users. In this study, three distinct algorithms for bandwidth allocation—namely, separate bandwidth allocation, overlapping bandwidth allocation, and hybrid bandwidth allocation—were developed for three user categories. The goal was to minimize interference between the Cellular Network and the Device-to-Device Communication Network. Bandwidth allocation was conducted fairly, taking into account users’ demand in each network.

The proposed algorithms were evaluated through simulations using MATLAB, considering Signal-to-interference plus noise ratio (SINR) and system capacity as performance metrics. The research results were presented by comparing the network’s performance for varying numbers of D2D users. The evaluation revealed that the size of D2D networks can significantly impact the performance of the cellular network, which stands as the first unique contribution of this research.

When the number of D2D users constituted up to 10% of the network, both the Hybrid and Separate bandwidth allocation algorithms outperformed the fixed bandwidth allocation method for D2D Users SINR, showing improvements of up to 34%. However, as the number of D2D users increased to over 30% in the network, the performance of these algorithms decreased to 27%. Consequently, as the number of D2D users grows in the network, the overall system performance declines.

For future research, it is recommended to further enhance the proposed algorithm to accommodate more D2D users and handle higher interference scenarios.

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