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