Analysis of User Capacity and SINR Variation under Different Frequency Reuse Factors

In cellular network design, the Frequency Reuse Factor (FRF) is a critical parameter that determines how frequently the same frequency resources are reused across different cells. The selection of FRF directly impacts both user capacity and signal quality (measured by SINR). Code implementation typically involves configuring FRF through network parameter settings in base station controllers, using algorithms that allocate frequency bands based on predefined reuse patterns.

When FRF is small (e.g., FRF=1), all cells utilize identical frequency resources. While this maximizes spectrum utilization efficiency, it introduces severe co-channel interference that degrades user SINR values. Though potential user capacity remains high, the actual achievable data rates become limited due to interference constraints. In simulation code, this scenario can be modeled using interference matrices where adjacent cells share identical frequency channels.

As FRF increases (e.g., FRF=3), frequency resources are reused more sparsely, significantly reducing inter-cell interference. This improves user SINR values, enabling higher-order modulation schemes and more reliable communications. At FRF=3, networks typically achieve an optimal balance between interference suppression and spectrum utilization, maximizing overall user capacity. Implementation-wise, this involves partitioning available spectrum into three subsets using modulo-based frequency allocation algorithms.

Further increasing FRF (e.g., FRF=7) reduces interference further but excessively fragments available frequency resources, decreasing bandwidth per cell. Although SINR may reach higher values, overall capacity declines because fewer resources are allocated per user. This can be simulated through frequency division algorithms that assign narrower bandwidths to each sector while maintaining interference isolation.

Therefore, FRF=3 represents a common optimization point that maximizes system capacity while maintaining high SINR. Practical network planning requires additional adjustments based on specific service requirements, user distributions, and coverage environments, often implemented through adaptive FRF algorithms that dynamically adjust reuse patterns according to real-time network load measurements.