Acoustic-based positioning with dynamic frequency pilot tones

Abstract

Aspects presented herein may enable a wireless device to dynamically change the frequency of pilot tones of the wireless device based on the detected distance of one or more objects, thereby enabling the wireless device to take advantage of both high-frequency pilot tones and low-frequency pilot tones. In one aspect, a wireless device transmits a first pilot tone at a first frequency. The wireless device detects whether an object is present within a specified distance of the wireless device based on a reflected signal of the first pilot tone. The wireless device transmits a second pilot tone at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency. The wireless device calculates a first distance of the at least one object relative to the wireless device based on the second pilot tone.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. non-provisional patent application serial number 18 / 157,017, filed on January 19, 2023, entitled “ACOUSTIC-BASED POSITIONING WITH DYNAMIC FREQUENCY PILOT TONE,” which is expressly incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure relates generally to communication systems and, more particularly, to wireless communications with respect to positioning. Background Art

[0004] Wireless communication systems are widely deployed to provide a variety of telecommunication services, such as telephony, video, data, messaging, and broadcasts. Typical wireless communication systems may employ multiple access technologies capable of supporting communication with multiple users by sharing available system resources. Examples of such multiple access technologies include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single-carrier frequency division multiple access (SC-FDMA) systems, and time division synchronous code division multiple access (TD-SCDMA) systems.

[0005] These multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different wireless devices to communicate at a city, country, region, and even global level. An example telecommunication standard is 5G New Radio (NR). 5G NR is part of the continued mobile broadband evolution promulgated by the 3rd Generation Partnership Project (3GPP) to meet new requirements associated with latency, reliability, security, scalability (e.g., with the Internet of Things (IoT)), and other requirements. 5G NR includes services associated with enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). Some aspects of 5G NR may be based on the 4G Long Term Evolution (LTE) standard. Further improvements to 5G NR technology are needed. These improvements may also be applicable to other multiple access technologies and telecommunication standards that employ these technologies. Summary of the Invention

[0006] The following presents a simplified summary of one or more aspects in order to provide a basic understanding of these aspects. This summary is not an extensive overview of all contemplated aspects. This summary does not identify key or critical elements of all aspects, nor does it delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that will be presented later.

[0007] In one aspect of the present disclosure, a method, computer-readable medium, and apparatus are provided. The apparatus transmits a first pilot tone at a first frequency. The apparatus detects the presence of an object within a specified distance of a wireless device based on a reflected signal of the first pilot tone. Based on detecting at least one object within the specified distance, the apparatus transmits a second pilot tone at a second frequency, wherein the second frequency is higher than the first frequency.

[0008] To achieve the foregoing and related ends, one or more aspects may include the features fully described below and particularly pointed out in the claims. The following description and the accompanying drawings set forth in detail some illustrative features of one or more aspects. However, these features are indicative of only some of the various ways in which the principles of the various aspects may be employed. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a diagram illustrating an example of a wireless communication system and an access network.

[0010] Figure 2A is a diagram illustrating an example of a first frame according to various aspects of the present disclosure.

[0011] Figure 2B is a diagram illustrating an example of downlink (DL) channels within a subframe according to various aspects of the present disclosure.

[0012] Figure 2C is a diagram illustrating an example of a second frame according to various aspects of the present disclosure.

[0013] Figure 2D is a diagram illustrating an example of uplink (UL) channels within a subframe according to various aspects of the present disclosure.

[0014] Figure 3 is a diagram illustrating an example of a base station and a user equipment (UE) in an access network.

[0015] Figure 4 is a diagram illustrating an example of UE positioning based on reference signal measurement.

[0016] Figure 5 is a diagram illustrating an example acoustic echo detection system according to various aspects of the present disclosure.

[0017] Figure 6 is a diagram illustrating an example acoustic echo detection system with dynamic adjustment of pilot tones according to various aspects of the present disclosure.

[0018] Figure 7 is a diagram illustrating an example acoustic echo detection system with dynamic adjustment of pilot tones according to various aspects of the present disclosure.

[0019] Figure 8 is a diagram illustrating an example acoustic echo detection system with dynamic adjustment of pilot tones according to various aspects of the present disclosure.

[0020] Figure 9 is a diagram illustrating an example of adjusting the periodicity of a pilot tone according to various aspects of the present disclosure.

[0021] Figure 10 is a diagram illustrating an example of adjusting the periodicity of a pilot tone according to various aspects of the present disclosure.

[0022] Figure 11 is a diagram illustrating an example of an acoustic echo detection system that adjusts / exchanges pilot tone frequencies among multiple speakers based on the location and / or movement of a target object according to various aspects of the present disclosure.

[0023] Figure 12 is a diagram illustrating an example of an acoustic echo detection system that adjusts / exchanges pilot tone frequencies among multiple speakers based on the location and / or movement of a target object according to various aspects of the present disclosure.

[0024] Figure 13 is a diagram illustrating an example of an acoustic echo detection system that adjusts / exchanges pilot tone frequencies among multiple speakers based on the location and / or movement of a target object according to various aspects of the present disclosure.

[0025] Figure 14 is a flow chart illustrating an example of an acoustic echo detection system that dynamically changes the frequency of a pilot tone among multiple speakers based on the location and / or movement of a target object according to various aspects of the present disclosure.

[0026] Figure 15 is a diagram illustrating an example of using a neural network to determine whether an object is approaching or moving away from a speaker (or acoustic echo detection system) according to various aspects of the present disclosure.

[0027] Figure 16 is a diagram illustrating an example of an acoustic echo detection system that injects an active noise control (ANC) signal according to various aspects of the present disclosure.

[0028] Figure 17 is a flow chart of a method of wireless communication.

[0029] Figure 18 is a flow chart of a method of wireless communication.

[0030] Figure 19 are diagrams illustrating examples of hardware implementations for example apparatuses and / or network entities. DETAILED DESCRIPTION

[0031] Various aspects presented herein can improve the accuracy and reliability of distance detection for one or more objects based on acoustic echo detection. Various aspects presented herein provide an acoustic echo detection system (which, in some examples, may also be referred to as a wireless device or user equipment (UE)) that can dynamically change the frequency of a pilot tone (e.g., a transmitted sound signal of the acoustic echo detection system) of the acoustic echo detection system based on the distance of one or more detected objects, thereby enabling the acoustic echo detection system to utilize the advantages of both non-audible frequency pilot tones (e.g., capable of detecting objects with higher accuracy) and audible frequency pilot tones (e.g., capable of traveling a longer detection distance). In some examples, the non-audible frequency pilot tone may indicate a pilot tone with a frequency greater than 20 kHz (which, for the purposes of this disclosure, may also be referred to as a "high-frequency pilot tone"), while the audible frequency pilot tone may indicate a pilot tone with a frequency between 20 Hz and 20 kHz (which, for the purposes of this disclosure, may also be referred to as a "low-frequency pilot tone"). In other words, the aspects presented herein may provide a dynamic pilot tone system capable of identifying short, medium, and long ranges by changing the frequency of the pilot tone.

[0032] For example, in one aspect of the present disclosure, an acoustic echo detection system having multiple speakers (e.g., two or more speakers) can be configured to perform dynamic pilot tone frequency changes, where one speaker can initially be configured to inject (e.g., transmit) a lower (or fundamental) frequency pilot tone (e.g., below 10 kHz) for wider, longer-range detection, and the other speakers can be configured to inject a higher frequency pilot tone (e.g., above 20 kHz) for narrower, shorter-range detection when an object is detected. This can provide more accurate distance detection of the object depending on the object's location. For example, if an object is detected (e.g., based on received echoes) near a speaker injecting a lower-frequency pilot tone, the frequency of the pilot tone injected by that speaker can be increased (e.g., to a higher-frequency pilot tone), and at least one other speaker that was transmitting the higher-frequency pilot tone can be switched to transmitting the lower (fundamental) frequency pilot tone instead. In some examples, a recurrent neural network (RNN) model can be used to determine the change / switch of pilot tone frequencies (e.g., between a higher-frequency pilot tone and a lower-frequency pilot tone) between the multiple speakers. For example, an RNN model can be trained to determine whether an object is approaching a speaker (or acoustic echo detection system) or moving away from the speaker. In another aspect of the present disclosure, if the acoustic echo detection system is injecting a pilot tone with an audible frequency (e.g., 50 Hz to 15 kHz—(ideally) 0 kHz to 20 kHz is audible sound, but 99% of people may only hear 50 Hz to 15 kHz) and a person is detected near the acoustic echo detection system, the acoustic echo detection system can be configured to send / inject an active noise control (ANC) signal in the direction of the person to reduce / cancel the sound / noise associated with the audible pilot tone. ANC (which may also be referred to as noise cancellation (NC) or active noise reduction (ANR)) is a mechanism that reduces unwanted sounds by adding a second sound specifically designed to cancel the first sound.

[0033] The detailed description set forth below in conjunction with the accompanying drawings is a description of various configurations and does not represent the only configurations in which the concepts described herein may be practiced. The detailed description includes specific details to provide a thorough understanding of the various concepts. However, these concepts may be practiced without these specific details. In some cases, well-known structures and components are shown in block diagram form to avoid obscuring such concepts.

[0034] Several aspects of telecommunication systems are presented with reference to various apparatuses and methods. These apparatuses and methods are described in the following detailed description and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, etc. (collectively referred to as "elements"). These elements can be implemented using electronic hardware, computer software, or any combination thereof. Whether such elements are implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system.

[0035] As an example, an element, or any part of an element, or any combination of elements can be implemented as a "processing system", which includes one or more processors. The example of a processor includes a microprocessor, a microcontroller, a graphics processing unit (GPU), a central processing unit (CPU), an application processor, a digital signal processor (DSP), a reduced instruction set computing (RISC) processor, a system on a chip (SoC), a baseband processor, a field programmable gate array (FPGA), a programmable logic device (PLD), a state machine, a gated logic component, a discrete hardware circuit and other suitable hardware configured to perform the various functions described throughout this disclosure. One or more processors in a processing system can execute software. Whether referred to as software, firmware, middleware, microcode, hardware description language or other terms, software should be broadly interpreted as meaning an instruction, an instruction set, a code, a code segment, a program code, a program, a subroutine, a software component, an application, a software application, a software package, a routine, a subroutine, an object, an executable file, a thread of execution, a process, a function or any combination thereof.

[0036] Thus, in one or more example aspects, specific implementations and / or use cases, the functions described may be implemented in hardware, software, or any combination thereof. If implemented in software, the functions may be stored or encoded as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media. A storage medium may be any available medium that can be accessed by a computer. As an example, such computer-readable media may include random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of these types of computer-readable media, or any other medium that can be used to store computer-executable code in the form of instructions or data structures that can be accessed by a computer.

[0037] Although various aspects, specific implementations and / or use cases are described in this application by way of illustration of some examples, additional or different aspects, specific implementations and / or use cases may be generated in many different arrangements and scenarios. The various aspects, specific implementations and / or use cases described herein may be implemented across many different platform types, devices, systems, shapes, sizes and packaging arrangements. For example, various aspects, specific implementations and / or use cases may be generated via integrated chip implementations and other devices based on non-module components (e.g., end-user devices, vehicles, communication equipment, computing equipment, industrial equipment, retail / purchase equipment, medical equipment, devices that enable artificial intelligence (AI), etc.). Although some examples may or may not be specifically for use cases or applications, the examples described may have a wide range of applicability. Various aspects, specific implementations and / or use cases may be within the scope of chip-level or modular components to non-modular, non-chip-level specific implementations, and further to the scope of aggregated, distributed or original equipment manufacturer (OEM) devices or systems in combination with one or more technologies herein. In some actual settings, the devices in combination with the various aspects and features described may also include additional components and features for implementing and practicing the claimed and described aspects. For example, the transmission and reception of wireless signals necessarily include multiple components for both analog and digital purposes (e.g., hardware components including antennas, RF chains, power amplifiers, modulators, buffers, processors, interleavers, adders / summers, etc.). The techniques described herein can be practiced in a wide variety of devices of various sizes, shapes, and configurations, including chip-level components, systems, distributed arrangements, aggregated or disaggregated components, end-user devices, and the like.

[0038] The deployment of a communication system (such as a 5G NR system) can be arranged in a variety of ways with various components or parts. In a 5G NR system or network, a network node, a network entity, a mobility element of a network, a radio access network (RAN) node, a core network node, a network element or network equipment (such as a base station (BS)) or one or more units (or one or more components) that perform base station functions can be implemented in a converged or decomposed architecture. For example, a BS (such as a Node B (NB), an evolved NB (eNB), an NR BS, a 5G NB, an access point (AP), a transmit receive point (TRP) or a cell, etc.) can be implemented as a converged base station (also known as a standalone BS or a monolithic BS) or a decomposed base station.

[0039] A converged base station may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node. A decomposed base station may be configured to utilize a protocol stack that is physically or logically distributed between two or more units, such as one or more central or centralized units (CUs), one or more distributed units (DUs), or one or more radio units (RUs). In some aspects, a CU may be implemented within a RAN node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed across one or more other RAN nodes. A DU may be implemented to communicate with one or more RUs. Each of the CU, DU, and RU may be implemented as a virtual unit, namely a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU).

[0040] Base station operation or network design may take into account the aggregated nature of base station functionality. For example, a disaggregated base station may be utilized in an integrated access backhaul (IAB) network, an open radio access network (O-RAN (a network configuration such as that initiated by the O-RAN Alliance)), or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN)). Disaggregation may include distributing functionality across two or more units at various physical locations, as well as virtually distributing functionality of at least one unit, which may enable flexibility in network design. Various units of a disaggregated base station or disaggregated RAN architecture may be configured for wired or wireless communication with at least one other unit.

[0041] Figure 1 FIG1 is a diagram 100 illustrating an example of a wireless communication system and access network. The illustrated wireless communication system includes a disaggregated base station architecture. The disaggregated base station architecture may include one or more CUs 110, which may communicate directly with a core network 120 via a backhaul link, or indirectly with the core network 120 through one or more disaggregated base station units, such as a near real-time (near-RT) RAN intelligent controller (RIC) 125 via an E2 link, or a non-real-time (non-RT) RIC 115 associated with a service management and orchestration (SMO) framework 105, or both. The CU 110 may communicate with one or more DUs 130 via corresponding midhaul links, such as the F1 interface. The DU 130 may communicate with one or more RUs 140 via corresponding fronthaul links. The RU 140 may communicate with corresponding UEs 104 via one or more radio frequency (RF) access links. In some implementations, a UE 104 may be served simultaneously by multiple RUs 140.

[0042] Each of the units (i.e., CU 110, DU 130, RU 140, and near-RT RIC 125, non-RT RIC 115, and SMO framework 105) may include or be coupled to one or more interfaces configured to receive or transmit signals, data, or information (collectively, signals) via a wired or wireless transmission medium. Each of the units, or an associated processor or controller that provides instructions to the communication interfaces of these units, may be configured to communicate with one or more of the other units via a transmission medium. For example, these units may include a wired interface configured to receive signals or transmit signals to one or more of the other units via a wired transmission medium. Additionally, these units may include a wireless interface that may include a receiver, transmitter, or transceiver (such as an RF transceiver) configured to receive and / or transmit signals to one or more of the other units via a wireless transmission medium.

[0043] In some aspects, the CU 110 may host one or more high-level control functions. Such control functions may include radio resource control (RRC), packet data convergence protocol (PDCP), service data adaptation protocol (SDAP), etc. Each control function may be implemented using an interface that is configured to communicate signals with other control functions hosted by the CU 110. The CU 110 may be configured to handle user plane functions (i.e., central unit-user plane (CU-UP)), control plane functions (i.e., central unit-control plane (CU-CP)), or a combination thereof. In some specific implementations, the CU 110 may be logically divided into one or more CU-UP units and one or more CU-CP units. When implemented in an O-RAN configuration, the CU-UP unit may communicate bidirectionally with the CU-CP unit via an interface such as an E1 interface. As needed, the CU 110 may be implemented to communicate with the DU 130 for network control and signaling.

[0044] The DU 130 may correspond to a logical unit that includes one or more base station functions for controlling the operation of one or more RUs 140. In some aspects, the DU 130 may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and one or more higher physical (PHY) layers (such as modules for forward error correction (FEC) encoding and decoding, scrambling, modulation and demodulation, etc.) based at least in part on a functional split, such as those defined by 3GPP. In some aspects, the DU 130 may also host one or more lower PHY layers. Each layer (or module) may be implemented using an interface configured to communicate signals with other layers (and modules) hosted by the DU 130 or with control functions hosted by the CU 110.

[0045] Lower layer functions may be implemented by one or more RUs 140. In some deployments, a RU 140 controlled by a DU 130 may correspond to a logical node that hosts RF processing functions or low PHY layer functions (such as performing Fast Fourier Transform (FFT), Inverse FFT (iFFT), digital beamforming, Physical Random Access Channel (PRACH) extraction and filtering, etc.), or both, based at least in part on a functional split such as a lower layer functional split. In such an architecture, the RU 140 may be implemented to handle over-the-air (OTA) communications with one or more UEs 104. In some implementations, both real-time and non-real-time aspects of control plane communications and user plane communications with the RU 140 may be controlled by the corresponding DU 130. In some scenarios, this configuration may enable the DU 130 and CU 110 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

[0046] The SMO framework 105 can be configured to support RAN deployment and provisioning of both non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO framework 105 can be configured to support the deployment of dedicated physical resources for RAN coverage requirements, which can be managed via an operations and maintenance interface (such as the O1 interface). For virtualized network elements, the SMO framework 105 can be configured to interact with a cloud computing platform (such as Open Cloud (O-Cloud) 190) to perform network element lifecycle management (such as to instantiate virtualized network elements) via a cloud computing platform interface (such as the O2 interface). Such virtualized network elements may include, but are not limited to, the CU 110, DU 130, RU 140, and near-RT RIC 125. In some implementations, the SMO framework 105 can communicate with hardware aspects of the 4G RAN (such as the Open eNB (O-eNB) 111) via the O1 interface. Additionally, in some implementations, the SMO framework 105 can communicate directly with one or more RUs 140 via the O1 interface. The SMO framework 105 may also include a non-RT RIC 115 configured to support the functionality of the SMO framework 105 .

[0047] The non-RT RIC 115 may be configured to include logic that enables non-real-time control and optimization of RAN elements and resources, artificial intelligence (AI) / machine learning (ML) (AI / ML) workflows including model training and updating, or policy-based guidance of applications / features in the near-RT RIC 125. The non-RT RIC 115 may be coupled to or in communication with the near-RT RIC 125 (e.g., via an A1 interface). The near-RT RIC 125 may be configured to include logic that enables near-real-time control and optimization of RAN elements and resources through data collection and actions over an interface (e.g., via an E2 interface) that connects one or more CUs 110, one or more DUs 130, or both, and an O-eNB with the near-RT RIC 125.

[0048] In some implementations, the non-RT RIC 115 may receive parameters or external enrichment information from an external server in order to generate an AI / ML model to be deployed in the near-RT RIC 125. This information may be utilized by the near-RT RIC 125 and may be received from a non-network data source or from a network function at the SMO framework 105 or the non-RT RIC 115. In some examples, the non-RT RIC 115 or the near-RT RIC 125 may be configured to tune RAN behavior or performance. For example, the non-RT RIC 115 may monitor long-term trends and patterns in performance and employ AI / ML models to perform corrective actions through the SMO framework 105 (such as via reconfiguration of O1) or by creating RAN management policies (such as A1 policies).

[0049] At least one of the CU 110, DU 130, and RU 140 may be referred to as a base station 102. Thus, the base station 102 may include one or more of the CU 110, DU 130, and RU 140 (each component is indicated by a dotted line to indicate that each component may or may not be included in the base station 102). The base station 102 provides an access point to the core network 120 for the UE 104. The base station 102 may include a macro cell (a high-power cellular base station) and / or a small cell (a low-power cellular base station). Small cells include femto cells, pico cells, and micro cells. A network that includes both small cells and macro cells may be referred to as a heterogeneous network. A heterogeneous network may also include a home evolved Node B (eNB) (HeNB), which may provide services to a restricted group called a closed subscriber group (CSG). The communication link between the RU 140 and the UE 104 may include uplink (UL) (also known as reverse link) transmissions from the UE 104 to the RU 140 and / or downlink (DL) (also known as forward link) transmissions from the RU 140 to the UE 104. The communication link may utilize multiple-input multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming, and / or transmit diversity. The communication link may be over one or more carriers. The base station 102 / UE 104 may utilize spectrum of up to Y MHz (e.g., 5 MHz, 10 MHz, 15 MHz, 20 MHz, 100 MHz, 400 MHz, etc.) bandwidth for each carrier allocated in a carrier aggregation for a total of up to Yx MHz (x component carriers) for transmission in each direction. These carriers may or may not be adjacent to each other. The allocation of carriers may be asymmetric with respect to DL and UL (e.g., more or fewer carriers may be allocated for DL compared to UL). The component carriers may include a primary component carrier and one or more secondary component carriers. The primary component carrier may be referred to as a primary cell (PCell) and the secondary component carrier may be referred to as a secondary cell (SCell).

[0050] Some UEs 104 may communicate with each other using a device-to-device (D2D) communication link 158. The D2D communication link 158 may use DL / UL wireless wide area network (WWAN) spectrum. The D2D communication link 158 may use one or more sidelink channels, such as a physical sidelink broadcast channel (PSBCH), a physical sidelink discovery channel (PSDCH), a physical sidelink shared channel (PSSCH), and a physical sidelink control channel (PSCCH). D2D communication may be performed via various wireless D2D communication systems, such as, for example, Wi-Fi, LTE, or NR based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard.

[0051] The wireless communication system may also include a Wi-Fi AP 150 that communicates with a UE 104 (also referred to as a Wi-Fi station (STA)) via a communication link 154, for example, in the 5 GHz unlicensed spectrum. When communicating in the unlicensed spectrum, the UE 104 / AP 150 may perform a clear channel assessment (CCA) to determine whether the channel is available before communicating.

[0052] The electromagnetic spectrum is typically subdivided into various categories, bands, channels, etc. based on frequency / wavelength. In 5G NR, two initial operating bands have been identified as frequency range designations FR1 (410 MHz - 7.125 GHz) and FR2 (24.25 GHz - 52.6 GHz). Although a portion of FR1 is greater than 6 GHz, FR1 is often (interchangeably) referred to as the "sub-6 GHz" band in various documents and articles. A similar naming issue sometimes occurs with respect to FR2, which is often (interchangeably) referred to as the "millimeter wave" band in documents and articles, although it is different from the extremely high frequency (EHF) band (30 GHz - 300 GHz) identified as the "millimeter wave" band by the International Telecommunication Union (ITU).

[0053] Frequencies between FR1 and FR2 are generally referred to as mid-band frequencies. Recent 5G NR research has identified the operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHz–24.25 GHz). Frequency bands falling within FR3 can inherit FR1 characteristics and / or FR2 characteristics, thus effectively extending the features of FR1 and / or FR2 to mid-band frequencies. In addition, higher frequency bands are currently being explored to extend 5G NR operation to more than 52.6 GHz. For example, three higher operating bands have been identified as frequency range designations FR2-2 (52.6 GHz–71 GHz), FR4 (71 GHz–114.25 GHz), and FR5 (114.25 GHz–300 GHz). Each of these higher frequency bands falls within the EHF band.

[0054] With the above in mind, unless otherwise specified, if the term "sub-6 GHz" or the like is used herein, it may broadly refer to frequencies that may be less than 6 GHz, may be within FR1, or may include mid-band frequencies. Furthermore, unless otherwise specified, if the term "millimeter wave" or the like is used herein, it may broadly refer to frequencies that may include mid-band frequencies, may be within FR2, FR4, FR2-2, and / or FR5, or may be within the EHF band.

[0055] Base station 102 and UE 104 may each include multiple antennas (such as antenna elements, antenna panels, and / or antenna arrays) to facilitate beamforming. Base station 102 may transmit beamformed signals 182 to UE 104 in one or more transmit directions. UE 104 may receive beamformed signals from base station 102 in one or more receive directions. UE 104 may also transmit beamformed signals 184 to base station 102 in one or more transmit directions. Base station 102 may receive beamformed signals from UE 104 in one or more receive directions. Base station 102 / UE 104 may perform beam training to determine the optimal receive and transmit directions for each of base station 102 / UE 104. The transmit and receive directions of base station 102 may or may not be the same. The transmit and receive directions of UE 104 may or may not be the same.

[0056] The base station 102 may include and / or be referred to as a gNB, a Node B, an eNB, an access point, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP, a network node, a network entity, a network equipment, or some other suitable terminology. The base station 102 may be implemented as an integrated access and backhaul (IAB) node, a relay node, a sidelink node, a converged (monolithic) base station having a baseband unit (BBU) (including a CU and a DU) and a RU, or as a disaggregated base station including one or more of a CU, a DU, and / or a RU. A collection of base stations that may include disaggregated base stations and / or converged base stations may be referred to as a next generation (NG) RAN (NG-RAN).

[0057] The core network 120 may include an access and mobility management function (AMF) 161, a session management function (SMF) 162, a user plane function (UPF) 163, a unified data management (UDM) 164, one or more location servers 168, and other functional entities. The AMF 161 is a control node that handles signaling between the UE 104 and the core network 120. The AMF 161 supports registration management, connection management, mobility management, and other functions. The SMF 162 supports session management and other functions. The UPF 163 supports packet routing, packet forwarding, and other functions. The UDM 164 supports the generation of authentication and key agreement (AKA) credentials, user identity handling, access authorization, and subscription management. The one or more location servers 168 are exemplified as including a gateway mobile location center (GMLC) 165 and a location management function (LMF) 166. However, in general, the one or more location servers 168 may include one or more location / positioning servers, which may include one or more of the GMLC 165, LMF 166, Position Determination Entity (PDE), Serving Mobile Location Center (SMLC), Mobile Positioning Center (MPC), etc. The GMLC 165 and LMF 166 support UE location services. The GMLC 165 provides an interface for clients / applications (e.g., emergency services) to access UE positioning information. The LMF 166 receives measurements and assistance information from the NG-RAN and UE 104 via the AMF 161 to calculate the location of the UE 104. The NG-RAN may utilize one or more positioning methods to determine the location of the UE 104. Positioning the UE 104 may involve signal measurements, position estimates, and optionally velocity calculations based on these measurements. Signal measurements may be performed by the UE 104 and / or the base station 102 serving the UE 104. The measured signals may be based on a satellite positioning system (SPS) 170 (e.g., one or more of a global navigation satellite system (GNSS), a global positioning system (GPS), a non-terrestrial network (NTN), or other satellite positioning / location systems), LTE signals, wireless local area network (WLAN) signals, signals, ultra-wideband (UWB) signals, terrestrial beacon systems (TBS), sensor-based information (e.g., atmospheric pressure sensors, motion sensors), NR enhanced cell ID (NR E-CID) methods, NR signals (e.g., multi-round trip time (multi-RTT), DL angle of departure (DL-AoD), DL time difference of arrival (DL-TDOA), UL time difference of arrival (UL-TDOA), and UL angle of arrival (UL-AoA) positioning) and / or one or more of other systems / signals / sensors.

[0058] Examples of UE 104 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, global positioning systems, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, tablets, smart devices, wearable devices, vehicles, electric meters, gas pumps, large or small kitchen appliances, healthcare devices, implants, sensors / actuators, displays, or any other similarly functional device. Some of UE 104 may be referred to as IoT devices (e.g., parking meters, gas pumps, toasters, vehicles, heart rate monitors, etc.). UE 104 may also be referred to as a station, mobile station, subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology. In some scenarios, the term UE may also apply to one or more companion devices, such as in a device constellation arrangement. One or more of these devices may access the network collectively and / or individually.

[0059] Reference again Figure 1 In some aspects, the UE 104 may be configured (e.g., via the acoustic echo detection component 198) to transmit a first pilot tone at a first frequency; detect the presence of an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone; and transmit a second pilot tone at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency. Figure 1 As further shown, base station 102 may include a neural network component 199.

[0060] Figure 2A FIG200 is a diagram illustrating an example of a first subframe within a 5G NR frame structure. Figure 2B FIG230 is a diagram illustrating an example of DL channels within a 5G NR subframe. Figure 2C FIG250 is a diagram illustrating an example of a second subframe within a 5G NR frame structure. Figure 2D FIG280 is a diagram illustrating an example of UL channels within a 5G NR subframe. The 5G NR frame structure may be frequency division duplex (FDD), where for a particular set of subcarriers (carrier system bandwidth), subframes within that subcarrier set are dedicated to either DL or UL, or may be time division duplex (TDD), where for a particular set of subcarriers (carrier system bandwidth), subframes within that subcarrier set are dedicated to both DL and UL. Figure 2A 、 Figure 2CIn the example provided, the 5G NR frame structure is assumed to be TDD, where subframe 4 is configured with slot format 28 (most of which are DL), where D is DL, U is UL, and F is flexible between DL / UL, and subframe 3 is configured with slot format 1 (all of which are UL). Although subframes 3 and 4 are shown as having slot formats 1 and 28, respectively, any particular subframe can be configured with any of the various available slot formats 0-61. Slot formats 0 and 1 are all DL and all UL, respectively. The other slot formats 2-61 include a mix of DL, UL, and flexible symbols. The UE is configured with the slot format via the received slot format indicator (SFI) (dynamically configured via DL control information (DCI) or semi-statically / statically configured via radio resource control (RRC) signaling). Note that the following description also applies to the 5G NR frame structure as TDD.

[0061] Figures 2A to 2D The frame structure is illustrated, and various aspects of the present disclosure are applicable to other wireless communication technologies that may have different frame structures and / or different channels. A frame (10ms) can be divided into 10 equally sized subframes (1ms). Each subframe may include one or more time slots. A subframe may also include a mini-time slot, which may include 7, 4, or 2 symbols. Each time slot may include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For a normal CP, each time slot may include 14 symbols, and for an extended CP, each time slot may include 12 symbols. The symbols on the DL may be CP orthogonal frequency division multiplexing (OFDM) (CP-OFDM) symbols. The symbols on the UL may be CP-OFDM symbols (for high throughput scenarios) or discrete Fourier transform (DFT) spread OFDM (DFT-s-OFDM) symbols (for power-limited scenarios; limited to single-stream transmission). The number of time slots within a subframe is based on the CP and the parameter set. The parameter set defines the subcarrier spacing (SCS) (see Table 1). Symbol length / duration can be scaled with 1 / SCS.

[0062]

[0063] Table 1: Parameter set, SCS and CP

[0064] For normal CP (14 symbols / slot), different parameter sets μ0 to 4 allow 1, 2, 4, 8, and 16 slots per subframe, respectively. For extended CP, parameter set 2 allows 4 slots per subframe. Thus, for normal CP and parameter set μ, there are 14 symbols / slot and 2 μ time slots / subframe. The subcarrier spacing can be equal to 2 μ*15kHz, where μ is parameter set 0 to 4. Therefore, the subcarrier spacing for parameter set μ=0 is 15kHz, and the subcarrier spacing for parameter set μ=4 is 240kHz. Symbol length / duration is inversely related to subcarrier spacing. Figures 2A to 2D An example is provided for a normal CP with 14 symbols per slot and a parameter set μ=2 with 4 slots per subframe. The slot duration is 0.25 ms, the subcarrier spacing is 60 kHz, and the symbol duration is approximately 16.67 μs. Within a frame set, there may be one or more different bandwidth parts (BWPs) that are frequency-division multiplexed (see Figure 2B ). Each BWP may have a specific parameter set and CP (normal or extended).

[0065] A resource grid can be used to represent the frame structure. Each slot includes a resource block (RB) (also known as a physical RB (PRB)) that extends over 12 consecutive subcarriers. The resource grid is divided into multiple resource elements (REs). The number of bits carried by each RE depends on the modulation scheme.

[0066] like Figure 2A As illustrated, some of the REs carry reference (pilot) signals (RS) for the UE. The RSs may include a demodulation RS (DM-RS) (indicated as R for a particular configuration, but other DM-RS configurations are possible) and a channel state information reference signal (CSI-RS) for channel estimation at the UE. The RSs may also include a beam measurement RS (BRS), a beam refinement RS (BRRS), and a phase tracking RS (PT-RS).

[0067] Figure 2BExamples of various DL channels within a subframe of a frame are illustrated. The physical downlink control channel (PDCCH) carries DCI within one or more control channel elements (CCEs) (e.g., 1, 2, 4, 8, or 16 CCEs), each CCE comprising six RE groups (REGs), each REG comprising 12 consecutive REs within an OFDM symbol of a RB. The PDCCH within a BWP may be referred to as a control resource set (CORESET). During a PDCCH monitoring opportunity on the CORESET, the UE is configured to monitor PDCCH candidates in a PDCCH search space (e.g., a common search space, a UE-specific search space), where the PDCCH candidates have different DCI formats and different aggregation levels. Additional BWPs may be located at higher and / or lower frequencies across the channel bandwidth. The primary synchronization signal (PSS) may be within symbol 2 of a specific subframe of the frame. The PSS is used by the UE 104 to determine subframe / symbol timing and physical layer identity. The secondary synchronization signal (SSS) may be within symbol 4 of a specific subframe of the frame. The SSS is used by the UE to determine the physical layer cell identity group number and radio frame timing. Based on the physical layer identity and the physical layer cell identity group number, the UE can determine the physical cell identifier (PCI). Based on the PCI, the UE can determine the location of the DM-RS. The physical broadcast channel (PBCH) carrying the master information block (MIB) can be logically grouped with the PSS and SSS to form a synchronization signal (SS) / PBCH block (also known as an SS block (SSB)). The MIB provides the number of RBs in the system bandwidth and the system frame number (SFN). The physical downlink shared channel (PDSCH) carries user data, broadcast system information not sent over the PBCH (such as the system information block (SIB)), and paging messages.

[0068] like Figure 2C As illustrated, some of the REs carry DM-RS (indicated as R for a specific configuration, but other DM-RS configurations are possible) for channel estimation at the base station. The UE may transmit the DM-RS of the physical uplink control channel (PUCCH) and the DM-RS of the physical uplink shared channel (PUSCH). The PUSCH DM-RS may be transmitted in the first or first two symbols of the PUSCH. Depending on whether a short PUCCH or a long PUCCH is transmitted and on the specific PUCCH format used, the PUCCH DM-RS may be transmitted in different configurations. The UE may transmit a sounding reference signal (SRS). The SRS may be transmitted in the last symbol of the subframe. The SRS may have a comb structure, and the UE may transmit the SRS on one of the teeth of the comb. The SRS may be used by the base station for channel quality estimation to achieve frequency-dependent scheduling of the UL.

[0069] Figure 2DExamples of various UL channels within a subframe of a frame are illustrated. The PUCCH may be located at a position as indicated in one configuration. The PUCCH carries uplink control information (UCI), such as a scheduling request, a channel quality indicator (CQI), a precoding matrix indicator (PMI), a rank indicator (RI), and hybrid automatic repeat request (HARQ) acknowledgement (ACK) (HARQ-ACK) feedback (i.e., one or more HARQ ACK bits indicating one or more ACKs and / or negative ACKs (NACKs)). The PUSCH carries data and may additionally be used to carry a buffer status report (BSR), a power headroom report (PHR), and / or UCI.

[0070] Figure 3 3 is a block diagram of a base station 310 in an access network communicating with a UE 350. In the DL, Internet Protocol (IP) packets may be provided to a controller / processor 375. The controller / processor 375 implements layer 3 and layer 2 functions. Layer 3 includes a radio resource control (RRC) layer, and layer 2 includes a service data adaptation protocol (SDAP) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The controller / processor 375 provides RRC layer functions associated with broadcasting of system information (e.g., MIB, SIB), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-radio access technology (RAT) mobility, and measurement configuration for UE measurement reporting; PDCP layer functions associated with header compression / decompression, security (ciphering, deciphering, integrity protection, integrity verification), and handover support functions; RLC layer functions associated with delivery of upper layer packet data units (PDUs), error correction through ARQ, concatenation, segmentation and reassembly of RLC service data units (SDUs), resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functions associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

[0071] The transmit (TX) processor 316 and receive (RX) processor 370 implement Layer 1 functions associated with various signal processing functions. Layer 1, which includes the physical (PHY) layer, may include error detection on the transport channel, forward error correction (FEC) coding / decoding of the transport channel, interleaving, rate matching, mapping onto the physical channel, modulation / demodulation of the physical channel, and MIMO antenna processing. The TX processor 316 handles the mapping to the signal constellation based on various modulation schemes (e.g., binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), M-order phase-shift keying (M-PSK), and M-order quadrature amplitude modulation (M-QAM)). The coded and modulated symbols are then separated into parallel streams. Each stream is then mapped to an OFDM subcarrier, multiplexed with a reference signal (e.g., a pilot) in the time and / or frequency domain, and then combined using an inverse fast Fourier transform (IFFT) to produce a physical channel carrying a time-domain OFDM symbol stream. The OFDM stream is spatially pre-decoded to generate multiple spatial streams. Channel estimates from a channel estimator 374 may be used to determine the coding and modulation schemes, as well as for spatial processing. The channel estimates may be derived from a reference signal and / or channel condition feedback transmitted by the UE 350. Each spatial stream may then be provided to a different antenna 320 via a separate transmitter 318Tx. Each transmitter 318Tx may modulate a radio frequency (RF) carrier using a corresponding spatial stream for transmission.

[0072] At the UE 350, each receiver 354Rx receives a signal via its corresponding antenna 352. Each receiver 354Rx recovers the information modulated onto the RF carrier and provides the information to a receive (RX) processor 356. The TX processor 368 and the RX processor 356 implement layer 1 functions associated with various signal processing functions. The RX processor 356 performs spatial processing on the information to recover any spatial streams destined for the UE 350. If multiple spatial streams are destined for the UE 350, they may be combined into a single OFDM symbol stream by the RX processor 356. The RX processor 356 then converts the OFDM symbol stream from the time domain to the frequency domain using a fast Fourier transform (FFT). The frequency domain signal includes a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols on each subcarrier, as well as the reference signal, are recovered and demodulated by determining the most likely signal constellation point transmitted by the base station 310. These soft decisions may be based on channel estimates calculated by the channel estimator 358. The soft decisions are then decoded and deinterleaved to recover the data and control signals originally sent on the physical channel by base station 310. The data and control signals are then provided to a controller / processor 359, which implements layer 3 and layer 2 functionality.

[0073] The controller / processor 359 may be associated with a memory 360 that stores program codes and data. The memory 360 may be referred to as a computer-readable medium. In the UL, the controller / processor 359 provides demultiplexing between transport and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets. The controller / processor 359 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.

[0074] Similar to the functions described in conjunction with DL transmissions performed by the base station 310, the controller / processor 359 provides RRC layer functions associated with system information (e.g., MIB, SIB) acquisition, RRC connection, and measurement reporting; PDCP layer functions associated with header compression / decompression and security (encryption, decryption, integrity protection, integrity verification); RLC layer functions associated with delivery of upper layer PDUs, error correction through ARQ, concatenation, segmentation, and reassembly of RLC SDUs, resegmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functions associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs, demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

[0075] Channel estimates derived by the channel estimator 358 based on a reference signal or feedback transmitted by the base station 310 may be used by the TX processor 368 to select the appropriate coding and modulation schemes and to facilitate spatial processing. The spatial streams generated by the TX processor 368 may be provided to different antennas 352 via separate transmitters 354Tx. Each transmitter 354Tx may modulate an RF carrier with a corresponding spatial stream for transmission.

[0076] UL transmissions are processed at the base station 310 in a manner similar to that described in conjunction with the receiver functionality at the UE 350. Each receiver 318Rx receives a signal through its corresponding antenna 320. Each receiver 318Rx recovers information modulated onto an RF carrier and provides the information to the RX processor 370.

[0077] The controller / processor 375 may be associated with a memory 376 that stores program codes and data. The memory 376 may be referred to as a computer-readable medium. In the UL, the controller / processor 375 provides demultiplexing between transport and logical channels, packet reassembly, decryption, header decompression, and control signal processing to recover IP packets. The controller / processor 375 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.

[0078] At least one of the TX processor 368, the RX processor 356, and the controller / processor 359 may be configured to perform operations related to Figure 1 The acoustic echo detection component 198 combines various aspects.

[0079] At least one of the Tx processor 316, the Rx processor 370, and the controller / processor 375 may be configured to perform Figure 1 The neural network component 199 combines various aspects.

[0080] Figure 4 is a diagram 400 illustrating an example of UE positioning based on reference signal measurements (which may also be referred to as "network-based positioning") according to various aspects of the present disclosure. UE 404 may be at time T SRS_TX UL-SRS 412 is sent and at time T PRS_RX Receive DL Positioning Reference Signal (PRS) (DL-PRS) 410. TRP 406 may be at time T SRS_RX Receive UL-SRS 412 and at time T PRS_TX 410. The UE 404 may receive the DL-PRS 410 before transmitting the UL-SRS 412, or may transmit the UL-SRS 412 before receiving the DL-PRS 410. In both cases, the positioning server (e.g., the location server 168) or the UE 404 may determine the UL-SRS 412 based on the || T SRS_RX –T PRS_TX |–|T SRS_TX –T PRS_RX || to determine RTT 414. Thus, multi-RTT positioning may utilize UE Rx-Tx time difference measurements (ie, |T SRS_TX –T PRS_RX |) and DL-PRS reference signal received power (RSRP) (DL-PRS-RSRP), and the measured TRP Rx-Tx time difference measurement (ie, |T SRS_RX –T PRS_TX|) and UL-SRS-RSRP. UE 404 uses assistance data received from the positioning server to measure the UE Rx-Tx time difference measurement (and optionally the DL-PRS-RSRP of the received signal), and TRP 402, 406 uses assistance data received from the positioning server to measure the gNB Rx-Tx time difference measurement (and optionally the UL-SRS-RSRP of the received signal). These measurements can be used at the positioning server or UE 404 to determine the RTT, which is used to estimate the position of UE 404. Other methods for determining RTT are possible, such as, for example, using DL-TDOA and / or UL-TDOA measurements.

[0081] PRS can be defined for network-based positioning (e.g., NR positioning) to enable UEs to detect and measure more neighboring transmit and receive points (TRPs), with multiple configurations supported to enable various deployments (e.g., indoor, outdoor, sub-6, mmW, etc.). To support PRS beam operation, beam scanning can also be configured for PRS. The UL positioning reference signal can be based on a sounding reference signal (SRS) with enhancement / adjustment for positioning purposes. In some examples, the UL-PRS can be referred to as "SRS for positioning," and a new information element (IE) can be configured for SRS for positioning in RRC signaling.

[0082] DL PRS-RSRP may be defined as the linear average of the power contributions (in watts) of the resource elements of the antenna ports carrying the configured DL PRS reference signal for RSRP measurement, within the considered measurement frequency bandwidth. In some examples, for FR1, the reference point for DL PRS-RSRP may be the UE's antenna connector. For FR2, DL PRS-RSRP may be measured based on the combined signal from the antenna elements corresponding to a given receiver branch. For both FR1 and FR2, if the UE uses receiver diversity, the reported DL PRS-RSRP value may not be lower than the corresponding DL PRS-RSRP of any of the individual receiver branches. Similarly, UL SRS-RSRP may be defined as the linear average of the power contributions (in watts) of the resource elements carrying the sounding reference signal (SRS). UL SRS-RSRP may be measured over the configured resource elements, within the considered measurement frequency bandwidth, and during configured measurement occasions. In some examples, for FR1, the reference point for UL SRS-RSRP may be the antenna connector of the base station (e.g., gNB). For FR2, the UL SRS-RSRP may be measured based on the combined signals from the antenna elements corresponding to a given receiver branch. For FR1 and FR2, if the base station uses receiver diversity, the reported UL SRS-RSRP value may not be lower than the corresponding UL SRS-RSRP of any of the individual receiver branches.

[0083] PRS-Path RSRP (PRS-RSRPP) can be defined as the power of the linear average of the channel response at the i-th path delay of the resource element carrying the DL PRS signal configured for measurement, where the DL PRS-RSRPP for the 1st path delay is the power contribution corresponding to the first detected path in time. In some examples, the PRS path phase measurement can refer to the phase associated with the i-th path of the channel derived using the PRS resource.

[0084] DL-AoD positioning may utilize the measured DL-PRS-RSRP of downlink signals received at a UE 404 from multiple TRPs 402, 406. The UE 404 uses assistance data received from a positioning server to measure the DL-PRS-RSRP of the received signals, and the resulting measurements, along with the azimuth angle of departure (A-AoD), zenith angle of departure (Z-AoD), and other configuration information, are used to position the UE 404 relative to neighboring TRPs 402, 406.

[0085] DL-TDOA positioning may utilize DL Reference Signal Time Difference (RSTD) (and optionally DL-PRS-RSRP) of downlink signals received at a UE 404 from multiple TRPs 402, 406. The UE 404 uses assistance data received from a positioning server to measure the DL RSTD (and optionally DL-PRS-RSRP) of the received signals, and the resulting measurements, along with other configuration information, are used to position the UE 404 relative to neighboring TRPs 402, 406.

[0086] UL-TDOA positioning may utilize the UL relative time of arrival (RTOA) (and optionally UL-SRS-RSRP) of uplink signals transmitted from a UE 404 at multiple TRPs 402, 406. The TRPs 402, 406 measure the UL-RTOA (and optionally UL-SRS-RSRP) of the received signals using assistance data received from a positioning server, and the resulting measurements, along with other configuration information, are used to estimate the position of the UE 404.

[0087] UL-AoA positioning may utilize the measured azimuth angle of arrival (A-AoA) and zenith angle of arrival (Z-AoA) of uplink signals sent from a UE 404 at multiple TRPs 402, 406. The TRPs 402, 406 measure the A-AoA and Z-AoA of the received signals using assistance data received from a positioning server, and the resulting measurements, along with other configuration information, are used to estimate the position of the UE 404. For purposes of this disclosure, positioning operations in which a UE provides measurements to a base station / positioning entity / server for use in calculating the UE's position may be described as "UE-assisted," "UE-assisted positioning," and / or "UE-assisted position calculation," while positioning operations in which a UE measures and calculates its own position may be described as "UE-based," "UE-based positioning," and / or "UE-based position calculation."

[0088] Additional positioning methods may be used to estimate the position of the UE 404, such as, for example, UE-side UL-AoD and / or DL-AoA. It should be noted that data / measurements from various technologies may be combined in various ways to increase accuracy, determine and / or enhance certainty, supplement / complete measurements, and / or replace / provide missing information. For example, some UE positioning mechanisms may be radio access technology (RAT) dependent (e.g., positioning of the UE is based on the RAT), such as downlink positioning (e.g., measurements of observed time difference of arrival (OTDOA)), uplink positioning (e.g., measurements of uplink time difference of arrival (UTDOA)), and / or combined DL and UL based positioning (e.g., measurements of RTT relative to neighboring cells), etc. Some wireless communication systems may also support an enhanced cell ID (E-CID) positioning procedure based on radio resource management (RRM) measurements. On the other hand, some UE positioning mechanisms may be RAT independent (e.g., positioning of the UE is not dependent on the RAT), such as enhanced GNSS, and / or WLAN, Terrestrial beacon system (TBS) positioning technology and / or sensor-based positioning technology (e.g., air pressure sensor, motion sensor), etc. Some UE positioning mechanisms may be based on a hybrid model, in which multiple positioning methods are used, which may include both RAT-dependent positioning technology and RAT-independent positioning technology (e.g., GNSS and OTDOA hybrid positioning).

[0089] It should be noted that the terms "positioning reference signal" and "PRS" generally refer to specific reference signals used for positioning in NR and LTE systems. However, as used herein, the terms "positioning reference signal" and "PRS" may also refer to any type of reference signal that can be used for positioning, such as, but not limited to, PRS, TRS, PTRS, CRS, CSI-RS, DMRS, PSS, SSS, SSB, SRS, UL-PRS, and the like, as defined in LTE and NR. Furthermore, the terms "positioning reference signal" and "PRS" may refer to either downlink or uplink positioning reference signals, unless otherwise indicated by the context. To further distinguish between the types of PRS, downlink positioning reference signals may be referred to as "DL PRS," and uplink positioning reference signals (e.g., SRS, PTRS used for positioning) may be referred to as "UL-PRS." Furthermore, for signals that can be transmitted in both the uplink and downlink (e.g., DMRS, PTRS), these signals may be prepended with "UL" or "DL" to distinguish their direction. For example, "UL-DMRS" may be distinguished from "DL-DMRS."

[0090] While GNSS-based positioning and / or network-based positioning can provide accurate positioning, these positioning mechanisms may not function properly in GNSS-denied areas (e.g., when GNSS signals are unavailable), outside network coverage areas, and / or in short-range areas. Therefore, in some scenarios, a local positioning system may be more suitable for positioning than GNSS / network-based positioning. A local positioning system may refer to a technology / mechanism used to estimate the position / distance of one or more objects within a short-range area or a defined area (e.g., typically within a few meters). For example, infrared (IR), lasers, audio echoes, and / or cameras are some example technologies that can be used to perform short-range detection / identification. In some examples, devices used to perform short-range detection / identification may also be referred to as distance sensors, which can detect the distance of one or more objects by outputting a signal and measuring the change in the signal when it returns. The measured change can take the form of, for example, the time it takes for the signal to return, the strength of the returning signal, and / or a change in the phase of the returning signal. However, some distance sensors (such as cameras or IR) may not function properly in very bright areas or low-light conditions.

[0091] Acoustic echo detection (which may also be referred to as audio echo detection or ultrasonic sensing) is one of the most suitable mechanisms for detecting nearby / short-range objects with high reliability. Acoustic echo detection (or ultrasonic sensors) can use sound waves (e.g., ultrasonic pulses) to measure the distance to an object. For example, an acoustic echo detection system (e.g., an ultrasonic sensor) may include a transducer (e.g., an audio sound transducer) that acts as a speaker and is capable of transmitting sound waves (typically at a frequency above the human hearing range) and also acts as a microphone for receiving sound waves reflected from a target. The acoustic echo detection system can then determine the distance to the target by measuring the time lapse between the transmission and reception of the sound waves. However, acoustic echo detection may have limitations in detection range (fixed) and resolution (applicable to a predefined range).

[0092] Figure 5 5 is a diagram illustrating an example acoustic echo detection system according to various aspects of the present disclosure. The acoustic echo detection system 502 may include at least one speaker and at least one microphone, wherein the speaker may be used to transmit acoustic waves / acoustic pulses and the microphone may be used to receive acoustic waves / acoustic pulses reflected from a target object (the reflected acoustic waves / acoustic pulses may be referred to as echoes).

[0093] For example, as shown at 506, the acoustic echo detection system 502 may transmit an acoustic pulse at a first time point (T1). Then, as shown at 508, the transmitted acoustic pulse may reach the target 504 and reflect from the target 504 at a second time point (T2). As shown at 510, at a third time point (T3), the acoustic echo detection system 502 may receive the reflected acoustic pulse. Based on the time difference between the transmission of the acoustic pulse (e.g., T1) and the reception of the reflected acoustic pulse (e.g., T3), the acoustic echo detection system 502 may determine / estimate the distance between the acoustic echo detection system 502 and the target 504. In some examples, the transmitted acoustic pulse / sound wave may be referred to as a pilot tone, where the acoustic echo detection system 502 may designate pilot tone injection (e.g., transmission) and pilot tone reception to measure the time difference. For the purposes of this disclosure, the term "injection" may be used interchangeably with the term "transmission."

[0094] Acoustic frequencies between 20 kHz and 150 kHz are commonly used for pilot tones (e.g., acoustic waves / acoustic pulses) to avoid human interference and provide a more directional acoustic signal, as this frequency range is generally inaudible to humans. However, the detectable range of an acoustic echo detection system may vary based on the frequency of the pilot tone used by the acoustic echo detection system. For example, while a high-frequency pilot tone may provide greater accuracy (e.g., in terms of direction and / or object shape) than a low-frequency pilot tone, the detection range of a high-frequency pilot tone may be shorter (e.g., approximately 2.5 meters for a 20 kHz pilot tone and approximately 1.8 meters for a 40 kHz pilot tone). On the other hand, a low-frequency pilot tone may have a wider transmission range and a longer detection range than a high-frequency pilot tone (e.g., approximately 3 meters for a 10 kHz pilot tone, approximately 3.5 meters for a 6 kHz pilot tone, and approximately 4.5 meters for a 1 kHz pilot tone). However, pilot tones with frequencies below 20 kHz may be audible to humans.

[0095] In one example, with an inaudible pilot tone above 20 kHz, beamforming the pilot tone using a speaker array (e.g., a set of speakers) and a microphone array (e.g., a set of microphones) can increase the detection range of an acoustic echo detection system from 1 meter to a significant 2.5 meters with high accuracy (e.g., greater than 95%). Furthermore, using an audible pilot tone of 6 kHz can increase the corresponding range to 3.5 meters, which can be suitable for indoor (e.g., across a room) use. In some examples, at a distance of 3.5 meters, a 20 kHz pilot tone can have an accuracy of 96.8±2.2% at 2.5 meters, while for a 6 kHz pilot tone, the accuracy can be 95.7±0.9%.

[0096] Various aspects presented herein can improve the accuracy and reliability of distance detection for one or more objects based on acoustic echo detection. Various aspects presented herein provide an acoustic echo detection system (which, in some examples, may also be referred to as a wireless device or user equipment (UE)) that can dynamically change the frequency of a pilot tone (e.g., a transmitted sound signal of the acoustic echo detection system) of the acoustic echo detection system based on the distance of one or more detected objects, thereby enabling the acoustic echo detection system to utilize the advantages of both non-audible frequency pilot tones (e.g., capable of detecting objects with higher accuracy) and audible frequency pilot tones (e.g., capable of traveling a longer detection distance). In some examples, the non-audible frequency pilot tone may indicate a pilot tone with a frequency greater than 20 kHz (which, for the purposes of this disclosure, may also be referred to as a "high-frequency pilot tone"), while the audible frequency pilot tone may indicate a pilot tone with a frequency between 20 Hz and 20 kHz (which, for the purposes of this disclosure, may also be referred to as a "low-frequency pilot tone"). In other words, the aspects presented herein may provide a dynamic pilot tone system capable of identifying short, medium, and long ranges by changing the frequency of the pilot tone.

[0097] For example, in one aspect of the present disclosure, an acoustic echo detection system having multiple speakers (e.g., two or more speakers) can be configured to perform dynamic pilot tone frequency changes, where one speaker can initially be configured to inject (e.g., transmit) a lower (or fundamental) frequency pilot tone (e.g., below 10 kHz) for wider, longer-range detection, and the other speakers can be configured to inject a higher frequency pilot tone (e.g., above 20 kHz) for narrower, shorter-range detection when an object is detected. This can provide more accurate distance detection of the object depending on the object's location. For example, if an object is detected (e.g., based on received echoes) near a speaker injecting a lower-frequency pilot tone, the frequency of the pilot tone injected by that speaker can be increased (e.g., to a higher-frequency pilot tone), and at least one other speaker that was transmitting the higher-frequency pilot tone can be switched to transmitting the lower (fundamental) frequency pilot tone instead. In some examples, a recurrent neural network (RNN) model can be used to determine the change / switch of pilot tone frequencies (e.g., between a higher-frequency pilot tone and a lower-frequency pilot tone) between the multiple speakers. For example, an RNN model can be trained to determine whether an object is approaching a speaker (or acoustic echo detection system) or moving away from the speaker. In another aspect of the present disclosure, if the acoustic echo detection system is injecting a pilot tone with an audible frequency (e.g., 50 Hz to 15 kHz—(ideally) 0 kHz to 20 kHz is audible sound, but 99% of people may only hear 50 Hz to 15 kHz) and a person is detected near the acoustic echo detection system, the acoustic echo detection system can be configured to send / inject an active noise control (ANC) signal in the direction of the person to reduce / cancel the sound / noise associated with the audible pilot tone. ANC (which may also be referred to as noise cancellation (NC) or active noise reduction (ANR)) is a mechanism that reduces unwanted sounds by adding a second sound specifically designed to cancel the first sound.

[0098] Figure 6 、 Figure 7 and Figure 8Figures 600, 700, and 800 illustrate example acoustic echo detection systems with dynamic adjustment of pilot tones according to various aspects of the present disclosure. The acoustic echo detection system 602 may include a set of speakers and a set of microphones that can be used to inject (e.g., transmit) pilot tones (e.g., sound waves / sound pulses) and receive echoes (e.g., reflected sound waves / sound pulses). For illustrative purposes, the acoustic echo detection system 602 in Figure 600 includes a first speaker 604 (speaker 1), a second speaker 606 (speaker 2), a third speaker 608 (speaker 3), and up to an Nth speaker 610 (speaker N), and also includes a first microphone 612 (mic 1), a second microphone 614 (mic 2), and up to an Mth microphone 616 (mic M). However, the various aspects presented herein may also be applicable to acoustic echo detection systems having one speaker and / or one microphone. In some implementations, the set of speakers can be configured to be evenly distributed on the acoustic echo detection system 602 (eg, the distance between two adjacent speakers can be the same) and / or distributed towards different / multiple directions.

[0099] As shown at 618, the first speaker 604 can be initially configured to inject a low-frequency pilot tone 618 (e.g., 1 kHz, 5 kHz, 10 kHz, etc.), which can cover a wider range and a longer detection distance (compared to higher-frequency pilot tones), such as shown at 622. For example, if a 5 kHz pilot tone is used, the detection range can be up to 6 meters. In some examples, more than one speaker can be configured to initially inject a low-frequency pilot tone 618. For example, the second speaker 606 and the third speaker 608 can also be configured to inject a low-frequency pilot tone 618, or alternatively, they can be configured to not initially (or by default) transmit any pilot tone.

[0100] In one example, if Figure 7 As shown at 628 and 630 of diagram 700, if the person 624 and the object 626 move into the detection range of the acoustic echo detection system 602 (or the first speaker 604), the acoustic echo detection system 602 may be able to detect the person 624 and the object 626 based on the echo of the low-frequency pilot tone 620 (e.g., reflected from the person 624 and the object 626 and received by one of the microphones). The acoustic echo detection system 602 may also calculate the distance of the person 624 and / or the distance of the object 626 based on the echo of the low-frequency pilot tone 620, such as in combination with Figure 5 described.

[0101] like Figure 8As shown in diagram 800 of FIGURE 8, after the acoustic echo detection system 602 detects a person 624 and / or an object 626, the acoustic echo detection system 602 may configure the second speaker 606 to inject a high-frequency pilot tone 632 (e.g., a 40 kHz pilot tone with a detection range of approximately 1.5 meters) and the third speaker 608 to inject another high-frequency pilot tone 634 (e.g., a 20 kHz pilot tone with a detection range of approximately 3 meters). The high-frequency pilot tone 632 and the high-frequency pilot tone 634 may have the same frequency or different frequencies depending on one or more conditions. For example, the frequency to be used by the second speaker 606 or the third speaker 608 may depend on the estimated distance of the detected object. For example, if the acoustic echo detection system 602 detects that the person 624 is approximately 1.5 meters away, the acoustic echo detection system 602 may configure the second speaker 606 to inject a pilot tone with a detection range greater than at least 1.5 meters (e.g., a pilot tone with a frequency lower than 40 kHz). Similarly, if the acoustic echo detection system 602 detects that the object 626 is approximately 3 meters away from it, the acoustic echo detection system 602 may configure the third speaker 608 to inject a pilot tone having a detection range greater than at least 3 meters (e.g., a pilot tone having a frequency less than 20 kHz). Thus, one or more speakers of the acoustic echo detection system 602 may dynamically inject a high-frequency pilot tone depending on the object distance, while the first speaker 604 continues to inject the low-frequency pilot tone 620 to cover a wide area and a longer detection distance. The acoustic echo detection system 602 may then further calculate the distance of the person 624 and / or the distance of the object 626 based on the echoes of the high-frequency pilot tones 632 and / or 634, such as in combination with the pilot tone. Figure 5 described.

[0102] Although pilot tones with higher frequencies (e.g., high-frequency pilot tones 632 and 634) may have shorter detection ranges, these higher-frequency pilot tones also tend to provide and exhibit more directional characteristics and higher resolution of detected objects compared to pilot tones with lower frequencies (e.g., low-frequency pilot tone 620). Therefore, by enabling the acoustic echo detection system 602 to dynamically inject pilot tones of different frequencies (e.g., both high and low frequencies) via different speakers, the acoustic echo detection system 602 may be able to cover different detection ranges without affecting the accuracy and reliability of object / distance detection (e.g., without a trade-off between using high-frequency pilot tones or low-frequency pilot tones). In some examples, if the person 624 and / or object 626 is no longer within the detection range of the acoustic echo detection system 602, the acoustic echo detection system 602 may stop transmitting the high-frequency pilot tones 632 and / or 634.

[0103] In another example, Figures 6 to 8As shown, the acoustic echo detection system 602 can be configured / designed to include multiple speakers facing multiple / different directions, thereby enabling the acoustic echo detection system 602 to transmit pilot tones to cover a wider area. For example, the acoustic echo detection system 602 can be a circular device with speakers facing different angles (relative to the center). Similarly, the acoustic echo detection system 602 can also include multiple microphones placed at different locations or facing different directions to capture reflected pilot tones from a wider area. In some examples, the acoustic echo detection system 602 can be configured to rotate the injection of the low-frequency pilot tone through different speakers, such as when no object is detected within a specified time period. For example, if the acoustic echo detection system 602 initially injects the low-frequency pilot tone 620 from the first speaker 604 but does not detect any object within 10 seconds, the acoustic echo detection system 602 can rotate the injection of the low-frequency pilot tone 620 to the second speaker 606. Similarly, if the acoustic echo detection system 602 does not detect any object within another 10 seconds, the acoustic echo detection system 602 may rotate the injection of the low-frequency pilot tone 620 to the third speaker 608, etc. Thus, the acoustic echo detection system 602 may periodically rotate the origin of the pilot tone (e.g., from different speakers) to cover a larger angular area (e.g., 360 degrees).

[0104] In another aspect of the present disclosure, to reduce power consumption of an acoustic echo detection system (eg, the acoustic echo detection system 602 ), the acoustic echo detection system may dynamically adjust the periodicity of pilot tone injection based on whether an object is detected.

[0105] Figure 9 FIG. 9 is a diagram illustrating an example of adjusting the periodicity of a pilot tone according to various aspects of the present disclosure. In one example, as shown at 902, when an acoustic echo detection system detects an object within its detection range (e.g., Figure 7700 ), the acoustic echo detection system may transmit its pilot tone (e.g., a low / base frequency pilot tone) at a shorter periodicity (e.g., 10 microseconds (ms) per pilot tone injection). However, as shown at 904 , if the acoustic echo detection system does not detect any objects within its detection range (e.g., within a certain period of time), the acoustic echo detection system may transmit the pilot tone at a longer periodicity (e.g., 20 microseconds (ms) per pilot tone injection). In some examples, a minimum periodicity for injecting pilot tones may also be defined for the acoustic echo detection system to allow the acoustic echo detection system sufficient time to receive reflected pilot tones. For example, if a pilot tone requires a maximum of X ms to reach a target at a maximum detection range (e.g., 6 meters) and reflect from the target (e.g., a total of 12 meters), the acoustic echo detection system may be configured to transmit the pilot tone at a minimum periodicity greater than X ms.

[0106] In another example, to reduce power consumption, the acoustic echo detection system may further change its output power (e.g., for injecting pilot tones) based on whether an object is detected. For example, when at least one object is detected within its detection range, the acoustic echo detection system may increase its output power for transmitting low-frequency pilot tones, and when no object is detected within its detection range (for a specified period of time), the acoustic echo detection system may reduce its output power for transmitting low-frequency pilot tones (or return to a default output power).

[0107] Similarly, to ensure that multiple pilot tones reflected from one or more objects are correctly received by the microphone of the acoustic echo detection system (e.g., acoustic echo detection system 602), the acoustic echo detection system can also dynamically adjust the periodicity of pilot tone injection based on the number of pilot tones used.

[0108] Figure 10 FIG1000 is a diagram illustrating an example of adjusting the periodicity of a pilot tone according to various aspects of the present disclosure. In one example, as shown at 1002, the acoustic echo detection system may be configured to send a low / base frequency pilot tone (e.g., a 5 kHz pilot tone) with a shorter periodicity (e.g., 10 ms) when the acoustic echo detection system is injecting only the low / base frequency pilot tone (e.g., sending one pilot tone). However, as shown at 1004, when the acoustic echo detection system is configured, such as in response to a combination of Figure 8When the described detection object is sent to transmit three pilot tones (e.g., with an additional first high-frequency pilot tone and a second high-frequency pilot tone), the acoustic echo detection system can transmit the low / base frequency pilot tone with a longer periodicity (e.g., 30 ms) to provide sufficient time for the acoustic echo detection system to transmit and receive the different pilot tones. For example, as shown at 1006, the low-frequency pilot tone, the first high-frequency pilot tone, and the second high-frequency pilot tone can be configured to be injected 10 ms apart, so that each pilot tone has sufficient time to reach the target, reflect from the target, and be received by the acoustic echo detection system. This configuration can also prevent the acoustic echo detection system from transmitting and / or receiving pilot tones simultaneously, which may affect the accuracy and reliability of object detection.

[0109] In another aspect of the present disclosure, to further improve the accuracy and reliability of an acoustic echo detection system with a dynamic pilot tone, the acoustic echo detection system may adjust the frequency of the pilot tone sent from each speaker of the acoustic echo detection system based on the location and / or movement of the target object.

[0110] Figure 11 、 Figure 12 and Figure 13 1100, 1200 and 1300 respectively illustrate examples of an acoustic echo detection system that adjusts / switch pilot tone frequencies between multiple speakers based on the location and / or movement of a target object according to various aspects of the present disclosure. In one example, Figure 11 As shown in FIG1100, by default or in response to detecting a target object within its detection range (for example, as combined with Figure 8 As described above, the acoustic echo detection system (e.g., acoustic echo detection system 602) may inject a low frequency pilot tone (e.g., low frequency pilot tone 620) via the second speaker (speaker 2) and inject a high frequency pilot tone (e.g., high frequency pilot tones 632, 634) via the first speaker (speaker 1) and the third speaker (speaker 3).

[0111] like Figure 12 As shown in FIG1200 , when the acoustic echo detection system detects that the target object is moving toward the second speaker and the third speaker (and / or away from the first speaker), the acoustic echo detection system may configure the first speaker to inject a low-frequency pilot tone, and configure the second speaker and the third speaker to inject a high-frequency pilot tone. This may enable the acoustic echo detection system to inject a high-frequency pilot tone from a speaker closer to the target object, thereby improving the accuracy and / or reliability of estimating the distance of the target object from the acoustic echo detection system. Similarly, as Figure 13As shown in FIG1300 , if the acoustic echo detection system detects that the target object is now moving toward the first speaker and the second speaker (and / or away from the third speaker), the acoustic echo detection system may configure the first speaker and the second speaker to inject a high-frequency pilot tone and configure the third speaker to inject a low-frequency pilot tone.

[0112] Figure 14 is a flow chart 1400 illustrating an example of an acoustic echo detection system that dynamically changes the frequency of a pilot tone among a plurality of speakers based on the location and / or movement of a target object according to various aspects of the present disclosure. The acoustic echo detection system may transmit a pilot tone via a set of speakers, such as in combination with Figures 6 to 8 The acoustic echo detection system may then receive reflections of the pilot tone via at least one microphone.

[0113] At 1402, after receiving the reflected pilot tone, the acoustic echo detection system may filter the reflected pilot tone, such as using a frequency shift filter or a log-Mel filter.

[0114] At 1404 , the acoustic echo detection system may calculate a time delay of the transmitted pilot tone, such as the time between when the pilot tone is transmitted and when the reflected pilot tone is received by the acoustic echo detection system.

[0115] At 1406 and 1408 , the acoustic echo detection system may generate a set of background signals, and the acoustic echo detection system may subtract the background signal of the reflected pilot tone based on the set of generated background signals.

[0116] At 1410, the acoustic echo detection system may estimate the size and / or direction (e.g., approaching, moving away, etc.) of the detected object, such as based on a machine learning (ML) model using maximum likelihood estimation (MLE). MLE may refer to a method for estimating the parameters of a hypothesized probability distribution given some observed data. This is achieved by maximizing a likelihood function so that the observed data is the most likely under the assumed statistical model.

[0117] At 1412, based on the estimated size and / or direction of movement of the detected object, the acoustic echo detection system may dynamically adjust the frequency of the pilot tone injected from its speaker, such as in conjunction with Figures 11 to 13 For example, if the acoustic echo detection system detects that an object is moving toward its left, the acoustic echo detection system may configure the speaker on its left to transmit a high-frequency pilot tone and the speaker on its right to transmit a low-frequency pilot tone.

[0118] In some implementations, the acoustic echo detection system can have the capability to classify / identify objects approaching or leaving a speaker using a specified set of input features and a neural network (NN).

[0119] Figure 15 FIG1500 is a diagram illustrating an example of using a neural network to determine whether an object is approaching or moving away from a speaker (or acoustic echo detection system) according to various aspects of the present disclosure. In one example, a neural network (e.g., a recurrent neural network (RNN), a convolutional neural network (CNN), etc.) may receive a feature sequence for each speaker in a set of speakers (e.g., speakers 1 to 3), wherein the feature sequence may be associated with a detected object and / or the corresponding speaker. For example, the features may include autocorrelation, velocity, frequency shift, amplitude shift (or amplitude decay), logarithmic Mel coefficients, and / or Mel-frequency cepstral coefficients associated with the speaker and the object. Based on the received feature sequence, the neural network may then classify the movement of the object, such as whether the object is approaching or moving away from a specified speaker (or acoustic echo detection system).

[0120] For example, as shown at 1502, the RNN can be used to classify the movement of an object given a feature sequence of T frames, where these features can be the log-Mel or frequency shift (Doppler effect) describing the relative speed between the corresponding speaker and the detected object. Then, based on the feature sequence, the RNN can generate an output y (which can also be called an inference), which is a single node:

[0121] y∈[0,1]. In one example, a higher value may indicate a higher probability that the object is close to the speaker. The frequency of the pilot tone (from the speaker) may then be determined based on the confidence value of the output node, for example, f pilot =(f max -f min )y+f min , where f max and f min The predefined maximum pilot tone frequency and minimum pilot tone frequency may be indicated, respectively.

[0122] In another aspect of the present disclosure, to avoid or reduce interference with humans when the acoustic echo detection system is injecting pilot tones having audible frequencies (e.g., 0 kHz-20 kHz), the acoustic echo detection system may be configured to transmit an active noise control (ANC) signal, which may be transmitted in response to detection of a human (e.g., by the acoustic echo detection system) or when audible frequencies are used for the pilot tones.

[0123] Figure 161600 is a diagram illustrating an example of an acoustic echo detection system injecting an ANC signal according to various aspects of the present disclosure. As shown at 1602, the acoustic echo detection system (e.g., acoustic echo detection system 602) may be injecting a pilot tone having an audible frequency (e.g., 0 kHz-20 kHz) via one of its speakers (e.g., speaker 1). Then, as shown at 1604, if a person is detected by the acoustic echo detection system (or if an audible frequency is used for the pilot tone), the acoustic echo detection system may inject an ANC signal (e.g., an inverse signal of the pilot tone) to cancel or reduce the sound / noise associated with the pilot tone.

[0124] In some examples, the acoustic echo detection system may be able to identify the identity of an object (e.g., a person, an animal, etc.) based on reflected pilot tones based on the use of an ML model (such as an ML model that can perform source separation). Source separation (which may also be referred to as blind signal separation (BSS) or blind source separation) is the separation of a set of source signals from a set of mixed signals without the help of (or with very little information about) information about the source signals or the mixing process. Source separation may involve analysis of a mixture of signals, where the goal is to recover the original component signals from the mixed signals. For the present disclosure, since the reflected signals (e.g., echoes) may be deterministic and known a priori, a mask vector or mask matrix may be generated a priori for each source, and thus source separation may be accomplished using a one-level NN or ML approach. In another example, using ML / models or NNs to perform source separation may also enable the acoustic echo detection system to perform source separation without configuring gaps between pilot tones sent from different speakers (e.g., as combined with Figure 10 In the case of a system (described above), two or more pilot tones may be injected because the acoustic echo detection system may be able to distinguish between reflected pilot tones from different speakers and frequencies. In other words, the acoustic echo detection system may simultaneously transmit multiple pilot tones of different frequencies from different speakers. As a result, the acoustic echo detection system may be able to perform faster scanning (e.g., object detection) and / or have a faster response time for relatively fast-moving objects, etc.

[0125] The various aspects presented herein may be suitable for devices that specify high-accuracy distance measurements in a short range (e.g., Internet of Things (IoT) devices, robots, cars, etc.). Although lasers, cameras, and infrared may be alternative methods for distance measurement, they may not work properly in bright light or dark environments, or may not have the ability to provide wide range and / or short-range detection. Since this acoustic echo detection can provide accurate and reliable distance measurements, it can be a good method for short-range detection. Since the fixed frequency ultrasonic method has the limitation of fixed range detection, the method cannot capture objects beyond the fixed range, and the detection accuracy of the method can be guaranteed within a limited range. Therefore, the acoustic echo detection system with dynamic pilot tone described herein can provide dynamic distance control with high detection accuracy. In some examples, such as Figures 6 to 8 As shown, the speakers of the acoustic echo detection system can be configured to inject pilot tones in different directions. For example, the acoustic echo detection system 602 can include N speakers and M microphones covering 360 directions.

[0126] Figure 17 1700 is a flow chart of a method of wireless communication. The method may be performed by a wireless device (e.g., UE 104, 404; acoustic echo detection system 502, 602; apparatus 1904). The method may enable the wireless device to dynamically change the frequency of the wireless device's pilot tone based on the distance of one or more detected objects, thereby enabling the wireless device to utilize the advantages of both high-frequency pilot tones and low-frequency pilot tones.

[0127] At 1702, the wireless device may transmit a first pilot tone at a first frequency, such as in conjunction with Figures 6 to 8 For example, Figure 6 As shown, the acoustic echo detection system 602 may inject (eg, transmit) a low frequency pilot tone 620 from a first speaker 604. The means for transmitting the first pilot tone may be provided by, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0128] At 1704, the wireless device may detect whether an object is within a specified distance of the wireless device based on the reflected signal of the first pilot tone, such as in conjunction with Figures 6 to 8 For example, Figure 7 As shown, the acoustic echo detection system 602 can detect people 624 and objects 626 within its detection distance (e.g., 6 meters) based on the echo of the low-frequency pilot tone 620 (e.g., reflected from people 624 and objects 626). The component for detecting whether there is an object within the specified distance can be composed of, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0129] In one example, to detect whether an object is within a specified distance based on a first pilot tone, the wireless device may receive a reflected signal of the first pilot tone from at least one object, calculate a distance of the at least one object relative to the wireless device based on the reflected signal of the first pilot tone, and determine that the at least one object is within the specified distance if the calculated distance is within the specified distance.

[0130] In another example, to detect whether an object is within a specified distance of the wireless device based on a reflected signal of a first pilot tone, the wireless device may identify the reflected signal as associated with the object based on source separation. In some implementations, the reflected signal may be identified as associated with the object based on source separation.

[0131] At 1706, the wireless device may transmit a second pilot tone at a second frequency based on detecting at least one object within a specified distance, wherein the second frequency is higher than the first frequency, such as in conjunction with Figures 6 to 8 For example, Figure 8 As shown, in response to detecting a person 624 and / or an object 626, the acoustic echo detection system 602 may transmit a higher frequency pilot tone 632 and / or a higher frequency pilot tone 634. The means for transmitting the second pilot tone may be provided by, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0132] In one example, the wireless device may estimate at least one of a size, a direction, or a distance of the at least one object based on a machine learning model, and the wireless device may further transmit a second pilot tone based on the size, direction, distance, or a combination thereof of the at least one object. In some implementations, the direction of the at least one object may indicate whether the at least one object is approaching or moving away from the wireless device.

[0133] At 1708, the wireless device may calculate a first distance of at least one object relative to the wireless device based on the second pilot tone, such as in combination with Figures 6 to 8 For example, Figure 8 As shown, the acoustic echo detection system 602 can further calculate the distance of the person 624 and / or the distance of the object 626 based on the echo of the high frequency pilot tone 632 and / or 634. The component for calculating the first distance of at least one object can be composed of, for example Figure 19The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0134] In one example, the wireless device may transmit a third pilot tone at a third frequency based on detecting at least one object within a specified distance, where the third frequency may be higher than the first frequency and different from the second frequency, and the wireless device may calculate a second distance of the at least one object relative to the wireless device based on the third pilot tone. In some implementations, the first pilot tone may be transmitted via a first speaker, the second pilot tone may be transmitted via a second speaker, and the third pilot tone may be transmitted via a third speaker.

[0135] At 1710, the wireless device may stop transmitting the second pilot tone based on at least one object no longer being within a specified distance, such as in conjunction with Figures 6 to 8 For example, Figure 8 As shown, if the person 624 and / or the object 626 are no longer within the detection range of the acoustic echo detection system 602, the acoustic echo detection system 602 may stop transmitting the high frequency pilot tones 632 and / or 634. The means for stopping transmitting the second pilot tone may be provided by, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0136] At 1712, the wireless device may detect that at least one object includes a person, and the wireless device may inject a reverse signal of the first pilot tone, such as in combination with Figure 16 For example, Figure 16 As shown at 1604 of FIG, if a person is detected, the acoustic echo detection system may inject a reverse signal of the pilot tone. The means for detecting that at least one object includes a person and / or the means for injecting a reverse signal of the first pilot tone may be provided by, for example Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0137] At 1714, if no object is detected within a specified distance of the wireless device within a specified time period, the wireless device may transmit the first pilot tone with a longer periodicity, such as in conjunction with Figure 9 For example, Figure 9As shown at 904 of FIG, if no object is detected in the area, the acoustic echo detection system 602 may send a low frequency pilot tone with a longer periodicity. The component for sending the first pilot tone with a longer periodicity may be, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0138] In one example, if at least one object is detected within a second specified distance of the wireless device, the wireless device may transmit a second pilot tone with a shorter periodicity.

[0139] In another example, a first pilot tone may be initially transmitted via a first speaker, and a second pilot tone may be initially transmitted via a second speaker. The wireless device may detect that at least one object is approaching the first speaker, and the wireless device may switch transmission of the first pilot tone to the second speaker and transmission of the second pilot tone to the first speaker based on the at least one object approaching the first speaker. In some implementations, to detect that the at least one object is moving toward the first speaker, the wireless device may send a set of features associated with the at least one object, the first speaker, the second speaker, or a combination thereof to the neural network. The wireless device may then receive an indication or inference from the neural network that the at least one object is approaching the first speaker. In some examples, the set of features may correspond to features collected during different time frames. In some examples, the set of features may include at least one of a frequency shift, an amplitude shift, a logarithmic Mel coefficient, or a Mel-frequency cepstral coefficient.

[0140] Figure 18 1800 is a flow chart of a method of wireless communication. The method may be performed by a wireless device (e.g., UE 104, 404; acoustic echo detection system 502, 602; apparatus 1904). The method may enable the wireless device to dynamically change the frequency of the wireless device's pilot tone based on the distance of one or more detected objects, thereby enabling the wireless device to utilize the advantages of both high-frequency pilot tones and low-frequency pilot tones.

[0141] At 1802, the wireless device may transmit a first pilot tone at a first frequency, such as in conjunction with Figures 6 to 8 For example, Figure 6 As shown, the acoustic echo detection system 602 may inject (eg, transmit) a low frequency pilot tone 620 from a first speaker 604. The means for transmitting the first pilot tone may be provided by, for example, Figure 19The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0142] At 1804, the wireless device may detect whether an object is within a specified distance of the wireless device based on the reflected signal of the first pilot tone, such as in conjunction with Figures 6 to 8 For example, Figure 7 As shown, the acoustic echo detection system 602 can detect people 624 and objects 626 within its detection distance (e.g., 6 meters) based on the echo of the low-frequency pilot tone 620 (e.g., reflected from people 624 and objects 626). The component for detecting whether there is an object within the specified distance can be composed of, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0143] In one example, to detect whether an object is within a specified distance based on a first pilot tone, the wireless device may receive a reflected signal of the first pilot tone from at least one object, calculate a distance of the at least one object relative to the wireless device based on the reflected signal of the first pilot tone, and determine that the at least one object is within the specified distance if the calculated distance is within the specified distance.

[0144] In another example, to detect whether an object is within a specified distance of the wireless device based on a reflected signal of a first pilot tone, the wireless device may identify the reflected signal as associated with the object based on source separation. In some implementations, the reflected signal may be identified as associated with the object based on source separation.

[0145] At 1806, the wireless device may transmit a second pilot tone at a second frequency based on detecting at least one object within a specified distance, wherein the second frequency is higher than the first frequency, such as in conjunction with Figures 6 to 8 For example, Figure 8 As shown, in response to detecting a person 624 and / or an object 626, the acoustic echo detection system 602 may transmit a higher frequency pilot tone 632 and / or a higher frequency pilot tone 634. The means for transmitting the second pilot tone may be provided by, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0146] In one example, the wireless device may estimate at least one of a size, a direction, or a distance of the at least one object based on a machine learning model, and the wireless device may further transmit a second pilot tone based on the size, direction, distance, or a combination thereof of the at least one object. In some implementations, the direction of the at least one object may indicate whether the at least one object is approaching or moving away from the wireless device.

[0147] In another example, the wireless device may calculate a first distance of at least one object relative to the wireless device based on the second pilot tone, such as in combination with Figures 6 to 8 For example, Figure 8 As shown, the acoustic echo detection system 602 can further calculate the distance of the person 624 and / or the distance of the object 626 based on the echo of the high frequency pilot tone 632 and / or 634. The component for calculating the first distance of at least one object can be composed of, for example Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0148] In another example, the wireless device may transmit a third pilot tone at a third frequency based on detecting at least one object within a specified distance, wherein the third frequency may be higher than the first frequency and different from the second frequency, and the wireless device may calculate a second distance of the at least one object relative to the wireless device based on the third pilot tone. In some implementations, the first pilot tone may be transmitted via a first speaker, the second pilot tone may be transmitted via a second speaker, and the third pilot tone may be transmitted via a third speaker.

[0149] In another example, the wireless device may stop transmitting the second pilot tone based on at least one object no longer being within a specified distance, such as in conjunction with Figures 6 to 8 For example, Figure 8 As shown, if the person 624 and / or the object 626 are no longer within the detection range of the acoustic echo detection system 602, the acoustic echo detection system 602 may stop transmitting the high frequency pilot tones 632 and / or 634. The means for stopping transmitting the second pilot tone may be provided by, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0150] In another example, the wireless device may detect that at least one object includes a person, and the wireless device may inject a reverse signal of the first pilot tone, such as in combination with Figure 16 For example, Figure 16As shown at 1604 of FIG, if a person is detected, the acoustic echo detection system may inject a reverse signal of the pilot tone. The means for detecting that at least one object includes a person and / or the means for injecting a reverse signal of the first pilot tone may be provided by, for example Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0151] In another example, if no object is detected within a specified distance of the wireless device within a specified time period, the wireless device may transmit the first pilot tone with a longer periodicity, such as in conjunction with Figure 9 For example, Figure 9 As shown at 904 of FIG, if no object is detected in the area, the acoustic echo detection system 602 may send a low frequency pilot tone with a longer periodicity. The component for sending the first pilot tone with a longer periodicity may be, for example, Figure 19 The system may be executed by the acoustic echo detection component 198, the application processor 1906, the cellular baseband processor 1924, the speaker 1934, the microphone 1936 and / or the transceiver 1922 of the device 1904.

[0152] In another example, if at least one object is detected within a second specified distance of the wireless device, the wireless device may transmit a second pilot tone with a shorter periodicity.

[0153] In another example, a first pilot tone may be initially transmitted via a first speaker, and a second pilot tone may be initially transmitted via a second speaker. The wireless device may detect that at least one object is approaching the first speaker, and the wireless device may switch transmission of the first pilot tone to the second speaker and transmission of the second pilot tone to the first speaker based on the at least one object approaching the first speaker. In some implementations, to detect that the at least one object is moving toward the first speaker, the wireless device may send a set of features associated with the at least one object, the first speaker, the second speaker, or a combination thereof to the neural network. The wireless device may then receive an indication or inference from the neural network that the at least one object is approaching the first speaker. In some examples, the set of features may correspond to features collected during different time frames. In some examples, the set of features may include at least one of a frequency shift, an amplitude shift, a logarithmic Mel coefficient, or a Mel-frequency cepstral coefficient.

[0154] Figure 191900 is a diagram illustrating an example of a hardware implementation for an apparatus 1904. The apparatus 1904 may be a UE, a component of a UE, or may implement UE functionality. In some aspects, the apparatus 1904 may include a cellular baseband processor 1924 (also referred to as a modem) coupled to one or more transceivers 1922 (e.g., a cellular RF transceiver). The cellular baseband processor 1924 may include on-chip memory 1924′. In some aspects, the apparatus 1904 may also include one or more subscriber identity module (SIM) cards 1920 and an application processor 1906 coupled to a secure digital (SD) card 1908 and a screen 1910. The application processor 1906 may include on-chip memory 1906′. In some aspects, the apparatus 1904 may also include one or more speakers 1934 and one or more microphones 1936. In some aspects, the device 1904 may also include a Bluetooth module 1912, a WLAN module 1914, an ultra-wideband (UWB) module 1938, an SPS module 1916 (e.g., a GNSS module), one or more sensor modules 1918 (e.g., a barometric pressure sensor / altimeter; a motion sensor such as an inertial measurement unit (IMU), a gyroscope, and / or an accelerometer; light detection and ranging (LIDAR), radio-aided detection and ranging (RADAR), sound navigation and ranging (SONAR), a magnetometer, audio, and / or other technologies for positioning), an additional memory module 1926, a power supply 1930, and / or a camera 1932. The Bluetooth module 1912, the WLAN module 1914, and the SPS module 1916 may include an on-chip transceiver (TRX) (or, in some cases, only a receiver (RX)). The Bluetooth module 1912, the WLAN module 1914, and the SPS module 1916 may include their own dedicated antennas and / or utilize an antenna 1980 for communication. The cellular baseband processor 1924 communicates with the UE 104 and / or RUs associated with the network entity 1902 via the transceiver 1922 via one or more antennas 1980. The cellular baseband processor 1924 and the application processor 1906 may each include computer-readable media / memory 1924′, 1906′, respectively. An additional memory module 1926 may also be considered a computer-readable medium / memory. Each computer-readable medium / memory 1924′, 1906′, 1926 may be non-transitory. The cellular baseband processor 1924 and the application processor 1906 are each responsible for general processing, including executing software stored on the computer-readable medium / memory. When executed by the cellular baseband processor 1924 / application processor 1906, this software enables the cellular baseband processor 1924 / application processor 1906 to perform the various functions described above. The computer-readable medium / memory may also be used to store data manipulated by the cellular baseband processor 1924 / application processor 1906 when executing the software.The cellular baseband processor 1924 / application processor 1906 may be a component of the UE 350 and may include the memory 360 and / or at least one of the TX processor 368, the RX processor 356, and the controller / processor 359. In one configuration, the device 1904 may be a processor chip (modem and / or applications) and include only the cellular baseband processor 1924 and / or the application processor 1906, and in another configuration, the device 1904 may be the entire UE (e.g., see ). Figure 3 350) and includes additional modules of device 1904.

[0155] As discussed above, acoustic echo detection component 198 is configured to transmit a first pilot tone at a first frequency. Acoustic echo detection component 198 may also be configured to detect the presence of an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone. Acoustic echo detection component 198 may also be configured to transmit a second pilot tone at a second frequency, higher than the first frequency, based on detection of at least one object within the specified distance. Acoustic echo detection component 198 may reside within cellular baseband processor 1924, application processor 1906, or both. Acoustic echo detection component 198 may be one or more hardware components specifically configured to perform the recited processes / algorithms, implemented by one or more processors configured to perform the recited processes / algorithms, stored on a computer-readable medium for implementation by one or more processors, or some combination thereof. As shown, device 1904 may include various components configured for various functions. In one configuration, the apparatus 1904 (and in particular the cellular baseband processor 1924 and / or the application processor 1906) includes means for transmitting a first pilot tone at a first frequency. The apparatus 1904 may also include means for detecting the presence of an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone. The apparatus 1904 may also include means for transmitting a second pilot tone at a second frequency, higher than the first frequency, based on detecting at least one object within the specified distance.

[0156] In one configuration, the apparatus 1904 may further include means for calculating a first distance of the at least one object relative to the wireless device based on the second pilot tone.

[0157] In another configuration, the means for detecting whether an object is within a specified distance based on a first pilot tone includes configuring apparatus 1904 to receive a reflected signal of the first pilot tone from at least one object, calculate a distance of the at least one object relative to the wireless device based on the reflected signal of the first pilot tone, and determine that the at least one object is within the specified distance if the calculated distance is within the specified distance.

[0158] In another configuration, the means for detecting the presence of an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone includes configuring the apparatus 1904 to identify the reflected signal as associated with the object based on source separation. In some implementations, the reflected signal can be identified as associated with the object based on source separation.

[0159] In another configuration, the apparatus 1904 may further include means for estimating at least one of a size, a direction, or a distance of the at least one object based on the machine learning model, and means for transmitting the second pilot tone further based on the size or direction of the at least one object. In some implementations, the direction of the at least one object may indicate whether the at least one object is approaching or moving away from the wireless device.

[0160] In another configuration, the apparatus 1904 may further include: means for transmitting a third pilot tone at a third frequency based on detecting at least one object within a specified distance, wherein the third frequency may be higher than the first frequency and different from the second frequency; and means for calculating a second distance of the at least one object relative to the wireless device based on the third pilot tone. In some implementations, the first pilot tone may be transmitted via a first speaker, the second pilot tone may be transmitted via a second speaker, and the third pilot tone may be transmitted via a third speaker.

[0161] In another configuration, the apparatus 1904 may further include means for ceasing to transmit the second pilot tone based on the at least one object no longer being within the specified distance.

[0162] In another configuration, the apparatus 1904 may further include means for detecting that the at least one object comprises a person, and means for injecting a reverse signal of the first pilot tone.

[0163] In another configuration, the apparatus 1904 may further include means for transmitting the first pilot tone with a longer periodicity if no object is detected within a specified distance of the wireless device within a specified time period.

[0164] In another configuration, the apparatus 1904 may further include means for transmitting a second pilot tone with a shorter periodicity if at least one object is detected within a second specified distance of the wireless device.

[0165] In another configuration, the first pilot tone may be initially transmitted via the first speaker, and the second pilot tone may be initially transmitted via the second speaker. Apparatus 1904 may also include means for detecting that at least one object is approaching the first speaker, and means for switching transmission of the first pilot tone to the second speaker and switching transmission of the second pilot tone to the first speaker based on the at least one object approaching the first speaker. In some implementations, means for detecting that the at least one object is moving toward the first speaker may include configuring apparatus 1904 to transmit a set of features associated with the at least one object, the first speaker, the second speaker, or a combination thereof to the neural network, and receiving an indication or inference from the neural network that the at least one object is approaching the first speaker. In some configurations, the set of features may correspond to features collected during different time frames. In some configurations, the set of features may include at least one of a frequency shift, an amplitude shift, a logarithmic Mel coefficient, or a Mel-frequency cepstral coefficient.

[0166] A component may be the acoustic echo detection component 198 of the device 1904 configured to perform the functions recited by the component. As described above, the device 1904 may include the TX processor 368, the RX processor 356, and the controller / processor 359. Thus, in one configuration, a component may be the TX processor 368, the RX processor 356, and / or the controller / processor 359 configured to perform the functions recited by the component.

[0167] It should be understood that the specific order or hierarchy of blocks in the disclosed process / flowchart is merely illustrative of exemplary methods. It should be understood that the specific order or hierarchy of blocks in the process / flowchart may be rearranged based on design preferences. Furthermore, some blocks may be combined or omitted. The accompanying method claims present elements of the various blocks in a sample order, but are not limited to the specific order or hierarchy presented.

[0168] The foregoing description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Therefore, the claims are not limited to the aspects described herein, but should be given the full scope consistent with the language claims. Unless specifically stated, references to elements in the singular do not mean "one and only one," but rather "one or more." Terms such as "if," "when," and "while" do not imply a direct temporal relationship or reaction. That is, these phrases, such as "when...", do not imply immediate action in response to the occurrence of an action or during the occurrence of an action, but simply imply that if the conditions are met, the action will occur, but no specific or immediate time limit is required for the action to occur. The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any aspect described herein as "exemplary" is not necessarily to be interpreted as preferred or advantageous over other aspects. Unless otherwise specifically stated, the term "some" refers to one or more. Combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” include any combination of A, B, and / or C, which may include multiple As, multiple Bs, or multiple Cs. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” may be only A, only B, only C, A and B, A and C, B and C, or A, B, and C, where any such combination may include one or more members of A, B, or C. A set should be interpreted as a set of elements, where the number of elements is one or more. Thus, for a set of X, X will include one or more elements. If a first device receives data from or sends data to a second device, the data may be received / sent directly between the first device and the second device, or indirectly between the first device and the second device through a collection of devices. All structural and functional equivalents of the elements of the various aspects described throughout this disclosure that are known or later become known to a person of ordinary skill in the art are expressly incorporated herein by reference and are covered by the claims. In addition, nothing disclosed herein is intended to be dedicated to the public, regardless of whether such disclosure is expressly recited in the claims. Words such as "module," "mechanism," "element," and "device" are not substitutes for the word "component." Therefore, no claim element will be interpreted as part-plus-function unless the element is expressly recited using the phrase "component for..."

[0169] As used herein, the phrase "based on" should not be interpreted as referring to a closed set of information, one or more conditions, one or more factors, etc. In other words, the phrase "based on A" (where "A" can be information, a condition, a factor, etc.) should be interpreted as "based at least on A" unless specifically stated differently.

[0170] The following aspects are merely illustrative and may be combined with other aspects or teachings described herein without limitation.

[0171] Aspect 1 is a method for wireless communication at a wireless device, the method comprising: sending a first pilot tone at a first frequency; detecting whether an object is present within a specified distance of the wireless device based on a reflected signal of the first pilot tone; and sending a second pilot tone at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency.

[0172] Aspect 2 is the method according to aspect 1, further comprising: calculating a first distance of the at least one object relative to the wireless device based on the second pilot tone.

[0173] Aspect 3 is a method according to aspect 1 or 2, the method further comprising: sending a third pilot tone at a third frequency based on detecting the at least one object within the specified distance, wherein the third frequency is higher than the first frequency and different from the second frequency; and calculating a second distance of the at least one object relative to the wireless device based on the third pilot tone.

[0174] Aspect 4 is a method according to aspect 3, wherein the first pilot tone is transmitted via a first speaker, the second pilot tone is transmitted via a second speaker, and the third pilot tone is transmitted via a third speaker.

[0175] Aspect 5 is a method according to any one of Aspects 1 to 4, wherein detecting whether the object is within the specified distance based on the first pilot tone includes: receiving the reflected signal of the first pilot tone from the at least one object; calculating the distance of the at least one object relative to the wireless device based on the reflected signal of the first pilot tone; and if the calculated distance is within the specified distance, determining that the at least one object is within the specified distance.

[0176] Aspect 6 is a method according to any one of Aspects 1 to 5, the method further comprising: estimating at least one of the size, direction, or distance of the at least one object based on a machine learning (ML) model; and sending the second pilot tone further based on the size or the direction of the at least one object.

[0177] Aspect 7 is the method according to aspect 6, wherein the direction of the at least one object indicates whether the at least one object is approaching or moving away from the wireless device.

[0178] Aspect 8 is the method according to any one of aspects 1 to 7, further comprising: ceasing to transmit the second pilot tone based on the at least one object no longer being within the specified distance.

[0179] Aspect 9 is a method according to any one of aspects 1 to 8, further comprising: detecting that the at least one object comprises a person; and injecting a reverse signal of the first pilot tone.

[0180] Aspect 10 is the method of aspect 9, wherein detecting whether the object is present within the specified distance of the wireless device based on the reflected signal of the first pilot tone comprises identifying that the reflected signal is associated with the object.

[0181] Aspect 11 is the method of aspect 10, wherein the reflection signal is identified as being associated with the object based on an ML model.

[0182] Aspect 12 is a method according to any one of aspects 1 to 10, further comprising: if no object is detected within the specified distance of the wireless device within a specified time period, sending the first pilot tone with a longer periodicity.

[0183] Aspect 13 is a method according to any one of aspects 1 to 12, further comprising: transmitting the second pilot tone with a shorter periodicity if the at least one object is detected within a second specified distance of the wireless device.

[0184] Aspect 14 is a method according to any one of Aspects 1 to 13, wherein the first pilot tone is initially sent via a first speaker and the second pilot tone is initially sent via a second speaker, the method further comprising: detecting that the at least one object is approaching the first speaker; and based on the at least one object approaching the first speaker, switching the transmission of the first pilot tone to the second speaker and switching the transmission of the second pilot tone to the first speaker.

[0185] Aspect 15 is a method according to Aspect 14, wherein detecting that the at least one object is moving toward the first speaker includes: providing a set of features associated with the at least one object, the first speaker, the second speaker, or a combination thereof to the NN; and receiving an indication or inference from the NN that the at least one object is approaching the first speaker.

[0186] Aspect 16 is the method of aspect 15, wherein the set of features corresponds to features collected during different time frames.

[0187] Aspect 17 is the method according to aspect 15, wherein the set of features comprises at least one of frequency shift, amplitude shift, log mel coefficients, or mel-frequency cepstral coefficients.

[0188] Aspect 18 is an apparatus for wireless communication at a wireless device, the apparatus comprising: a memory; and at least one processor, the at least one processor being coupled to the memory and configured to implement any one of aspects 1 to 17 based at least in part on information stored in the memory.

[0189] Aspect 19 is the apparatus of aspect 18, further comprising at least one of a transceiver or an antenna coupled to the at least one processor.

[0190] Aspect 20 is an apparatus for wireless communication, comprising means for implementing any one of aspects 1 to 17.

[0191] Aspect 21 is a computer-readable medium (eg, non-transitory computer-readable medium) storing computer-executable code, wherein the code, when executed by a processor, causes the processor to implement any one of aspects 1 to 17.

Claims

1. An apparatus for wireless communication at a wireless device, the apparatus comprising: Memory; and at least one processor coupled to the memory, the at least one processor configured to: transmitting a first pilot tone at a first frequency; detecting whether an object is within a specified distance of the wireless device based on a reflected signal of the first pilot tone; as well as A second pilot tone is transmitted at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency.

2. The apparatus of claim 1 , wherein the at least one processor is further configured to: A first distance of the at least one object relative to the wireless device is calculated based on the second pilot tone.

3. The apparatus of claim 2, wherein the at least one processor is further configured to: transmitting a third pilot tone at a third frequency based on detecting the at least one object within the specified distance, wherein the third frequency is higher than the first frequency and different from the second frequency; and A second distance of the at least one object relative to the wireless device is calculated based on the third pilot tone. 4 . The apparatus of claim 3 , wherein the at least one processor is configured to transmit the first pilot tone via a first speaker, transmit the second pilot tone via a second speaker, and transmit the third pilot tone via a third speaker.

5. The apparatus of claim 1 , wherein to detect whether the object is present within the specified distance based on the first pilot tone, the at least one processor is configured to: receiving the reflected signal of the first pilot tone from the at least one object; calculating a distance of the at least one object relative to the wireless device based on the reflected signal of the first pilot tone; and If the calculated distance is within the specified distance, it is determined that the at least one object is within the specified distance.

6. The apparatus of claim 1 , wherein the at least one processor is further configured to: estimating at least one of a size, a direction, or a distance of the at least one object based on a machine learning (ML) model; and The second pilot tone is transmitted further based on the size, the direction, the distance, or a combination thereof of the at least one object. 7 . The apparatus of claim 6 , wherein the direction of the at least one object indicates whether the at least one object is approaching or moving away from the wireless device.

8. The apparatus of claim 1 , wherein the at least one processor is further configured to: Transmitting the second pilot tone is stopped based on the at least one object no longer being within the specified distance.

9. The apparatus of claim 1 , wherein the at least one processor is further configured to: detecting that the at least one object comprises a person; and Inject a reverse signal of the first pilot tone.

10. The apparatus of claim 1 , wherein to detect whether the object is present within the designated distance of the wireless device based on the reflected signal of the first pilot tone, the at least one processor is configured to: The reflected signal is identified as being associated with the object based on source separation. 11 . The apparatus of claim 10 , wherein the at least one processor is configured to identify that the reflected signal is associated with the object based on a machine learning (ML) model.

12. The apparatus of claim 1 , wherein the at least one processor is further configured to: If no object is detected within the specified distance of the wireless device within a specified time period, the first pilot tone is transmitted with a longer periodicity.

13. The apparatus of claim 1 , wherein the at least one processor is further configured to: If the at least one object is detected within a second specified distance of the wireless device, the second pilot tone is transmitted with a shorter periodicity.

14. The apparatus of claim 1 , wherein the at least one processor is configured to initially transmit the first pilot tone via a first speaker, and the at least one processor is configured to initially transmit the second pilot tone via a second speaker, wherein the at least one processor is configured to: detecting that the at least one object is approaching the first speaker; and Based on the at least one object being approaching the first speaker, transmission of the first pilot tone is switched to the second speaker and transmission of the second pilot tone is switched to the first speaker.

15. The apparatus of claim 14, wherein to detect that the at least one object is moving toward the first speaker, the at least one processor is configured to: providing a neural network (NN) with a set of features associated with the at least one object, the first speaker, the second speaker, or a combination thereof; and An indication or inference is received from the NN that the at least one object is approaching the first speaker. The apparatus of claim 15 , wherein the set of features corresponds to features collected during different time frames.

17. The apparatus of claim 15, wherein the set of features comprises at least one of frequency shift, amplitude shift, log-Mel coefficients, or Mel-frequency cepstral coefficients.

18. A method of wireless communication at a wireless device, the method comprising: transmitting a first pilot tone at a first frequency; detecting whether an object is within a specified distance of the wireless device based on a reflected signal of the first pilot tone; as well as A second pilot tone is transmitted at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency.

19. The method according to claim 18, further comprising: A first distance of the at least one object relative to the wireless device is calculated based on the second pilot tone.

20. The method according to claim 19, further comprising: transmitting a third pilot tone at a third frequency based on detecting the at least one object within the specified distance, wherein the third frequency is higher than the first frequency and different from the second frequency; as well as A second distance of the at least one object relative to the wireless device is calculated based on the third pilot tone.

21. The method of claim 18, wherein detecting whether the object is within the specified distance based on the first pilot tone comprises: receiving the reflected signal of the first pilot tone from the at least one object; calculating a distance of the at least one object relative to the wireless device based on the reflected signal of the first pilot tone; as well as If the calculated distance is within the specified distance, it is determined that the at least one object is within the specified distance.

22. The method according to claim 18, further comprising: estimating at least one of a size, a direction, or a distance of the at least one object based on a machine learning (ML) model; as well as The second pilot tone is transmitted further based on the size or the direction of the at least one object.

23. The method according to claim 18, further comprising: Transmitting the second pilot tone is stopped based on the at least one object no longer being within the specified distance.

24. The method according to claim 18, further comprising: detecting that the at least one object includes a person; as well as Inject a reverse signal of the first pilot tone.

25. The method of claim 18, wherein detecting whether the object is present within the specified distance of the wireless device based on the reflected signal of the first pilot tone comprises: The reflected signal is identified as being associated with the object.

26. The method of claim 18, further comprising: If no object is detected within the specified distance of the wireless device within a specified time period, the first pilot tone is transmitted with a longer periodicity.

27. The method of claim 18, wherein the first pilot tone is initially transmitted via a first speaker and the second pilot tone is initially transmitted via a second speaker, the method further comprising: detecting that the at least one object is approaching the first speaker; as well as Based on the at least one object being approaching the first speaker, transmission of the first pilot tone is switched to the second speaker and transmission of the second pilot tone is switched to the first speaker.

28. The method of claim 27, wherein detecting that the at least one object is moving toward the first speaker comprises: providing a neural network (NN) with a set of features associated with the at least one object, the first speaker, the second speaker, or a combination thereof; as well as An indication or inference is received from the NN that the at least one object is approaching the first speaker.

29. An apparatus for wireless communication at a wireless device, the apparatus comprising: means for transmitting a first pilot tone at a first frequency; means for detecting the presence of an object within a specified distance of the wireless device based on a reflected signal of the first pilot tone; and means for transmitting a second pilot tone at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency.

30. A computer-readable medium storing computer-executable code at a wireless device, the code, when executed by a processor, causing the processor to: transmitting a first pilot tone at a first frequency; detecting whether an object is within a specified distance of the wireless device based on a reflected signal of the first pilot tone; as well as A second pilot tone is transmitted at a second frequency based on detecting at least one object within the specified distance, wherein the second frequency is higher than the first frequency.

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