Uploaded by absarece

LTE Throughput Optimization

LTE Throughput Optimization: Part 1 –
PDCCH Capacity Enhancement
There are many ways to optimize LTE throughput and I will try to cover all of them. The LTE
throughput optimization procedure described in this article requires PDCCH enhancements. The
general idea is that the LTE subframe is made up of PDCCH and PDSCH as explained in my
article LTE Frame Structure Made Simple.
The PDCCH is used for control information while the PDSCH carries the actual data. So, if the
PDCCH resources are reduced then that means that the PDSCH resources can increase which in
turn means that there will be more data per sub frame. Since, each subframe is 1 ms in LTE so it
actually means there will be more bits per millisecond which is the definition of throughput.
Firstly, let’s try to understand PDCCH itself and how it works.
A PDCCH is used to give scheduling allocations to the UE on the PDSCH or PUSCH. For
example, if the UE has data in the PDSCH, it needs to know where the data is located. The
PDCCH will tell the UE that the data it is looking for is located at this location on PDSCH.
This means that if the UE is unable to decode PDCCH then the UE cannot read the PDSCH in
that sub frame and consistent decoding failures of PDCCH lead to RLF (Radio Link Failure) due
to N310.
Hence, the decoding of PDCCH is extremely important and that is why it uses a special
structure which is different than other channels.
PDCCH is made up of CCEs (Control Channel Elements) and each CCE is made up of 36
REs (Resource Elements).
PDCCH further uses a concept of aggregation layers which is a group of CCEs.
There are 4 aggregation layers in the normal PDCCH
– Aggregation layer 1: This uses 1 CCE or 36 REs and it is the smallest block so it is only used
in very good radio conditions.
– Aggregation layer 2 : This uses 2 CCEs or 72 REs and it is usually the most common
aggregation layer in normal radio conditions.
– Aggregation layer 4: This uses 4 CCEs and it is a robust allocation. It can be used for
signalling and control information allocations.
– Aggregation layer 8 : This uses 8 CCEs and it is the most robust allocation. Users in very bad
radio conditions are allocated with this layer or it can be used for control information.
Let’s have a look at how many users can be scheduled by PDCCH in a sub frame.
This depends on the number of CCEs that the sub frame can handle
which in turn depends on many factors. Let’s have a look at a
couple of examples
The Number of CRS Antenna Ports must be ≤ the Total number of Antennas.
– Consider a 10 MHz channel using 2×2 MIMO (2 CRS ports).
The PDCCH can span over 3 symbols at maximum and may use 1 symbol at minimum. The
number of RBs in a 10 MHz channel is 50 and this means that a symbol can hold a maximum of
600 REs.
However, in the first symbol, we have 2 RS per RB for each antenna port.
This means that there will be a total of 4 RS per RB in the first symbol and since there are 50
RBs so total RS count will be 4*50 =200 REs.
Moreover, there is a PCFICH control channel that spans over 4 REGs or 16 REs.
Then there are PHICH groups and each PHICH group occupies 3 REGs or 12 REs. If the Ng
parameter is 1 then there will be 7 PHICH groups in 10 MHz channel so the total PHICH
overhead will be 12*7=84.
What is Ng value in LTE?
The number of PHICH groups is a cell level parameter and it is also transmitted as part of MIB,
so as to assist the UE in getting the control channel mapping. The PHICH group value/Ng
is decided based on how much users per subframe would the system want to support in
Uplink PUSCH
RS - 200RE s/ 200 RS s ( 50*4 = 200)
1 PCFICH channel- 16 RE s
7 PHICH groups- 84 RE s ( 7*12 = 84)
Number of REs in one symbol : 50*12 = 600
Overhead in Symbol 1 = 200 RS + 16 REs of PCFICH + 84 REs of PHICH = 300 REs
Overhead in symbol 2 = 0 REs
Overhead in symbol 3 = 0 REs
Total REs available for PDCCH (REs available in 3 symbols) = 1800 – 300 = 1500 REs
Total CCEs available for PDCCH = 1500 REs / 36 = 41 CCEs
This means that if all the users are in very good radio conditions, then there can be 41 users
scheduled in 1 TTI (1 ms) with 3 PDCCH symbols. However, this does not happen because the
radio conditions of the users are usually distributed and there are common allocations like TPC
(transmit power control) commands which are usually at a bigger aggregation layer since it
carries allocations for multiple users. So, if there is one TPC command which takes 8 CCEs then
around 33 CCEs are remaining.
These CCEs will be divided between downlink and uplink data allocations. Usually, downlink
data is more so most of the allocations are taken by downlink.
Consider that the users are in good conditions and require 2 CCEs each then there can be 16
users in each TTI (16*2 =32 CCEs) with 3 PDCCH symbols.
Now that the PDCCH structure is out of the way, let’s have a look at the optimization procedures
for PDCCH.
15% Improvement:
As described above, the PDCCH symbol usage can go up to 3. Each subframe has 14 symbols so
if PDCCH uses 3 symbols, then the PDSCH will only be able to use 11 symbols. If the PDCCH
symbol number is reduced to 1, then the PDSCH symbol count can increase to 13 which is
around 15% improvement in throughput or capacity.
However, if we change the PDCCH symbol count to 1 then that means that the available
PDCCH CCEs will reduce to 8 (300/36=8) since the first symbol has 300 REs available and
other 300 REs are used by RS, PCFICH and PHICH. And if we need to transmit a TPC
command then it will utilize all the CCEs and we cannot transmit any data allocations.
In order to tackle this, most of the vendors have introduced a dynamic algorithm that changes the
PDCCH symbol count with respect to the requirement of the users.
If there is data for 6 users and a TPC command, it will use 2 symbols for PDCCH and if there is
only 1 user that needs to be scheduled, it will reduce the PDCCH symbol count to 1.
Activating this algorithm is the first step to ensure optimum balance between PDCCH and
PDCCH allocation
1. BLER Target
The PDCCH allocation is mostly based on a BLER target accompanied by a CQI input. If the
UE is showing a good CQI, the eNB will allocate a good aggregation layer. For example, the UE
reported CQI index 12 which shows that it is in good radio conditions then the eNB will allocate
it aggregation layer 2 which uses 2 CCEs. Now, consider that the UE moves away and eNB
experiences BLER so the eNB will increase the aggregation layer to 4 to provide more
robustness to the PDCCH.
2. PDCCH Power
However, there is another way to increase the robustness and that is to increase the PDCCH
Vendors have dynamic power features for PDCCH and if such a feature is used, it will increase
the PDCCH power with the same aggregation layer to increase the robustness. This means that
the UE will stay with the same aggregation layer using 2 CCEs and since it did not expand to 4
CCEs so there was a gain of 2CCEs or 72 REs which might prevent the eNB to increase the
PDCCH symbol from 1 to 2 resulting in an extra symbol for PDSCH.
3. Tune PDCCH BLER target
Another approach is to tune the PDCCH BLER target. If the BLER target is slightly increased,
then the eNB will use the same PDCCH aggregation layer for longer and this will reduce
expansion of PDCCH resulting in a lower CCE utilization and reduced overhead. However, if the
BLER target is increased excessively, the UEs might fail to decode the PDCCH resulting in
4. Coding rate dimensioning for the PDCCH aggregation layers
Another dimension is the coding rate for the PDCCH aggregation layers. If there is more
number of bits in a particular PDCCH allocation, then it might exceed the upper limit of the
Aggregation Layer 1. So, the eNB will have to expand to the bigger aggregation layer. This
happens because the eNB has a threshold for maximum coding rate per aggregation layer.
However, if the maximum coding rate threshold is increased, the eNB will be able to send
more bits within the same aggregation layer. This would reduce the transitions to higher
aggregation layers and might reduce the overhead.
As an example, a transmit diversity allocation uses lesser number of PDCCH bits compared to a
Open Loop Spatial Multiplexing (TM3) allocation. So, if a network has Transmit
Diversity and it moves to Open Loop Spatial Multiplexing, an increase in
aggregation layer will be observed.
Similarly, if the network shifts from Open Loop to Closed Loop, another increase in
aggregation layer will be observed as Closed Loop MIMO allocations take more number of
bits on PDCCH compared to Open Loop MIMO allocations.
This can be mitigated by increasing the maximum coding rate threshold for the PDCCH.
But increasing it reduces the robustness of the PDCCH and therefore, a balance must be
The gain of the PDCCH optimization is directly proportional to the utilization and load on the
PDCCH. If the network is lightly loaded then most of the time PDCCH will only be using 1
symbol and since that is the minimum number of symbols allocated to PDCCH so there will be
no gain with any of the above mentioned changes. If the network is congested and PDCCH is
consistently using 3 symbols then such measures can help in reducing the symbols to 2 which
can expand the PDSCH or data capacity. However, in all the cases, special care must be taken
that this does not increase decoding failures excessively.
Consider checking corresponding counters
In order to check the throughput being effected due to each of the section. One recommendation
is to check the counters for each of the section.
The counters value, will tell you, how throughput is performing with respect to that specific
section of the network. Based on the value, you can take respective action to mitigate the
negative influence (if that’s the case)
Channel Quality Indicator CQI :
Look for CQI counters. I am not going to list counters here specifically. For Samsung, it will
have different counters compared to what Ericsson will have and same goes on for other vendors.
Look for Throughput counters for a specific vendor in Downlink and Uplink.
Counters such as which show, how much data is there in PDCP, or how much data volume was
accumulated in the last Transmission Time Interval (TTI).
Also the counter which keeps track of how throughput is being estimated for the UE is
important to know.
In Downlink (DL), there are no counters at the UE side.
But the way we measure DL RF conditions is based on the following which measure interference
on the UE side.
For example, CQI distribution counters.
UE Rank Reporting distribution counters and Transmission rank distribution counters, will
give you RF information, which will translate to interference condition at the DL UE side. .
For Uplink (UL)
In this case check for Interference counters for Interference on:
SINR Distribution on PUCCH
SINR Distribution on PUSCH
For Block Error Rate (BLER)
In Downlink (DL):
For Downlink measure, you need to look for Hybrid Automatic Repeat Request (HARQ)
Acknowledgements and Negative acknowledgements counters for each modulation type such as:
Having information of these counters, can help identify BLER.
In Uplink (UL) :
For Uplink. Measure HARQ UL success and Failure for each modulation type in uplink such as:
16- QAM
Using the above counters, you can identify BLER for UL case
For Downlink
In this case, look for counter which keeps track of UEs in Active mode at cell level. Also
counters, which keep track of UEs which are being scheduled in the DL.
For Uplink :
In this case, look for counter which keeps track of UEs in Active mode at cell level in Uplink.
Also counters, which keep track of UEs which are being scheduled in the UL.
There is another type of CQI reports known as Aperiodic CQIs but we will discuss that in the
next episode of the throughput optimization.
Adaptive BLER Targets
Firstly, lets understand the concept of BLER. It can be divided into two categories:
Initial BLER: When the eNB sends data to the UE and UE is unable to decode it, then it
will send a HARQ NACK to the eNB. A NACK means that the eNB will have to
retransmit the data and this NACK is considered IBLER or Initial Block Error.
Residual BLER: If the UE is unable to decode the data even after retransmission, the UE
will send another NACK and the eNB will have to retransmit again. However, there is a
limit to these retransmissions and usually they are configurable.
Commonly, these retransmissions are set to 4 and after 4 retransmissions, the eNB will
not retransmit at HARQ level and consider this as a Residual Block Error.
The BLER target is maintained by the IBLER so this means that the eNB tries to maintain an
IBLER of 10% for each UE.
RBLER is usually very low and it is supposed to be less than 0.5%. The question may arise
that why don’t we reduce the IBLER further and make it low as that should reduce
retransmissions. The problem here is that lowering IBLER means that we need to lower the
MCS. Even a very low MCS will not ensure a linear decrease in IBLER but it will degrade
throughput excessively. So, various simulations and field trials were done to come up with an
optimum target of 10% for IBLER which is followed by most of the vendors.
However, recently it has been found that BLER target of 10% works fine in fair conditions but
when the radio conditions are bad or good, other BLER targets provide higher gains. For
instance, if the radio conditions are bad, a BLER target of 10% keeps the MCS very conservative
and increasing the BELR target, increases the MCS and it provides higher throughput gains. So,
such parameters can be tuned if available to get better results.
– Mobility Strategy:
One thing that can really help in increasing the throughput is the optimum mobility strategy.
Transition to Higher CQI layer
Consider two LTE layers, for instance L800 and L1800 with same bandwidth. In this case, L800
will have a higher coverage as it is a lower frequency. So, the user count on L800 will be
higher compared to L1800. However, the lower frequency layer also has higher interference
since it has a bigger coverage radius. So, that will result in a lower CQI and a bad throughput.
L1800 throughput will usually be better even with same bandwidth because it will have better
CQI. So, the most important thing is to ensure that the layer with the better CQI gets most
of the traffic. This can be done in many ways and I have jotted down a few of those.
The easiest way is to give a higher priority to L1800 and that will
shift most of the UEs in L1800 coverage away from L800. This will
ensure better CQI for users and thus a better throughput.
Another way would be to keep them on same priority and provide a
frequency offset to move the users to L1800. This is more reasonable
if L1800 is also getting overloaded then the amount of load to be
shifted can be tuned by varying the offsets.
I prefer load shifting by cell reselection instead of handovers.
If the handover thresholds are changed or frequency priority based
handovers are used, then it initiates gap periods.
For UE, to move from one frequency to another frequency in connected mode,
it needs to measure the target frequency. In order to measure the target
frequency, the UE goes into a gap mode of 6 ms.
This gap mode repeats itself after every 40 or 80ms. So, if it repeats every 40ms then that means
that the UE cannot be scheduled for 6ms in every 40ms.
Moreover, when the UE gets data, it needs to send a HARQ ACK/NACK after 4ms.
So, it means that since the eNB knows that the UE will be in gap mode so the eNB will not
That makes it 10ms in
each 40ms that the UE cannot be scheduled which is
around 25% of the time.
schedule any data for the UE 4ms before the gap mode.
So, inter-frequency handovers should be minimized as it can
cause a 25% degradation in throughput. Cell reselection
works in idle mode so it is a much better way to move users
between the layers.
Load Balancing
Another way is to enable load balancing between the layers and ensuring that the higher CQI
layer gets more load. Load balancing usually also comes in two modes
Connected Mode: In this case, the eNB calculates the PRBs or user count and tries to
maintain target load values by performing load based handovers between the layers.
Idle Mode: In this case, the eNB sends the frequency in the RRC Release command to
the UE. eNB increases the priority of the target frequency for that UE temporarily and the
UE tries to reselect to that frequency in idle mode.
Once again, I prefer idle mode based load balancing as it does not introduce the inter-frequency
handovers and also gets the work done.
But idle mode based load balancing will not have significant impact in case the
layers have different priorities since one layer already has higher priority and
idle mode based load balancing also moves users by increasing the priority.
So, if the UEs are not moving to higher priority layer than that means that the
layer has coverage constraints and then the idle mode based load balancing
will also be unable to shift the load.
Vertical Beam-Width
Another important factor is that many times, the low band like L800 has a bigger vertical beam
width than the corresponding higher band. This effectively means that at the same tilt value, the
L800 will have a much bigger coverage foot print than the L1800. So, before making any
mobility strategy, it is important to verify the antenna patterns especially the vertical beam-width
for all the layers. If the beam-width of one layer is significantly wider than the
other, then ensure to put a tilt offset between the two to keep an optimum and
balanced coverage.
– Scheduler Fairness:
Another important factor is the scheduler type. A scheduler can work in multiple modes
Round Robin: In this mode, the scheduler provides equal resources to all users. This is not an
optimum algorithm as different users have different data requirements.
Max C/I: This mode provides significantly higher resources to users in good coverage
conditions. This mode can starve the cell edge users and they will not get enough data resulting
in degradation in user experience.
Proportion Fair: This scheme maintains a fairness between all users maintaining a healthy
resource sharing between all user types. The basic concept of this mode is to strike a balance
between users and it does that by prioritizing based on CQI and data rates. So, if the CQI is high,
it will give resource to that user first but since it needs to maintain a fair data rate for all users,
the cell edge users will also be scheduled. This scheme is essentially a combination of both
round robin and Max C/I as it provides more resources to users with higher CQI as compared to
round robin but it also provides more resources to cell edge users when compared to Max C/I.
Hence, it gets the name Proportional fair.
The user throughput KPI improves with Max C/I scheduler as it provides more resources to good
users resulting in higher user throughput but the cell throughput is improved with Proportional
Fair algorithm as it strikes a balance between all users.
So, if the user throughput KPI is to be improved then the scheduler
can be tilted towards Max C/I while Proportional Fair can be used if
cell throughput gain is required.
The optimization at this level really needs deep understanding of the scheduler’s algorithm and
it also depends if the specific vendor provides the options to play with the scheduling weights.
LTE Throughput Optimization: Part 2 –
PDSCH Spectral Efficiency
I explained the gains of optimizing the PDCCH (control part) of the LTE subframe in my
previous article.
Let’s have a look at the data part (PDSCH) and find out various ways to improve its efficiency.
The spectral efficiency is simply the number of bits transmitted over a frequency bandwidth in a
specific time and is measured in bits/s/Hz. It is proportional to throughput as the throughput is
also bits per time transmitted in a certain bandwidth.
From LTE’s perspective, if the number of bits transmitted in a subframe (time) over a specific
number of Resource Blocks (frequency bandwidth) is high, then it will correspond to higher
throughput and higher spectral efficiency.
Let’s understand the various factors impacting the spectral efficiency and ways to perform LTE
throughput optimization.
1. Signal to Noise & Interference Ratio:
The most basic and common factor that controls the spectral efficiency and throughput is the
SINR (Signal to Noise and Interference Ratio).
If the SINR of a network is bad, then that puts a limit on the throughput gain that it can achieve.
So, the first thing to verify is the average SINR of the network. Let’s check some of the
factors that impact SINR
2. Inter-site distance
This one is a basic thing. If sites are too close to each other, they will have a higher tendency to
interfere with each other and will require aggressive down-tilts to limit overshooting. The
distance is something that is usually fixed as LTE sites mostly use the previously deployed
network. So, there is not much to do at this level other than downtilts to improve SINR and
reduce overshooting.
3. Electrical Tilt Ports: It is better to use antennas which assign a different RET
port (electrical tilt) to LTE. That provides flexibility for optimization. If the
network uses the same RET port for LTE and other RATs (3G or 2G) then any
change on LTE tilt will impact the other RAT and it takes away the flexibility. So,
it is a good idea to keep this in mind in the design or expansion phase.
4. Pa & Pb: Another thing that can be done in case of smaller inter-site distance is to
use a more balanced RS power (Reference Signal).
There are two parameters in LTE Pa and Pb which define the power of the
Reference Signals against the other symbols e.g. PDSCH Symbols. I will just
explain with an example. If the Pa is -3 and Pb is 1, then that means that the
Reference Signals will be having 3 dB higher power than the PDSCH symbols.
When the inter-site distance is low, then high reference signal power can result in
higher interference.
If the inter-site distance is large then this configuration can be helpful as a 3dB
Reference Signal boost will improve coverage as LTE coverage is controlled with
RSRP and RSRP is the direct outcome of RS power.
However, in case of small inter-site distance, Pb and Pa values of 0 might
provide a more optimized solution as in this case, the RS power will not be
boosted compared to the PDSCH symbols.
Moreover, the PDCCH/PDSCH symbols in which Reference Signals are
present will have a slightly higher power for 2 and 4 antenna port systems.
This happens because previously with 0,-3 configuration, the RS were taking the
extra available power but now with the 0,0 configuration, the extra power is used by
the other channels instead of RS.
So, that improves the credibility of PDSCH and can result in better throughput
results. This is a big topic so I am just touching it here and will cover this in more
details in the future articles.
5. Load & Utilization
Second factor is the load in the area or cluster. Higher the load, higher the interference to the
neighboring cells.
As the load increases, the power per Resource Element increases which will
result in higher aggregate power in the area increasing the RSSI.
By Load balancing feature/ tuning cell reselection or mobility parameters
For neighboring cell, such a power is considered interference. So, if the load increases above a
threshold, it is better to add another carrier or if another carrier already exists,
then it will be better to offload the congested carrier and shift the load to the
uncongested carrier. This can be done using Load Balancing features or by
tuning the cell reselection or mobility parameters.
Physical Optimization
Sometimes, the actual traffic volume is not that high but the utilization of the cell is still very
high. This is usually caused due to low signal quality as the users with bad SINR will
take a lot RBs at a lower modulation.
In case, the traffic is not high but utilization is still high, it is a good idea to see the TA and
CQI for the cell.
If TA is pretty high and CQI is below 8 (value depends on the frequency layer) then it might be a
better idea to physically optimize the area or cell.
PDCCH optimization
Introducing PDCCH optimization also helps in such cases as it can add to the PDSCH
capacity relieving congestion to an extent.
6. PCI Planning
As described in my PCI planning article, if the adjacent cells with overlapping coverages have
same PCI modulo 3, then there is a probability of RS interference between them. Such an
interference will reduce the overall RS SINR and demodulation capability resulting in
throughput degradation. So, it should be tried to avoid PCI modulo3 conflicts wherever
In FDD networks, it is better to ensure that time synchronization is not enabled as that adds a
randomness to the system and PCI mod3 impact is reduced significantly.
7. CQI & MCS Mapping:
The next step is the CQI (Channel Quality Indicator). Once the UE measures it’s SINR, it
will convert it to a CQI value so it can report to the eNB. The eNB will take this
CQI and map it to a MCS (Modulation & Coding Scheme) value. A higher SINR
will result in a higher CQI value and consequently, a higher MCS index. As MCS increases, the
throughput usually increases so we need to ensure that we have the most optimum CQI and
MCS indexes for each SINR value.
In LTE, there are 16 CQI indexes and 32 MCS indexes. Usually, the CQI value of below 7 is
considered bad and CQI value of around 10 is considered fair.
CQI Adjustment Algorithms
The eNB adjusts the raw CQI value shared by the UE to find an optimum CQI and this provides
a higher spectral efficiency. There are basically two scenarios where this comes into play
Consider a UE-1 that measures its SINR value to be around 10 dB and based on that it calculates
a CQI of 9 and sends it to the eNB.
Another UE, let’s call it UE-2, measures its SINR value to be around 8 dB but based on that it
sends CQI of 9 as the UEs have different chipsets from different vendors and can have a
different CQI value for same SINR indexes.
The eNB will have two UEs with same CQI value and if the eNB provides both of them with the
same MCS (for example MCS20) then it is possible that the UE-1 might be able to work with
MCS20 but the UE-2 will not be able to decode MCS20 properly at 8 dB SINR.
So, to address this issue, the eNB maintains another index which is like the outer loop of BLER
(Block Error Rate). Most of the vendors maintain a BLER target of 10%. Now consider the
same scenario, both UEs get MCS20 and UE-1 works with a BLER value of 10% but the UE-2
had lower SINR so it will have a relatively higher BLER.
Let’s say, the eNB calculates the BLER to be around 13% so the eNB will lower the MCS for the
UE-2 and make it 19. If the BLER still remains above 10%, the eNB will reduce it further to
ensure that the BLER target is maintained.
Similarly, if the UE sends a CQI value of 8 and eNB initiates downlink data with a MCS of 16
and it finds out that the BLER value is below 10%, it will increase MCS to 17 or 18 until the
BLER target is achieved.
This scenario will increase the spectral efficiency and the throughput.
So, we need to ensure that
CQI adjustment or dynamic CQI assignment algorithms or outer loop control based on
BLER is activated to achieve maximum gains from the channel.
CQI Convergence
Another important thing is that some vendors use low CQI values initially. For example, if the
UE has just accessed the cell and it shares a CQI value of 9, the eNB will treat it as a CQI of 7
and a corresponding MCS will be allocated to it. Then after subsequent transmissions, the eNB
will keep monitoring BLER and once the credibility of the UE’s CQI is ensured, the eNB
will converge to the effective CQI.
Some vendors keep this as a hard-coded algorithm while others provide parameters to tune this
and then these parameters can be tuned to limit this behaviour resulting in faster convergence
and higher throughputs especially for small packet data transfers.
For instance, a UE which has a small amount of data accesses the cell and gets its data within
two to three TTIs (subframes), then the eNB will not have enough CQI samples to converge
quickly. The same UE will try again next time and the eNB will keep using a conservative CQI
and MCS for such a UE. So, if the delta for initial CQI value is reduced, such UEs will get a less
conservative CQI and MCS resulting in better data rates.
CQI Periodicity
Another thing that helps is the CQI periodicity or the frequency of CQI reporting from the UE. If
the UE reports CQI after a large interval, then the eNB might not have the most accurate CQI to
begin with and it will take longer time to converge to the optimum MCS.
Usually CQI reports are shared every 40 or 80 ms but if the UE is moving or if the channel
is fluctuating then 40 or 80 ms can be considered a large interval.
If we shift the CQI period to a smaller value like 20ms or 10ms, then the CQI will be more
accurate and that should improve the spectral efficiency.
However, the lower the interval, higher the number of CQI reports and higher the PUCCH
Periodic CQI reports are sent over PUCCH in uplink so if we reduce the CQI reporting interval,
that will increase the load on PUCCH. This can lead to interference on PUCCH and it
can also result in RRC rejections due to PUCCH congestion.
eNB needs PUCCH for CQI, HARQ & SRIs so if the PUCCH is congested, then it will have
to reject new incoming access requests. This can be solved by using the following two
Adaptive or Dynamic PUCCH: This is introduced by vendors to resolve the RRC
Rejections due to PUCCH overload. This allows the PUCCH to expand and it can
consume more Resource Blocks if required.
The down side is that the PUCCH takes the Resource Blocks from the PUSCH which can
then limit the uplink throughput. However, usually the networks require higher downlink
capacity so uplink can be compromised to an extent.
Adaptive CQI Period : This is another enhancement that some vendors have. This
makes the CQI reporting interval dynamic and the eNB can adjust it based on the user’s
This way, if the eNB finds a UE that has no channel fluctuation (mostly
stationary), it can use longer CQI reporting interval like 80ms and eNB
can reduce the interval to 10ms for a UE that has high fluctuation. This
provides an optimum performance gain in CQI accuracy without
impacting the PUCCH load to that extent.
If you are going to ask this question from an academic or researcher.
You would receive one of the two responses below.
1. Maximize SINR available
2. Reduce Network Load
Those are rationally and scientifically proven facts.
However, if you are performance engineer when you see Throughput Key Performance
Indicators (KPIs) are getting degraded?
What do you do?
In a live network. Do you always have a choice to perform either of the above two steps? If yes,
you can start from scratch.
Otherwise, below are the quick steps you can take note of and start investigating when it comes
to improving LTE Throughput
Throughput Optimization
In LTE, end user quality of service is impacted by the cumulative effect of various nodes and
interfaces. There is not one factor, but a number of contributing factors which affect the end user
PREREQUISTE : General Guidelines Before diving into Throughput Investigation:
1. One of the first things to do is: confirm parameter settings, system configuration and RF
2. KPIs co-relate and depend on each other. Therefore knowledge of other KPIs such as
Accessibility, Retainability, Mobility etc. is helpful to know, how they are performing .
For example if Accessibility and Retainiabilty KPIs are bad, this will directly influence the
throughput and end user QoS.
3. Do a site hardware audit (including jumpers, cables, connectors, antennas etc.)
4. Investigation of RF environment is a good idea to perform such as SINR, antenna types and
Cumulative Effect on Throughput
The main factors which have a cumulative effect on throughput are shown in the figure below.
Throughput is a cumulative of Whole Network health
The above diagram shows us, how various nodes and factors can affect the user throughput.
As an RF Performance engineer, you need to have knowledge of what counters do you need
to take a look at in order to improve throughput?
Different vendors can have different names for the same counters.
What counters to look for when looking for Throughput improvement in LTE?
Answer: It is better to understand the behavior of a certain part of the network. After that you
can always figure out, where to go and look for counters.
(Find the exact counter name in the documentation of the specific vendor)
What Sections and their Counters to look for w.r.t Throughput?
As from the diagram above, you can look at the 7 sections to start with in order to improve
throughput at RAN side.
LOW PDSCH UTILIZATION means capacity issue
Your UNC Charlotte Student ID is 801282457,