Patent Application
20230412290
Exemplary embodiments herein relate generally to wireless networks and, more specifically, relates to determining whether user equipment (UEs) need measurement modifications, e.g., for radio resource management (RRM) modifications and/or are stationary in the networks.
In 3GPP Rel-17 (third generation project, release 17), reduced capability (RedCap) UEs will be introduced. See, e.g., Ericsson, “New SID on Support of Reduced Capability NR Devices”, RP-193238, 3GPP TSG RAN Meeting #86, Sitges, Spain, Dec. 9-12, 2019. The intended use cases for RedCap UEs include the following.
1) Industrial wireless sensors: Communication service availability is 99.99% and end-to-end latency less than 100 ms. The reference bit rate is less than 2 Mbps (potentially asymmetric, e.g., uplink heavy traffic) for all use cases and the device is stationary. The battery should last at least a few years. For safety-related sensors, latency requirement is lower, 5-10 ms.
2) Video Surveillance: As described in 3GPP TR (technical report) 22.804 (see 3GPP TR 22.804 V16.3.0 (2020-07)), reference economic video bitrate would be 2-4 Mbps, latency <500 ms, reliability 99%-99.9%. High-end video, e.g., for farming, would require 7.5-25 Mbps. It is noted that traffic pattern is dominated by UL (uplink) transmissions.
3) Wearables: Reference bitrate for a smart wearable application can be 10-50 Mbps in DL (downlink) and minimum 5 Mbps in UL and peak bit rate of the device is higher, 150 Mbps for downlink and 50 Mbps for uplink. Battery of the device should last multiple days (up to 1-2 weeks).
The study item (RP-193238) has the following objective:
Study UE power saving and battery lifetime enhancement for reduced capability UEs in applicable use cases (e.g. delay tolerant):
1) Reduced PDCCH (physical downlink control channel) monitoring by smaller numbers of blind decodes and CCE (control channel element) limits.
2) Extended DRX (discontinuous reception) for RRC (radio resource control) Inactive and/or Idle state.
3) RRM (radio resource management) relaxation for stationary devices.
One issue with these reduced capability UEs is determining stationarity of the devices.
This section is intended to include examples and is not intended to be limiting.
In an exemplary embodiment, a method is disclosed that includes receiving, by a user equipment connected to a base station in a wireless network, one or more parameters to be used to identify the user equipment for measurement modification. The method includes determining an estimate of a level of signal variation for signals received at the user equipment, and identifying, using at least the one or more parameters, the user equipment for measurement modification based at least on the estimate of the level of signal variation. The method further includes modifying, by the user equipment, a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification.
An additional exemplary embodiment includes a computer program, comprising code for performing the method of the previous paragraph, when the computer program is run on a processor. The computer program according to this paragraph, wherein the computer program is a computer program product comprising a computer-readable medium bearing computer program code embodied therein for use with a computer. Another example is the computer program according to this paragraph, wherein the program is directly loadable into an internal memory of the computer.
An exemplary apparatus includes one or more processors and one or more memories including computer program code. The one or more memories and the computer program code are configured to, with the one or more processors, cause the apparatus to perform operations comprising: receiving, by a user equipment connected to a base station in a wireless network, one or more parameters to be used to identify the user equipment for measurement modification; determining an estimate of a level of signal variation for signals received at the user equipment; identifying, using at least the one or more parameters, the user equipment for measurement modification based at least on the estimate of the level of signal variation; and modifying, by the user equipment, a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification.
An exemplary computer program product includes a computer-readable storage medium bearing computer program code embodied therein for use with a computer. The computer program code includes: code for receiving, by a user equipment connected to a base station in a wireless network, one or more parameters to be used to identify the user equipment for measurement modification; code for determining an estimate of a level of signal variation for signals received at the user equipment; code for identifying, using at least the one or more parameters, the user equipment for measurement modification based at least on the estimate of the level of signal variation; and code for modifying, by the user equipment, a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification.
In another exemplary embodiment, an apparatus comprises means for performing: receiving, by a user equipment connected to a base station in a wireless network, one or more parameters to be used to identify the user equipment for measurement modification; determining an estimate of a level of signal variation for signals received at the user equipment; identifying, using at least the one or more parameters, the user equipment for measurement modification based at least on the estimate of the level of signal variation; and modifying, by the user equipment, a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification.
In an exemplary embodiment, a method is disclosed that includes determining, by a base station, one or more parameters to be used by a user equipment in order to identify the user equipment for measurement modification. The method also includes signaling the one or more parameters to the user equipment.
An additional exemplary embodiment includes a computer program, comprising code for performing the method of the previous paragraph, when the computer program is run on a processor. The computer program according to this paragraph, wherein the computer program is a computer program product comprising a computer-readable medium bearing computer program code embodied therein for use with a computer. Another example is the computer program according to this paragraph, wherein the program is directly loadable into an internal memory of the computer.
An exemplary apparatus includes one or more processors and one or more memories including computer program code. The one or more memories and the computer program code are configured to, with the one or more processors, cause the apparatus to perform operations comprising: determining, by a base station, one or more parameters to be used by a user equipment in order to identify the user equipment for measurement modification; and signaling the one or more parameters to the user equipment.
An exemplary computer program product includes a computer-readable storage medium bearing computer program code embodied therein for use with a computer. The computer program code includes: code for determining, by a base station, one or more parameters to be used by a user equipment in order to identify the user equipment for measurement modification; and code for signaling the one or more parameters to the user equipment.
In another exemplary embodiment, an apparatus comprises means for performing: determining, by a base station, one or more parameters to be used by a user equipment in order to identify the user equipment for measurement modification; and signaling the one or more parameters to the user equipment.
In the attached Drawing Figures:
Abbreviations that may be found in the specification and/or the drawing figures are defined below, at the end of the detailed description section.
The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. All of the embodiments described in this Detailed Description are exemplary embodiments provided to enable persons skilled in the art to make or use the invention and not to limit the scope of the invention which is defined by the claims.
The exemplary embodiments herein describe techniques for dynamic UE signal level correction for stationarity detection. Additional description of these techniques is presented after a system into which the exemplary embodiments may be used is described.
Turning to
The RAN node 170 is a base station that provides access by wireless devices such as the UE 110 to the wireless network 100. In the text below, the term “base station” (or BS) is also used for the RAN node 170. The RAN node 170 may be, for instance, a base station for 5G, also called New Radio (NR). In 5G, the RAN node 170 may be a NG-RAN node, which is defined as either a gNB or an ng-eNB. A gNB is a node providing NR user plane and control plane protocol terminations towards the UE, and connected via the NG interface to a 5GC (e.g., the network element(s) 190). The ng-eNB is a node providing E-UTRA user plane and control plane protocol terminations towards the UE, and connected via the NG interface to the 5GC. The NG-RAN node may include multiple gNBs, which may also include a central unit (CU) (gNB-CU) 196 and distributed unit(s) (DUs) (gNB-DUs), of which DU 195 is shown. Note that the DU may include or be coupled to and control a radio unit (RU). The gNB-CU is a logical node hosting RRC, SDAP and PDCP protocols of the gNB or RRC and PDCP protocols of the en-gNB that controls the operation of one or more gNB-DUs. The gNB-CU terminates the F1 interface connected with the gNB-DU. The F1 interface is illustrated as reference 198, although reference 198 also illustrates a link between remote elements of the RAN node 170 and centralized elements of the RAN node 170, such as between the gNB-CU 196 and the gNB-DU 195. The gNB-DU is a logical node hosting RLC, MAC and PHY layers of the gNB or en-gNB, and its operation is partly controlled by gNB-CU. One gNB-CU supports one or multiple cells. One cell is supported by one gNB-DU. The gNB-DU terminates the F1 interface 198 connected with the gNB-CU. Note that the DU 195 is considered to include the transceiver 160, e.g., as part of an RU, but some examples of this may have the transceiver 160 as part of a separate RU, e.g., under control of and connected to the DU 195. The RAN node 170 may also be an eNB (evolved NodeB) base station, for LTE (long term evolution), or any other suitable base station.
The RAN node 170 includes one or more processors 152, one or more memories 155, one or more network interfaces (N/W I/F(s)) 161, and one or more transceivers 160 interconnected through one or more buses 157. Each of the one or more transceivers 160 includes a receiver, Rx, 162 and a transmitter, Tx, 163. The one or more transceivers 160 are connected to one or more antennas 158. The one or more memories 155 include computer program code 153. The CU 196 may include the processor(s) 152, memories 155, and network interfaces 161. Note that the DU 195 may also contain its own memory/memories and processor(s), and/or other hardware, but these are not shown.
The RAN node 170 includes a control module 150, comprising one of or both parts 150-1 and/or 150-2, which may be implemented in a number of ways. The control module 150 may be implemented in hardware as control module 150-1, such as being implemented as part of the one or more processors 152. The control module 150-1 may be implemented also as an integrated circuit or through other hardware such as a programmable gate array. In another example, the control module 150 may be implemented as control module 150-2, which is implemented as computer program code 153 and is executed by the one or more processors 152. For instance, the one or more memories 155 and the computer program code 153 are configured to, with the one or more processors 152, cause the RAN node 170 to perform one or more of the operations as described herein. Note that the functionality of the control module 150 may be distributed, such as being distributed between the DU 195 and the CU 196, or be implemented solely in the DU 195.
The one or more network interfaces 161 communicate over a network such as via the links 176 and 131. Two or more RAN nodes 170 communicate using, e.g., link 176. The link 176 may be wired or wireless or both and may implement, e.g., an Xn interface for 5G, an X2 interface for LTE, or other suitable interface for other standards.
The one or more buses 157 may be address, data, or control buses, and may include any interconnection mechanism, such as a series of lines on a motherboard or integrated circuit, fiber optics or other optical communication equipment, wireless channels, and the like. For example, the one or more transceivers 160 may be implemented as a remote radio head (RRH) 195 for LTE or a distributed unit (DU) 195 for gNB implementation for 5G, with the other elements of the RAN node 170 possibly being physically in a different location from the RRH/DU, and the one or more buses 157 could be implemented in part as, e.g., fiber optic cable or other suitable network connection to connect the other elements (e.g., a central unit (CU), gNB-CU) of the RAN node 170 to the RRH/DU 195. Reference 198 also indicates those suitable network link(s).
The wireless network 100 may include a network element or elements 190 that may include core network functionality, and which provides connectivity via a link or links 181 with a data network 191, such as a telephone network and/or a data communications network (e.g., the Internet). Such core network functionality for 5G may include access and mobility management function(s) (AMF(s)) and/or user plane functions (UPF(s)) and/or session management function(s) (SMF(s)). Such core network functionality for LTE may include MME (Mobility Management Entity)/SGW (Serving Gateway) functionality. These are merely exemplary functions that may be supported by the network element(s) 190, and note that both 5G and LTE functions might be supported. The RAN node 170 is coupled via a link 131 to a network element 190. The link 131 may be implemented as, e.g., an NG interface for 5G, or an S1 interface for LTE, or other suitable interface for other standards. The network element 190 includes one or more processors 175, one or more memories 171, and one or more network interfaces (N/W I/F(s)) 180, interconnected through one or more buses 185. The one or more memories 171 include computer program code 173. The one or more memories 171 and the computer program code 173 are configured to, with the one or more processors 175, cause the network element 190 to perform one or more operations.
It is noted that description herein indicates that “cells” perform functions, but it should be clear that the base station that forms the cell will perform the functions. The cell makes up part of a base station. That is, there can be multiple cells per base station. For instance, there could be three cells for a single carrier frequency and associated bandwidth, each cell covering one-third of a 360-degree area so that the single base station's coverage area covers an approximate oval or circle. Furthermore, each cell can correspond to a single carrier and a base station may use multiple carriers. So, if there are three 120-degree cells per carrier and two carriers, then the base station has a total of 6 cells.
In the example of
The wireless network 100 may implement network virtualization, which is the process of combining hardware and software network resources and network functionality into a single, software-based administrative entity, a virtual network. Network virtualization involves platform virtualization, often combined with resource virtualization. Network virtualization is categorized as either external, combining many networks, or parts of networks, into a virtual unit, or internal, providing network-like functionality to software containers on a single system. Note that the virtualized entities that result from the network virtualization are still implemented, at some level, using hardware such as processors 152 or 175 and memories 155 and 171, and also such virtualized entities create technical effects.
The computer readable memories 125, 155, and 171 may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The computer readable memories 125, 155, and 171 may be means for performing storage functions. The processors 120, 152, and 175 may be of any type suitable to the local technical environment, and may include one or more of general-purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on a multi-core processor architecture, as non-limiting examples. The processors 120, 152, and 175 may be means for performing functions, such as controlling the UE 110, RAN node 170, and other functions as described herein.
In general, the various embodiments of the user equipment 110 can include, but are not limited to, cellular telephones such as smart phones, tablets, personal digital assistants (PDAs) having wireless communication capabilities, portable computers having wireless communication capabilities, vehicles with a modem device for wireless V2X (vehicle-to-everything) communication, image capture devices such as digital cameras having wireless communication capabilities, gaming devices having wireless communication capabilities, music storage and playback appliances having wireless communication capabilities, Internet appliances (including Internet of Things, IoT, devices) permitting wireless Internet access and possibly browsing, IoT devices with sensors and/or actuators for automation applications with wireless communication tablets with wireless communication capabilities, as well as portable units or terminals that incorporate combinations of such functions.
Having thus introduced one suitable but non-limiting technical context for the practice of the exemplary embodiments, the exemplary embodiments will now be described with greater specificity.
Before proceeding to describe the exemplary embodiments, it is helpful to provide an overview of this technological area. Some technical standards do not describe determining whether a UE is stationary, but there is the related concept of “mobility”, including “low mobility”. For instance, it is specified in 3GPP TS 36.304 (see 3GPP TS 36.304 V16.1.0 (2020-07)) that UEs use received signal strength to detect what their mobility states are. The physical layer details are in 3GPP TS 38.304. Further details on signaling can also be found in 3GPP TS 38.133. In 3GPP TS 36.304, low mobility is not discussed, but instead normal/medium/high mobility are introduced. The low mobility introduced in 3GPP TS 38.304 is an extension of the mobility concepts in 3GPP TS 36.304. In these schemes, a UE compares its received signal strength to a cell specific signal variation parameter broadcast by the BS. The stationarity detection has been problematic in LTE for UEs in the outer region 83 (e.g., a cell edge 81) of the cells and also in the inner region 84 (including the cell center 82) of the cells 80, as the UEs observe different signal variations. With the introduction of NR, there are many novel factors introduced that affect the UE's signal strength variation, such as antenna types, device capabilities and many more. Thus, with NR, it is generally not possible to detect stationarity via a cell specific variation parameter for a wider range of UEs.
Two examples are detailed below.
1) In one example of this problem, a UE1 that is closer to the cell edge 81 would experience a higher signal variation compared to a UE2 that is closer to the center 82 of the cell as a result of lower chance of a LoS path with increasing distance.
With reference to
2) In another example of the problem, a UE1 with an omnidirectional antenna that is rotating in a (e.g., somewhat) fixed position would experience no change in its measurements while a UE2 with directional antenna would experience sudden changes in measurements due to its rotation.
In more detail, the UEs are expected to deploy various antenna types out of which may be the omnidirectional antenna (
In both of these scenarios, the BS has the following two choices.
1) The BS can set the RSRP variation threshold to detect stationarity for UE1 (close to cell edge UE or multipanel UE). In this case, as higher variations are tolerated, even though UE2 (close to cell center UE or omni antenna UE) is mobile, the UE2 110-2 may be identified as stationary, leading to a false positive.
2) The BS can set the RSRP variation threshold to detect stationarity for UE2 110-2. In this case, as only lower variations are tolerated, the stationarity for UE1 110-1 cannot be detected. This would lead to a false negative.
Furthermore, these examples are not exhaustive, and a scenario-specific variation of the signal level can be extended to other scenarios. These embodiments can be extended and reliable stationarity detection cannot be achieved in many scenarios. Detection of stationarity is needed for radio measurement relaxation, RAN notification area update, tracking area update and many signaling procedures to cover the problems that can be raised by the mobility of the UE. Measurement relaxation allows the UE to perform fewer measurements over time (e.g., than currently performed under a current configuration), such as the UE will perform measurements less frequently, the UE is allowed to skip some measurements, the UE is allowed to determine when to perform measurements, and/or the UE will measure fewer cells or frequencies. It is also noted that “measurement relaxation” may include the “relaxed measurements” in, e.g., 3GPP TS 38.304 or other technical standards.
Importantly, such problems cannot be solved only at the UE side, as the variations are affected by the cell settings. That is, the BS has to communicate additional parameters to achieve stationary detection.
With respect to exemplary embodiments herein, first an overview is provided, then more details are provided. As an overview, exemplary embodiments herein include a method in, e.g., cellular networks for a UE to detect if the UE is stationary or not. The method involves a cell specific signal variation parameter and a high/medium variation parameter calculated and broadcast by a BS in a cell and a UE detecting if the UE has high signal variation or not. One exemplary idea is to group the variations seen by different UEs as low, medium and high signal variations. The BS broadcasts a signal variation parameter corresponding to each of the three variation groups. Three new parameters are defined, in an exemplary embodiment, as part of the new stationarityEvaluation configuration: SSearchDeltaP (different from a legacy value defined in lowMobilityEvaluation), stationary_UE_medium_variation_correction, and stationary_UE_high_variation_correction. These are described in more detail below, but can be used to place the UE into one of the three variation groups. Each UE identifies itself to be in one of these three variation groups and will use the corresponding variation parameter to detect stationarity. Note that using three variation groups is merely exemplary, and fewer or more groups could be used.
Exemplary operations may include the following.
1) The Base Station broadcasts SSearchDeltaP in a new parameter stationarityEvaluation with relaxedMeasurement configuration in SIB2.
2) In addition to this cell-specific parameter, the BS also broadcasts additional high/medium variation parameters [e.g., stationary_UE_high_variation_correction, stationary_UE_medium_variation_correction], and a new parameter stationarityEvaluation in, e.g., SIB2. In an example, “stationarityEvaluation” is a configuration container, contained in the relaxedMeasurement configuration. The relaxedMeasurement configuration also includes the parameters for high and medium variation in an example.
3) The UE has performed intra-frequency or inter-frequency measurements for at least time TSearchDeltaP after (re-)selecting a new cell.
4) If the UE supports relaxed measurements and relaxedMeasurement is present in SIB2, the UE may further relax the needed measurements, as specified in clause 5.2.4.9 of 3GPP TS 38.304.
5) The UE sets Srxlev.Ref=Srxlev when a new serving cell has been selected or reselected.
6) The UE detects if the UE is a high/medium signal variation UE or not (i.e., it is a low signal variation UE). For this detection, the UE may use a logic that combines its configuration, its state, and the parameters broadcast by the BS. The state of the user equipment can be based on its location, received power, antenna type, and/or capability. An exemplary decision mechanism is detailed below in section 2.1 below.
7) The UE determines whether the UE is stationary by evaluating a criterion that depends on the signal variation as detected in the previous operation:
a) If a UE has high signal variation, then the UE uses the following:
Srxlev.Ref−Srxlev<SSearchDeltaP+stationary_UE_high_variation_correction.
b) If a UE has medium signal variation, then the UE uses the following:
Srxlev.Ref−Srxlev<SSearchDeltaP+stationary_UE_medium_variation_correction.
c) Otherwise, the UE uses the following:
Srxlev.Ref−Srxlev<SSearchDeltaP.
8) If the criterion for stationarity tested by the UE is fulfilled:
a) The UE concludes it is stationary.
b) This may be used to relax RRM measurements or perform other procedures; however, how the stationarity detection outcome is used is not detailed in this disclosure.
9) Otherwise, the UE concludes the UE is not stationary and as such the UE does not modify its behavior.
Now that an overview has been provided, additional details are provided. For ease of reference, the rest of this document is divided into labeled sections. The labeling is merely for reference and is not intended to be limiting.
The table in
In the following sections, UE variation scenarios are detailed. Initially, the reasons for observing UE-specific variations are explained. This is followed by the explanation of why each problem can be solved by a parameter broadcast from the BS and cannot be solved by UE by itself.
Increasing the distance to the base station 170 decreases the probability of a LoS path to the BS 170. Consequently, a UE 110 near the edge 81 of the cell 80 will have mostly NLoS to the BS.
Another important piece of information is the effect of shadowing with respect to LoS and NLoS. Shadowing causes the signal received by the UE to fluctuate. Typically, with NLoS, a UE 110 has higher variations compared to LoS variations. Shadowing is the effect of an object blocking the electro-magnetic signals, e.g., like the sun rays, resulting in a shadow. As the signal is reflected from many different objects, there is not a complete blockage of the electro-magnetic signal, but decreasing its strength.
Thus, combining these two pieces of information, one can see that a UE that is further away from the BS observes higher signal variation compared to the UE that is closer to the BS.
However, one can argue that the UE can detect its distance to the BS and correct this change in signal variation. This would be true if the amount of variations would not depend on the cell settings. Referring to
It can be seen that even if all the UE parameters are kept the same except the cell settings, the variations observed by two UEs are different as emphasized by the standard deviations, 4.04 (σ1) and 5.64 (σ2) in sparse and dense clutters, respectively. This emphasizes the need of a variation parameter by each BS depending on the cell settings.
The UEs are expected to deploy various antenna types, out of which may be the omnidirectional antenna and a multipanel antenna. In the omni antenna case, it is clear that when a UE is stationary, irrespective of its rotation, the received power will be similar. However, for a multipanel UE, some physical rotation of the UE will impact the signal power observed and can hinder the stationarity detection. This will be particularly specific to the radiation pattern of the antenna and the behavior of the UE.
Similarly, base stations are already located with many antenna types that are configured in multiple ways physically and electronically. Thus, the matching between the UE and the BS antenna type will play an important role with respect to each cell.
There are many factors that can affect the measurement accuracy of a UE. Some of these can be related to implementation, while some are related to the BW allocated to the UE by the network. Intuitively, the wider bandwidth that is used for measurements, the more precise the measurements are for the UE.
Similar to the first scenario in section 1.1, the amount of variations with respect to the measurement accuracy will depend on the cell settings.
The methodology to set the parameters of stationary_UE_high/medium_variation_correction can follow the logic used to set SSearchDeltaP (which is currently considered in the specifications). Below are additional processes to set this parameter.
1. Using site/cell measurement campaigns.
2. Building an estimator following user UL reference signals.
3. Using parameters affected by RRM measurement relaxation, and, i.e., fine tuning relaxation with respect to change of these parameters. One parameter affecting the setting of the variation parameter can be RLF. If a UE performs false stationarity detection, i.e., variation parameter is set too high, the UE 110 may experience more frequent RLF and this may call for reducing the variation parameter.
a. However, UEs are not reporting which “UE variation correction parameters” they are using, so correlating the UE RLF parameter to the “UE variation correction parameters” is not necessarily intuitive.
b. Similarly, having too low of correction would be harder for the BS to observe, as the correction mostly affects the UE. So, in an exemplary embodiment, the BS 170 can try to be on the aggressive side and use a high “variation value”. This could result in more RLF. If so, then the BS can reduce the “variation value” and can monitor the RLF for further adjustments.
Note that one BS 170 can communicate the information in this section between this base station and other base station(s) and can coordinate setting the values for high/medium variations. For instance, the values of stationary_UE_high/medium_variation_correction can be communication from this base station to other base stations during the processes above, and this could help coordination to set these values.
The UE variation detection merges cell-specific measurements with UE configuration.
As independent embodiments causing higher perceived signal level variation for the UE can occur, the UE should merge these cases to adjust its variation correction parameter, as illustrated in
The flow starts 605 and in block 610, the UE 110 determines if the UE is configured to have high variation. The process for this determination is referred to as “subroutine 1”.
That is, the UE initially checks if it is configured for high variation through subroutine 1. Subroutine 1 involves the UE's capabilities, including, e.g., physical and software configurations, that can lead to high variation. One example can be the antenna type of the UE and can be set as a flag in the decision mechanism. That is “if antenna type is multi-panel, set high variation to true”. Different UEs have different numbers of antennas, this can be a physical configuration and provide different capability. Also, some UEs may disable the use of some antennas through software configuration even though they physically have those antennas, and this also is a capability of the UE. That would be an example of software configuration. Similar examples can be given for bandwidth, half duplexing and so on, as examples of capabilities of the UE. The measurement accuracy is again a configuration of the device and this can be set directly through a flag in the UE.
After the subroutine 1, the UE goes through subroutine 2. That is, the no result from block 610 passes to block 620, which performs subroutine 2. The yes result from block 610 passes to block 640, which also performs subroutine 2. The subroutine 2 is a bit more complex than subroutine 1, as this subroutine aims to detect the location of the UE, i.e., whether if the UE is in the outer region 83 of the cell 80, such as being on a cell edge 81, or not.
For subroutine 2, the UE gathers RSRPavet values for multiple cells, and, as one would expect for a UE in the outer region 83 (e.g., on the cell edge 81), these values should be closer to each other than if the UE were farther away from the outer region 83/cell edge 81. The RSRPavet for multiple cells is compared by a threshold, e.g., cell_edge_measurements_tolerance, and the UE can decide whether the UE is in the outer region 83 (e.g., on the cell edge 81) or not.
Consider the following example:
RSRPavet (cell1)−RRSRPavet (cell2)≤celledge measurement tolerance where the right-hand side may have measurements in, e.g., dBm, and the left-hand side has a comparison value, e.g., in dBm. Note that the use of dBm is merely exemplary, and other units might be used.
If the above condition holds, the UE would return yes, otherwise the UE would return no.
In block 620, if the UE determines it is not in the outer region 83 (e.g., on the cell edge 81) (block 620=no), then the UE determines the UE has low variation in block 630. If the UE determines it is in the outer region 83 (e.g., on the cell edge 81) for block 620 (block 620=yes) or if the UE determines it is not in the outer region 83 (e.g., on the cell edge 81) for block 640 (block 640=no), the UE determines in block 650 that it has medium variation. If the UE determines it is in the outer region 83 (e.g., on the cell edge 81) for block 640 (block 640=yes), the UE determines in block 660 that it has high variation. Each of the three variations in 630, 650, and 660 are groups, and there could be more or fewer groups.
It is noted that another alternative rather than (or possibly in addition to) determining a location of the UE and whether the UE is in an outer region of a cell is to use received power (see block 615) as an indicator of signal variation. The received power might be more indicative of the signal variation level (e.g., low received power (e.g., RSRP) means higher variation) and the received signal power is in a way related to location but not always.
In another embodiment, the UE can report its configuration and some additional parameters related to its signal reception. Thus, the variation of a UE can be decided by the base station. Also, the UE can detect its signal level variation and report this to the BS.
This section uses
1) In step 705, the UE performs a cell (re-)selection.
2) In block 710, the UE 110 checks if the UE supports RRM relaxation.
i. If not (block 710=no), the UE stops the stationary UE detection logic in block 720.
ii. If the UE supports RRM relaxation (block 710=yes), the UE sets (block 725) srxlev.ref to srxlev. The srxlev is a processed measurement value set as srxlev=Qrxlevmeas−Qrxlevmin+QrxlevminOffset−Pcompenstation as described in 3GPP TS 25.133. In more detail, once the UE performs cell selection, the UE sets Srxlev.Ref as the initial measurement from the serving cell, e.g., measured in dBm, although other units may be used. The Srxlev.Ref value can be updated with a period T. Srxlev is the instantaneous serving cell measurement value, e.g., in dBm (as one example of a unit that might be used), and the UE performs this measurement a lot more frequently than period T.
iii. Srxlev.ref will be used to detect stationarity later on.
3) The UE receives SIB2 and checks (block 730) if relaxedMeasurement and stationarityEvaluation are present in SIB2.
i. If these are not present (block 730=no), the UE stops the stationary UE detection logic in block 720.
ii. Otherwise (block 730=yes), the UE 110 detects the UE variation level in block 745.
4) The UE variation is detected as described in section 2.1.
5) The UE identifies (block 755) the UE for measurement relaxation. While other options are possible, a check of stationarity may be used, such that a UE determined to be stationary is identified for measurement relaxation and a UE that is not determined to be stationary is not identified for measurement relaxation. Block 755 is based on the outcome of the step 4 as follows.
i. If a UE has high signal variation, then the UE uses the following:
Srxlev.Ref−Srxlev<SSearchDeltaP+stationary_UE_high_variation_correction.
ii. If a UE has medium signal variation, then the UE uses the following:
Srxlev.Ref−Srxlev<SSearchDeltaP+stationary_UE_medium_variation_correction.
iii. Otherwise, the UE uses the following:
Srxlev.Ref−Srxlev<SSearchDeltaP.
With respect to the equations above, the UE compares the left-hand part that the UE measured, with the right-hand part. If the inequality mathematically holds for a period of time, e.g., of a predetermined time period T, then the UE declares the stationarity is detected.
As the parameters are used to detect different variations of the signal level, medium and high variation parameters can be different. It is expected that the medium variation will be smaller (e.g., in absolute value) than the high variation parameter. If a medium variation is used, stationary is less likely to be detected than if the high variation is used.
Srxlev represents, in an exemplary embodiment, the filtered outcome of recent measurements, i.e., layer 1 filtering. In one embodiment, the BS can communicate to the UE different timer parameters for different variation levels. Different timer parameters may depict the need to use different number of samples for filtering of measurements, i.e., layer 1 filtering. Also, different timer parameters may depict different sliding window for filtering, i.e., layer 1 filtering.
These timer parameters may be part of parameters configured for the UE, and the UE may use these to determine the estimate of the level of signal variance. For instance, first and second timer parameters may be configured (e.g., by the BS) for the UE. The UE may use the first timer parameter to determine the estimate of the level of signal variance as having the high signal variation. The UE may use the second timer parameter to determine the estimate of the level of signal variance as having the medium signal variation.
6) If the condition in step 5 is fulfilled (block 755=yes, meaning meas. relaxation is suitable, such as the UE is stationary):
i. The UE identifies the UE as being suitable for measurement relaxation (e.g., being stationary, e.g., by setting a stationarity flag) (see block 750). The reason a flag (or other indication) can be used is because stationarity can be beneficial for other features.
ii. The UE relaxes the RRM measurements (see block 750) and extends its measurement periodicity, such as to 24 hours.
iii. And, the UE checks if the UE performed a cell re-selection (block 735). If yes (block 735=yes), then the UE re-starts the UE detection logic by proceeding to step 705.
iv. Optionally, the UE reports its stationarity to the BS through RNA update for signaling procedure optimization, i.e., mobility signaling.
7) Otherwise (block 735=no), the UE 110 goes back to checking (block 755) stationarity with each new measurement.
8) If the condition in step 5 is not fulfilled (block 755=no, meaning the UE is not suitable for meas. relaxation, e.g., is not stationary):
i. The UE continues RRM measurements (see block 740) as previously configured.
ii. And, the UE checks if the UE performed a cell re-selection in block 735.
i. If yes, (block 735=yes), the UE then re-starts the UE detection logic in block 705.
ii. Otherwise (block 735=no), the UE goes back to checking stationarity with each new measurement in block 755.
The description in
In another embodiment, a UE-specific signal variation correction parameter for each UE is transmitted through RRC signaling to the UE 110 from the BS 170. This value is specific to a UE. This incurs extra overhead, as transmitting the parameter requires specific signaling to each UE. And the above-mentioned method, where the UEs are grouped in high and medium variation, is more resource efficient to utilize. Regardless, transmitting the parameter separately to each UE is a viable alternative.
The examples above consider mainly RRM measurement relaxation, where time between RRM measurements is extended from a current time to a longer time. It is, however, possible to modify the time between RRM measurements in a different way. For instance, the signal variation in
Turning to
In block 765, the UE identifies whether the UE should be identified for measurement modification, and one factor can be stationarity of the UE. If there is no measurement modification (block 755=no), the flow proceeds to block 740. If there is measurement modification (block 755=yes), the flow proceeds to block 760. In block 760, the UE is identified for measurement modification and the RRM measurements are modified by increasing or decreasing the time between RRM measurements from a current time to an increased or decreased time, as the case may be. Flow proceeds to block 735, which is described above.
While there are other ways to support implementing the exemplary embodiments, one option is to modify relaxedMeasurement configuration in SIB2. To support the exemplary embodiments, and in an exemplary embodiment, a stationarityEvaluation container could be used. The container may be contained in a relaxedmeasurement configuration, and include the s-SearchDeltaP-r16 and t-SearchDeltaP-r17 parameters. This relaxedMeasurement configuration also may contain the parameters for high/medium variation correction, e.g., stationary_UE_high_variation_correction and stationary_UE_medium_variation_correction. This is only one example of how these might be implemented, and other examples are possible.
This section relates one possible example. This example uses
In
The UE acquires SIB2 (from signaling 915) and detects the relaxedMeasurement is set in SIB2. It also detects that the optional parameter stationarityEvaluation is available. The s-SearchThresholdP is also detected. Further, the UE 110 extracts the stationarity_UE_high/medium_variation_correction parameters.
The UE starts the RRM measurements in operation 917. Assume the UE in this example is an omni-antenna UE having high measurement accuracy and the UE is in the outer region 83 (e.g., or close to the cell edge 81). The UE detects (block 920) that the UE is in the outer region 83 (e.g., or close to the cell edge 81), using logic given in 2.1, described above.
As the UE decides it is a high variation UE, the UE 110 decides to use the stationary_UE_high_variation_correction parameter to detect stationarity. The UE in block 925 measures Srxlev periodically.
The UE considers Srxlev.Ref−Srxlev<SSearchDeltaP+stationary_UE_high_variation_correction, and the UE observes that the inequality holds for a period of T-searchDeltaP. The UE therefore detects it is stationary in block 930.
The UE optionally reports that it is stationary in RNA update 935, with a stationarity declaration. The UE extends its RRM measurement timer (see reference 940), in this example to be 24 hours. That is, each 24-hour period, the UE wakes up and performs the RRM measurements and determines if the previous conditions still hold. Although a 24-hour period is used, other periods shorter or longer than that may also be used.
Turning to
In block 950, the UE 110 receives one or more parameters to be used to identify the user equipment for measurement modification. The UE 110 is connected to a base station 170 in a wireless network 100. In block 960, the UE 110 determines an estimate of a level of signal variation for signals received at the UE 110. The UE 110, in block 970, identifies, using at least the one or more parameters, the user equipment for measurement modification based at least on the estimate of the level of signal variation. The UE 110 in block 980 modifies, by the user equipment, a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification.
It is noted that the modification in time between measurements may be similar to the previously described measurement relaxation. As described above, measurement relaxation allows the UE to perform fewer measurements over time (e.g., than currently performed under a current configuration), such as the UE will perform measurements less frequently, the UE is allowed to skip some measurements, the UE is allowed to determine when to perform measurements, and/or the UE will measure fewer cells or frequencies. In case the time between measurements is decreased, the UE can perform more measurements over time (e.g., than currently performed under a current configuration), such as the UE will perform measurements more frequently, the UE is not allowed to skip some measurements, the UE is not allowed to determine when to perform measurements, and/or the UE will measure more cells or frequencies.
In block 1010, the BS 170 determines one or more parameters to be used by a UE 110 in order to identify the user equipment for measurement modification. The BS 170 in block 1020 signals the one or more parameters to the UE 110.
The following are additional examples.
Example 1. A method, comprising:
Example 2. The method of example 1, wherein the current time and the different time are configured via signaling received by the user equipment from the base station.
Example 3. The method of any one of examples 1 or 2, wherein the determining the estimate of the level of signal variation uses one or more second parameters involving a state of the user equipment.
Example 4. The method of example 3, wherein the one or more parameters involving a state of the user equipment comprise a received power.
Example 5. The method of example 3, wherein the one or more parameters involving a state of the user equipment comprise a location of the user equipment within a cell formed by the base station.
Example 6. The method of example 3, wherein the one or more parameters involving a state of the user equipment comprise antenna type of the user equipment.
Example 7. The method of any one of examples 1 to 6, wherein:
Example 8. The method of example 7, wherein:
Example 9. The method of example 8, wherein determining whether the user equipment is configured to have high variation in received signals comprises determining that a capability of the user equipment is a capability that can lead to high variation and assigning the user equipment to have high variation in response.
Example 10. The method of any one of examples 7 to 9, wherein:
Example 11. The method of example 10, wherein the multiple parameters comprise a threshold, and wherein identifying the user equipment for measurement modification based at least on the estimate of the level of signal variation comprises:
Example 12. The method of any of the above examples, wherein identifying the user equipment for measurement modification comprises determining that the user equipment is stationary and identifying the user equipment as suitable for measurement modification because the user equipment is stationary.
Example 13. A method, comprising:
Example 14. The method of example 13, wherein the user equipment for measurement modification is to adjust a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification, and wherein the base station signals the current time and the different time toward the user equipment.
Example 15. The method of either of example 13 or 14, wherein the one or more parameters comprise parameters for multiple groups indicating variations of the signal, values of the parameters for the multiple groups are determined by the base station using one or more of the following processes:
Example 16. The method of example 15, further comprising coordinating results of the one or more processes in order to set the values of the parameters for the multiple groups.
Example 17. The method of any one of examples 15 or 16, wherein the parameters for the multiple groups comprise parameters for a medium variation group and a high variation group.
Example 18. The method of any one of examples 13 to 17, wherein the one or more parameters to be used by the user equipment in order to identify the user equipment for measurement modification are for determining that the user equipment is stationary.
Example 19. A computer program, comprising code for performing the methods of any of examples 1 to 18, when the computer program is run on a computer.
Example 20. The computer program according to example 19, wherein the computer program is a computer program product comprising a computer-readable medium bearing computer program code embodied therein for use with the computer.
Example 21. The computer program according to example 19, wherein the computer program is directly loadable into an internal memory of the computer.
Example 22. An apparatus, comprising means for performing:
Example 23. The apparatus of example 22, wherein the current time and the different time are configured via signaling received by the user equipment from the base station.
Example 24. The apparatus of any one of examples 22 or 23, wherein the determining the estimate of the level of signal variation uses one or more second parameters involving a state of the user equipment.
Example 25. The apparatus of example 24, wherein the one or more parameters involving a state of the user equipment comprise a received power.
Example 26. The apparatus of example 24, wherein the one or more parameters involving a state of the user equipment comprise a location of the user equipment within a cell formed by the base station.
Example 27. The apparatus of example 24, wherein the one or more parameters involving a state of the user equipment comprise antenna type of the user equipment.
Example 28. The apparatus of any one of examples 22 to 27, wherein:
Example 29. The apparatus of example 28, wherein:
Example 30. The apparatus of example 29, wherein determining whether the user equipment is configured to have high variation in received signals comprises determining that a capability of the user equipment is a capability that can lead to high variation and assigning the user equipment to have high variation in response.
Example 31. The apparatus of any one of examples 28 to 30, wherein:
Example 32. The apparatus of example 31, wherein the multiple parameters comprise a threshold, and wherein identifying the user equipment for measurement modification based at least on the estimate of the level of signal variation comprises:
Example 33. The apparatus of any one of examples 22 to 32, wherein identifying the user equipment for measurement modification comprises determining that the user equipment is stationary and identifying the user equipment as suitable for measurement modification because the user equipment is stationary.
Example 34. An apparatus, comprising means for performing:
Example 35. The apparatus of example 34, wherein the user equipment for measurement modification is to adjust a time between measurements for radio resource management from a current time to a different time in response to the user equipment being identified for measurement modification, and wherein the base station signals the current time and the different time toward the user equipment.
Example 36. The apparatus of either of example 34 or 35, wherein the one or more parameters comprise parameters for multiple groups indicating variations of the signal, values of the parameters for the multiple groups are determined by the base station using one or more of the following processes:
Example 37. The apparatus of example 36, further comprising means for coordinating results of the one or more processes in order to set the values of the parameters for the multiple groups.
Example 38. The apparatus of any one of examples 36 or 37, wherein the parameters for the multiple groups comprise parameters for a medium variation group and a high variation group.
Example 39. The apparatus of any one of examples 34 to 38, wherein the one or more parameters to be used by the user equipment in order to identify the user equipment for measurement modification are for determining that the user equipment is stationary.
Example 40. The apparatus of any one of examples 22 to 39 wherein the means comprises:
Example 41. A communication system comprise an apparatus of any of examples 22 to 33 and an apparatus of any of examples 34 to 39.
Example 42. An apparatus, comprising:
Example 43. An apparatus, comprising:
Without in any way limiting the scope, interpretation, or application of the claims appearing below, a technical effect and advantage of one or more of the example embodiments disclosed herein is stationarity of heterogenous devices can be detected. Another technical effect and advantage of one or more of the example embodiments disclosed herein is that stationary UEs can decrease the signaling stemming from energy heavy mobility signaling procedures, thereby saving energy.
As used in this application, the term “circuitry” may refer to one or more or all of the following:
This definition of circuitry applies to all uses of this term in this application, including in any claims. As a further example, as used in this application, the term circuitry also covers an implementation of merely a hardware circuit or processor (or multiple processors) or portion of a hardware circuit or processor and its (or their) accompanying software and/or firmware. The term circuitry also covers, for example and if applicable to the particular claim element, a baseband integrated circuit or processor integrated circuit for a mobile device or a similar integrated circuit in server, a cellular network device, or other computing or network device.
Embodiments herein may be implemented in software (executed by one or more processors), hardware (e.g., an application specific integrated circuit), or a combination of software and hardware. In an example embodiment, the software (e.g., application logic, an instruction set) is maintained on any one of various conventional computer-readable media. In the context of this document, a “computer-readable medium” may be any media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer, with one example of a computer described and depicted, e.g., in
If desired, the different functions discussed herein may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the above-described functions may be optional or may be combined.
Although various aspects of the invention are set out in the independent claims, other aspects of the invention comprise other combinations of features from the described embodiments and/or the dependent claims with the features of the independent claims, and not solely the combinations explicitly set out in the claims.
It is also noted herein that while the above describes example embodiments of the invention, these descriptions should not be viewed in a limiting sense. Rather, there are several variations and modifications which may be made without departing from the scope of the present invention as defined in the appended claims.
The following abbreviations that may be found in the specification and/or the drawing figures are defined as follows:
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2020/056659 | 10/21/2020 | WO |
