WO2020056552A1

WO2020056552A1 - Apparatus, method and computer program

Info

Publication number: WO2020056552A1
Application number: PCT/CN2018/105992
Authority: WO
Inventors: Jun Wang; Gang Shen; Liuhai LI; Liang Chen; Kan LIN; Zhihua Wu; Chaojun Xu; Jiexing GAO
Original assignee: Nokia Shanghai Bell Co., Ltd.; Nokia Solutions And Networks Oy
Priority date: 2018-09-17
Filing date: 2018-09-17
Publication date: 2020-03-26
Also published as: CN112703759A

Abstract

An apparatus comprising: at least one processor; and at least one memory including computer program code; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to: cause a user equipment to report reference signal measurements; and cause the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.

Description

APPARATUS, METHOD AND COMPUTER PROGRAM

Field of the disclosure

The present disclosure relates to an apparatus, a method and a computer program for adjusting at least one time parameter associated with at least one operation at a user equipment (e.g. periodicity of a measurement report operation, time to trigger of a handover operation, etc. ) .

Background

A communication system can be seen as a facility that enables communication sessions between two or more entities such as user terminals, base stations/access points and/or other nodes by providing carriers between the various entities involved in the communications path. A communication system can be provided for example by means of a communication network and one or more compatible communication devices. The communication sessions may comprise, for example, communication of data for carrying communications such as voice, electronic mail (email) , text message, multimedia and/or content data and so on. Non-limiting examples of services provided comprise two-way or multi-way calls, data communication or multimedia services and access to a data network system, such as the Internet. In a wireless communication system at least a part of a communication session between at least two stations occurs over a wireless link.

A user can access the communication system by means of an appropriate communication device or terminal. A communication device of a user is often referred to as user equipment (UE) or user device. A communication device is provided with an appropriate signal receiving and transmitting apparatus for enabling communications, for example enabling access to a communication network or communications directly with other users. The communication device may access a carrier provided by a station or access point, and transmit and/or receive communications on the carrier.

The communication system and associated devices typically operate in accordance with a given standard or specification which sets out what the various entities associated with the system are permitted to do and how that should be achieved. Communication protocols and/or parameters which shall be used for the connection are also typically defined. One example of a communications system is UTRAN (3G radio) . Another example of an architecture that is known as the long-term evolution (LTE) of the Universal Mobile Telecommunications System (UMTS) radio-access technology. Another example communication system is so called 5G radio or NR (new radio) access technology.

Summary

According to an aspect there is provided an apparatus comprising at least one processor and at least one memory including computer code for one or more programs, the at least one memory and the computer code configured, with the at least one processor, to cause the apparatus at least to: cause a user equipment to report reference signal measurements; and cause the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.

The reference signal measurements may comprise reference signal received power measurements.

The reference signal measurements may comprise reference signal received quality measurements.

The time parameter associated with the operation may comprise a periodicity associated with a reference signal measurement report operation.

The time parameter associated with the operation may comprise a periodicity associated with a reference signal measurement report operation, if the reference signal measurement report operation is periodic.

The time parameter associated with the operation may comprise a time to trigger associated with a handover operation.

The time parameter associated with the operation may comprise a time to trigger associated with a handover operation, if a reference signal measurement report operation is event triggered.

The reference signal measurements may comprise a current reference signal measurement and a previous reference signal measurement.

The at least one reference signal measurement variation may comprise a current reference signal measurement variation.

The current reference signal measurement variation may be determined based on the current reference signal measurement and the previous reference signal measurement.

The at least one reference signal measurement variation may comprise a prediction of a subsequent reference signal measurement variation.

The prediction of the subsequent reference signal measurement variation may be based on the current reference signal measurement and a prediction of a subsequent reference signal measurement.

The prediction of the subsequent reference signal measurement may be determined based on a prediction of a subsequent location.

The prediction of the subsequent location may be determined based on a current location and a prediction of a subsequent velocity.

The prediction of the subsequent location may be determined based on a current orientation.

The current orientation may be determined based on a current location and a previous location.

The prediction of the subsequent velocity may be determined based on a current velocity and a prediction of the current velocity.

The current velocity may be determined based on the current location and the previous location and a time difference separating the collection of the current reference signal measurement and the previous reference signal measurement.

The current location and the previous location may be determined based on the current reference signal measurement and the previous reference signal measurement.

The current location and the previous location may be determined based on a fingerprint database associating the current reference signal measurement to the current location and the previous reference signal measurement to the previous location.

According to an aspect there is provided an apparatus comprising means for: causing a user equipment to report reference signal measurements; and causing the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.

According to an aspect there is provided an apparatus comprising circuitry configure to: cause a user equipment to report reference signal measurements; and cause the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.

According to an aspect there is provided a method comprising: causing a user equipment to report reference signal measurements; and causing the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.

According to an aspect there is provided a computer program comprising computer executable code which when run on at least one process is configured to: cause a user equipment to report reference signal measurements; and cause the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.

According to an aspect, there is provided a computer readable medium comprising program instructions stored thereon for performing at least one of the above methods.

According to an aspect, there is provided a non-transitory computer readable medium comprising program instructions stored thereon for performing at least one of the above methods.

According to an aspect, there is provided a non-volatile tangible memory medium comprising program instructions stored thereon for performing at least one of the above methods.

According to an aspect, there is provided a computer readable medium storing a set of time parameters for an operation at user equipment, the time parameters being associated with respective reference signal measurement variations.

According to an aspect, there is provided a non-transitory computer readable medium storing a set of time parameters for an operation at user equipment, the time parameters being associated with respective reference signal measurement variations.

According to an aspect, there is provided a non-volatile tangible memory medium storing a set of time parameters for an operation at user equipment, the time parameters being associated with respective reference signal measurement variations.

In the above, many different aspects have been described. It should be appreciated that further aspects may be provided by the combination of any two or more of the aspects described above.

Various other aspects are also described in the following detailed description and in the attached claims.

List of abbreviations

CGI: Cell Global Identifier

GPS: Global Positioning System

HO: Handover

ILA: In-Location Alliance

LBS: Location Based Service

LTE: Long Term Evolution

MR: Measurement Report

PCell: Primary Cell

RAT: Radio Access Technology

RRH: Remote Radio Head

RSRP: Reference Signal Received Power

RSRQ: Reference Signal Received Quality

SCell: Secondary Cell

SON: Self Organized Network

UE: User Equipment

WSN: Wireless Sensor Network

Brief Description of the Figures

Embodiments will now be described, by way of example only, with reference to the accompanying Figures in which:

Figure 1 shows a schematic representation of a communication system;

Figure 2 shows a schematic representation of a control apparatus;

Figure 3 shows a schematic representation of a communication device;

Figure 4 shows a schematic representation of a graph illustrating the relation between the distance between a user equipment and a cell and the signal to interference plus noise ratio for the cell;

Figure 5 shows a schematic representation of a diagram of a method for adjusting at least one time parameter associated with at least one operation at a user equipment; and

Figure 6 shows a schematic representation of a non-volatile memory medium storing instructions which when executed by a processor allow the processor to perform one or more of the steps of the method of Figure 5.

Detailed Description of the Figures

In the following certain embodiments are explained with reference to mobile communication devices capable of communication via a wireless cellular system and mobile communication systems serving such mobile communication devices. Before explaining in detail the exemplifying embodiments, certain general principles of a wireless communication system, access systems thereof, and mobile communication devices are briefly explained with reference to Figures 1 to 3 to assist in understanding the technology underlying the described examples.

Figure 1 illustrates an example of a wireless communication system 100. The wireless communication system 100 comprises

wireless communication devices

102, 104, 105. The

wireless communication devices

102, 104, 105 are provided wireless access via at least one

base station

106 and 107 or similar wireless transmitting and/or receiving node or point.

Base stations

106 and 107 are typically controlled by at least one appropriate controller apparatus. The controller apparatus may be part of the

base stations

106 and 107.

Base stations

106 and 107 are connected to a wider communications network 113 via gateway 112. A further gateway function may be provided to connect to another network.

Base stations

116, 118 and 120 associated with smaller cells may also be connected to the network 113, for example by a separate gateway function and/or via the macro level stations. The

base stations

116, 118 and 120 may be pico or femto level base stations or the like. In the example,

base stations

116 and 118 are connected via a gateway 111 whilst base station 120 connects via the base station 106. In some embodiments, the smaller base stations116, 118 and 120 may not be provided.

Figure 2 illustrates an example of a control apparatus 200 for a node, for example to be integrated with, coupled to and/or otherwise for controlling a base station, such as the

base station

106, 107, 116, 118 or 120 shown on Figure 1. The control apparatus 200 can be arranged to allow communications between a user equipment and a core network. For this purpose the control apparatus comprises at least one random access memory (RAM) 211a and at least on read only memory (ROM) 211b, at least one

processor

212, 213 and an input/output interface 214. The at least one

processor

212, 213 is coupled to the RAM 211a and the ROM 211b. Via the interface the control apparatus 200 can be coupled to relevant other components of the base station. The at least one processor 212, 213may be configured to execute an appropriate software code 215 to perform one or more of the steps of the method described below in reference to Figure 5. The software code 215 may be stored in the ROM 211b. It shall be appreciated that similar components can be provided in a control apparatus provided elsewhere in the network system, for example in a core network entity. The control apparatus 200 can be interconnected with other control entities. The control apparatus 200 and functions may be distributed between several control units. In some embodiments, each base station can comprise a control apparatus. In alternative embodiments, two or more base stations may share a control apparatus.

Base stations and associated controllers may communicate with each other via a fixed line connection and/or via a radio interface. The logical connection between the base stations can be provided for example by an X2 or the like interface. This interface can be used for example for coordination of operation of the base stations and performing reselection or handover operations.

Figure 3 illustrates an example of a user equipment or wireless communication device 300, such as the

wireless communication device

102, 104 or 105 shown on Figure 1. The wireless communication device 300 may be provided by any device capable of sending and receiving radio signals. Non-limiting examples comprise a mobile station (MS) or mobile device such as a mobile phone or what is known as a ’smart phone’ , a computer provided with a wireless interface card or other wireless interface facility (e.g., USB dongle) , personal data assistant (PDA) or a tablet provided with wireless communication capabilities, machine-type communications MTC devices, IoT type communication devices or any combinations of these or the like. A device may provide, for example, communication of data for carrying communications. The communications may be one or more of voice, electronic mail (email) , text message, multimedia, data, machine data and so on.

The device 300 may receive signals over an air or radio interface 307 via appropriate apparatus for receiving and may transmit signals via appropriate apparatus for transmitting radio signals. In Figure 2 transceiver apparatus is designated schematically by block 306. The transceiver apparatus 306 may be provided for example by means of a radio part and associated antenna arrangement. The antenna arrangement may be arranged internally or externally to the mobile device.

The wireless communication device 300 may be provided with at least one processor 301, at least one memory ROM 302a, at least one RAM 302b and other possible components 303 for use in software and hardware aided execution of tasks it is designed to perform, including control of access to and communications with access systems and other communication devices. The at least one processor 301 is coupled to the RAM 211a and the ROM 211b. The at least one processor 301 may be configured to execute an appropriate software code 308 to perform one or more of the steps of the method described below in reference to Figure 5. The software code 308 may be stored in the ROM 211b.

The processor, storage and other relevant control apparatus can be provided on an appropriate circuit board and/or in chipsets. This feature is denoted by reference 304. The device may optionally have a user interface such as key pad 305, touch sensitive screen or pad, combinations thereof or the like. Optionally one or more of a display, a speaker and a microphone may be provided depending on the type of the device.

One or more of the following embodiments relate to accurate indoor positioning of wireless communication devices.

Accurate indoor positioning of wireless communication devices may unlock a new set of possibilities for mobile services. Consumers may benefit from personalized, contextual information and offers, as well as new services such as indoor navigation. It may also create new marketing opportunities, which means proper services and information may be delivered according to user’s current location or future location. Emerging indoor location based services (LBS) may include social networking, people finders, marketing campaigns, asset tracking, etc. Also, accurate indoor positioning may have a big impact not only by simplifying people’s lives, but for example also by helping firefighters, police, soldiers, medical personnel to save lives and perform specific tasks.

The In-Location Alliance (ILA) was originally formed by twenty two companies and has now expanded to ninety five companies including Nokia. It was launched to drive innovation and market adoption of high-accuracy indoor positioning and related services.

There may be multiple difficulties when it comes to achieving accurate indoor positioning. Standard approaches including Global Positioning System (GPS) that are used for outdoor positioning may not be easily used indoor due to unreliability of the GPS signal, source of interference and obstacles that are present in indoor environments.

One solution to provide accurate indoor positioning may be for a cellular operator to provide a unified continuous localization system, as the communication system. However, most of the WiFi systems/wireless sensor network (WSN) may not be built by the cellular operator, and cellular positioning systems may offer limited accuracy. Further, the cellular network may be optimized for communication but not for localization. For example, cellular indoor localization may mainly depends on reference signal receiving power (RSRP) measurements and/or reference signal receiving quality (RSRQ) measurements from a user equipment (UE) . These measurements are sent by the UE to a base station in measurement reports (MR) .

As defined in 3GPP TS 36.331, for long term evolution (LTE) , the triggering mechanism for MR may be either event driven or periodic. An event driven MR may be based upon events A1, A2, A3, A4, A5 and A6. A periodic MR may be based upon the expiry of a timer. The purpose of periodic reporting is signalled to either ‘reporting the strongest cells’ or ‘reporting cell global identifier (CGI) ’ . The triggering quantity can be specified to be RSRP or RSRQ. The reported quantity can be specified to be either the same as the triggering quantity, or both RSRP and RSRQ. The maximum number of cells to report is specified.

For inter radio access technology (RAT) , the triggering mechanism for sending an MR maybe either event driven or periodic. An event driven MR may be based upon events B1 and B2. A periodic MR may be based upon the expiry of a timer. The purpose of periodic reporting may be signalled to be either ‘reporting the strongest cells’ , ‘reporting the strongest cells for self-organising network (SON) ’ or ‘reporting a CGI’ . The maximum number of cells to report may be specified.

Table 1: Event list predefined in 3GPP E-UTRA standard

A base station may calculate the distance to a UE using RSRP and/or RSRQ measurements and triangulation or fingerprinting techniques. Fingerprinting is a technique where a fingerprint database is created during an offline measurement phase. Fingerprints are formed based on RSRP and/or RSRQ measurements collected at various known locations and are stored in the fingerprint database. Fingerprints are associated with respective locations in the fingerprint database. In an online measurement phase, a fingerprint is formed based on RSRP and/or RSRQ measurements collected at an unknown location. The fingerprint is compared with the fingerprints stored in the fingerprint database and a matching fingerprint is identified. The unknown location is then identified based on the known location associated with the matching fingerprint.

In an indoor environment the deployment of small cells, remote radio hear (RRH) or leaky cable or the presence of walls or obstacles may render triangulation or fingerprinting techniques less accurate or reliable. In such environment, it would be advantageous to adjust the density of MRs based on RSRP and/or RSRQ measurement variations, UE’s velocity or other to increase the accuracy of indoor positioning. For example, the density of MRs may be increased when an RSRP and/or RSRQ measurement variation is high or when a UE is moving. For example, a fast moving UE, in particular within the coverage of several cells (e.g. small cells) , may send MRs more frequently than a stationary or slow moving UE.

One or more of the following embodiments propose to adjust the density of MRs to provide accurate indoor localization and trajectory tracking. The density of MRs may for example be adjusted based on RSRP and/or RSRQ measurement variations and may take into consideration the velocity of a UE, the orientation of a UE and/or others.

In LTE, after a handover event a serving eNB constantly compares signal to interference plus noise ratio (SINR) of a UE for a serving cell with that of a handover target cell during a time to trigger (TTT) .

According to 3GPP TS 36.133, the relation between the SINR and RSRQ (in dB) may be given by: SINR = 1/ (1/ (Nsc ＊RSRQ) -x) , where Nsc represents the number of subcarriers per resource block (e.g. 12) and x is the instantaneous serving cell subcarrier activity factor (e.g. 0 ＜ x ≤ 1) .

During TTT, if the SINR for the serving cell is higher than that in the target cell, a “leaving event” occurs and handover is not executed. By using TTT, a ping-pong handover rate may be reduced. However, a radio link failure (RLF) rate may be increased because of delayed handover execution during TTT.

Figure 4 illustrates the effects of TTT on the ping-pong handover rate and the RLF rate. With a long TTT, a UE may move far from the serving cell. The likelihood of a RLF may be increased due to the severely degraded SINR in the serving cell before handover is actually executed. However, the likelihood of a ping-pong handover is reduced because there is a large difference between the SINR for the serving cell and the SINR for the neighbouring cell at the end of TTT. With a short TTT, a UE may remain close to the serving cell. The likelihood of a RLF may be reduced as the SINR remains high for the serving cell before handover is actually executed. However, the likelihood of a ping-pong handover is increased because there is only a small difference between the SINR for the serving cell and the SINR for the neighbouring cell at the end of TTT.

One or more of the following embodiments propose to adjust the TTT to provide an optimized tradeoff between ping-pong handover rate and RLF rate. The TTT may for example be adjusted based on RSRP and/or RSRQ measurement variations and take into consideration the velocity of a UE, the orientation of a UE and/or others.

Figure 5 shows a schematic representation of a diagram of a method for adjusting at least one time parameter associated with at least one operation at a user equipment.

In step 400, a sequence of reference signal measurements may be collected by a UE and reported to a base station in one or more MRs. The MRs may be periodic or event triggered. The MRs may be stored at the base station. The reference signal measurements may comprise RSRP measurements, RSRQ measurement and/or other reference signal measurements.

The sequence of reference signal measurements comprises at least a current reference signal measurement ψ (n) collected at a current time t (n) and a previous reference signal measurement ψ (n-1) collected at a previous time t (n-1) , wherein ‘n’ is an integer greater than or equal to 1. A current time interval T (n) may be obtained based on the previous time t (n-1) and the current time t (n) . For example, the current time interval T (n) may be obtained by subtracting the previous time t (n-1) to the current time t (n) .

T (n) = t (n) -t (n-1) [Equation 1]

In step 402, a current reference signal variation Δ (n) may be determined. The current reference signal variation Δ (n) may be determined based on the current reference signal measurement ψ (n) and based on the previous reference signal measurement ψ (n-1) . For example, the current reference signal variation Δ (n) may be determined by subtracting the previous reference signal measurement ψ (n-1) to the current reference signal measurement ψ (n) . However, it will be understood that the current reference signal variation Δ (n) may be obtained in other manners.

Δ (n) = ψ (n) -ψ (n-1) [Equation 2]

In step 404, a current location L (n) and a previous location L (n-1) may be determined. The current location L (n) may comprise coordinates X (n) along a first direction and Y (n) along a second direction. The previous location L (n-1) may comprise coordinates X (n-1) along the first direction and Y (n-1) along the second direction.

L (n) = (X (n) , Y (n) ) [Equation 3]

L (n-1) = (X (n-1) , Y (n-1) ) [Equation 4]

The current location L (n) may be determined based on the current reference signal measurement ψ (n) obtained in step 400. The previous location L (n-1) may be determined based on the previous reference signal measurement ψ (n-1) obtained in step 400.

In an example, a current fingerprint may be formed based on the current reference signal measurement (n) . The current fingerprint may be individually compared with fingerprints stored in a fingerprint database. A matching fingerprint maybe identified. The current location L (n) may be identified based on the location associated with the matching fingerprint. Likewise, a previous fingerprint may be formed based on the previous reference signal measurement (n-1) . The previous fingerprint may be individually compared with fingerprints stored in a fingerprint database. A matching fingerprint maybe identified. The previous location L (n-1) may be identified based on the location associated with the matching fingerprint.

In another example, the sequence formed by current fingerprint and the previous fingerprint maybe compared together (i.e. instead of individually) with sequences of fingerprints stored in the fingerprint database to find a matching sequence and to increase the accuracy of the current location L (n) and the previous location L (n-1) .

In an example, a hidden Markov model maybe used.

It will be understood that the current location L (n) and the previous location L (n-1) may be determined in other manners.

In step 406, a current velocity V (n) may be determined. The current velocity V (n) may comprise coordinates V_X (n) along the first direction and V_Y (n) along the second direction.

V (n) = (V_X (n) , V_Y (n) ) [Equation 5]

The current velocity V (n) may be determined based on the current location L (n) , the previous location L (n-1) and the current time interval T (n) obtained in step 404. The current velocity V (n) may be determined as follow.

V_X (n) = (X (n) -X (n-1) ) /T (n) [Equation 6]

V_Y (n) = (Y (n) -Y (n-1) ) /T (n) [Equation 7]

|V (n) | = sqrt (V_X (n) ² + V_Y (n) ²) [Equation 8]

However, it will be understood that the current velocity V (n) may be determined in other manners.

In step 408, a prediction of a subsequent velocity V’ (n+1) may be determined. The prediction of the subsequent velocity V’ (n+1) may comprise coordinates V’_X (n+1) along the first direction and V’_Y (n+1) along a second direction.

V’ (n+ 1) = (V’_X (n+ 1) , V’_Y (n+1) ) [Equation 9]

When the environment wherein the UE is located does not have fixed paths (e.g. alleys of an exhibition centre or a supermarket, corridor of a hospital, etc. ) , the subsequent velocity V’ (n+1) may be determined based on a prediction of a current velocity V’ (n) obtained in a previous instance of step 410 and an the current velocity V (n) obtained in step 406. The subsequent velocity V’ (n+1) may also be determined based on a filter parameter α. The filter parameter αr may be determined empirically or computed. The filter parameter α may reduce inertia effect and sudden changes caused for example due to interference (e.g. 0＜ α ＜ 1) . The subsequent velocity V’ (n+1) may also be determined based on a predetermined prediction of an initial velocity V’ (1) (e.g. V’ (1) = V (1) ) . The subsequent velocity V’ (n+1) may be determined as follow.

V’ (n+1) = (1-α) V’ (n+1) + α V (n) [Equation 10]

Moreover, a current orientation may be determined. The current orientation may be determined based on the current location L (n) and the previous location L (n-1) obtained in step 404.

When the environment wherein the UE is located has fixed paths, the prediction of the subsequent velocity V’ (n+1) may be determined using a Dijkstra shortest connected path algorithm. The current location L (n) obtained in step 406 may be mapped to a location on a fixed path and the subsequent velocity V’ (n+1) and the current orientation may be interpolated.

In step 410, a prediction of a subsequent location L’ (n+1) may be determined. The prediction of the subsequent location L’ (n+1) may comprise coordinates X’ (n+1) along the first direction and Y’ (n+1) along the second direction.

L’ (n+1) = (X’ (n+1) , Y’ (n+1) ) [Equation 11]

The prediction of the subsequent location L’ (n+1) may be determined based on the current location L (n) obtained in step 404, the prediction of the subsequent velocity V’ (n+1) , the current orientation obtained in step 408 and/or a subsequent time interval T (n+1) . The subsequent time interval T (n+1) may be assumed to be equal to the current time interval T (n) . The prediction of a subsequent location L’ (n+1) may be also be refined based on a map modelling the environment wherein the UE is located. The prediction of a subsequent location L’ (n+1) may be determined as follow.

X’ (n+ 1) = X (n) +V’_X (n+ 1) ＊T (n+1) [Equation 12]

Y’ (n+ 1) = Y (n) +V’_Y (n+ 1) ＊T (n+1) [Equation 13]

In step 412, a prediction of a subsequent reference signal measurement ψ’ (n+1) may be determined. The prediction of the subsequent reference signal measurement ψ’ (n+1) may be determined based on the prediction of a subsequent location L’ (n+1) obtained in step 410. The prediction of the subsequent reference signal measurement ψ’ (n+1) may be determined based on a fingerprint database.

In an example, the prediction of a subsequent location L’ (n+1) may be compared with locations stored in a fingerprint database. A matching location may be identified. The prediction of the subsequent reference signal measurement ψ’ (n+1) may be identified based on the reference signal measurement forming the fingerprint associated with the matching location. However, it will be understood that the prediction of the subsequent reference signal measurement ψ’ (n+1) may be determined in other manners.

In step 414, a prediction of a subsequent reference signal measurement variation Δψ’ (n+1) may be determined. The prediction of the subsequent reference signal measurement variation Δψ’ (n+1) may be determined based on the prediction of the subsequent reference signal measurement ψ’ (n+1) obtained in step 412 and the reference signal measurement variation Δψ (n) obtained in step 402. For example, the prediction of the subsequent reference signal measurement variation Δψ’ (n+1) may be determined by subtracting the current reference signal measurement ψ (n) to the prediction of the subsequent reference signal measurement ψ’ (n+1) . However, it will be understood that the current reference signal variation Δψ’ (n+1) may be obtained in other manners.

Δψ’ (n+1) = ψ’ (n+1) -ψ (n) [Equation 14]

In step 416, a weight mean average of reference signal measurement variation Ω (n+1) may be determined. The weight mean average of reference signal measurement variation Ω (n+1) may be determined based on the reference signal measurement variation Δψ (n) obtained in step 402, the prediction of a subsequent reference signal measurement variation Δψ’ (n+1) obtained in step 416, the current time interval T (n) obtained in step 400 and/or a filter parameter β. The filter parameter β may be determined empirically or computed. The filter parameter β may reduce inertia effect and sudden changes caused for example due to external interference (e.g. 0 ＜ β ＜ 1) . The weight mean average of reference signal measurement variation Ω (n+1) may be determined as follow. However, it will be understood the weight mean average of reference signal measurement variation Ω (n+1) may be determined in other manners.

Ω (n+1) = ( (1-β) Δψ (n) + β Δψ’ (n+1) ) /T (n) [Equation 15]

Then, if a subsequent MR is event triggered the method goes to step 418. If the subsequent MR is periodic the method goes to step 420.

In step 418 (i.e. the subsequent MR is event triggered) , the TTT is adjusted by the UE. The adjusted TTT may be determined based on weight mean average of reference signal measurement variation Ω (n+1) obtained in step 416, a first threshold ψh1 and a second threshold ψh2 and the current reference signal measurement ψ (n) .

The first threshold ψ h1 may be determined so that if a reference signal measurements ψ is greater than the first threshold ψ h1, a ping pong handover may occur. The second threshold ψ h2 may be determined so that if the current reference signal measurements ψ is lower than second threshold ψ h2, a RLF may occur. Ideally, the reference signal measurements ψ should be between the first threshold ψ h1 and the second threshold ψ h2 at the end of the adjusted TTT. The first threshold ψ h1 and the second threshold ψ h2 may be determined empirically or computed. The adjusted TTT may be determined as follow. However, it will be understood the adjusted TTT may be determined in other manners.

TTT = ( (ψ h1 + ψ h2) /2 - (n) ) /Ω (n+1) [Equation 16]

In step 420 (i.e. the subsequent MR is periodic) , the MR periodicity is adjusted and the subsequent time interval T (n+1) is determined. The subsequent time interval T (n+1) defines a subsequent time t (n+1) when a subsequent reference signal measurement ψ (n+1) will be collected and reported by the UE to the base station in a subsequent MR.

T (n+1) = t (n+1) -t (n) [Equation 17]

In an example, subsequent time interval T (n+1) may be determined based on the weight mean average of reference signal measurement variation Ω (n+1) obtained in step 416. A predetermined set of time intervals T may be stored in a table and associated with respective reference signal measurement variations Δψ to meet a localisation accuracy requirement. The weight mean average of reference signal measurement variation Ω (n+1) may be compared to the reference signal measurement variations Δψ in the table and a matching reference signal measurement variation Δψ may be identified. The subsequent time interval T (n+1) may then be determined based on the time interval T associated with the matching reference signal measurement variation (e.g. the subsequent time interval T (n+1) is equal to the time interval T associated with the matching reference signal measurement variation Δψ.

In another example, the subsequent time interval T (n+1) may be determined based on the weight mean average of reference signal measurement variation Ω (n+1) obtained in step 416 and a predetermined reference signal measurement variation Δψ that sets localisation accuracy requirement. The predetermined reference signal measurement variation Δψ that sets localisation accuracy requirement in the fingerprint database. Then, the subsequent time interval T (n+1) may be determined as follow.

T (n+1) = Δψ /Ω (n+1) [Equation 18]

However, it will be understood that the subsequent time interval T (n+1) may be determined in other manners. The subsequent time interval T (n+1) may be may then be added to a predefined set of time intervals T (e.g. the predefined set of 3GPP TS 36.331) .

It will be understood that steps 400, 418 and 420 may be performed by a UE. The

steps

402, 404, 406, 408, 410, 412, 414 and/or 416 may be performed by a UE, a base station or any other entity of a communication network.

It will also be understood that although the method has been described in the context of LTE, it may be applicable to other communication systems.

An advantage of one or more of the above embodiments is that an adaptive measurement report scheme is provided, in particular for indoor environments (but it will be understood that it would also be applicable in outdoor environments) . The MR periodicity may be optimized to meet a localization accuracy requirement in a complex indoor scenario and reduce the signaling overhead. Moreover, the TTT may be optimized to find an appropriate tradeoff between a ping pong handover rate and a RLF rate.

Figure 6 shows a schematic representation of non-volatile memory media 600a (e.g. computer disc (CD) or digital versatile disc (DVD) ) and 600b (e.g. universal serial bus (USB) memory stick) storing instructions and/or parameters 602 which when executed by a processor allow the processor to perform one or more of the steps of the method of Figure 5.

It is noted that while the above describes example embodiments, there are several variations and modifications which may be made to the disclosed solution without departing from the scope of the present invention.

The embodiments may thus vary within the scope of the attached claims. In general, some embodiments may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although embodiments are not limited thereto. While various embodiments may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that these blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.

The embodiments may be implemented by computer software stored in a memory and executable by at least one data processor of the involved entities or by hardware, or by a combination of software and hardware. Further in this regard it should be noted that any procedures, e.g., as in Figure 4, may represent program steps, or interconnected logic circuits, blocks and functions, or a combination of program steps and logic circuits, blocks and functions. The software may be stored on such physical media as memory chips, or memory blocks implemented within the processor, magnetic media such as hard disk or floppy disks, and optical media such as for example DVD and the data variants thereof, CD.

The memory 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, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The data processors 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) , application specific integrated circuits (ASIC) , gate level circuits and processors based on multi-core processor architecture, as non-limiting examples.

Alternatively or additionally some embodiments may be implemented using circuitry. The circuitry may be configured to perform one or more of the functions and/or method steps previously described. That circuitry may be provided in the base station and/or in the communications device.

As used in this application, the term “circuitry” may refer to one or more or all of the following:

(a) hardware-only circuit implementations (such as implementations in only analogue and/or digital circuitry) ;

(b) combinations of hardware circuits and software, such as:

(i) a combination of analogue and/or digital hardware circuit (s) with software/firmware and

(ii) any portions of hardware processor (s) with software (including digital signal processor (s) ) , software, and memory (ies) that work together to cause an apparatus, such as the communications device or base station to perform the various functions previously described; and

(c) hardware circuit (s) and or processor (s) , such as a microprocessor (s) or a portion of a microprocessor (s) , that requires software (e.g., firmware) for operation, but the software may not be present when it is not needed for operation.

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 integrated device.

The foregoing description has provided by way of exemplary and non-limiting examples a full and informative description of some embodiments However, various modifications and adaptations may become apparent to those skilled in the relevant arts in view of the foregoing description, when read in conjunction with the accompanying drawings and the appended claims. However, all such and similar modifications of the teachings will still fall within the scope as defined in the appended claims.

Claims

An apparatus comprising:

at least one processor; and

at least one memory including computer program code;

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to:

cause a user equipment to report reference signal measurements; and

cause the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.
The apparatus of claim 1, wherein the reference signal measurements comprise reference signal received power measurements.
The apparatus of claim 1 or claim 2, wherein the reference signal measurements comprises reference signal received quality measurements.
The apparatus of any of claims 1 to 3, wherein the time parameter associated with the operation comprises a periodicity associated with a reference signal measurement report operation.
The apparatus of any of claims 1 to 3, wherein the time parameter associated with the operation comprises a time to trigger associated with a handover operation.
The apparatus of any of claims 1 to 5, wherein the reference signal measurements comprise a current reference signal measurement and a previous reference signal measurement.
The apparatus of any of claim 6, wherein the at least one reference signal measurement variation comprises a current reference signal measurement variation.
The apparatus of claim 7, wherein the current reference signal measurement variation is determined based on the current reference signal measurement and the previous reference signal measurement.
The apparatus of any of claim 6 or claim 7, wherein the at least one reference signal measurement variation comprises a prediction of a subsequent reference signal measurement variation.
The apparatus of claim 9, wherein the prediction of the subsequent reference signal measurement variation is based on the current reference signal measurement and a prediction of a subsequent reference signal measurement.
The apparatus of claim 10, wherein the prediction of the subsequent reference signal measurement is determined based on a prediction of a subsequent location.
The apparatus of claim 11, wherein the prediction of the subsequent location is determined based on a current location and a prediction of a subsequent velocity.
The apparatus of claim 12, wherein the prediction of the subsequent location is determined based on a current orientation.
The apparatus of claim 13, wherein the current orientation is determined based on a current location and a previous location.
The apparatus of any of claims 12 to 14, wherein the prediction of the subsequent velocity is determined based on a current velocity and a prediction of the current velocity.
The apparatus of claim 15, wherein the current velocity is determined based on the current location and the previous location and a time difference separating the collection of the current reference signal measurement and the previous reference signal measurement.
The apparatus of any of claims 12 to 16, wherein the current location and the previous location is determined based on the current reference signal measurement and the previous reference signal measurement.
The apparatus of claim 16, wherein the current location and the previous location is determined based on a fingerprint database associating the current reference signal measurement to the current location and the previous reference signal measurement to the previous location.
A method comprising:

causing a user equipment to report reference signal measurements; and

causing the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.
A computer program comprising computer executable instructions which when run on one or more processors perform the steps of:

causing a user equipment to report reference signal measurements; and

causing the user equipment to adjust a time parameter associated with an operation at the user equipment, said time parameter being dependent on at least one reference signal measurement variation.