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 • 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 Parameter settings 1 Cell A Cell B cellSubscriptionCapacity 100000 100000 qciSubscriptionQuanta 500 500 lbThreshold 0.05 0.05 Expected Distribution1 50% 50% Threshold in RAB’s2 10.0 10.0 1 qciSubscriptionQuanta / ∑qciSubscriptionQuantaCell 2 cellSubscriptionCapacity x lbThreshold / qciSubscriptionQuanta 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 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 Only adding to Cell A Cell A RAB Cell B RAB 0 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 10 0 11 1 12 2 13 3 14 4 › 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 QX QCISubscriptionQanta for Cell X TX Threshold for activation for Cell X [RAB] Only adding to Cell B Cell A RAB Cell B RAB 0 10 1 11 2 12 3 13 4 14 5 15 6 16 7 17 8 18 9 19 10 20 11 21 12 22 13 23 14 24 › 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 QX QCISubscriptionQanta for Cell X TX Threshold for activation for Cell X [RAB] 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 Parameter settings 2 Field Settings Frequency A Frequency B cellSubscriptionCapacity 115000 115000 qciSubscriptionQuanta 500 700 lbThreshold 0.05 0.05 Expected Distribution1 58.3% 41.7% Threshold in RAB’s2 11.5 8.2 1 qciSubscriptionQuanta / ∑qciSubscriptionQuantaCell 2 cellSubscriptionCapacity x lbThreshold / qciSubscriptionQuanta 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… 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 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 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 THNAK YOU