Selecting the Optimal Fractional Frequency Reuse Scheme in Long Term Evolution Networks

A flexible mid-term frequency domain scheduler for resource allocation in HetNets based on the SINR requested by users

“…On the other hand, classical FFR proposals [43] divide the cell space in two regions, select the optimal size for each one, and establish the optimal frequency reuse factor considering this space division. In our approach, instead of varying the border of each sector, we identify users in each sector having the least gain with respect to their base station, so they are located in their respective Z i subzone (i = 1, 2, 3).…”

Stochastic Geometry Based Framework for Coverage and Rate in Heterogeneous Networks with Sectored Fractional Frequency Reuse

“…The Joint Laplace transform for the femto-tier interference would be; The final result is therefore realized in (C4) similar to Lemma 5 defined in (18).…”

“…Dynamic schemes [15][16][17] exhibit more resilience to traffic and interference variation but also have higher signaling overheads and increased complexity, making the static schemes [6,[18][19][20][21] very popular when appropriately provisioned. Such regular grid models make idealistic assumptions and are not practical for realistic network deployments with irregular geometry and complex distributions of diverse access points as obtainable in Hetnets.…”

“…Using the above resource allocation mechanism associates performance metrics with the FFR threshold T 0 allowing for design trade-offs in terms of load balancing, increasing peak rate or fairness similar to simulation-based grid models [6,[17][18][19][20].…”

Self-organized dynamic resource allocation using fraction frequency reuse scheme in long term evolution networks

“…Their results showed that if the fairness of the UE throughput distribution is to be maintained, FFR offers no gain if proper scheduling is employed. The authors in [20] proposed a dynamic mechanism that selects the optimal FFR scheme based on a custom metric, which is called User Satisfaction (US). Their proposed mechanism divides the cell into two regions, the inner and outer region and calculates the US metric for successive combinations of the inner region radius and inner region frequency allocation and then selects the optimal size as well as the optimal frequency allocation between these regions with main target to maximize the US metric.…”