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Expected IFLB RAB Distribution under Ideal Conditions

Expected IFLB RAB Distribution under Ideal Conditions. Introduction. IFLB is used to control the RAB distribution between LTE frequencies Current practice uses a basic model to predict the distribution That model does not consider lbThreshold , the minimum load need to trigger offloading

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Expected IFLB RAB Distribution under Ideal Conditions

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  1. Expected IFLB RAB Distribution under Ideal Conditions

  2. Introduction • IFLB is used to control the RAB distribution between LTE frequencies • Current practice uses a basic model to predict the distribution • That model does not consider lbThreshold, the minimum load need to trigger offloading • This over site is significant at typical loading levels and has lead to the erroneous belief that the feature is not working • In this presentation we will • Calculate the expected distribution ratio using the current method • Expand the method to include lbThreshold • Compare both methods with field results

  3. Parameter settings 1 1 qciSubscriptionQuanta / ∑qciSubscriptionQuantaCell 2 cellSubscriptionCapacity x lbThreshold / qciSubscriptionQuanta

  4. lbThreshold Impact at Low load • Consider two cells with an IFLB relationship enabled • RAB’s are added one at a time to Cell A • Cell A can have 10 UE’s before off loading to Cell B • This means for less than 10 UE’s the RAB distribution will be 100% on Cell A • Clearly this is very far from the expected distribution

  5. Modeling lbThreshold Impact • Our model must include the 100% distribution at low load and progress towards the Expected Distribution • We do this by considering two extreme situations • Only adding RAB’s to Cell A • Only adding RAB’s to Cell B • To facilitate the formation of a mathematical model we make the following assumption: • When the number of RAB’s is greater than the threshold, RAB’s will be distributed proportional to the Expected Distribution

  6. Only adding to Cell A • By only adding to Cell A, Cell B must have 0 RAB when below the lbThreshold (10 RAB) • Then for every RAB on Cell A, there must be one on Cell B as the Expected Distribution is 50% • Formula to describe this is: • RB = MAX(0,RA x QA / QB - TB) RX Number of RAB on Cell X QXQCISubscriptionQanta for Cell X TX Threshold for activation for Cell X [RAB]

  7. Only adding to Cell B • By only adding to Cell B, Cell B must have 10 RAB before the first appears on Cell A (10 RAB) • Then for every RAB on Cell A, there must be one on Cell B as the Expected Distribution is 50% • Formula to describe this is: • RB = MAX(0,RA x QA / QB + TB) RX Number of RAB on Cell X QXQCISubscriptionQanta for Cell X TX Threshold for activation for Cell X [RAB]

  8. Plotting Results • Formula for distribution of RAB on Cell A is straight forward • RA / (RA + RB) • Plotting shows we do tend to the Expected Distribution while also modeling the predicted low load behavior

  9. Parameter settings 2Field Settings 1 qciSubscriptionQuanta / ∑qciSubscriptionQuantaCell 2 cellSubscriptionCapacity x lbThreshold / qciSubscriptionQuanta

  10. Field Results • Results were collected from an IFLB field trial • Average RRC Connections was used as a proxy for the number of RAB • Cells had up to 8 IFLB neighbors • The median value for RAB Distribution was 43.3% on Frequency A • The design was for 58.3% • So let’s examine factor in the number of RAB’s…

  11. Field Results • The plot below shows that the number of RRC connections significantly impacts the distribution of RAB’s. • The distribution of RAB’s for cells with greater than 40 RCC connection’s is close to the Expected Distribution • The majority of Freq A cells are below the 40 RRC Connection point

  12. Field Results vs Model • The model reasonably predicts the spread distribution with low loading • It suggests that the “Add to Cell B Only” phenomenon is dominate in the network • This indicates that Freq B is attracting initial attaches • Idle mode users having a preference for Freq B is one possible explanation

  13. Conclusion • We demonstrated that the impact from the load balancing threshold is significant at low loading • We developed a model to more accurately predict low load distribution • We demonstrated the expected load balancing distribution will fall in a range of values • That median of RAB distributions is not an accurate indication of IFLB design efficacy • That field results are likely being impacted by • Many cells with a low number of connections • Freq B attracting initial connections

  14. THNAK YOU

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