IP Library › Granted Patent US 12,284,099
Granted Patent B2
US 12,284,099 · App. 17/417,706 · Granted Apr 22, 2025

Method for latency estimation in wireless networks

Inventors: Roman Zhohov (Linkoping, SE); Dimitar Minovski (Skelleftea, SE); Per Gustaf Anders Johansson (Skelleftea, SE); Niclas Ögren (Ursviken, SE); Irina Cornelia Cotanis (Warrentown, VA)
Assignee: INFOVISTA SAS
H04L43/0852H04L41/14H04L41/16H04W24/02H04W24/08H04W36/0085
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,284,099
App. No.
17/417,706
Granted
Apr 22, 2025
Kind
B2
Abstract

A method for estimating up-link latency, and/or down-link latency, and/or round-trip latency in a packet based wireless network for communication between two network nodes, wherein the method includes: a. measuring one or more metrics and/or using information from network procedures to estimate metrics, wherein the metrics have at least one or more of radio metrics available to a UE (User Equipment) or to a BS (Base Station) or similar access-point, b. measuring the metrics defined in a) either in a dedicated mode using packet sequence, and/or in a dedicated mode using available traffic, and/or in an idle mode, c. measuring the metrics defined in a) both on a serving and a non-serving cells, and/or beams, d. estimating up-link latency, and/or down-link latency, and/or round-trip latency by using multivariable, non-linear or linear function prediction, machine learning based prediction or mathematical or logical predictions based on the metrics defined in a).

Claims (165)

1. A method for estimating latency in a packet based wireless network for communication between two network nodes, wherein the method comprises:

a. measuring at least one of the following metrics while in idle mode from a serving cell and/or non-serving cell and/or beams:

i. total received power at a user equipment,

ii. pilot signals power,

iii. reference signals power,

iv. interference power,

v. noise power,

vi. signal to noise ratio,

vii. signal to interference-plus-noise ratio,

viii. number of re-transmissions,

ix. cell re-selection,

x. cell configuration;

b. estimating latency by using multivariable, non-linear or linear function prediction, machine learning based prediction or mathematical or logical predictions based on the at least one metric,

c. wherein the at least one measured metric is filtered and/or, when several metrics are measured, aggregated during a measurement window to create new higher level at least one metric resulting in improved latency estimation accuracy, where the measurement window comprises either one or several combinations of:

a. measurements from prior time,

b. measurements during the transmission interval,

c. measurements within a spatial area.

2. The method according to claim 1 , wherein the wireless network is an UMTS network, wherein the method further comprises:

a. using at least one of the following metrics while in dedicated mode:

i. Cell re-selection,

ii. Cell configuration,

iii. Physical throughput,

iv. Handover,

v. Dynamic Channel Assignment (DCA),

vi. Timeslot Interference Signal Code Power (ISCP),

vii. Received Signal Code Power (RSCP) from one or more detectable cells,

viii. Common Pilot Channel (CPICH) Ec/No from one or more detectable cells,

ix. Evolved Universal Terrestrial Radio Access (E-UTRA) Reference signal Receive Power (RSRP) from one or more detectable cells,

x. Evolved Universal Terrestrial Radio Access (E-UTRA) Reference Signal Receive Quality (RSRQ) from one or more detectable cells,

xi. Evolved Universal Terrestrial Radio Access (E-UTRA) Signal-to-interference-plus-noise ratio (SINR),

xii Universal Terrestrial Radio Access (UTRA) carrier Received Strength Indicator (RSSI) from one or more detectable cells,

xiii. Global System for Mobile Communication (GSM) carrier Received Signal Strength Indicator (RSSI) from one or more detectable cells,

xiv. Signal to interference ratio (SIR),

xv. Transport channel Block Error Rate (BLER),

xvi. User Equipment (UE) transmitted power,

xvii. User Equipment (UE) Global System for Mobile Communication (GPS),

b. or using at least one of the following metrics while in idle mode:

i. Cell re-selection,

ii. Cell configuration,

iii. Timeslot Interference signal code power (ISCP),

iv. received signal code power (RSCP) from one or more detectable cells,

v. Evolved Universal Terrestrial Radio Access (E-UTRA) Reference Signal Receive Power (RSRP) from one or more detectable cells,

vi. Evolved Universal Terrestrial Radio Access (E-UTRA) Reference Signal Receive Quality (RSRQ) from one or more detectable cells,

vii. Evolved Universal Terrestrial Radio Access (E-UTRA) Signal-to-interference-plus-noise ratio (SINR),

viii. Universal Terrestrial Radio Access (UTRA) carrier Received Signal Strength Indicator (RSSI) from one or more detectable cells,

ix. Global System for Mobile Communication (GSM) carrier received Signal Strength Indicator (RSSI) from one or more detectable cells,

x. Signal to interference ratio (SIR),

xi. Transport channel Block Error Rate (BLER),

xii. User Equipment (UE) transmitted power,

xiii. User Equipment (UE) Global System for Mobile Communication (GPS).

3. The method according to claim 1 , wherein the wireless network is an LTE network, wherein the method further comprises:

a) using at least one of the following metrics while in dedicated mode

i. Received Signal Strength Indicator (RSSI),

ii. Received Power, received quality, carrier to interference plus noise ratio, signal to interference plus noise ratio, retrieved from the:

1. Channel State Information Reference Signal (CSI-RS),

2. Multicast Broadcast Single Frequency Network Reference Signal (MBSFN-RS),

3. Cell Specific Reference Signal (CRS),

4. User Equipment Reference Signal (UERS),

5. Positioning Reference Signal (PRS),

6. Demodulation Reference Signal (DMRS),

7. Secondary Synchronization Signal (SSS),

8. Sounding Reference Signal (SRS),

iii. Physical Downlink Shared Channel (PDSCH) Physical Throughput,

iv. Physical Uplink Shared Channel (PUSCH) Physical Throughput,

v. Transmit Power per bandwidth and/or per reference signal/channel,

vi. Channel Quality Indicator (CQI) Code,

vii. Cell re-selection,

viii. Handover Information,

ix. Intra-frequency Handover,

X. Re-transmissions,

xi. Block Error Rate (BLER),

xii. Carrier Aggregation, and

xiii. Cell configuration,

b. or using at least one of the following metrics while in idle mode:

i. Received Signal Strength Indicator (RSSI),

ii. Received Power, received quality, carrier to interference plus noise ratio, signal to interference plus noise ratio, retrieved from the:

1. Channel State Information Reference Signal (CSI-RS)

2. Multicast Broadcast Single Frequency Network Reference Signal (MBSFNRS)

3. Cell Specific Reference Signal (CRS)

4. User Equipment Reference Signal (UERS)

5. Positioning Reference Signal (PRS)

6. Demodulation Reference Signal (DMRS),

7. Secondary Synchronization Signal (SSS), or

8. Sounding Reference Signal (SRS),

iii. Transmit Power per bandwidth and/or per reference signal/channel,

iv. Cell re-selection,

v. Carrier Aggregation,

vi. Cell configuration.

4. The method according to claim 1 , wherein the wireless network is an 5G/NR network, wherein the method further comprises:

a. using at least one of the following metrics while in dedicated mode:

i. Received Signal Strength Indicator (RSSI) from one or more detectable cells and/or beams,

ii. Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Signal to Interference Plus Noise Ratio (SINR)/channel quality, retrieved from the:

1. Secondary Synchronization Signal (SSS),

2. Channel State Information Reference Signal (CSI-RS),

3. Sounding Reference Signal (SRS),

4. Demodulation Reference Signal (DMRS),

5. Phase Tracking Reference Signal (PTRS),

6. Beam Reference Signal (BRS),

iii. Transmit Power per bandwidth and/or per reference signal/channel,

iv. User Equipment Global Navigation Satellite System (UE GNSS),

v. Reference Signal Time Difference (RSTD),

vi. Framing Time Difference (SFTD),

vii. System Frame Number (SFN),

viii. BeamIdx,

ix. Beam acquisition,

x. Handover (HO) Info,

xi. Intra-frequency Handover,

xii. Block Error Rate (BLER),

xiii. Physical and application layer throughput,

xiv. Carrier Aggregation,

xv. Transmission Point Configuration Information (TPCI),

xvi. Cell configuration,

xvii. Modulation schema,

xviii. Frequency spacing,

xix. Channel Quality Indicator (CQI),

xx. Rank Indicator (RI),

b. or using at least one of the following metrics while in idle mode:

i. Received Signal Strength Indicator (RSSI) from one or more detectable cells and/or beams,

ii. reference signal received power (RSRP), reference signal received quality (RSRQ), signal to interference plus noise ratio (SINR)/channel quality, retrieved from the:

1. Secondary synchronization signal (SSS),

2. Channel state information reference signal (CSI-RS),

3. Sounding reference signal (SRS),

4. Demodulation reference signal (DMRS),

5. Phase tracking reference signal (PTRS),

6. Beam reference signal (BRS),

iii. user equipment Global navigation satellite system (UE GNSS),

iv. reference signal time difference (RSTD),

v. Framing time difference (SFTD),

vi. system frame number (SFN),

vii. block error rate (BLER),

viii. Cell configuration,

ix. Frequency spacing.

5. The method according to claim 1 , wherein the at least one metric is measured and/or derived from one or more of:

a. Physical layer,

b. Medium Access Control/Data Link (MAC/DL) layer,

c. Radio Link Control/Radio Resource Control/Radio Resource Management (RLC/RRC/RR) layer,

d. Packet Data Convergence Protocol (PDCP) layer,

e. Non-Access Stratum (NAS) layer,

f. transport layer,

g. Application layer.

6. The method according to claim 1 , wherein the method further comprises the step of measuring at least one of the following metrics while in dedicated mode using packet sequence and/or available traffic from a serving cell and/or beams:

ii. throughput,

iii. block error rate,

iv. total received power at a user equipment,

v. pilot signals power,

vi. reference signals power,

vii. interference power,

viii. noise power,

ix. signal to noise ratio,

x. signal to interference-plus-noise ratio,

xi. transmit power,

xii. used modulation scheme,

xiii. handover,

xiv. number of re-transmissions,

xv. cell re-selection,

xvi. cell configuration,

xvii. carrier aggregation,

xviii. spatial and/or temporal multiplexing,

xix. beam acquisition,

xx. beam switching,

xxi. phase tracking.

7. A system, comprising:

a. one or more processors;

b. one or more non-transitory storage media storing instructions which, when executed by the one or more processors, cause in a packet based wireless network for communication between two network nodes, the implementation of the method of claim 1 .

8. The system according to claim 7 , wherein at least one of the two network nodes is either deployed physically or virtually, and consists of a User Equipment, and/or a Base Station, and/or any node with wireless network interface.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 23, 2021
From: ZHOHOV, ROMAN; MINOVSKI, DIMITAR; JOHANSSON, PER GUSTAF ANDERS; ÖGREN, NICLAS; CORNELIA COTANIS, IRINA
To: INFOVISTA SAS
Reel/Frame 056643/0311 →
Priority Claims (1)
EP 18306881 · Dec 28, 2018 · regional
Continuity (1)
Related Publication 20220078099A1 · Mar 10, 2022
References Cited (27)
US 20070217343A1 · Znamova · 2007 [cited by examiner]
US 20120131129A1 · Agarwal · 2012 [cited by examiner]
US 20150263921A1 · Lee et al. · 2015 [cited by applicant]
US 20180175926A1 · Rudrapatna · 2018 [cited by applicant]
US 20200195539A1 · Sivaraj · 2020 [cited by examiner]
US 20210266247A1 · Sivaraj · 2021 [cited by examiner]
Zhu et al., “On the Accuracy of Packet Delay Estimation in Distributed Service Networks,” Journal of Network and Systems Management, vol. 21, (4), pp. 623-649, Dec. 2013 (Year: 2013). [cited by examiner]
European Search Report and Written Opinion received for Application No. 18306881.6, dated May 28, 2019. [cited by applicant]
International Search Report and Written Opinion received for PCT/EP2019/085204, mailed Feb. 17, 2020. [cited by applicant]
Corcoran, P., “A Matter of Timing: Consumer Electronics and Network Time,” IEEE Consumer Electronics Magazine, vol. 2, No. 4, 2013, pp. 20-25. [cited by applicant]
Eidson, J., et al., “IEEE Standard for a Precision Clock Synchronization Protocol for Networked Measurement and Control Systems and Applications to the Power Industry,” IEEE Std 1588-2008, (Revision of IEEE Std 1588-200… [cited by applicant]
Endace Technology Limited, “IEEE 1588 PTP clock synchronization over a WAN backbone,” 2016, 14 pages. [cited by applicant]
Goodfellow, I., et al. “Deep learning,” vol. 1, Chapter 12: Applications (George Dahl, et al.), Cambridge: MIT press, 2016, pp. 443-485. [cited by applicant]
Huawei, et al., “Radio measurements for feMDT,” Discussion and Decision, Agenda Item 7.8, SI: Further MDT enhancements, Fukuoka, Japan, May 2015, 2 pages. [cited by applicant]
Infovista Sas, “A Machine Learning Approach in SG12,” Study Group 12: Discussion on Machine Learning, Telecommunication Standardization Sector, Geneva, Switzerland, Nov.-Dec. 2018, 4 pages. [cited by applicant]
Kopetz, H., “Real-time systems: design principles for distributed embedded applications,” Chapter 7: Real-Time Communications, Springer Science & Business Media, 2011, pp. 145-171. [cited by applicant]
Kyocera, “Potential solutions for UL latency measurements,” Discussion and Decision, Agenda Item 7.8, Fukuoka, Japan, May 2015, 2 pages. [cited by applicant]
Mills, D., et al., “Network Time Protocol Version 4: Protocol and Algorithms Specification,” Network, 2010, 110 pages. [cited by applicant]
Sutton, C., “Classification and Regression Trees, Bagging, and Boosting,” Handbook of Statistics, vol. 24, 2005, pp. 303-329. [cited by applicant]
Wang, M., et al., “Machine Learning for Networking: Workflow, Advances and Opportunities,” IEEE Network, vol. 32, No. 2, 2018, pp. 92-99. [cited by applicant]
Yuan, Z., et al., “A Machine Learning Based Approach to Mobile Network Analysis,” 27th IEEE International Conference on Computer Communication and Networks, Jul. 2018, 9 pages. [cited by applicant]
3GPP, TS 36.213, “3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical layer procedures,” Technical Specification, Release… [cited by applicant]
3GPP ,TS 36.211, “3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Physical channels and modulation,” Technical Specification, … [cited by applicant]
3GPP, TS 36.321, “LTE; Evolved Universal Terrestrial Radio Access(E-UTRA); Medium Access Control (MAC) protocol specification,” Technical Specification, Version 10.1.0, Release 10, 2011, 55 pages. [cited by applicant]
3GPP, TS 36.322, “Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Link Control (RLC) protocol specification,” version 10.0.0, Release 10, 2011, 42 pages. [cited by applicant]
3GPP, TS 28.627, “3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Telecommunication Management; Self-Organizing Networks (SON) Policy Network Resource Model (NRM) Integrati… [cited by applicant]
3GPP, TS 38.201, “5G; NR; Physical layer; General description,” Technical Specification; version 15.0.0, Release 15, 2018, 14 pages. [cited by applicant]