3GPP TSG-RAN WG1 Meeting #121	     R1-2503247
St Julian’s, Malta, 19-23 May, 2025

Agenda Item:	9.7.1
Source:	Huawei, HiSilicon
Title:	Deployment scenarios for ISAC channel model
Document for:	Discussion and Decision

Conclusions
The calibration results are provided for sensing UAV, vehicle in urban grid with and without EO type-2 and spatial consistency based on the agreed simulation assumptions in this contribution.  
Proposal: Incorporate the calibration results for sensing UAV, vehicle in urban grid with and without EO type-2 and spatial consistency as in the attachment. 

3GPP TSG RAN WG1 #121                                                            R1-2503372
St Julian, Malta, May 19th – 23rd, 2025

Source:	vivo
Title:	Views on Rel-19 ISAC deployment scenarios
Agenda Item:	9.7.1
Document for:	Discussion and Decision

Conclusions
In this contribution, we have discussed the views on ISAC channel calibration. The observations and proposals are summarized as follows.
Proposal 1: The scenario randomly paired with multiple STs and multiple UTs can be an additional calibrated scenario.

3GPP TSG RAN WG1 Meeting #121 	          	     	           R1-2503445
Malta, May 19th – 23rd, 2025
Agenda Item:	9.7.1
Source: 	EURECOM
Title: 	Discussion on ISAC deployment scenarios and requirements
Document for:	Discussion and decision

Conclusions
In this contribution, the following proposals are put forward:
Proposal 1: The parameters of CM calibration for full calibration for human indoor/outdoor use cases are shown in Table 1.
Proposal 2: The parameters of CM calibration for large scale for human indoor/outdoor use cases are shown in Table 2.
Proposal 3: The parameters of CM calibration for full calibration for Automotive vehicles use cases are shown in Table 3.
Proposal 4: The parameters of CM calibration for full calibration for AGV use cases are shown in Table 4.
Proposal 5: The parameters of CM calibration for large scale for AGV use cases are shown in Table 5.
Proposal 6: The parameters of CM calibration for full calibration for objects creating hazards on roads/railways use cases are shown in Table 6.
Proposal 7: The parameters of CM calibration for large scale for objects creating hazards on roads/railways use cases are shown in Table 7.

3GPP TSG RAN WG1 #121			R1-2503576
St Julian’s, Malta, May 19th – 23th, 2025

Agenda item:	9.7.1 
Title:	Discussion on ISAC Deployment Scenarios 
Source:	Samsung 
Document for:	Discussion and Decision

Conclusion
The coupling loss get results the complex values even though the calibration assumed the single dual-pol isotropic antenna 
RAN1 consider the absolute value of coupling loss to derive CDF
When calculating coupling loss, large-scale calibration considers  within the power scaling factor. However, for large-sized objects such as vehicles, UAVs, and human types, full calibration involves generating the angular-dependent RCS component within the channel coefficient, which is represented as , and this is applied along with  to the path power 
RAN1 clarify whether should be applied to either the large-scale or small-scale elements exclusively, or if it can be applied to both without restriction
For EO type-2, major objects could be buildings. The shape of buildings defined by 3GPP represents the cell layout of an Urban Grid scenario, considering the inter-site distance (ISD) of an UMa, resulting in a 2D size of 433 m x 250 m, However, EO type-2 should not be limited to simply being a cell layout element but rather play the role of deterministic clutters within channels.
EO type-2s may take the form of buildings. Nonetheless, these forms of EO type-2 should no vary across different scenarios but rather have standardized shapes applicable to all scenarios.
RAN1 consider the sensing target as EO type-1 for each sensing target scenario in unintended/environment object category
RAN1 discuss the detailed shape and size for EO type-2 in unintended/environment object category

Appendix. Simulation assumption for calibration

Table 1. Simulation assumptions for large scale calibration for UAV sensing targets

Table 2. Simulation assumptions for full calibration for UAV sensing targets

Table 3. Simulation assumptions for large scale calibration for Automotive sensing targets

Table 4. Simulation assumptions for full calibration for Automotive sensing targets

3GPP TSG RAN WG1 #121                                        R1-2503697
St Julian’s, Malta, May 19th – 23th, 2025

Source:	ZTE Corporation, Sanechips, CAICT
Title:	Discussion on ISAC deployment scenarios
Agenda item:	9.7.1
Document for:	Discussion and Decision

Conclusion
In this contribution, we provide our views on ISAC deployment scenarios, and we have the following proposals:
Proposal 1: For ISAC channel modelling, do not calibrate combined channel.
Proposal 2: For both large scale calibration and full calibration for automotive vehicle, support the following change:
Proposal 3: There is no need to set a different deadline for the calibration of optional channel modelling features.
Proposal 4: Regarding CDF of delay spread and angle spread for monostatic background channel calibration, support the following:

3GPP TSG-RAN WG1 Meeting #121	R1-2503752
St Julian’s, Malta, May 19th – 23rd, 2025

Agenda Item:	9.7.1
Source:	InterDigital, Inc.
Title:	Discussion on ISAC deployment scenarios
Document for:	Discussion and Decision

Conclusion 
In this contribution, we discussed the calibration parameters and results for scenarios associated with different sensing targets. Based on the discussion, we made the following observations and proposals:
Observation 1: Micro-Doppler signatures can be used to distinguish between sensing targets and the unintended targets
Proposal 1: Use Table 1 for the spatial consistency calibration for UMa-AV deployment scenario for UAV sensing

Table 1 Parameters for spatial consistency for UAV
Proposal 2: Incorporate the micro-Doppler signatures of the sensing targets, unintended targets for different deployment scenarios.

3GPP TSG RAN WG1 #121			R1-2503760
St Julian’s, Malta, May 19th – 23th, 2025

Agenda item:	9.7.1 
Title:	Discussion on ISAC deployment scenario
Source:	SK Telecom
Document for:	Discussion and Decision
1. 

Conclusion
We propose to focus the large-scale calibration on TRP monostatic and TRP-UE bistatic modes only.
We recommend adopting a similar MIMO BS antenna configuration for the ISAC channel model calibration, following the precedent set in TR 38.901.

3GPP TSG RAN WG1 #121		R1-2503803
St Julian’s, Malta, May 19th – 23th, 2025

Source:	CATT, CICTCI
Title:	Discussion on ISAC deployment scenarios
Agenda Item:	9.7.1
Document for:	Discussion and Decision

Conclusion
In this contribution, we provide large scale calibration and full scale calibration results for the scenarios of UAV, Automotive vehicles, EO type-2 and spatial consistency based on the progress so far. The simulation assumptions for the scenarios are also listed in the corresponding sections. The implementation of the simulation platform is based on the existing Chairman’s Notes and CR.

3GPP TSG RAN WG1 #121			        R1-2503841
St Julian’s, Malta, May 19th – 23st, 2025

Agenda item:	9.7.1
Source: 	CMCC
Title: 	Discussion on ISAC channel model calibration
Document for:	Discussion and Decision

Conclusions
In this contribution, we provide our initial results on large scale and full calibration for UAV sensing target, and the following proposals are made:
Proposal 1: We provide our large scale calibration results in Figure 1 and Figure 2 with assumptions in  Table 1, while detailed CDF data can be found in attached files.
Proposal 2: We provide our full calibration result in Figure 3 and Figure 4 with assumptions in Table 2, while detailed CDF data can be found in attached files.

3GPP TSG RAN WG1 #121                                           R1-2503858     
Malta, MT   May 19th – May 23th, 2025
Agenda Item: 		   9.7.1
Source: 			   BUPT, CMCC, X-Net
Title:                Discussion on ISAC channel calibration
Document for: 	      Discussion and Decision

Conclusions
In this contribution, we analyze and summarize the assumptions, metrics, RCS, and convolution methods for ISAC channel calibration.. The proposals are as follows:

Proposal 1: For vehicle targets in urban grid and highway scenarios, their initial orientation can be determined by their dropped lane position. 
Proposal 2: For human, UAV, and AGV targets, the initial orientation can be fixed at 0°in the global coordinate system by default.
Proposal 3：When 1 by 1 randomly coupling is used for concatenation, NLOS-NLOS power normalization should be applied to align the power with that of Option 0, ensuring compliance with the objective physical law of energy conservation.
Proposal 4: When simulating the ST-Rx link, after generating channel parameters using existing TRs (or modifications based on existing TRs), the horizontal angle parameters (AOA, ZOA) and vertical angle parameters (AOD, ZOD) should be swapped to ensure the correctness of the link direction.

3GPP TSG RAN WG1 Meeting #121	 R1-2503892
St Julian’s, Malta, May 19th – 23rd, 2025
Source: 	Xiaomi
Title:	Scenarios and calibration discussion for ISAC CM
Agenda Item:	9.7.1
Document for:	Discussion and Decision

Conclusion
In this contribution, we discuss the remaining issues of evaluation parameters for the ISAC deployment scenarios. In addition, we propose detailed simulation assumptions for UAV, human indoor, and automotive vehicles sensing scenarios.
Proposal 1：EO is not included in the table for evaluation parameters of UAV sensing scenarios. 
Proposal 2: The fix value of min 3D distance between sensing targets at human indoor scenario is set to 1m.
Proposal 3: EO is not included in the table for evaluation parameters of human indoor scenario.

3GPP TSG RAN WG1 #121	R1- 2503954
Malta. 19th – 23rd May 2025

Agenda item:		9.7.1
Source:	Nokia, Nokia Shanghai Bell
Title:	Discussion on ISAC Deployment Scenarios
WI code:	FS_Sensing_NR
Release:	Rel-19
Document for:		Discussion and Decision

Conclusion
In this contribution, we are making the following proposals.
Proposal 1: Consider our large-scale results in Figures 1 and 2 for the TRP-based monostatic UAV sensing scenario in the UMA-AV channel to the ISAC channel model calibration effort, and capture them accordingly
Proposal 2: Consider our results in Figures 3 and 4 for the TRP-based bistatic UAV sensing scenario in the UMA-AV channel to the ISAC channel model calibration effort and capture them accordingly
Proposal 3: Consider our full-scale results in Figure 5 for the TRP-based monostatic UAV sensing scenario in the UMA-AV channel to the ISAC channel model calibration effort, and capture them accordingly
Proposal 4: Discuss our large-scale results in Figures 6 and 7 for the TRP-based monostatic Human Sensing Scenario in Indoor office deployment, and consider them in the ISAC channel model calibration effort
Proposal 5: Discuss our large-scale results in Figures 8 and 9 for the TRP-based bistatic Human Sensing Scenario in Indoor office deployment, and consider them in the ISAC channel model calibration effort
Proposal 6: Discuss our full-scale results in Figure 10 for the TRP-based monostatic Human Sensing Scenario in Indoor office deployment, and consider them in the ISAC channel model calibration effort
Proposal 7: Discuss our large-scale results in Figures 11 and 12 for the TRP-based monostatic Automotive Sensing Scenario UMa Urban Grid deployment, and consider them in the ISAC channel model calibration effort
Proposal 8: Discuss our large-scale results in Figures 13 and 14 for the TRP-based bistatic Automotive Sensing Scenario UMa Urban Grid deployment, and consider them in the ISAC channel model calibration effort

References

3GPP TSG RAN WG1 #121		R1- 2503967
St Julian’s, Malta, May 19th – 23rd, 2025

Source:	Tiami Networks
Title:	Discussion on ISAC deployment scenarios
Agenda Item:	9.7.1
Document for:	Discussion and Decision

Introduction:
The following agreements were achieved during RAN#120 meeting . 



Based on the agreed calibration parameters, we have provided the large-sale calibration results for target channel of the BS-monostatic UMa-AV UAV target, BS-UE bistatic UMa-AV UAV, and BS-monostatic UMa Human detection scenarios in Appendix A.
It is essential for ISAC calibration to be able to handle the difference in signal strength between the target reflections and background clutter. This is because traditional calibration methods might miss target channel errors because the background is so much stronger. That's why we need to calibrate the target and background channels separately - to properly check the RCS, positioning accuracy, and signal strength. Furthermore, we should consider controlled tests setups like a single transmitter-receiver pair instead of complicated full-system simulations. This helps spot errors in how we model radar reflections (RCS) and signal polarization. By checking basic measurements like signal strength and angle/delay variations, we can ensure the model is being implemented consistently across all companies’ efforts. 
Proposal 1: ISAC target-channel calibration should be considered assuming simple simulation setups to verify RCS and polarization modeling. Key metrics like received power, angle/delay spreads, and Doppler shifts must be standardized for consistent implementation.
Back to the evaluation parameters for the targets, we believe the minimum distance between the targets needs to be considered more carefully. At least for a UAV target, assuming a fixed value of 10m is too optimistic and might result in unrealistic target detection results. Hence, the minimum distance between sensing targets should be defined as no less than the physical dimensions of the largest target while avoiding arbitrary restrictions that could limit sensing resolution.

Proposal 2: The minimum distance between targets should be at least equal to the target's size.

Conclusion
Proposal 1: ISAC target-channel calibration should be considered assuming simple simulation setups to verify RCS and polarization modeling. Key metrics like received power, angle/delay spreads, and Doppler shifts must be standardized for consistent implementation.
Proposal 2: The minimum distance between targets should be at least equal to the target's size.


Appendix A
Coupling loss results for large-scale calibration. 

Figure 1. CDF of Coupling loss for the BS monostatic sensing for a human target in UMa.

Figure 2. CDF of Coupling loss for the BS monostatic sensing for a UAV target in UMa-AV.

Figure 3. CDF of Coupling loss for a BS-UE bistatic sensing for the UAV target in UMa-AV.

TDoc file conclusion not found

TDoc file unavailable

3GPP TSG-RAN WG1 Meeting #121	R1- 2503992
St Julian’s, Malta, May 19th – 23rd, 2025
Agenda Item:	9.7.1
Source:	NVIDIA
Title:	Deployment scenarios for integrated sensing and communication with NR
Document for:	Discussion
1	

Conclusion
In the previous sections, we discuss general aspects of deployment scenarios for ISAC in NR and make the following observations:
Observation 1: Wireless channel modelling needs to provide consistency and, above all, a correct representation of the frequency, spatial, and temporal correlation across base stations, devices, and objects in the environment.
Observation 2: ISAC evaluation without a propagation model grounded on the underlying physics of the scattering phenomena is simply unnatural, prone to modelling error and possibly a huge waste of effort for the industry.
Observation 3: Deterministic, physics-based modelling for wireless propagation, especially ray tracing, is essential for ISAC evaluation.
Observation 4: WLAN sensing Task Group IEEE 802.11bf has embraced ray tracing-based channel model for Wi-Fi sensing.
Observation 5: Though ray tracing has been considered in the map-based hybrid channel model in TR 38.901, the map-based hybrid model defined is not calibrated and has not been used in 3GPP simulation campaigns.
Observation 6: A common reference scenario defined for ray tracing not only can be used for ISAC evaluation but also other key technologies toward 6G, including reconfigurable intelligent surface (RIS), larger antenna arrays in new spectrum such as 7-24 GHz and sub-THz bands, and AI/ML, to name a few.
Based on the discussion in the previous sections we propose the following:
Proposal 1: Define a common reference scenario for ray tracing to be used in ISAC evaluation. 
Proposal 2: Select one the following options to define a common reference scenario for ray tracing to be used in ISAC evaluation:
Option 1: Real-scenario map that is a virtual representation of a real area on earth. 
Option 2: Synthetic-scenario map that is artificially constructed to mimic a certain physical environment such as urban macro, rural macro, indoor office, or indoor factory.
Proposal 3: Describe the scene geometry and the characteristics of the materials involved in the ISAC deployment scenarios to be used for ray tracing in ISAC evaluation.
Proposal 4: For the urban grid defined for V2X in TR 37.885, the scene geometry can be described by including assumption on building height, and assumptions on the materials for the buildings and roads can be included.
Proposal 5: Agree on the evaluation parameters for environment objects in automotive sensing scenarios assuming urban grid (ISAC – Automotive) as in Table 1.
Table 1: Evaluation parameters for environment objects in ISAC-Automotive 

3GPP TSG-RAN WG1 #121			R1-2504012
Malta, Malta, May 19th – 23rd, 2025

Agenda item:	9.7.1 
Title:	Discussion on ISAC Deployment Scenarios
Source:	          National Institute of Standards and Technology (NIST)
Document for:	Discussion and Decision

Conclusion
In summary, our proposals are listed as follows:

Proposal 1: Include our TRP monostatic large-scale calibration results for UAV sensing targets in the UMA-AV scenario to support ISAC channel model calibration efforts and incorporate them in the TR.

Proposal 2: Include our TRP monostatic full-scale calibration results for UAV sensing targets in the UMA-AV scenario to support ISAC channel model calibration efforts and incorporate them in the TR.

Proposal 3: Include our TRP-TRP bi-static large-scale calibration results for UAV sensing targets in the UMA-AV scenario to support ISAC channel model calibration efforts and incorporate them in the TR.
Proposal 4: Include our TRP-TRP bi-static full-scale calibration results for UAV sensing targets in the UMA-AV scenario to support ISAC channel model calibration efforts and incorporate them in the TR.

Proposal 5: Include our large-scale background channel calibration results for the UMA-AV scenario to support ISAC channel model calibration efforts and incorporate them in the TR.

Proposal 6: Include our full-scale background channel calibration results for the UMA-AV scenario to support ISAC channel model calibration efforts and incorporate them in the TR.

References

3GPP TSG RAN WG1 #121			R1-2504053
St, Julian’s Malta, May 19th – 23th, 2025

Agenda item:		9.7.1
Source:	China Telecom
Title:	Discussion on ISAC deployment scenarios
Document for:		Discussion

Conclusions
In this contribution, we discuss ISAC deployment scenarios related issues and have following proposals:
Proposal 1: It should be decided which concatenation method of Tx-target and target-Rx link is used in channel model calibration.
Proposal 2: For full-scale calibration, support SIR as a metric to be calibrated if interference is modeled.
Proposal 3: The SIR can be defined as follows: 

where S is defined as received power summation at sensing Rx of the signal across the sensing target from serving sensing Tx, I1 is the received signal power from target channel of other targets with the same pair of sensing Tx and Rx, and I2 is the received signal from other sensing Tx to the same sensing Rx.
Proposal 4: Support simulation assumptions for large scale calibration for human sensing targets as listed in Table 1.
Proposal 5: Support simulation assumptions for full scale calibration for human sensing targets as listed in Table 2.

3GPP TSG-RAN WG1 Meeting #121		R1-2504068
St Julian's, Malta, 19 - 23 May, 2025

Agenda item:	9.7.1
Source:	Sony
Title:	Remaining Issues on ISAC Deployment Scenarios
Document for:	Discussion and Decision

Conclusion
In this contribution, we have provided our ISAC channel model (CM) calibration results of the target channel for both large scale and full scale calibration for the case of small UAV as the sensing target. The considered sensing topologies are TRP-TRP monostatic and TRP-TRP bistatic. For the large scale, the coupling loss of sensing target channel were provided. For the full scale, the angular spread, such as Azimuth Angular Spread of Departure (ASD), Zenith Angular Spread of Departure (ZSD), Azimuth Angular Spread of Arrival (ASA), and Zenith Angular Spread of Arrival (ZSA), were given. All of the results were provided for the calibration purposes of the ISAC channel model.

TDoc file unavailable

3GPP TSG RAN WG1 #121                                          R1-2504126
St Julian’s, Malta, May 19th – 23th, 2025

Source:	CALTTA
Title:	Discussion on ISAC deployment scenarios
Agenda item:	9.7.1
Document for:	Discussion and Decision

Conclusion
In this contribution, we provide our views on details of the calibration issues and parameters for human and automotive scenarios, and we have the following proposals:
Proposal 1: Support the following for ISAC calibration:
Do not calibrate combined channel
For the calibration of optional channel modelling features, establishing a dedicated deadline, unlike the deadlines set for other calibration tasks, is unnecessary.
Proposal 2: For ISAC calibration with human as sensing target, (19.81, 4.25) dB is used as mean and standard deviation values of XPR of human.
Proposal 3: Support the calibration parameters for automotive vehicle scenario. 

TDoc file unavailable

3GPP TSG RAN WG1 #121                                  R1-2504220
St Julian’s, Malta, May 19th – 23rd, 2025

Source:	OPPO
Title:          Discussion on ISAC channel model calibration
Agenda Item:   9.7.1
Document for:  Discussion and Decision

Description
In RAN1 #120 and previous meetings, the baseline of evaluation parameters for all five sensing scenarios were agreed. In this contribution, we discuss the assumptions and metrics for channel model calibration.
Calibration assumption
Simulation assumption for human indoor/outdoor
According to the discussion in previous meetings, communication scenarios are applied for related sensing scenarios. The Table 7.8-1 and Table 7.8-2 in TR38.901 for calibration could be starting point. Table 1 could be used as simulation assumption for human indoor/outdoor scenarios. Both TRP and UE are considered as sensing node for human case. The calibration shall consider TRP mono-static mode, TRP bi-static mode, TRP-UE bi-static mode, and UE bi-static mode.
Table-1 Large-scale calibration assumptions for human indoor/outdoor scenario


Table-2 Full calibration assumptions for human indoor/outdoor scenario

Proposal 1: Use simulation assumptions in Table 1 and Table 2 for calibration of human indoor/outdoor scenarios.
Calibration result for UAV
This section provides large scale calibration result for UAV case with TRP bistatic mode and TRP monostatic mode, as shown in Figure 1. The simulation parameter assumptions are attached in Appendix.

TRP-TRP mono-static, FR1					TRP-TRP mono-static, FR2

TRP-TRP bi-static, FR1				TRP-TRP bi-static, FR2
Figure 1 Large-scale calibration results for UAV scenario
Conclusion 
This contribution is concluded with the following proposal. 
Proposal 1: Use simulation assumptions in Table 1 and Table 2 for calibration of human indoor/outdoor scenarios.
Reference 
RP-234069 New SID: Study on channel modelling for Integrated Sensing And Communication (ISAC) for NR
TR 38.901 Study on channel model for frequencies from 0.5 to 100 GHz
TR 36.777 Study on Enhanced LTE Support for Aerial Vehicles
TR 37.885 Study on evaluation methodology of new Vehicle-to-Everything (V2X) use cases for LTE and NR
TR 38.802 Study on New Radio Access Technology Physical Layer Aspects
R1-2405964 LS on Physical Properties of Sensing Targets in Automotive Scenarios for ISAC, 5GAA WG4
TR 25.996 Spatial channel model for Multiple Input Multiple Output (MIMO) simulations


Appendix
Simulation parameters assumption for calibration of UAV case

TDoc file conclusion not found

3GPP TSG RAN WG1 #121                                                                          R1-2504239
St Julian's, Malta, 19 - 23 May, 2025

Agenda item:		9.7.1
Source:	 	Lenovo
Title:		Discussion on ISAC deployment scenarios 
Document for:		Discussion and decision

Conclusion
In this contribution, we have provided initial large scale and full calibration results for the UMa-AV scenario, considering the bistatic TRP-TRP sensing scenario deployment, and following the agreed details in the previous RAN1#120bis meeting. 

3GPP TSG RAN WG1 #121		 R1-2504268
St Julian’s, Malta, May 19th - 23rd, 2025
Source: 	MediaTek Inc.
Title:	Discussion on ISAC deployment scenario
Agenda item:	9.7.1
Document for:	Discussion

Conclusion 
In this contribution, we provide the large-scale calibration results for UAV and Human outdoor scenario based on the agreed calibration parameters.
Proposal 1: Providing the above simulation results of UAV and Human outdoor scenario for calibration purpose.

3GPP TSG RAN WG1 #121		R1-2504336
St Julian’s, Malta, May 19th – 23th, 2025

Agenda Item:	9.7.1
Source:	Apple Inc.
Title:	Discussion on ISAC deployment scenarios and Calibration
Document for:	Discussion/Decision

Conclusion


Observation 1: The following calibration results have been shown

coupling loss for the LOS+ LOS path in the Human sensing target for the outdoor UMi channel 

Proposal 1: RAN1 to clarify the following:

The BS tilt angle for calibration. 
Option 1: set to zero with omni-directional antenna
Option 2: set to scenario parameters with vertically directional antenna (and horizontally omni-directional antenna)
# of UEs for calibration vs evaluation. 
In calibration we assume a hexagonal cell with a single 360 sector. However, in the evaluation case we assume 3 sectors per site with 10 UTs per cell. RAN1 to clarify if we have 10 UTs per hexagonal sector or 30 UTs per hexagonal cell

3GPP TSG RAN WG1 #121		             			           	R1-2504363
St Julian’s, Malta, May 19th – 23rd, 2025

Agenda Item: 		9.7.1
Source: 		Moderator (AT&T)
Title: 	 FL Summary #1 on ISAC Scenarios and Calibrations
Document for: 	  Discussion and Decision

Conclusion
RAN1 will consider the recommendations for the physical characteristics (e.g., sizes, shapes, materials, velocities, etc.) of sensing targets and objects provided in 5GAA LS (R1-2405964), along with the relevant characteristics defined in 3GPP TRs, within the scope of the Rel-19 study item.
No LS response from RAN1 to 5GAA is necessary.
R1-2405964 is proposed to be NOTED.

Agreement
General principles for all sensing target deployment scenarios should consider the following:
“Sensing mode” is removed in the scenario tables, but may be included in the evaluation/calibration phase. Per the SI, all sensing modes are possible for the deployment scenarios.
“Sensing area” may be addressed as part of the sensing target distribution and/or Tx/Rx characteristics and/or cell layout.



Agreement
For UAV sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#117 as a baseline.
Note: Additional parameters, value/value ranges are not precluded.

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-UAV

Details on ISAC-UAV scenarios are listed in Table x.

Table x. Evaluation parameters for UAV sensing scenarios
Note: further down-selection between the options in the table is not precluded.

RAN1#118-bis Agreements

Agreement
For Automotive sensing target scenarios, the following table is used as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for Automotive sensing scenarios
NOTE1: calibration for UMi, Uma, RMa is not performed for the automotive scenario, but UMi, Uma, RMa can be considered for future evaluations of the automotive sensing target scenarios. Calibration for UMi, Uma, RMa is expected to be performed for another sensing scenario.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Human sensing target scenarios, (indoor and outdoor), the following table is used as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for Human (indoor and outdoor) sensing scenarios

NOTE1: For the human (indoor and outdoor) sensing targets, additional communication scenarios can be considered for future evaluations. Channel model calibration for Urban Grid with outdoor humans is expected to be performed from Objects creating hazards on the road/railway sensing scenarios.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Automated Guided Vehicles (AGV) target scenarios, the following table is used as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for Automated Guided Vehicles
NOTE1: For the AGV sensing targets, additional communication scenarios can be considered for future evaluations.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.
NOTE3: RAN1 can further discuss narrowing down the number of sub-scenarios of InF


Agreement
For objects creating hazards use cases, RAN1 to consider the following table as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for objects creating hazards 

NOTE1: For the objects creating hazards sensing targets, additional communication scenarios can be considered for future evaluations. 
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.

RAN1#119 Agreements

Agreement
For UAV sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118 as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-UAV

Details on ISAC-UAV scenarios are listed in Table x.

Table x. Evaluation parameters for UAV sensing scenarios
NOTE: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Automotive sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-Automotive

Details on ISAC-Automotive scenarios are listed in Table x.


Table x. Evaluation parameters for Automotive sensing scenarios
NOTE1: calibration for UMi, Uma, RMa is not performed for the automotive scenario, but UMi, Uma, RMa can be considered for future evaluations of the automotive sensing target scenarios. Calibration for UMi, Uma, RMa is expected to be performed for another sensing scenario.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Human (indoor and outdoor) sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-Human

Details on ISAC-Human scenarios are listed in Table x.

Table x. Evaluation parameters for Human (indoor and outdoor) sensing scenarios

NOTE1: For the human (indoor and outdoor) sensing targets, additional communication scenarios can be considered for future evaluations. Channel model calibration for Urban Grid with outdoor humans is expected to be performed from Objects creating hazards on the road/railway sensing scenarios.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.



Agreement
For AGV sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-AGV

Details on ISAC-AGV are listed in Table x.

Table x. Evaluation parameters for Automated Guided Vehicles
NOTE1: For the AGV sensing targets, additional communication scenarios can be considered for future evaluations.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.
NOTE3: RAN1 can further discuss narrowing down the number of sub-scenarios of InF


Agreement
For Objects creating hazards sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-Hazards

Details on ISAC-Hazards are listed in Table x.

Table x. Evaluation parameters for objects creating hazards 

NOTE1: For the objects creating hazards sensing targets, additional communication scenarios can be considered for future evaluations. 
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


RAN1#120 Agreements for CM Calibration


Agreement
For ISAC channel modelling calibration, RAN1 considers both large-scale and full-scale calibration to include parameters and values for at least the following: 
large scale parameters, where fast fading is not included
full-scale calibration parameters, which includes fast fading.
NOTE0: one part of calibration work does not include additional components and does not include spatial consistency
FFS: whether spatial consistency is specified as an additional component for ISAC CM
NOTE1: additional calibrations including spatial consistency can also be considered case by case for different scenarios.
NOTE2: Inclusion of EO in ISAC CM calibrations can also be considered case by case for different scenarios.

Agreement
Calibration of ISAC CM includes separate calibration of the target channel and of the background channel
FFS: additional calibration for the combined channel (combination of target and background channel).


Agreement
For the purposes of large scale calibration for UAV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for large scale calibration for UAV sensing targets


RAN1#120-bis Agreements for CM Calibration (including agreements from the post-RAN1#120-bis email discussion)


Agreement
For the purposes of large scale calibration for UAV sensing targets, the following revised calibration parameters are proposed below in Table x. Note that the change bars are against the agreements from RAN1#120.


Table x. Simulation assumptions for large scale calibration for UAV sensing targets


Agreement
For the purposes of full calibration for UAV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for UAV sensing targets


Agreement
For the purposes of large scale calibrations for Automotive sensing targets, the following parameters are proposed below in Table x. 
FFS: which type of UE is used for UT in different sensing mode
FFS: impact of spatial consistency, if any, in case of vehicle with 5 scattering points
FFS: cell layout for ISD = 250 m

Table x. Simulation assumptions for large scale calibration for Automotive sensing targets


R1-2503150 Email summary on Post-120bis-ISAC-01
Endorsed proposals:
Proposal 4-2-2
Proposal 4-3-2
Proposal 5-3-1 
Proposal 5-4-2
Proposal 6-2-1 
Proposal 6-3-2
Proposal 8.1.1.1
Proposal 8-1-2 
Proposal 8-3 

Proposal 4-2-2

Proposal 4-2-2:  For the purposes of large scale calibrations for Automotive sensing targets, the following parameters are updated below in Table x based on the agreements in RAN1#120-bis. 


Table x. Simulation assumptions for large scale calibration for Automotive sensing targets



Proposal 4-3-2

Proposal 4-3-2:  For the purposes of full calibrations for Automotive sensing targets, the following parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for Automotive sensing targets


Proposal 5-3-1 

Proposal 5-3-1:  For the purposes of large scale calibration for Human (indoor and outdoor) sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for large scale calibration for Human sensing targets





Proposal 5-4-2

Proposal 5-4-2:  For the purposes of full calibration for Human sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for Human sensing targets




Proposal 6-2-1 

Proposal 6-2-1:  For the purposes of large scale calibration for AGV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for large scale calibration for AGV indoor sensing targets 



Proposal 6-3-2

Proposal 6-3-2:  For the purposes of full calibration for AGV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for AGV indoor sensing targets



Proposal 8.1.1.1

Proposal 8-1-1-1:  RAN1 may calibrate EO Type-2 for ISAC in Rel-19. Interested companies can provide results. For the purposes of EO Type-2 calibration, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for calibration of EO type-2



Proposal 8-1-2 

Proposal 8-1-2:  RAN1 may calibrate spatial consistency for ISAC in Rel-19. Interested companies can provide results. For the purposes of spatial consistency calibration, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for calibration of spatial consistency



Proposal 8-3 

Proposal 8-3:  For the purposes of full calibration for UAV sensing targets, the following update is proposed below based on the agreement from RAN1#120-bis for Coupling loss for target channel:

3GPP TSG RAN WG1 #121		             			           	R1-2504364
St Julian’s, Malta, May 19th – 23rd, 2025

Agenda Item: 		9.7.1
Source: 		Moderator (AT&T)
Title: 	 FL Summary #2 on ISAC Scenarios and Calibrations
Document for: 	  Discussion and Decision

Conclusion
RAN1 will consider the recommendations for the physical characteristics (e.g., sizes, shapes, materials, velocities, etc.) of sensing targets and objects provided in 5GAA LS (R1-2405964), along with the relevant characteristics defined in 3GPP TRs, within the scope of the Rel-19 study item.
No LS response from RAN1 to 5GAA is necessary.
R1-2405964 is proposed to be NOTED.

Agreement
General principles for all sensing target deployment scenarios should consider the following:
“Sensing mode” is removed in the scenario tables, but may be included in the evaluation/calibration phase. Per the SI, all sensing modes are possible for the deployment scenarios.
“Sensing area” may be addressed as part of the sensing target distribution and/or Tx/Rx characteristics and/or cell layout.



Agreement
For UAV sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#117 as a baseline.
Note: Additional parameters, value/value ranges are not precluded.

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-UAV

Details on ISAC-UAV scenarios are listed in Table x.

Table x. Evaluation parameters for UAV sensing scenarios
Note: further down-selection between the options in the table is not precluded.

RAN1#118-bis Agreements

Agreement
For Automotive sensing target scenarios, the following table is used as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for Automotive sensing scenarios
NOTE1: calibration for UMi, Uma, RMa is not performed for the automotive scenario, but UMi, Uma, RMa can be considered for future evaluations of the automotive sensing target scenarios. Calibration for UMi, Uma, RMa is expected to be performed for another sensing scenario.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Human sensing target scenarios, (indoor and outdoor), the following table is used as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for Human (indoor and outdoor) sensing scenarios

NOTE1: For the human (indoor and outdoor) sensing targets, additional communication scenarios can be considered for future evaluations. Channel model calibration for Urban Grid with outdoor humans is expected to be performed from Objects creating hazards on the road/railway sensing scenarios.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Automated Guided Vehicles (AGV) target scenarios, the following table is used as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for Automated Guided Vehicles
NOTE1: For the AGV sensing targets, additional communication scenarios can be considered for future evaluations.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.
NOTE3: RAN1 can further discuss narrowing down the number of sub-scenarios of InF


Agreement
For objects creating hazards use cases, RAN1 to consider the following table as a starting point for deployment scenario parameters/values.
The detailed scenario description in this clause can be used for channel model calibration.
Note: Additional parameters, value/value ranges are not precluded.

Table x. Evaluation parameters for objects creating hazards 

NOTE1: For the objects creating hazards sensing targets, additional communication scenarios can be considered for future evaluations. 
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.

RAN1#119 Agreements

Agreement
For UAV sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118 as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-UAV

Details on ISAC-UAV scenarios are listed in Table x.

Table x. Evaluation parameters for UAV sensing scenarios
NOTE: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Automotive sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-Automotive

Details on ISAC-Automotive scenarios are listed in Table x.


Table x. Evaluation parameters for Automotive sensing scenarios
NOTE1: calibration for UMi, Uma, RMa is not performed for the automotive scenario, but UMi, Uma, RMa can be considered for future evaluations of the automotive sensing target scenarios. Calibration for UMi, Uma, RMa is expected to be performed for another sensing scenario.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


Agreement
For Human (indoor and outdoor) sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-Human

Details on ISAC-Human scenarios are listed in Table x.

Table x. Evaluation parameters for Human (indoor and outdoor) sensing scenarios

NOTE1: For the human (indoor and outdoor) sensing targets, additional communication scenarios can be considered for future evaluations. Channel model calibration for Urban Grid with outdoor humans is expected to be performed from Objects creating hazards on the road/railway sensing scenarios.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.



Agreement
For AGV sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-AGV

Details on ISAC-AGV are listed in Table x.

Table x. Evaluation parameters for Automated Guided Vehicles
NOTE1: For the AGV sensing targets, additional communication scenarios can be considered for future evaluations.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.
NOTE3: RAN1 can further discuss narrowing down the number of sub-scenarios of InF


Agreement
For Objects creating hazards sensing target scenarios, the following table is agreed for deployment scenario parameters/values using the agreements from RAN1#118-bis as a baseline:

The detailed scenario description in this clause can be used for channel model calibration.

ISAC-Hazards

Details on ISAC-Hazards are listed in Table x.

Table x. Evaluation parameters for objects creating hazards 

NOTE1: For the objects creating hazards sensing targets, additional communication scenarios can be considered for future evaluations. 
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.


RAN1#120 Agreements for CM Calibration


Agreement
For ISAC channel modelling calibration, RAN1 considers both large-scale and full-scale calibration to include parameters and values for at least the following: 
large scale parameters, where fast fading is not included
full-scale calibration parameters, which includes fast fading.
NOTE0: one part of calibration work does not include additional components and does not include spatial consistency
FFS: whether spatial consistency is specified as an additional component for ISAC CM
NOTE1: additional calibrations including spatial consistency can also be considered case by case for different scenarios.
NOTE2: Inclusion of EO in ISAC CM calibrations can also be considered case by case for different scenarios.

Agreement
Calibration of ISAC CM includes separate calibration of the target channel and of the background channel
FFS: additional calibration for the combined channel (combination of target and background channel).


Agreement
For the purposes of large scale calibration for UAV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for large scale calibration for UAV sensing targets


RAN1#120-bis Agreements for CM Calibration (including agreements from the post-RAN1#120-bis email discussion)


Agreement
For the purposes of large scale calibration for UAV sensing targets, the following revised calibration parameters are proposed below in Table x. Note that the change bars are against the agreements from RAN1#120.


Table x. Simulation assumptions for large scale calibration for UAV sensing targets


Agreement
For the purposes of full calibration for UAV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for UAV sensing targets


Agreement
For the purposes of large scale calibrations for Automotive sensing targets, the following parameters are proposed below in Table x. 
FFS: which type of UE is used for UT in different sensing mode
FFS: impact of spatial consistency, if any, in case of vehicle with 5 scattering points
FFS: cell layout for ISD = 250 m

Table x. Simulation assumptions for large scale calibration for Automotive sensing targets


R1-2503150 Email summary on Post-120bis-ISAC-01
Endorsed proposals:
Proposal 4-2-2
Proposal 4-3-2
Proposal 5-3-1 
Proposal 5-4-2
Proposal 6-2-1 
Proposal 6-3-2
Proposal 8.1.1.1
Proposal 8-1-2 
Proposal 8-3 

Proposal 4-2-2

Proposal 4-2-2:  For the purposes of large scale calibrations for Automotive sensing targets, the following parameters are updated below in Table x based on the agreements in RAN1#120-bis. 


Table x. Simulation assumptions for large scale calibration for Automotive sensing targets



Proposal 4-3-2

Proposal 4-3-2:  For the purposes of full calibrations for Automotive sensing targets, the following parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for Automotive sensing targets


Proposal 5-3-1 

Proposal 5-3-1:  For the purposes of large scale calibration for Human (indoor and outdoor) sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for large scale calibration for Human sensing targets





Proposal 5-4-2

Proposal 5-4-2:  For the purposes of full calibration for Human sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for Human sensing targets




Proposal 6-2-1 

Proposal 6-2-1:  For the purposes of large scale calibration for AGV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for large scale calibration for AGV indoor sensing targets 



Proposal 6-3-2

Proposal 6-3-2:  For the purposes of full calibration for AGV sensing targets, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for full calibration for AGV indoor sensing targets



Proposal 8.1.1.1

Proposal 8-1-1-1:  RAN1 may calibrate EO Type-2 for ISAC in Rel-19. Interested companies can provide results. For the purposes of EO Type-2 calibration, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for calibration of EO type-2



Proposal 8-1-2 

Proposal 8-1-2:  RAN1 may calibrate spatial consistency for ISAC in Rel-19. Interested companies can provide results. For the purposes of spatial consistency calibration, the following calibration parameters are proposed below in Table x. 

Table x. Simulation assumptions for calibration of spatial consistency



Proposal 8-3 

Proposal 8-3:  For the purposes of full calibration for UAV sensing targets, the following update is proposed below based on the agreement from RAN1#120-bis for Coupling loss for target channel:

TDoc file unavailable

TDoc file unavailable

3GPP TSG RAN WG1 #121                       		R1-2504367
St Julian’s, Malta, May 19th – 23rd, 2025

Agenda Item:	9.7.1
Source:	AT&T, FirstNet
Title:	ISAC scenarios and 7-24GHz alignment
Document for:	Discussion/Decision

Conclusion
In this contribution, we discussed the updating the deployment scenarios for the ISAC channel model. We made the following observations and proposals:

Observation 1: Applicable communications scenarios for ISAC channel modelling does not account for new communications scenarios defined in the 7-24GHz agenda item.  Additionally, some references for the scenarios are incomplete.

Proposal 1: For ISAC evaluations, RAN1 considers the updates made in Rel. 19 SI on channel modeling for 7-24GHz as needed and applicable.
Proposal 2: RAN1 includes the following updates to the applicable communication scenario rows for Evaluation parameters for UAV sensing scenarios as shown below in Table x:
Table x. Evaluation parameters for UAV sensing scenarios

Proposal 3: RAN1 includes the following updates to the applicable communication scenario rows for Evaluation parameters for Human (indoor and outdoor) sensing scenarios as shown below in Table y:

Table y. Evaluation parameters for Human (indoor and outdoor) sensing scenarios

3GPP TSG RAN WG1 #121			 R1-2504404
Malta, Malta, May 19th – 23rd, 2025

Agenda item:	9.7.1
Source: 	Qualcomm Incorporated
Title: 	ISAC Deployment Scenarios
Document for:		Discussion

Conclusion
We have provided the calibration results for the following cases:  
UAV Sensing: Monostatic+ Bistatic TRP-TRP sensing,  option 0 + option 3
Automotive: Bistatic TRP-UE,  option 0 
Indoor Human: Bistatic TRP-UE,  option 0 + option 3

3GPP TSG-RAN WG1 Meeting #121	Tdoc R1-2504454
St Julian’s, Malta, May 19th – 23rd, 2025

Agenda Item:	9.7.1
Source:	Ericsson
Title:	Discussion on ISAC Deployment Scenarios
Document for:	Discussion, Decision
Discussion
The objective of the study on channel modelling for Integrated Sensing And Communication (ISAC) for NR [1] includes the following: 

Draft CR to TR 38.901 was provided in RAN1#120bis [2] and a follow-up one was endorsed after post-meeting email discussion [7]. The CR captures the previous agreements, but some further discussions and refinements are needed to address multiple options and FFS.
Evaluation parameters for section 7.9.1 of 38.901
Tables with the title of evaluation parameters were discussed starting from RAN1#117. A long-time ambiguity in RAN1 discussion was whether the tables are for future evaluation, calibration, or for general description of capability/restriction of ISAC channel model. Therefore, ‘a starting point’ was added in every agreement. As the need of calibration parameters arose, the discussions and agreements were about calibration only. Section 7.9.1 in the draft CR [7], quoted in Annex, captures tables which were agreed as a starting point. However, some refinements are needed to fit the tables for the section. 
Parameters in section 7.9.1 for ISAC channel model correspond to those in tables in section 7.2 of 38.901, which define the values/value ranges of parameters the channel model is valid for, i.e., validity ranges. Validity ranges of the parameters depict the capabilities and limitations of the channel model and helps readers of the TR to better understand the capabilities of the model and prevent some future work in vain. For example, the channel model is valid for specific BS antenna height for different communication scenarios. Note that the intention of parameters in section 7.2 is not for simulation or evaluation in future study items. Tables in section 7.9.1 sensing scenarios should follow the rationale in section 7.2 communication scenarios.
Tables in section 7.2 of 38.901 define the values/value ranges of parameters the channel model is valid for, i.e., validity ranges. Validity ranges of parameters depict the capabilities and limitations of the channel model and help reader of the TR to better understand the capabilities of the model and prevent some future work in vain.
Tables in section 7.9.1 sensing scenarios should follow the rationale in section 7.2 communication scenarios and define validity range of the channel model.
Regarding applicable communication scenario, a small number of scenarios were agreed for a sensing scenario to reduce the efforts of calibration, which explains ‘Calibration for UMi, Uma, RMa is expected to be performed for another sensing scenario’ in the note of agreement for automotive sensing scenario. Meanwhile, the notes in the agreements as quoted below allow additional communication scenarios considered for the future evaluations, which indicates more scenarios are also applicable communication scenario for the particular sensing scenarios. 
Notes in the agreements allow additional communication scenarios considered for the future evaluations, which indicates more scenarios are applicable communication scenario for the particular sensing scenarios.
The channel model TR should provide a complete list of applicable communication scenarios for each sensing scenario, for which we suggest Table 1, with additional scenarios in red. In particular, UMa, UMi, RMa are applicable communication scenarios for automotive, indoor human and objects creating hazards sensing scenarios. Regarding UMi UMa, and RMa for indoor human scenario, note that most indoor traffic in current 4G and 5G networks is served by outdoor macro BS and to a much lesser extent micro BS. This corresponds to the 80% indoor UT ratio in UMi and UMa scenarios in 38.901 and 50% indoor UT ratio in RMa scenario. Therefore, outdoor BSs and the large number of indoor UEs in UMa, UMi, and RMa communication scenarios can be considered as sensing transmitters/receivers for indoor human sensing scenario.
Outdoor BSs and the large number of indoor UEs in UMa, UMi, and RMa communication scenarios can be considered as sensing transmitters/receivers for indoor human sensing scenario.
Add UMa, UMi, RMa as applicable communication scenarios for automotive, indoor human and objects creating hazards sensing scenarios. 
Table 1	Sensing scenarios and corresponding applicable communication scenarios

Regarding 3D distribution of targets, three options were captured in the draft CR, such as the following for outdoor human sensing scenario. Channel model is independent from the number of targets and all targets being dropped in one cell or in every cell, since these are simulation assumption for future study item. We suggest uniform distribution as in tables in section 7.2 of 38.901. UAV and bird’s height range follows the value in the row of Height  (aerial) in Table A.1-1 of 36.777. 
Option A: N targets uniformly distributed within one cell. 
Option B: N targets uniformly distributed per cell. 
Option C: N targets uniformly distributed within an area not necessarily determined by cell boundaries. 
NOTE1: N=0 may be considered for the evaluation of false alarm

We suggest reusing uniform distribution for 3D distribution of target. For UAV height, we suggest reusing the value for Height  (aerial) in Table A.1-1 of 36.777.
The parameter minimum 3D distance between sensing targets is needed for future evaluation to determine the sensing resolution. Option 1 is sufficient to avoid spatially overlapping targets, which would not happen in real world. But Option 2 sets a restriction of channel model, and the future sensing algorithms would not be able to support a smaller resolution. 
Option 1: At least larger than the physical size of a sensing target
Option 2: Fixed value, [x] m. value of x is FFS
Option 2: Fixed value for the parameter minimum 3D distance between sensing targets sets a restriction of channel model. the future sensing algorithms would not be able to support a smaller resolution.
Support Option 1: At least larger than the physical size of a sensing target for the parameter minimum 3D distance between sensing targets.
Truck/bus, child and animal were agreed as sensing targets with the following sizes. However, their RCS models have not been discussed yet. Two sizes of AGV were agreed with only one RCS model. To fix the inconsistency, we suggest studying RCS of these targets. 
Type 3 (truck/bus): 13m x 2.6m x 3m
Child: 0.2m x 0.3m x 1m
AGV Option 1: 0.5m x 1.0m x 0.5m
AGV Option 2: 1.5 m x 3.0m x 1.5 m
Animal: 1.5m x 0.5m x 1 m
Study RCS of truck/bus, child, and animal based on agreed sizes in AI 9.7.1 and RCS of AGV of both sizes
We provide RCS models for Type-1 EO including bird and tree in our companion contribution [8]. Without Type-1 EO, the following objectives in SID are not fulfilled and the study is not complete.
Study RCS of Type-1 EO including bird and tree.
Type-2 EO is now only supported for automotives and objects creating hazards in urban grid scenario and FFS for other targets. One argument was that there are buildings and walls modelled in urban grid. However, walls are implicitly modelled by room size in indoor scenarios. Note that random orientation and random direction was agreed for 3D mobility of human. Similarly, in addition to the walls modelled in urban grid, a Type-2 EO can be modelled with a random orientation and a physical size in other outdoor scenarios and modelled reusing the room size in indoor scenarios.
Moreover, in the agreements, one table is for a sensing scenario and models just one type of sensing targets. Such simplification can reduce calibration effort, while multiple types of sensing targets may co-exist in a real scenario. One important use case of sensing is to avoid collision between different types of sensing targets, such as animals and vehicles/trains, AGVs and workers. In the future evaluations, companies can select multiple co-existing types of targets in a communication scenario, such as vehicles and outdoor humans in UMa scenario. In this sense, a single table of parameters in section 9.7.1 is sufficient, and there is no need to generate tables for separate sensing scenarios in section 9.7.1. 
In addition to the walls modelled in urban grid, a Type-2 EO can be modelled with a random orientation and a physical size in other outdoor scenarios and modelled reusing the room size in indoor scenarios.
To reduce calibration effort, only one type of targets is modelled in a sensing scenario. However, multiple types of sensing targets may co-exist in a scenario.
One table of parameters in section 9.7.1 is sufficient. There is no need to generate tables for separate sensing scenarios in section 9.7.1. 
With all the discussions, Table 2 summarizes ISAC parameters for section 7.9.1 of 38.901.
Support the parameters in Table 2 for section 7.9.1 of 38.901.
Table 2	ISAC parameters for section 7.9.1 of 38.901
To help readers have a quick and clear understanding of each sensing scenario, we suggest a brief introduction preceding the table. Similar approach has been adopted for RMa, Indoor Factory scenario, and SMa scenario in 38.901. 
ISAC-UAV
In the ISAC-UAV scenario, the sensing targets are outdoor UAVs below or above the buildings in urban or rural areas. Monostatic or bistatic sensing can be performed using TRPs and/or UEs, including UEs on other UAVs.
ISAC-Automotive
In the ISAC-Automotive scenario, the sensing targets are passenger vehicles or trucks and buses traveling on roads and streets in urban and rural areas. Monostatic or bistatic sensing can be performed using TRPs and/or UEs, including UEs on other vehicles and roadside UEs (RSU-type UEs).
ISAC-Human
In the ISAC-Human scenario, the sensing targets are children and adult persons in indoor (room, office, factory) and outdoor (urban, rural) locations. Monostatic or bistatic sensing can be performed using TRPs and/or UEs in the corresponding communication scenarios. 
ISAC-AGV
In the ISAC-AGV scenario, the sensing targets are automated guided vehicles (AGVs) inside a factory. Monostatic or bistatic sensing can be performed using TRPs and/or UEs in the corresponding communication scenario. 
ISAC-Objects creating hazards
In the ISAC-Objects creating hazards scenario, the sensing targets are adult humans and children [and animals] in communication scenarios involving vehicles or high-speed trains. Monostatic or bistatic sensing can be performed using TRPs and/or UEs, including UEs on other vehicles and roadside UEs (RSU-type UEs).
Add the short description of sensing scenarios preceding table of evaluation parameters in section 7.9.1 of 38.901.
Conclusion
In the previous sections we made the following observations: 
Observation 1	Tables in section 7.2 of 38.901 define the values/value ranges of parameters the channel model is valid for, i.e., validity ranges. Validity ranges of parameters depict the capabilities and limitations of the channel model and help reader of the TR to better understand the capabilities of the model and prevent some future work in vain.
Observation 2	Tables in section 7.9.1 sensing scenarios should follow the rationale in section 7.2 communication scenarios and define validity range of the channel model.
Observation 3	Notes in the agreements allow additional communication scenarios considered for the future evaluations, which indicates more scenarios are applicable communication scenario for the particular sensing scenarios.
Observation 4	Option 2: Fixed value for the parameter minimum 3D distance between sensing targets sets a restriction of channel model. the future sensing algorithms would not be able to support a smaller resolution.
Observation 5	To reduce calibration effort, only one type of targets is modelled in a sensing scenario. However, multiple types of sensing targets may co-exist in a scenario.

Based on the discussion in the previous sections we propose the following:
Proposal 1	Outdoor BSs and the large number of indoor UEs in UMa, UMi, and RMa communication scenarios can be considered as sensing transmitters/receivers for indoor human sensing scenario.
Proposal 2	Add UMa, UMi, RMa as applicable communication scenarios for automotive, indoor human and objects creating hazards sensing scenarios.
Proposal 3	We suggest reusing uniform distribution for 3D distribution of target. For UAV height, we suggest reusing the value for Height  (aerial) in Table A.1-1 of 36.777.
Proposal 4	Support Option 1: At least larger than the physical size of a sensing target for the parameter minimum 3D distance between sensing targets.
Proposal 5	Study RCS of truck/bus, child, and animal based on agreed sizes in AI 9.7.1 and RCS of AGV of both sizes
Proposal 6	Study RCS of Type-1 EO including bird and tree.
Proposal 7	In addition to the walls modelled in urban grid, a Type-2 EO can be modelled with a random orientation and a physical size in other outdoor scenarios and modelled reusing the room size in indoor scenarios.
Proposal 8	One table of parameters in section 9.7.1 is sufficient. There is no need to generate tables for separate sensing scenarios in section 9.7.1.
Proposal 9	Support the parameters in Table 2 for section 7.9.1 of 38.901.
Proposal 10	Add the short description of sensing scenarios preceding table of evaluation parameters in section 7.9.1 of 38.901.

Annex
7.9.1	Scenarios
The detailed sensing scenario description in this clause can be used for channel model calibration.
ISAC-UAV
Details on ISAC-UAV scenarios are listed in Table 7.9.1-1.
Table 7.9.1-1: Evaluation parameters for UAV sensing scenarios
NOTE: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.

ISAC-Automotive
Details on ISAC-Automotive scenarios are listed in Table 7.9.1-2.
Table 7.9.1-2: Evaluation parameters for Automotive sensing scenarios
NOTE1: calibration for UMi, Uma, RMa is not performed for the automotive scenario, but UMi, Uma, RMa can be considered for future evaluations of the automotive sensing target scenarios. Calibration for UMi, Uma, RMa is expected to be performed for another sensing scenario.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.

ISAC-Human
Details on ISAC-Human scenarios are listed in Table 7.9.1-3.
Table 7.9.1-3: Evaluation parameters for Human (indoor and outdoor) sensing scenarios
NOTE1: For the human (indoor and outdoor) sensing targets, additional communication scenarios can be considered for future evaluations. Channel model calibration for Urban Grid with outdoor humans is expected to be performed from Objects creating hazards on the road/railway sensing scenarios.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.

ISAC-AGV
Details on ISAC-AGV are listed in Table 7.9.1-4.
Table 7.9.1-4: Evaluation parameters for Automated Guided Vehicles
NOTE1: For the AGV sensing targets, additional communication scenarios can be considered for future evaluations.
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.
NOTE3: RAN1 can further discuss narrowing down the number of sub-scenarios of InF

ISAC-Objects creating hazards
Details on ISAC-Hazards are listed in Table 7.9.1-5.
Table 7.9.1-5: Evaluation parameters for objects creating hazards 
NOTE1: For the objects creating hazards sensing targets, additional communication scenarios can be considered for future evaluations. 
NOTE2: A percentage of TRPs/UEs that have sensing capabilities may be considered for future evaluations.
References
RP-242348, Revised SID: Study on channel modelling for Integrated Sensing And Communication (ISAC) for NR, Xiaomi, AT&T, 3GPP TSG RAN Meeting #105, September 2024
R1-2502552, Draft CR to introduce channel model for ISAC, Xiaomi, AT&T, RAN1 #120bis, April, 2025
R1-2405964, LS on Physical Properties of Sensing Targets in Automotive Scenarios for ISAC, 5GAA, RAN1#118, August 2024
TR 22.837, Feasibility Study on Integrated Sensing and Communication, v19.1.0, September 2023
P.S.Bokare and A.K.Maurya, “Acceleration-Deceleration Behaviour of Various Vehicle Types,” World Conference on Transport Research, WCTR 2016 Shanghai. 10-15 July 2016
TR 36.878, Study on performance enhancements for high speed scenario in LTE, v13.0.0, January 2016
R1-2503157, Draft CR for TR 38.901 to introduce channel model for ISAC, Xiaomi, AT&T, RAN1 #120bis, April, 2025
R1-2504455, Discussion on ISAC Channel Modelling, Ericsson, RAN1 #121, May, 2025

TDoc file conclusion not found

3GPP TSG RAN WG1 #121			        R1-2504539
St Julian's, Malta, May 19th – 23rd, 2025

Agenda item:	9.7.1
Source: 	ITRI, Tron Future Tech Inc.
Title: 	Discussion of calibration for UAV sensing targets
Document for:	Discussion and Decision

Conclusions
In this contribution, we provide our results on large scale calibration for UAV sensing target, and the following proposal is made:

Proposal: Calibration results for large scale calibration to be captured in the TR are evaluated based on simulation assumptions for UAV sensing targets.

3GPP TSG RAN WG1 Meeting #121  	          	     		R1-2504566
St Julian’s, Malta, May 19-23, 2025
_____________________________________________________________________Agenda item: 9.7.1
Source: LG Electronics
Title: 	Discussion on ISAC deployment scenarios
Document for: Discussion and decision

Conclusions
In this contribution, the ISAC deployment scenarios were discussed. The following observations and proposals were made as conclusions.
Proposal 1: Only a single type of sensing target that needs to be detected in the associated sensing scenario is dropped for evaluation.
Proposal 2: If the multiple types of sensing target objects are allowed for dropping in a sensing scenario, except the sensing target that needs to be detected in the sensing scenario, other types of sensing target objects are modeled as type-1 EO.
Proposal 3: In UAV sensing, in option C for the horizontal plane of 3D distribution of a sensing target, ‘the area not necessarily determined by cell boundaries’ is defined by a sphere space, which is represented by the 3D center position and the radius.
Proposal 4: In the automotive sensing scenario, only the wall having the single-bounce specular reflection point is modelled for evaluation.
Proposal 5: In human sensing, for the horizontal plane of 3D distribution of a sensing target, both option A and C are supported.
Option A: N targets uniformly distributed within one cell. 
Option C: N targets uniformly distributed within an area not necessarily determined by cell
Proposal 6: In human sensing, for option C for the horizontal plane of 3D distribution of a sensing target, ‘the area not necessarily determined by cell boundaries’ is defined by a 2D circle space, which is represented by the center position and the radius.
Proposal 7: For the human indoor sensing scenario, the walls, ceil and floor inside the indoor space are modeled as type-2 EO.
Proposal 8: In AGV sensing, for the horizontal plane of 3D distribution of a sensing target, option B is supported.
Option B: Uniformly distributed in horizontal plane
Proposal 9: For the automated guided vehicle sensing scenario, the walls, ceil and floor inside the factory are modeled as type-2 EO.
Proposal 10: In AGV sensing, for the horizontal plane of 3D distribution of a sensing target, option B is supported.
For the evaluation parameters, we have FFS point regarding the number of buildings as follows.
Proposal 11: In the hazardous object sensing scenario, only the wall having the single-bounce specular reflection point is modelled for evaluation.
Proposal 12: Remove the bracket for the power threshold and FFS point in the row for the power threshold for removing clusters in step 6 in section 7.5, TR 38.901 for background channel, in the full calibration tables for UAV, human and AGV.
Proposal 13: Just adopt the power threshold for path dropping after concatenation for target channel, which is agreed from the ISAC channel modelling agenda, and remove the FFS point in the full calibration tables for UAV, automotive, human, AGV,

3GPP TSG RAN WG1 #121	R1-2504705
St Julian’s, Malta, May 19th – 23th, 2025

Title 	: Discussion on ISAC channel model calibration
Source 	:  NTT DOCOMO, INC.
Agenda item	:  9.7.1
Document for:  Discussion and Decision

Conclusion
In this contribution, we provide our large scale calibration results for UAV sensing targets and the following proposal is made:
Proposal 1: Our large scale calibration results for TRP-TRP bistatic and TRP-UE bistatic target channel for UAV sensing targets shown in Fig. 1, 2 and 3 should be considered and incorporated in the TR.

3GPP TSG RAN WG1 #121							R1-2504950	
St Julian’s, Malta, May 19th – 23rd, 2025

Agenda item:	9.7.1
Source:	Moderator (AT&T)
Title:	Initial ISAC calibration results
Document for:	Information

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