LTE <> UMTS Cell Reselection

[anita_2k]

hi again...

background:

(in 3GPP) thresX-High or threshx, High - threshold used for Higher priority Layer (ex. LTE over UMTS)
(in NSN) there are threshold High parameter
1. IRFIM > EUTRA inter frequency threshold high (interFrqThrH) - This specifies the threshold used by the UE when reselecting towards a higher priority frequency X than the current serving frequency
2. UFFIM > UTRA inter frequency threshold high (utraFrqThrH) - same meaning

Question:
I am just confused which one to use IRFIM (interFrqThrH) or UFFIM (utraFrqThrH) as threshold for UMTS to LTE reselection.

anybody has document or experienced?
basically just want to tune parameter to avoid LTE user in losing signal bar on phone / no service

on the documents i found, it was on 3gpp name, not NSN parameter name. really confuse though.

thanks/Anita

[anita_2k]

LOGFILES containing thresX-High
Reflected on IRFIM Object

[anita_2k]

LOGFILES again containing threshX-High
but now in UFFIM Object.
FYI/R

[incoincov]

Hi Anita,

In my opinion
IRFIM (interFrqThrH) refers to cell reselection LTE(EUTRAN) -> WCDMA(UTRAN) when WCDMA has a higher prio.In your case UTRA has lower prio and interFrqThrH is not applicable. Instead you should consider utraFrqThrL if not 0dB.
UFFIM (utraFrqThrH) is used for cell reselection WCDMA (UTRA) -> LTE (EUTRA) when LTE has higer prio (your case)

With your IRAT cell reselection threshold settings you have:
http://www.finetopix.com/image/png;base64,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34825
If from the Utran network perspective the LTE network has priority = 7 and the Utran network has priority = 3 . The LTE network must be better than qRxLevMinEUTRA(-140 dBm )+ thresholdXhigh(2 dB) = -138 dBm in order to trigger a cell reselection from 3G->LTE.
If we assume higher thresholds for cell reselction in WCDMA e.g.:
•EutranFreqRelation / qRxLevMin = -124 dBm
•EutranFreqRelation / ThreshHigh = 20 dB
•UtranCell / absPrioCellRes.cellReselectionPriority = 3
•EutranFreqRelation / cellReselectionPriority = 7
then:
LTE network has priority = 7 and the Utran network has priority = 3 from the Utran network perspective. The LTE network must be better than -124 dBm + 20 dB = -104 dBm in order to trigger a cell reselection from 3G->LTE.

In a real life scenario it might be wise to set the thresholds lower if it is wanted to keep the UEs in LTE as long as possible.
BUT if the radio conditions drop too quickly and that the UE will be suddenly out of coverage before the reselection/redirection (connected mode) has been performed.
If you'd like to speed up the cell reselection you can also decrease sNonIntrSearch to 16 and thus start to perform IRAT meas at -114dBm instead of at -110dBm.
I hope that for the time being it will help you at least to get the main concept.
I am still looking for live network threshold setting and ,as promised will let you know as soon as i get the result.

BR!

[incoincov]

Hi again Anita,

here is a file containing 2 sheets:
1.Recommended IRAT cell reselection parameters
2. IRAT cell reselection parameter templates from various live networks.

Pls do not forget the REP if you find it helpful:D

[anita_2k]

thanks alot my friend.
just want to share what i found again...

1. Example number 1: LTE Has Higher Priority over UMTS/WCDMA
RSRP is <=LNCEL:sNonIntrsearch
UE will measure @ RSRP is UFFIM: utraFrqThrL


2. Example Number 2: LTE Has Lower priority over UMTS/WCDMA
UE will measure @ RSRP is > LNCEL:sNonIntrsearch
UE will trigger / execute @ SnonservingCell > UFFIM: utraFrqThrH

this is why i am really-really confuse on this thresholdXhigh

here are the images:

[anita_2k]

here is our actual settings...
the first image i attached was only found at the net.

LTE -> UMTS (i don't have issue here)

sIntrasearch = 62
sNonIntrsearch = 22
threshSrvLow = 12
utraFrqThrL = 12
qrxlevmin = -118

UMTS -> LTE (here i am still confuse about the parameters)
the one i found on net, it was controlled by 2 parameters.
1. qRxLevMinEUTRA - no such thing on NSN dictionary, rather they have the following
a. qRxLevMinInterF
b. qrxlevmin
c. qrxlevminintraF
d. qRxLevMinUtra

2. threshXhigh
based on the new docs i found, when LTE has lower priority over WCDMA, utraFrqThrH is being used (under UFFIM not with IRFIM)
which i think contradict your opinion? (but I am still thinking about the opinion you posted, it makes sense thouhg).
i am just confused.


last question,

the one you attached (actual network settings) qQualMinUtra has value of -18dB? we only set it to 0dB as minimum, do you think its wrong?
because i did not see any reference concerning this qQualMinUtra that will influence the reselection.

thanks alot again my friend...
Anita

[gulzarsingh]

Hi Anita,

Even i have the same question in mind, kindly share if you get the answer.

[incoincov]

Hi Anita,

Thanks for the feedback. It's really interesting for me too.
What i've posted is based on Nsn concept and approach. You are right that it contadicts the info you've found and posted?!.....
Concerning qQualMinUtra I notice that it's usually set to -16, -18, -22dB in different networks.
I will do further research and i'll come back to you.

[anita_2k]

hello all,

i already found what i am looking for.
sorry to bother, but the threshold for UMTS going to LTE can be found at the
ADJL & HOPL Object.
further studies on LTE interworking can also be obtained in NED
just search for RAN2067 LTE Interworking feature.

if you find it helpful, please click thanks and REP button.

this thread is now close.

thanks
anita