Cross technology specific absorption rate management techniques

Abstract

A user equipment (UE) in a mobile cellular network implements one or more techniques to perform cross-technology specific absorption rate (SAR) budget allocation. The UE computes an individual SAR budget for each radio access technology (RAT) module of a plurality of RAT modules at the UE based on operational context data associated with the UE. The UE sends each individual SAR budget to a corresponding RAT module of the plurality of RAT modules. The UE then adjusts, at one or more RAT modules of the plurality of RAT modules, transmission parameters based on the corresponding individual SAR budget.

Description

CROSS TECHNOLOGY SPECIFIC ABSORPTION RATE MANAGEMENT TECHNIQUESBACKGROUND

[0001] Mobile communication relies on high-frequency electromagnetic fields to transmit information. When data or messages are sent or when a phone call is made using a wireless device, some of the energy from these electromagnetic fields is absorbed by the user's body. Wireless devices are subject to safety standards for energy absorption. The specific absorption rate (SAR) is the measure of the amount of energy absorbed by the body, expressed in watts per kilogram (W / kg). SAR is used to ensure compliance with standards established by regulatory bodies like the Federal Communications Commission (FCC). Mobile devices must meet SAR requirements specific to the region where they will be sold. Modern wireless user equipment (UE) supports the concurrent activation of multiple technologies, allowing the UE to transmit and receive data across different types of radio access technologies (RATs), such as wireless wide-area networks (WANs) (e.g., cellular networks including 3G, 4G LTE, and 5G NR), wireless local-area networks (WLANs) (e.g., Wi-Fi), and short-range wireless networks (e.g., Bluetooth®), simultaneously. The radios for these technologies must collectively comply with the device’s overall SAR limit. In general, SAR requirements are not dependent on the technology or radio access technology (RAT) used. Instead, SAR specifications set limits on the overall radiation emitted by the device, regardless of the number or type of technologies active on the mobile device.SUMMARY OF EMBODIMENTS

[0002] In accordance with one aspect, a method, at a user equipment (UE) in a cellular network, includes computing an individual specific absorption rate (SAR) budget for each radio access technology (RAT) module of a plurality of RAT modules at the UE based on operational context data associated with the UE, sending each individual SAR budget to a corresponding RAT module of the plurality of RAT modules, and adjusting, at one or more RAT modules of the plurality of RATmodules, transmission parameters of the corresponding RAT module based on the corresponding individual SAR budget.

[0003] In at least some embodiments, the operational context data includes sensor data indicative of device interaction context.

[0004] In at least some embodiments, the sensor data includes at least one of earpiece activation data, touch sensor data, device motion data, hinge status data, or user device configuration data.

[0005] In at least some embodiments, the operational context data includes operational metrics indicative of current operating conditions of one or more RAT modules of the plurality of RAT modules.

[0006] In at least some embodiments, the operational metrics include at least one of a current SAR budget associated with one or more RAT modules of the plurality of RAT modules, a current SAR utilization associated with one or more RAT modules of the plurality of RAT module, a current transmission power associated with one or more RAT modules of the plurality of RAT module, a current transmission rate associated with one or more RAT modules of the plurality of RAT module, link budget information associated with one or more RAT modules of the plurality of RAT module, buffer occupancy or load information associated with one or more RAT modules of the plurality of RAT module, or channel state information associated with one or more RAT modules of the plurality of RAT module.

[0007] In at least some embodiments, the method further includes periodically updating the individual SAR budgets during successive monitoring windows based on changes in the operational context data.

[0008] In at least some embodiments, the method further includes predicting future SAR utilization for each RAT module of the plurality of RAT modules based on historical SAR utilization data and current operating conditions, and wherein computing the individual SAR budget for each RAT module of the plurality of RAT modules includes reallocating SAR budgets among the plurality of RAT modules based on the predicted future SAR utilization.

[0009] In at least some embodiments, reallocating the SAR budgets includes transferring at least a portion of unused SAR budget from a first RAT module having a predicted SAR utilization below a first threshold to a second RAT module having a predicted SAR utilization above a second threshold.

[0010] In at least some embodiments, the method further includes, responsive to determining antenna-specific SAR contributions, separately managing SAR budgets based on the determined antenna-specific SAR contributions and at least one of antenna location or grouping within the UE.

[0011] In at least some embodiments, the method further includes predicting future SAR utilization for each RAT module of the plurality of RAT modules based on historical SAR utilization data and anticipated operational conditions, and updating the computed SAR budget for each RAT module based on the predicted future SAR utilization.

[0012] In at least some embodiments, predicting the future SAR utilization includes estimating anticipated airtime utilization based on predicted traffic demand and predicted link availability, estimating anticipated emissions based on predicted airtime utilization and predicted transmission power levels, and calculating normalized SAR contributions for each RAT module of the plurality of RAT modules based on the estimated anticipated emissions.

[0013] In accordance with another aspect, a user equipment device includes a plurality of radio access technology (RAT) modules, at least one processor coupled to the plurality of RAT modules, and at least one memory storing executable instructions that, when executed by the at least one processor, cause at least one of the one or more of the plurality of RAT modules or the at least one processor to perform the methods described above and herein.

[0014] In accordance with a further aspect, a computer-readable storage medium embodies a set of executable instructions, the set of executable instructions to manipulate a user equipment device to perform the methods described above and herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present disclosure may be better understood, and its numerous features and advantages made apparent to those skilled in the art, by referencing the accompanying drawings. The use of the same reference symbols in different drawings indicates similar or identical items.

[0016] FIG. 1 illustrates an example mobile cellular network employing a user equipment (UE) configured for cross-technology specific absorption rate (SAR) management in accordance with some embodiments.

[0017] FIG. 2 illustrates various operational modes implemented by the SAR management mechanism employed by the UE of FIG. 1 in accordance with some embodiments.

[0018] FIG. 3 illustrates an example hardware configuration of a UE employing the SAR management techniques described herein in accordance with some embodiments.

[0019] FIG. 4 illustrates an example integration and interaction of the multi-radio access technology resource controller and SAR manager within an application processor (AP) of a UE in accordance with some embodiments.

[0020] FIG. 5 illustrates example data interactions and exchanges between the SAR manager and various wireless technology subsystems to dynamically manage SAR budgets in accordance with some embodiments.

[0021] FIG. 6 illustrates an example of internal functional decomposition of the SAR manager into predictive and optimization components for dynamic SAR budget allocation in accordance with some embodiments.

[0022] FIG. 7 illustrates an example of an operational timeline depicting dynamic SAR budget sharing and reconfiguration procedures between a cellular modem and a wireless local area network controller in accordance with some embodiments.

[0023] FIG. 8 illustrates a flow diagram of an example method for dynamic crosstechnology SAR budget allocation in accordance with some embodiments.

[0024] FIG. 9 illustrates a flow diagram of an example method for predictive SAR utilization calculation in accordance with some embodiments.DETAILED DESCRIPTION

[0025] Specific absorption rate (SAR) management on many wireless devices is typically limited to independent per-technology algorithms that ensure each technology does not exceed its own allocated SAR budget. Such per-technology SAR budgets are generally assigned sem i-statically, for instance, allocating 50% of the SAR budget to wireless wide area network (WAN) (e.g., cellular technology) and 50% to wireless local area network (WLAN). Under this conventional approach, each technology remains constrained within its respective budget regardless of real-time SAR utilization by other technologies. This approach fails to account for actual instantaneous SAR contributions from multiple concurrently active technologies, often leading devices to operate suboptimally below their full wireless performance potential. Consequently, conservative SAR management policies unnecessarily limit wireless throughput, battery efficiency, and user experience.

[0026] To address these and other challenges, the following describes centralized cross-technology SAR management systems and methods for multi-technology wireless user equipment (UE), such as smartphones, tablets, or wearable devices. The described SAR management system dynamically and periodically reallocates radio resources, including SAR budget and antenna resources, across active RATs, such as cellular, WLAN, Bluetooth (BT), and others. In at least some embodiments, a centralized SAR manager continuously receives, for example, realtime SAR utilization data, current transmission power, modem operational status, instantaneous link-quality metrics including current transmission rate from each active RAT, a combination thereof, or the like. Additionally, the SAR manager leverages sensor data reflecting the device interaction context, such as hand grip, head proximity, device motion data, hinge status data in foldable devices, earpiece activation data, touch sensor data, and user device configuration data, to infer current user scenarios more accurately. Based on this integrated, real-time data, the SAR manager employs predictive algorithms subdivided into modular predictive blocks for tractability, including traffic pattern prediction, link-quality and availability prediction,airtime and emissions prediction, SAR utilization prediction, a combination thereof, or the like. These predictions are then used to compute optimal per-technology SAR budgets dynamically for upcoming monitoring periods, taking into account historical SAR utilization data and anticipated operational conditions. The SAR manager, in at least some embodiments, further communicates periodic SAR budget updates, synchronization signals for aligning successive monitoring windows, and updated SAR allocations (individual SAR budgets) to each RAT, allowing the wireless device to optimize overall SAR utilization actively rather than passively adhering to static limits. In at least some embodiments, SAR budget allocation decisions further consider one or more of per-radio link budgets, antenna location, antenna-specific SAR contributions, current and anticipated traffic types and service requirements, user preferences and historical usage patterns, historical transmit and receive activities, regulatory constraints, or interfaces with third-party modules for obtaining traffic and service characteristics and aligning radiation monitoring timing and adjustment frequencies

[0027] In at least some embodiments, the centralized SAR manager makes window-by-window decisions at intervals (e.g., on the order of seconds), dynamically reallocating SAR budgets among active technologies based on predicted future SAR utilization, historical SAR utilization data, predicted utilization thresholds, and current modem statuses. This granular and adaptive SAR budget reallocation substantially enhances system performance and user experience. For example, unused SAR budget in low-duty-cycle cellular scenarios, such as voice calls, can be reallocated to boost WI_AN transmit power significantly, resulting in measurable improvements in WLAN range, uplink and downlink throughput, and overall reliability. Additionally, SAR budget allocation decisions can dynamically adapt to changing user scenarios or rapidly shifting wireless link conditions, ensuring both regulatory compliance and optimized user experience even under challenging multi-technology usage scenarios.

[0028] The centralized cross-technology SAR management techniques disclosed herein thus offer advantages over traditional static SAR management methods. By dynamically reallocating SAR budgets based on real-time predictions and modem conditions, these techniques enhance wireless link stability, significantly reducelatency during network handovers, and minimize battery drain. Empirical results validate substantial improvements in practical use cases, such as hotspot tethering and concurrent cellular / WLAN communications, showing tangible gains in wireless link performance. Moreover, predictive interference mitigation reduces unwanted emissions, improving signal integrity and call quality. This dynamic approach ultimately provides users with seamless multitasking capabilities, enabling simultaneous activities, such as high-quality music streaming during phone calls, without sacrificing device performance or regulatory compliance.

[0029] For ease of illustration, the following techniques are described in an example context in which one or more UEs and one or more radio access networks (RANs) implement at least a Fifth Generation (5G) New Radio (NR) standard (e.g. , Third Generation Partnership Project (3GPP) Release 15, 3GPP Release 16, etc.) (hereinafter, “5G NR” or “5G NR standard”). However, it should be understood that the present disclosure is not limited to networks employing a 5G NR RAT configuration, but rather the techniques described herein can be applied to any combination of different RATs, such as LTE, NR, WLAN (e.g., Wi-Fi), orfuture technologies employed at UEs and cellular networks. It should also be understood that the present disclosure is not limited to any specific network configurations or architectures described herein. Also, the present disclosure is not limited to the examples and context described herein, but rather, the techniques described herein can be applied to any network environment where a UE device implements SAR management techniques.

[0030] FIG. 1 illustrates a mobile cellular network 100 (also referred to here as “cellular network 100” or “network 100”) in accordance with at least some embodiments. As shown, the mobile cellular network 100 includes a device, such as a user equipment (UE) 102, that is configured to communicate with one or more base stations (BSs) 104 (illustrated as BS 104-1 and BS 104-2) through one or more wireless communication links 106 (illustrated as wireless links 106-1 and 106-2). The UE 102, in at least some embodiments, includes any of a variety of wireless communication devices, such as a cellular phone, a cellular-enabled tablet computer or cellular-enabled notebook computer, a cellular-enabled wearable device, anautomobile, or other vehicle employing cellular services (e.g., for navigation, provision of entertainment services, in-vehicle mobile hotspots, etc.), and so on. In at least some embodiments, the UE 102 employs a single RAT 108. In other embodiments, the UE 102 is a multi-mode UE that employs multiple RATs 108 (illustrated as RAT 108-1 and RAT 108-2). Examples of multiple RATs include cellular-based RATs, such as a 3GPP Long-Term Evolution (3GPP LTE) RAT, a 3GPP Fifth Generation New Radio (5G NR) RAT, a WLAN (e.g., Wi-Fi) RAT, and future cellular or wireless technologies. It should be understood that although FIG. 1 only shows the UE 102 implementing two different RATs 108, the UE 102, in at least some implementations, implements three or more different RATs 108. In at least some embodiments, one or more RAT modules 110 (illustrated as RAT module 110-1 and RAT module 110-2) manage the RATs 108 and enable communication between the UE 102 and the radio access technology of the network 100. The one or more RAT modules 110, in at least some embodiments, include hardware and software to implement a corresponding RAT, such as one or more of modem chipset(s) of the UE 102, protocol stack(s), driver software, and the like. Also, in some configurations, the antennas 302 may be shared among multiple RAT modules 110 or may include antenna groups or arrays optimized for particular frequency bands or operating conditions associated with the different RATs.

[0031] In at least some embodiments, the BSs 104 are implemented in a macrocell, microcell, small cell, picocell, and the like, or any combination thereof. Examples of base stations 104 include an Evolved Universal Terrestrial Radio Access Network Node B (E-UTRAN Node B), Evolved Node B (eNodeB or eNB), Next Generation (NG or NGEN) Node B (gNode B or gNB), and so on. The BSs 104 communicate with the UE 102 via the wireless links 106, which are implemented using any suitable type of wireless link. The wireless links 106, in at least some embodiments, include a downlink of data and control information communicated from the base stations 104 to the UE 102, an uplink of data and control information communicated from the UE 102 to the BSs 104, or both. In at least some embodiments, the wireless links 106 (or bearers), such as data radio bearers (DRBs) and signal radio bearers (SRBs), are implemented using any suitable communication protocol or standard, or combination of communication protocols or standards, such as 3GPP 4G LTE, 5G NR, and so on.In at least some embodiments, multiple wireless links 106 are aggregated in a carrier aggregation to provide a higher data rate for the UE 102. Also, multiple wireless links 106 from multiple BSs 104 are configured, in at least some embodiments, for coordinated multipoint (CoMP) communication with the UE 102, as well as dual connectivity, such as single-RAT LTE-LTE or NR-NR dual connectivity or multi-radio access technology (Multi-RAT) dual connectivity (MR-DC) including E-UTRA-NR dual connectivity (EN-DC), NGEN radio access network (RAN) E-UTRA-NR dual connectivity (NGEN-DC), and NR E-UTRA dual connectivity (NE-DC).

[0032] The BSs 104 collectively form a Radio Access Network (RAN) 112, such as an E-UTRAN or 5G NR RAN. The base stations 104 are connected to a core network (GN) 114 (illustrated as CN 114-1 and CN 114-2) via control-plane and userplane interfaces through one or more links 116 (illustrated as link 116-1 and link 116- 2). Depending on the configuration of the mobile cellular network 100, the core network 114 is either an Evolved Packet Core (EPC) network 114-1 or a 5G Core Network (5GC) 114-2. For example, in an E-UTRAN configuration or a 5G non- standalone (NSA) EN-DC configuration, the core network 114 is an EPC network 114-1 that includes, for example, a Mobility Management Entity (MME) 118, a Serving Gateway (SGW) 120, and a Packet Data Network Gateway (PGW) 122. The MME 118 provides control-plane functions, such as registration and authentication of multiple UEs 102, authorization, mobility management, and so on. The SGW 120 transfers user-plane packets related to audio calls, video calls, Internet traffic, and the like. The PGW 122 provides connectivity from the UE 102 to external packet data networks 124, such as the Internet 126 and a multimedia communications subsystem network 128 (e.g., an IMS network), by serving as the point of exit and entry of traffic for the UE 102. In a 5G SA configuration or an NSA NE-DC or NGEN-DC configuration, the core network 114 is a 5GC network 114-2. The 5GC 114-2 includes, for example, an Access and Mobility Management function (AMF) 130, a User Plane Function (UPF) 132, and a Session Management Function (SMF) 134. The AMF 130 provides control-plane functions such as registration and authentication of multiple UEs 102, authorization, mobility management, and so on. The UPF 132 transfers user-plane packets related to audio calls, video calls, Internet traffic, and the like. The SMF 134 manages protocol data unit (PDU) sessions.

[0033] In at least some embodiments, the core network 114 communicatively couples the DE 102 to a multimedia communications subsystem network 128 via the RAN 112. The multimedia communications subsystem network 128 provides various multimedia services to the UE 102, such as multimedia short messages, unstructured supplementary service data (USSD), value-added service data, supplementary service data, voice calls, and video calls. To this end, an entity (e.g., a server or a group of servers) operating in the multimedia communications subsystem network 128 supports packet exchange with the UE 102. The packets convey signaling (such as session initiation protocol (SIP) messages, IP messages, or other suitable messages) as well as media, such as voice or video data. In at least some embodiments, the multimedia communications subsystem network includes entities (not shown) such as, but not limited to, a Proxy Call Session Control Function (P- CSCF), an Interrogating Call Session Control Function (l-CSCF), a Serving Call Session Control Function (S-CSCF), a Home Subscriber Server (HSS), a Media Gateway Control Function (MGCF), and the like.

[0034] As described above, the UE 102 implements multiple different RATs 108, such as a cellular RAT, a WLAN RAT (e.g., a Wi-Fi RAT), a short-range wireless communication RAT (e.g., a Bluetooth RAT), and the like. The UE 102 is able to transmit and receive data across these different RATs simultaneously or at different times. Each RAT 108 contributes to the overall specific absorption rate (SAR), a measure of radiofrequency (RF) energy absorbed by the user's body, and collectively must comply with the UE’s overall SAR limit. Conventional SAR management systems typically employ independent algorithms assigning semi-static SAR budgets per technology, for instance, equally dividing the SAR budget between cellular and WLAN. Such an approach does not dynamically account for actual instantaneous SAR contributions from each RAT, resulting in overly conservative SAR management that unnecessarily limits wireless performance and battery efficiency.

[0035] To address these and other limitations, the UE 102 employs a SAR management mechanism 136 that dynamically optimizes device performance by intelligently selecting transmit power levels across different RATs while ensuring compliance with SAR requirements. As described below, the SAR manager 136performs centralized SAR management during which instantaneous data from all RATs 108 on the DE 102 is fused with device sensor data on user interaction (hand grip, head proximity, motion, etc.) to compute an optimal per-technology SAR budget that gets dynamically and periodically updated to ensure that total SAR budget is optimally allocated to each RAT 108.

[0036] For example, FIG. 2 illustrates various operational modes implemented singularly or collectively by the centralized SAR management mechanism 136 to achieve this optimization, in accordance with at least some embodiments. These modes are further detailed below. A first operational mode includes a dynamic resource monitoring mode 202. During this mode, the SAR management mechanism 136 continuously monitors, for example, real-time SAR utilization data, transmit power requirements, modem status information, link-quality metrics from all active RATs, a combination thereof, or the like. Additionally, in at least some embodiments, the mechanism 136 gathers sensor data indicative of user interactions, such as device handling, head proximity, motion, and hinge position in foldable devices, to accurately infer current user scenarios.

[0037] A second operational mode comprises a predictive analysis mode 204.During this mode, the SAR management mechanism 136 utilizes predictive blocks to estimate, for example, traffic patterns, link quality and availability, anticipated airtime, emission levels, SAR utilization across RATs, a combination thereof, or the like for upcoming monitoring periods. These predictions facilitate informed, proactive SAR resource management decisions. Another mode includes a dynamic SAR budget allocation mode 206. During this mode, the SAR management mechanism 136 leverages real-time monitoring and predictive analysis to dynamically allocate or reallocate SAR budgets among active RATs. In at least some embodiments, this mode reallocates unused SAR capacity from technologies currently underutilizing their allocated budget to technologies experiencing high utilization or demanding more resources, such as WLAN during hotspot tethering or Bluetooth during voice streaming.

[0038] An additional mode is a periodic reconfiguration mode 208. In this mode, theSAR management mechanism 136 periodically updates and communicates revisedSAR budgets, synchronization signals for aligning SAR monitoring windows, and other relevant parameters to each RAT. This periodic reconfiguration ensures optimized, synchronized, and efficient SAR management tailored to current and predicted wireless conditions. By integrating real-time monitoring, advanced predictive analysis, dynamic SAR budget allocation, and periodic reconfiguration modes, the SAR management mechanism 136 substantially improves wireless performance, battery efficiency, user experience, and regulatory compliance, while adapting intelligently and proactively to diverse user scenarios and wireless conditions.

[0039] FIG. 3 illustrates an example device diagram 300 of a UE 102. In at least some embodiments, the device diagram 300 describes a UE that implements the SAR management techniques described herein. The UE 102 may include additional functions and interfaces that are omitted from FIG. 3 for the sake of clarity. The UE 102, in at least some embodiments, includes antennas 302, a radio frequency (RF) front end 304, and a modem subsystem 306. The modem subsystem 306 includes multiple transceivers 308 (e.g. , a 3GPP 4G LTE transceiver 308-1 and a 5G NR transceiver 308-2) for communicating with one or more base stations 104 in a RAN 112, such as a 5G RAN, an E-UTRAN, a combination thereof, and so on. The modem subsystem 306 also includes an RF modem, such as cellular modem 310 (also referred to as a baseband processor or a communication processor) that is responsible for managing the operations of the transceivers 308. In at least some embodiments, the modem 310 is implemented as a modem baseband processor, software-defined radio module, configurable modem (e.g., multi-mode, multi-band modem), wireless data interface, wireless modem, and so on. The modem 310 supports, for example, one or more of data access, messaging, or data-based services of a wireless network, as well as various audio-based communication (e.g., voice calls).

[0040] The RF front end 304, in at least some embodiments, includes a transmitting (Tx) front end 304-1 and a receiving (Rx) front end 304-2. The Tx front end 304-1 includes components such as one or more power amplifiers (PA), drivers, mixers, filters, and so on. The Rx front end 304-2 includes components such as low-noiseamplifiers (LNAs), mixers, filters, and so on. The RF front end 304, in at least some embodiments, couples or connects the modem subsystem 306, including the LTE transceiver 308-1 and the 5G NR transceiver 308-2, to the antennas 302 to facilitate various types of wireless communication.

[0041] In at least some embodiments, the antennas 302 of the UE 102 include an array of multiple antennas configured similarly to or different from each other. The antennas 302 and the RF front end 304, in at least some embodiments, are tuned to or are tunable to one or more frequency bands, such as those defined by the 3GPP LTE, 3GPP 5G NR, IEEE Wireless Local Area Network (WLAN), IEEE Wireless Metropolitan Area Network (WMAN), or other communication standards. In at least some embodiments, the antennas 302, the RF front end 304, and the transceivers 308 are configured to support beamforming (e.g., analog, digital, or hybrid) or In- Phase and Quadrature (l / Q) operations (e.g., I / Q modulation or demodulation operations) for the transmission and reception of communications with one or more base stations 104. By way of example, the antennas 302 and the RF front end 304 operate in sub-gigahertz bands, sub-6 GHz bands, above 6 GHz bands, or a combination of these bands defined by the 3GPP LTE, 3GPP 5G NR, or other communication standards.

[0042] In at least some embodiments, the antennas 302 include one or more receiving antennas positioned in a one-dimensional shape (e.g., a line) or a two- dimensional shape (e.g., a triangle, a rectangle, or an L-shape) for implementations that include three or more receiving antenna elements. While the one-dimensional shape enables the measurement of one angular dimension (e.g., an azimuth or an elevation), the two-dimensional shape enables two angular dimensions to be measured (e.g., both azimuth and elevation). Using at least a portion of the antennas 302, the UE 102 can form beams that are steered or un-steered, wide or narrow, or shaped (e.g., as a hemisphere, cube, fan, cone, or cylinder). The one or more transmitting antennas may have an un-steered omnidirectional radiation pattern or may produce a wide steerable beam. Either of these techniques enables the UE 102 to transmit a radio signal to illuminate a large volume of space. In some embodiments, the receiving antennas generate thousands of narrow steered beams(e.g., 2000 beams, 4000 beams, or 6000 beams) with digital beamforming to achieve desired levels of angular accuracy and angular resolution.

[0043] The UE 102, in at least some embodiments, includes one or more sensors 312 implemented to detect one or more properties, states, or contexts of the UE 102, such as temperature, supplied power, power usage, battery state, device orientation, motion, proximity to the user’s head or body, transmit power associated with each active radio, or the like. Examples of sensors 312 include a thermal sensor, a battery / power usage sensor, motion or orientation sensor (e.g., accelerometer, gyroscope), proximity or capacitive sensor, and RF front-end or transmit-power sensor. These sensors 312 provide real-time contextual and device-state information that the SAR management mechanism 136 uses to infer usage scenarios, such as in-hand operation, head proximity, or sustained radio activity, and to dynamically adjust SAR budget allocation across multiple active RATs while maintaining regulatory compliance and optimized performance.

[0044] The UE 102 also includes at least one processor 314. The processor 314, in at least some embodiments, is a single-core processor or a multiple-core processor composed of a variety of materials, such as silicon, polysilicon, high-K dielectric, copper, and so on. In at least some embodiments, the processor 314 is implemented at least partially in hardware, including, for example, components of an integrated circuit or a System-on-a-Chip (SoC), a Digital-Signal-Processor (DSP), an Application-Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), a Complex Programmable Logic Device (CPLD), other implementations in silicon or other hardware, or a combination thereof. Examples of the processor(s) 314 include a communication processor (if not implemented within the modem subsystem 306), an application processor, microprocessors, DSPs, controllers, and so on. An application processor, in at least some embodiments, provides computing resources to applications executing on the UE 102. For example, an application provides a self-contained operating environment that delivers system capabilities (e.g., graphics processing, memory management, and multimedia processing) to support applications executing on the UE 102.

[0045] The UE 102, in at least some embodiments, further includes a WLAN controller 316, which is responsible for managing the device’s connection to WLANs, such as Wi-Fi or other WLANs. The WLAN controller 316 handles tasks such as scanning for available networks, establishing and maintaining WLAN connections, and managing data transmission over a WLAN. The UE 102 interacts with the modem subsystem 306 and other components to coordinate network access and ensure seamless switching between WLANs and cellular networks. The WLAN controller 316, in at least some embodiments, is implemented as an integrated circuit (IC), either part of an SoC, or as a discrete component within the UE 102.

[0046] The UE 102 further includes a power management unit (PMU) 318, which is responsible for managing power distribution across the various components of the UE 102, including the RF front end 304, the modem subsystem 306, and the modem 310. The PMU 318 dynamically adjusts power delivery based on each component’s operational state, such as when the SAR Manager deprioritizes or disables a specific RAT module under its dynamic cross-technology SAR allocation scheme. By scaling the power supplied to radios that are throttled or turned off, the PMU 318 conserves energy and prevents unnecessary heat generation while maintaining regulated SAR exposure levels. During periods of heightened radio activity, the PMU 318 ensures efficient power delivery to support optimal transmit performance. The PMU 318 can be implemented as part of an SoC or as a discrete IC within the UE 102.

[0047] The UE 102 further includes a non-transitory computer-readable storage media 320 (CRM 320). The computer-readable storage media described herein excludes propagating signals. The CRM 320, in at least some embodiments, includes any suitable memory or storage device such as random-access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), non-volatile RAM (NVRAM), read-only memory (ROM), or Flash memory useable to store device data 322 of the UE 102. In at least some embodiments, the device data 322 includes user data, multimedia data, beamforming codebooks, applications 324, an operating system 326 of the UE 102, a user interface(s) 328, and so on, which are executable by the processor(s) 314 to enable user-plane communication, control-plane signaling, and user interaction with the UE 102. In at least some embodiments, the CRM 320 isconfigured as a memory storing executable instructions that, when executed by the processor(s) 314, cause the UE 102 to perform operations described herein. The user interface 328, in at least some embodiments, is configured to receive inputs from a user of the UE 102, such as to receive input from a user that defines or facilitates one or more aspects of SAR management. In at least some embodiments, the user interface 328 includes a graphical user interface (GUI) that receives the input information via a touch input. In other instances, the user interface 328 includes an intelligent assistant that receives the input information via an audible input or speech. Alternatively, or additionally, the operating system 326 of the UE 102 is maintained as firmware or an application on the CRM 320 and executed by the processor(s) 314.

[0048] The CRM 320, in at least some embodiments, further includes a communication manager 330. Alternatively, or additionally, the communication manager 330, in at least some embodiments, is implemented in whole or part as hardware logic or circuitry integrated with or separate from other components of the UE 102. In at least some embodiments, the communication manager 330 configures the RF front end 304, the LTE transceiver 308-1 , the 5G NR transceiver 308-2, or a combination thereof to perform one or more wireless communication operations. The UE 102 also includes a SAR manager 332. In at least some embodiments, the SAR manager 332 is integrated within a multi-RAT resource controller 334, which is a centralized control module responsible for cross-technology management of device resources, such as antenna allocation, RAT selection, transmit power adjustments, and dynamic SAR budget reallocation. The multi-RAT resource controller 334, which can operate in coordination with or as part of an application processor, provides high- level optimization decisions based on comprehensive cross-layer data, including realtime modem statuses, user context data from sensors 312, and predictive analyses. In various embodiments, the SAR manager 332 and the multi-RAT resource controller 334 are implemented in whole or part as hardware logic or circuitry integrated with or separate from other components of the UE 102. Alternatively, or additionally, one or more portions of the SAR manager 332 and the multi-RAT resource controller 334 are implemented as software or firmware stored within the CRM 320 and executed by the processor(s) 314. Also, in at least someembodiments, the SAR manager 332 is implemented separately from the multi-RAT resource controller 334, while in other embodiments, the SAR manager 332 is implemented in place of the multi-RAT resource controller 334, performing its functions described herein.

[0049] FIG. 4 illustrates an example of an application processor (AP) 402 integrating the multi-RAT resource controller 334 and the SAR manager 332 in accordance with at least some embodiments. The AP 402 hosts the multi-RAT resource controller 334, which is responsible for dynamically managing resources across multiple RATs, such as a cellular RAT 404 and a WLAN RAT 406, within the UE 102. In this example, the SAR manager 332 and the multi-RAT resource controller 334 are shown integrated within the AP 402. However, in other configurations, one or both of these components are implemented externally to the AP 402. Additionally, in some embodiments, the multi-RAT resource controller 334 is not separately implemented, and the SAR manager 332 alone performs the functions of the multi-RAT resource controller 334, or vice versa.

[0050] The SAR manager 332 dynamically allocates SAR budgets among different RATs to optimize overall SAR utilization, enhance performance, and ensure compliance with regulatory SAR limits. For example, inputs to the multi-RAT resource controller 334 and the SAR manager 332 include cellular metrics (e.g. , cellular SAR utilization, modem power state, link quality indicators), metrics from other RATs such as WLAN, Bluetooth (BT), or Ultra- Wideband (UWB) (e.g., SAR utilization, modem state, data throughput, link quality), user context data (e.g., user preferences, historical usage patterns, or interaction data), application-level context data (e.g., the type of active applications and associated performance requirements), sensor inputs (e.g., proximity sensors, motion sensors, and thermal sensors), a combination thereof, or the like. Additionally, regulatory tables specifying SAR constraints and back-off conditions for different regulatory regions or exposure scenarios may also serve as inputs to the SAR manager 332.

[0051] As illustrated, the cellular RAT 404 includes a maximum transmit power level (MTPL) unit 408 that provides cellular SAR utilization information 401 to the SAR manager 332. Similarly, the WLAN RAT 406 includes a SAR unit 410 that providesWLAN state and SAR utilization information 403 to the SAR manager 332. The SAR manager 332 processes these inputs, along with other illustrative examples, such as additional cellular metrics (e.g., modem power state, link quality), metrics from other RATs (e.g., Wi-Fi, Bluetooth, Ultra-Wideband (UWB)), user context information (e.g., user preferences, historical usage), and application-level data (e.g., active applications and their performance requirements), to make real-time, window-by- window decisions regarding SAR budget allocation. Based on these inputs, the SAR manager 332 dynamically communicates WLAN state and SAR configuration / reconfiguration information 405 back to the MTPL 408, and SAR configuration / reconfiguration information 407 back to the SAR unit 410 of the WLAN RAT 406. As further illustrative examples, outputs from the SAR manager 332 and the multi-RAT resource controller 334 can include antenna selection parameters, band / channel selection information, and tuning codes to optimize wireless performance.

[0052] This dynamic SAR allocation contrasts with conventional fixed SAR budgeting approaches, which typically assign a static power ratio to each RAT regardless of instantaneous demands. For example, allocating a fixed SAR limit of 0.4 W / kg to WLAN and 1 .2 W / kg to cellular during concurrent operation. The architecture shown in FIG. 4, enabled by dynamic SAR budget sharing, allows for enhanced system-wide SAR budget utilization, leading to improved device performance, better user experience, and efficient regulatory compliance.

[0053] FIG. 5 illustrates an example of a SAR management architecture 500, depicting data interactions between the SAR manager 332 and the wireless technology subsystems introduced in FIG. 4. While FIG. 4 provided a high-level overview of how the SAR manager 332 interfaces with these wireless subsystems, FIG. 5 provides a more detailed structural view, illustrating example subsystems, inputs, outputs, and the corresponding data exchanges that enable the centralized cross-technology SAR management techniques described herein. As illustrated in FIG. 5, the SAR manager 332 dynamically manages the SAR budget across multiple concurrently active wireless technologies through interactions with firmware and SAR-algorithm subsystems associated with each wireless technology. For example,in the example illustrated in FIG. 5, the UE 102 includes a WLAN / Bluetooth (BT) subsystem 502 and a cellular subsystem 504. Each of these wireless technology subsystems represents a logical grouping of firmware and SAR-algorithm components responsible for managing SAR budgeting and control for their respective wireless technologies. For example, the WLAN / BT subsystem 502 includes WLAN / BT firmware 506 responsible for firmware-level control of WLAN and Bluetooth operations, and WLAN / BT SAR algorithm(s) 510, which manage SAR utilization for WLAN and Bluetooth operations. Similarly, the cellular subsystem 504 comprises modem firmware 508 for cellular operations control, and cellular SAR algorithm(s) 512, which manage SAR utilization for cellular technologies, such as LTE and NR. Although illustrated with multiple wireless subsystems, the architecture 500 depicted in FIG. 5 represents a generalized and comprehensive view of the SAR management system and can be readily adapted or simplified for specific operational scenarios, including those involving fewer wireless subsystems or even single-technology scenarios, such as a WLAN-only configuration.

[0054] FIG. 5 also shows a WLAN / BT Radio 514 and a Cellular Radio 516 as separate physical hardware components situated outside of their respective firmware and SAR-algorithm subsystems 502, 504. These physical radio components represent the actual hardware responsible for transmitting and receiving wireless signals for WLAN / BT and cellular communications, respectively. The radios 514, 516 operate under the direct operational control of their respective firmware subsystems, receiving transmit power and operational instructions generated based on dynamic SAR budget allocations determined by the SAR manager 332 and translated by the firmware 506, 508 and SAR algorithms 510, 512.

[0055] In at least some embodiments, the SAR manager 332 receives operational context data, including real-time and context-rich input data from multiple input sources. These include, for example, sensor data indicative of device interaction context, provided by sensors 312, user profile data 518 reflecting historical usage patterns and user preferences, and regulatory constraints included within regulatory tables 520. The sensors 312, in at least some embodiments, provide sensor data indicative of device interaction context, such as earpiece activation data (signifyingproximity to the user’s head), touch sensor data indicating direct handling via capacitive or touch sensor interactions, device motion data revealing device motion and orientation obtained from accelerometers, gyroscopes, or other motion sensors, hinge status data from foldable devices indicating their current open or closed state, and various user device configuration data, including preferred network types (e.g., Wi-Fi preferred), data roaming settings, and other user-defined parameters relevant for optimized SAR budgeting. The user profile data 518, in at least some embodiments, further enriches the contextual understanding by providing the SAR manager 332 with historical usage trends, active application-specific data, and other relevant contexts useful in inferring likely device behaviors and SAR management requirements. The regulatory tables 520, in at least some embodiments, include detailed SAR limits, compliance criteria, and regional SAR back-off conditions defined by relevant regulatory authorities, ensuring the SAR manager’s allocations consistently adhere to local regulatory standards.

[0056] In at least some embodiments, the SAR manager 332 also receives instantaneous (or non-instantaneous) operational data directly from each of the active wireless subsystems 502, 504. For example, from the WLAN / BT subsystem 502, the SAR manager 332 receives information 411 , such as SAR utilization information, predicted load information, and channel quality indicator (CQI) / link budget information. SAR utilization information encompasses, for example, metrics such as current SAR budgets expressed in, for example, watts per kilogram (W / kg), and current SAR utilization data covering ongoing time-averaged SAR (TAS) monitoring windows (e.g., typically 1 -minute intervals as mandated by applicable regulatory requirements under 6 GHz). Predicted load information reflects, for example, WLAN-specific traffic demands, including buffer occupancy information, predicted data throughput, and anticipated network load. CQI / link budget information includes, for example, detailed link quality metrics such as current transmission power, current transmission rate, received signal strength indicators (RSSI), reception (RX) quality metrics, modulation and coding schemes (MCS), power amplifier (PA) gain status, maximum possible TX power, current regulatory or non- SAR-related operational limits, and other WLAN or Bluetooth channel state information. Analogous operational inputs 413 are provided by the cellularsubsystem 504, similarly including cellular SAR utilization data (such as current SAR budget and real-time utilization), cellular predicted load metrics (anticipated traffic load and buffer states), and cellular-specific CQI / link budget information encompassing cellular TX power levels, modulation and coding schemes (MCS), and other pertinent cellular link quality indicators.

[0057] Utilizing this comprehensive real-time and contextual data, the SAR manager 332 computes optimized SAR budgets for each active wireless subsystem and communicates operational instructions back to these subsystems 502, 504 as updated SAR budget information 415, 417. These updated SAR budgets reflect dynamically adjusted SAR limits determined by the SAR manager 332 based on one or more of real-time operational data, device sensor inputs, user context, predicted traffic conditions, or regulatory requirements, ensuring optimal SAR utilization and compliance across the multiple wireless technologies. In at least some embodiments, the updated SAR budgets provided by the SAR manager 332 indicate to each subsystem 502, 504 the maximum allowable SAR utilization or radiation exposure permitted during the upcoming monitoring window, guiding each subsystem 502, 504 in determining appropriate transmission power levels, operational states, and radio resource allocations to ensure the UE 102 remains within regulatory compliance limits while optimizing wireless performance. Additionally, in at least some embodiments, parameters communicated along with the updated SAR budgets include one or more of the periodicity of SAR budget updates, synchronization signals aligning SAR monitoring windows across active RATs, or detailed subdivisions of SAR budgets based on antenna groups or device regions. Such subdivisions might differentiate, for example, between antennas at the top and bottom of the user equipment (UE) 102, allowing precise allocation of SAR budgets tailored to antenna locations, user interactions, and regulatory requirements. In at least some embodiments, SAR budget allocation decisions account for antenna location, allowing SAR budgets to be managed and adjusted based on the physical placement or positioning of individual antennas or antenna groups within the UE 102. Additionally, antenna-specific SAR contributions are determined for each antenna or antenna group, enabling separate and precise SAR management at the antenna level within the UE 102.

[0058] Moreover, in at least some embodiments, each subsystem 502, 504 employs specialized SAR algorithms to manage internal SAR budgets and transmit power limits. For example, the WLAN subsystem 502 employs a WLAN / BT SAR algorithm 510 utilizing, for example, Time-Averaged SAR (TAS) monitoring over one or more intervals (e.g., 30 second intervals), adapting transmit power limits and duty cycles on a per-second basis. This WLAN algorithm 510 includes control mechanisms, such as a power boost mechanism, to temporarily increase power when SAR utilization is low, a duty cycle control mechanism to sustain connections within compliance limits, and a failsafe mode that temporarily mutes transmissions under emergency conditions. Similarly, the cellular subsystem 504 employs a cellular SAR algorithm 512 configured with discrete transmit power limit levels dynamically adjusting based on instantaneous and average transmit power observed during each monitoring window (e.g., every 80 milliseconds for certain frequency ranges such as FR1).

[0059] As further illustrated in FIG. 5, within each subsystem 502, 504, the updated SAR budget information 415, 417 received from the SAR manager 332 are provided to their respective firmware components (e.g., WLAN / BT firmware 506 and modem firmware 508). Each firmware component translates these received SAR budgets into subsystem-specific parameters and communicates this translated information to their corresponding SAR algorithm components (e.g., WLAN / BT SAR algorithm 510 and cellular SAR algorithm 512). The SAR algorithm components then use this translated information to determine the operational configuration, such as exact transmission power settings or duty cycles, and subsequently provide these operational instructions directly to their corresponding physical radios (e.g., WLAN / BT radio 514 and cellular radio 516). The radios 514, 516 then adjust their actual wireless transmissions, including transmit power, modulation schemes, transmission timing, or duty cycles, based on these instructions. Consequently, the radios 514, 516 implement the SAR manager’s optimized budget allocations in real-time, ensuring effective control of radiation emissions, compliance with SAR regulatory limits, and optimized wireless performance under current operating conditions. Furthermore, in at least some embodiments, regulatory and operational considerations are managed when transitioning between different SAR parameter sets or resource state indicators (RSI). For example, during transitions betweendifferent RSI modes or SAR parameter configurations (e.g., shifting from higher to lower SAR limits), mechanisms are in place to control and measure transmit power adjustments explicitly, ensuring continuous regulatory compliance without transient exceedances during transition periods.

[0060] Continuing from FIG. 5, FIG. 6 illustrates an internal structural view of the SAR manager 332, depicting example predictive and optimization components utilized by the SAR manager 332 to determine optimal instantaneous SAR budgets and transmission power limits. As previously described with respect to FIG. 5, the SAR manager 332 dynamically and periodically computes updated SAR budget allocations for wireless subsystems based on a variety of input data, such as realtime operational metrics, sensor data, regulatory constraints, and user context. FIG.6 illustrates a functional decomposition of how the SAR manager 332 leverages this comprehensive input data, received from sources as illustrated in FIG. 5, into logical predictive and optimization components that collectively determine optimized SAR budget allocations and radio operating parameters.

[0061] In the example shown in FIG. 6, the SAR manager 332 includes a traffic pattern predictor 602, a link quality and availability predictor 604, an airtime and emissions predictor 606, a SAR utilization predictor 608, and a SAR budget allocator 610. Each of these components performs specialized tasks to collectively facilitate comprehensive and optimized SAR budget allocation.

[0062] In at least some embodiments, the traffic pattern predictor 602 receives input data, including user profiles and historical usage preferences, active application data indicating which applications are running or expected to generate data traffic, transmit buffer data reflecting buffered or queued transmissions, specific Quality-of- Service (QoS) requirements associated with one or more types of data transmission, a combination thereof, or the like. Utilizing these inputs, the predictor 602 forecasts anticipated data transmission demands for an upcoming SAR monitoring interval, typically spanning, for example, approximately one minute for wireless systems operating below 6 GHz (as defined by applicable regulatory requirements).Examples of techniques employed by the predictor 602 include machine learning algorithms trained on, for example, historical radio access technology (RAT) datasets (e.g. , detailed traffic patterns observed historically for Wi-Fi, Bluetooth, and cellular usage), deep packet inspection (DPI) methodologies capable of identifying and classifying traffic flows with highly predictable patterns such as voice-over-IP (VoIP) calls or Bluetooth audio streaming sessions, a combination thereof, or the like. Using these techniques, the predictor 602 generates a highly accurate cumulative traffic pattern, effectively representing the superposition of anticipated underlying data flows, thereby providing precise, data-driven guidance for subsequent SAR management and allocation decisions. The SAR manager 332 uses the output of the traffic pattern predictor 602 as an input for subsequent predictive and decisionmaking blocks.

[0063] The link quality and availability predictor 604, in at least some embodiments, takes in recent history and real-time channel information, including metrics such as RSSI, reference signal received power (RSRP), rank, CQI, MCS, recent scheduling information and grants from a base station, Wi-Fi and Bluetooth channel contention and backoff counters, and Bluetooth adaptive frequency hopping (AFH) status, a combination thereof, or the like. The link quality and availability predictor 604 forecasts data rates and channel availability (predicted link availability) expected for each wireless subsystem within the upcoming SAR monitoring window. In at least some embodiments, predictor 604 further integrates traffic demand forecasts provided by the traffic pattern predictor 602 to estimate anticipated data transmission needs more precisely, ensuring that link availability predictions account for both predicted traffic demand and network conditions. Collectively, these forecasts represent anticipated operational conditions, facilitating predictions of SAR utilization and enabling optimized allocation of SAR budgets.

[0064] Techniques employed by the link quality and availability predictor 604 include, for example, signal processing algorithms capable of extrapolating and predicting wireless channel conditions, particularly in time-varying environments characterized by finite Doppler spreads. Such algorithms analyze past and current channel states to identify patterns and project future channel conditions. Additionally, the link quality and availability predictor 604 can leverage machine learning algorithms trained on, for example, historical datasets comprising prior channelestimates, channel statistics, and specific channel state information tailored to distinct operational configurations (e.g., specific Evolved Universal Terrestrial Radio Access Network New Radio Dual Connectivity (ENDC) cellular connections with precise uplink / downlink Multiple Input Multiple Output (MIMO) arrangements, particular modulation schemes, or distinct antenna configurations). These predictive techniques enhance accuracy and reliability in estimating channel quality and availability, thereby enabling the SAR manager to perform more accurate and optimized SAR budgeting and power allocation decisions across multiple concurrent wireless technologies.

[0065] The SAR manager 332 utilizes the output from the link quality and availability predictor 604 to accurately estimate the achievable data transmission rates, anticipated channel conditions, and expected resource availability for each wireless subsystem during the upcoming SAR monitoring window. For example, the SAR manager uses this predicted information to inform subsequent predictive components, such as the airtime and emissions predictor 606, and to guide precise SAR budget allocations. By understanding the predicted data rates, link quality, and availability for each wireless technology, the SAR manager 332 can proactively allocate SAR budgets, dynamically adjusting permissible transmit power levels, prioritizing resources among subsystems based on anticipated needs, and ensuring both regulatory compliance and optimized wireless performance.

[0066] In at least some embodiments, the airtime and emissions predictor 606 receives outputs from, for example, the traffic pattern predictor 602 and the link quality and availability predictor 604. The airtime and emissions predictor 606 uses predicted traffic demand information provided by the traffic pattern predictor 602 to, for example, ascertain the anticipated data volume and transmission requirements during the upcoming SAR monitoring period. The airtime and emissions predictor 606 uses the link quality and data rate predictions from the link quality and availability predictor 604 to, for example, determine the feasible data throughput, channel availability, and anticipated link conditions.

[0067] By integrating these inputs, the airtime and emissions predictor 606 calculates anticipated airtime utilization and estimated anticipated emissions for eachRAT. In at least some embodiments, airtime prediction is computed based on predicted traffic demand, for example, as the minimum between the predicted traffic demand (as determined by the traffic pattern predictor 602) and predicted channel availability (as determined by the link quality and availability predictor 604). This ensures that the airtime prediction accurately reflects realistic data transmission capabilities under anticipated traffic loads and channel conditions. Further, emissions calculations, in at least some embodiments, involve calculating the cumulative energy emission based on predicted wireless transmissions. This calculation is based on predicted airtime utilization and comprises a linear sum of the lengths of anticipated data packets (derived from the predicted traffic pattern from the traffic pattern predictor 602) multiplied explicitly by their respective predicted transmission power levels (derived from predicted link quality and data rates provided by the link quality and availability predictor 604). The resulting calculation provides the estimated anticipated emissions for each RAT, enabling accurate SAR utilization predictions and optimized SAR budget allocations.

[0068] In at least some embodiments, the SAR manager 332 uses the output of the airtime and emissions predictor 606 as an intermediate calculation to determine the predicted total emissions and resource usage across multiple or all RATs. This information is then provided as input to subsequent predictive components, such as the SAR utilization predictor 608, facilitating the SAR manager’s precise determination of per-technology SAR utilization and ultimately informing the optimal allocation of SAR budgets and allowable transmission power levels across active wireless subsystems.

[0069] The SAR utilization predictor 608, in at least some embodiments, receives predictions generated by the airtime and emissions predictor 606, including anticipated airtime utilization and anticipated emissions. In addition, the SAR utilization predictor 608 accesses regulatory tables stored in the DE 102, which define SAR compliance limits and back-off conditions specific to each regulatory domain in which the UE 102 operates. The SAR utilization predictor 608 further considers historical SAR utilization data. Using this set of inputs, the SAR utilizationpredictor 608 calculates normalized SAR contributions for each RAT active on the DE 102.

[0070] In at least some embodiments, the SAR utilization calculation involves a mathematical computation that sums the energies of all packets anticipated to be transmitted during the SAR optimization period, typically around one second in duration (or more or less) for regulatory compliance purposes. This summation involves, for example, calculating the linear sum of individual packet energies, determined as the product of predicted packet lengths (derived from airtime predictions provided by the airtime and emissions predictor 606) and predicted transmit powers (also determined by the airtime and emissions predictor 606). This cumulative sum of energies is then divided explicitly by the total duration of the SAR optimization or monitoring window (e.g., 1 second). The resulting value is subsequently scaled by multiplying explicitly by the maximum allowable transmit power per technology, corresponding to 100% SAR utilization, to yield the normalized SAR contribution.

[0071] The SAR manager 332, in at least some embodiments, uses these calculated normalized SAR contributions provided by SAR utilization predictor 608 to ascertain the precise percentage of the SAR budget each technology is projected to consume during the upcoming monitoring period. By quantifying predicted future SAR utilization, the SAR manager 332 can accurately evaluate the headroom or shortfall in SAR budgets across the various RATs and wireless subsystems. This information directly feeds into subsequent optimization processes (e.g., performed by the SAR budget allocator 610), enabling dynamic reallocation of SAR budgets to optimize wireless performance, minimize interference, maintain regulatory compliance, and prevent data stalls due to overly aggressive power reductions.

[0072] In at least some embodiments, the SAR budget allocator 610 evaluates the link requirements for each wireless technology using the outputs generated by one or more of the traffic pattern predictor 602, the link quality and availability predictor 604, the airtime and emissions predictor 606, or SAR utilization predictor 608. The SAR budget allocator 610 then computes an optimal SAR budget allocation for each RAT based on one or more of the respective predicted traffic, link quality, airtimeavailability, emissions estimates, or SAR utilization metrics. The optimization algorithm implemented by the SAR budget allocator 610 performs various tasks. For example, the SAR budget allocator 610 reallocates unused or underutilized SAR budgets from one wireless technology (e.g., RAT A) to another wireless technology (e.g., RAT B), ensuring the total SAR exposure from the UE 102 remains consistently below applicable thresholds or regulatory limits. Moreover, the SAR budget allocator 610 maintains sufficient SAR budget headroom per technology to avoid inadvertent data stalls or transmission interruptions resulting from excessively aggressive SAR budget reductions, thereby avoiding scenarios where a technology must temporarily deactivate or significantly reduce its transmission power to remain within regulatory limits. Additionally, the SAR budget allocator 610 decouples SAR contributions from antenna groups that are spatially separated enough that they do not contribute to the same SAR exposure regions, recognizing independent limits explicitly set by regulatory bodies based on specific body-mass-based SAR exposure regions (e.g., 1 gram (g) or 10 g regions).

[0073] As a result of these optimization capabilities, several user benefits are provided. For example, a cellular connection characterized by low-duty-cycle voice traffic that does not fully utilize its allocated SAR budget can explicitly have its excess budget dynamically reassigned to other technologies, such as Wi-Fi or Bluetooth, improving their performance. Similarly, technologies with robust link budgets that transmit at high modulation rates but relatively low transmit power due to constraints such as error vector magnitude (EVM) explicitly free up SAR budget capacity that can then be reassigned to technologies experiencing higher utilization or greater link stress. Furthermore, latency-sensitive systems such as voice connections explicitly benefit from being assigned larger SAR budgets to ensure link stability under stressed link conditions. Also, SAR budget reallocation capabilities allow temporary redistribution of SAR budget between antenna groups positioned at different device locations, for example, temporarily shifting SAR budgets from bottom-positioned antennas to top-positioned antennas (or vice versa), optimizing overall wireless performance, regulatory compliance, and user experience dynamically in real-time according to evolving user scenarios and system states.

[0074] FIG. 7 provides an operational timeline diagram 700 depicting an example implementation of dynamic SAR budget sharing on a window-by-window basis. FIG. 7 illustrates a time-based operational sequence involving interactions between the multi-RAT resource controller 334, the cellular modem 310, and the WLAN controller 316. For clarity, the sequence is depicted as three horizontal timelines, including a multi-RAT resource controller timeline 702, a cellular modem timeline 704, and a WLAN controller timeline 706. This sequence depicts multiple sequential SAR successive monitoring windows, shown as Window W708, Window (I / I / +1) 710, and Window (W+D) 712. Also, although cellular and WLAN RATs are specifically used as illustrative examples in this description, the techniques, methods, and systems described herein are not limited exclusively to these technologies. Rather, they can be broadly applied to any suitable combination or number of wireless technologies or RATs (e.g., Bluetooth, Ultra-Wideband (UWB), LTE, NR, future RATs, or any combination thereof) implemented by a UE 102.

[0075] In the illustrated example, each SAR management cycle is executed within discrete monitoring windows, typically spanning intervals on the order of seconds, depending on factors such as periodicity of SAR status updates, reconfiguration intervals, and the dynamics of uplink (UL) duty cycles and power control conditions. For instance, the periodicity of SAR status updates and reconfigurations may be approximately 80 milliseconds for the cellular modem 310 and approximately one second for the WLAN controller 316, reflecting typical operational characteristics of these subsystems. However, other intervals are applicable as well.

[0076] In at least some embodiments, each SAR management cycle within a monitoring window comprises multiple sequential actions. Initially, during each monitoring window 708 to 712, the multi-RAT resource controller 334 conducts status polling operations 714 to 718, interacting with both the cellular modem 310 and WLAN controller 316. This polling involves, for example, retrieving real-time operational data, such as current SAR utilization (expressed, for example, in average power levels, P_avg), predicted load conditions, current link quality metrics, and the WLAN operational state (on / off). After obtaining modem / controller status information, the multi-RAT resource controller 334 proceeds to decision-making phases 720 to724. During each decision-making phase, the controller 334 evaluates whether to dynamically share a portion of the SAR budget from the cellular modem 310 to the WLAN controller 316. In at least some embodiments, this decision-making process involves, for example, evaluating at least two conditions: whether cellular SAR utilization is predicted to fall below a predetermined threshold (X), and whether the WLAN subsystem is active and its SAR utilization is predicted to exceed another predetermined threshold (Y). In an initial implementation illustrated in FIG. 7, the decision-making process assumes a binary outcome (sharing or not sharing). Alternative embodiments, however, can extend this to more granular, multi-level SAR budget-sharing decisions, potentially enabling bidirectional and variable-amount SAR sharing between the cellular modem 310 and WLAN controller 316.

[0077] Following each decision-making phase, the multi-RAT resource controller 334 initiates reconfiguration phases 726 to 730 for time-averaged SAR (TA-SAR) parameters in both the cellular modem 310 and WLAN controller 316, activating appropriate SAR configurations based on the decision outcome. Reconfiguring these TA-SAR parameters involves, for example, adjusting radio transmission parameters (e.g., transmit power levels or duty cycles) according to newly allocated SAR budgets. In at least some embodiments, to avoid undesirable “ping-pong” effects (rapid oscillations between sharing and non-sharing states), particularly when cellular SAR utilization fluctuates near threshold X, reconfiguration criteria, such as hysteresis margins or minimum sharing duration constraints, are employed.

[0078] FIG. 7 also illustrates a fixed delay period (“Delay D” 732) before SAR budget-sharing decisions and TA-SAR parameter reconfigurations from Window W 708 take effect in subsequent windows (e.g., Window I / +1 710, Window W+D 712). This fixed delay (D) accounts for practical constraints, including processing delays, reconfiguration delays, and WLAN “cooling down” periods. For example, if the cellular modem 310 seeks to reclaim previously shared SAR budget from the WLAN controller 316, delay D represents the maximum expected duration required for the WLAN subsystem to reduce its emissions accordingly. FIG. 7 further illustrates that the SAR management sequence repeats continuously, with status polling 714 to 718, decision-making 720 to 724, and TA-SAR parameter reconfiguration 726 to 730cycles carried out in each successive monitoring window. This continuous adaptive process ensures optimized SAR utilization dynamically across multiple wireless technologies, maintaining regulatory compliance limits.

[0079] In at least some embodiments, the decision-making phases 720 to 726 employ one or more predictive algorithms as represented by EQ. 1 below. For example, EQ. 1 calculates predicted SAR utilization U'(W + D) for a future window (IV + D) as follows:

[0081] where U'(W + D) represents predicted SAR utilization in future window (IV + £)), Pmaxindicates the maximum possible SAR consumed within a single monitoring window, D denotes the fixed delay period before a SAR budget-sharing decision from the current window (l / V) becomes effective, Pkdenotes actual SAR consumed in a historical window k, M represents the number of monitoring windows considered in the SAR averaging period, and Piimitsignifies the regulatory SAR limit (maximum allowable SAR per monitoring window).

[0082] This predictive formula enables the multi-RAT resource controller 334 to anticipate future SAR utilization based on historical utilization patterns and current SAR-sharing decisions. The results inform the controller 334 whether sufficient SAR budget headroom exists to support sharing from the cellular modem 310 to WLAN controller 316 without violating regulatory limits, thus enabling proactive and optimized SAR management decisions. Additionally, in at least some embodiments, regulatory considerations are addressed during transitions between different SAR configurations or resource state indicators (RSI), with controlled transmit power adjustments explicitly ensuring continuous regulatory compliance and avoiding transient exceedances during configuration transitions.

[0083] FIG. 8 illustrates an example method 800 for dynamic cross-technology SAR budget allocation, in accordance with at least some embodiments. The operations described below with respect to the method 800 have been described above in greater detail with reference to FIG. 1 through FIG. 7. It should be understood thatthe method 800 is not limited to the sequence of operations shown in FIG. 8, as at least some of the described operations can be performed in parallel or in a different sequence. Moreover, in at least some implementations, the method 800 can include one or more different operations than those shown in FIG. 8. Also, although cellular, WLAN (Wi-Fi), and Bluetooth RATs are specifically referenced to describe the method 800, the described dynamic SAR management techniques are broadly applicable to any current or future radio access technologies.

[0084] In at least some embodiments, the method 800 initiates at block 802 with the SAR manager 332 initiating a SAR management cycle. At block 804, the SAR manager 332 collects real-time operational data, including current SAR utilization metrics, transmit power requirements, modem statuses, and sensor-derived user interaction data. At block 806, predictive analyses are performed by the SAR manager 332 using modular predictive blocks 602 to 608, which include traffic pattern predictions, link quality and availability predictions, airtime and emissions predictions, and SAR utilization predictions. At block 808, the SAR manager 332 evaluates predicted SAR utilization across multiple active RATs based on predictive analyses performed at block 806. At block 810, the SAR manager 332 decides on dynamic SAR budget reallocation among the active technologies, identifying any underutilized SAR budget from one RAT that can be allocated to another RAT experiencing higher SAR utilization or resource demands.

[0085] At block 812, the SAR manager 332 updates the SAR budget allocations by communicating revised SAR budgets and parameters, including synchronization signals for aligning SAR monitoring windows across each RAT subsystem. Subsequently, at block 814, the respective RAT subsystems (e.g., cellular modem, WLAN controller, Bluetooth controller) reconfigure their operational parameters based on the updated SAR budget allocations. Reconfiguration operations include, for example, adjusting transmission power levels, duty cycles, modulation schemes, or antenna utilization as necessary. At block 816, the SAR manager 332 and respective subsystems verify regulatory compliance, ensuring that updated SAR budget allocations and transmission parameters meet regulatory SAR exposure limits. At block 818, the process proceeds to the next monitoring interval, with the SARmanager 332 restarting the SAR management cycle to continually monitor, predict, allocate, and optimize SAR budgets dynamically across multiple radio access technologies.

[0086] FIG. 9 illustrates an example method 900 for predictive SAR utilization calculation for dynamic SAR budget allocation, in accordance with at least some embodiments. The operations described below with respect to the method 900 have been described above in greater detail with reference to FIG. 1 through FIG. 7. It should be understood that the method 900 is not limited to the sequence of operations shown in FIG. 9, as at least some of the described operations can be performed in parallel or in a different sequence. Moreover, in at least some implementations, the method 900 can include one or more different operations than those shown in FIG. 9. Also, although cellular RATs (e.g., LTE, NR) and WLANs are specifically referenced to describe the method 900, the described predictive SAR utilization calculation techniques are broadly applicable to any current or future radio access technologies.

[0087] In at least some embodiments, the method 900 initiates at block 902 with the SAR manager 332 retrieving historical SAR utilization data for active wireless subsystems, such as cellular, WLAN, Bluetooth, or other RATs. At block 904, the SAR manager 332 performs traffic pattern prediction based on historical usage, current user context, and application-level data to anticipate the expected wireless traffic demands during the upcoming SAR monitoring interval. This operation leverages, for example, machine learning algorithms and deep packet inspection to identify predictable traffic patterns. At block 906, the SAR manager 332 predicts link quality and availability for each active RAT using current and historical metrics, including RSSI, RSRP, CQI, MCS, scheduling grants, channel contention states, and adaptive frequency hopping (AFH) status. At block 908, the SAR manager 332 uses the predicted traffic and link quality information to compute anticipated airtime utilization and emissions for each RAT. The emissions calculations integrate predicted packet lengths and anticipated transmit power levels.

[0088] At block 910, the SAR manager 332 calculates the predicted SAR contributions by, for example, summing anticipated energy emissions over the SARmonitoring interval. This calculation involves, for example, multiplying the predicted packet lengths by their respective predicted transmit power levels. At block 912, the SAR manager 332 normalizes these predicted SAR contributions by dividing the cumulative energy emissions by the duration of the monitoring interval and then scaling by the maximum allowable transmit power per technology to yield normalized SAR utilization percentages. At block 914, the SAR manager 332 outputs the normalized predicted SAR utilization data to subsequent processes, such as dynamic SAR budget allocation, enabling precise SAR budget distribution and transmit power adjustments to ensure optimal wireless performance and regulatory compliance. At block 916, the SAR manager 332 outputs the predicted SAR utilization. At block 918 the process terminates, concluding the predictive SAR utilization calculation cycle.

[0089] In some embodiments, certain aspects of the techniques described above may be implemented by one or more processors of a processing system executing software. The software comprises one or more sets of executable instructions stored or otherwise tangibly embodied on a non-transitory computer-readable storage medium. The software can include the instructions and certain data that, when executed by the one or more processors, manipulate the one or more processors to perform one or more aspects of the techniques described above. The non-transitory computer-readable storage medium can include, for example, a magnetic or optical disk storage device, solid-state storage devices such as Flash memory, a cache, random access memory (RAM) or other non-volatile memory device or devices, and the like. The executable instructions stored on the non-transitory computer-readable storage medium may be in source code, assembly language code, object code, or other instruction format that is interpreted or otherwise executable by one or more processors.

[0090] A computer-readable storage medium may include any storage medium, or combination of storage media, accessible by a computer system during use to provide instructions and / or data to the computer system. Such storage media can include, but is not limited to, optical media (e.g., compact disc (CD), digital versatile disc (DVD), Blu-Ray disc), magnetic media (e.g., floppy disc , magnetic tape, or magnetic hard drive), volatile memory (e.g., random access memory (RAM) orcache), non-volatile memory (e.g., read-only memory (ROM) or Flash memory), or microelectromechanical systems (MEMS)-based storage media. The computer- readable storage medium may be embedded in the computing system (e.g., system RAM or ROM), fixedly attached to the computing system (e.g., a magnetic hard drive), removably attached to the computing system (e.g., an optical disc or Universal Serial Bus (USB)-based Flash memory), or coupled to the computer system via a wired or wireless network (e.g., network accessible storage (NAS)).

[0091] Note that not all of the activities or elements described above in the general description are required, that a portion of a specific activity or device may not be required, and that one or more further activities may be performed, or elements included, in addition to those described. Still further, the order in which activities are listed are not necessarily the order in which they are performed. Also, the concepts have been described with reference to specific embodiments. However, one of ordinary skill in the art appreciates that various modifications and changes can be made without departing from the scope of the present disclosure as set forth in the claims below. Accordingly, the specification and figures are to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope of the present disclosure.

[0092] Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any feature(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature of any or all the claims. Moreover, the particular embodiments disclosed above are illustrative only, as the disclosed subject matter may be modified and practiced in different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. No limitations are intended to the details of construction or design herein shown, other than as described in the claims below. It is therefore evident that the particular embodiments disclosed above may be altered or modified and all such variations are considered within the scope of the disclosed subject matter. Accordingly, the protection sought herein is as set forth in the claims below.

Claims

WHAT IS CLAIMED IS:1 . A method, at a user equipment (UE) in a cellular network, comprising: computing an individual specific absorption rate (SAR) budget for each radio access technology (RAT) module of a plurality of RAT modules at the UE based on operational context data associated with the UE; sending each individual SAR budget to a corresponding RAT module of the plurality of RAT modules; and adjusting, at one or more RAT modules of the plurality of RAT modules, transmission parameters of the corresponding RAT module based on the corresponding individual SAR budget.

2. The method of claim 1 , wherein the operational context data comprises sensor data indicative of device interaction context.

3. The method of claim 2, wherein the sensor data comprises at least one of: earpiece activation data; touch sensor data; device motion data; hinge status data; or user device configuration data.

4. The method of any of claims 1 to 3, wherein the operational context data comprises operational metrics indicative of current operating conditions of one or more RAT modules of the plurality of RAT modules.

5. The method of claim 4, wherein the operational metrics comprise at least one of: a current SAR budget associated with one or more RAT modules of the plurality of RAT modules; a current SAR utilization associated with one or more RAT modules of the plurality of RAT module; a current transmission power associated with one or more RAT modules of the plurality of RAT module;a current transmission rate associated with one or more RAT modules of the plurality of RAT module; link budget information associated with one or more RAT modules of the plurality of RAT module; buffer occupancy or load information associated with one or more RAT modules of the plurality of RAT module; or channel state information associated with one or more RAT modules of the plurality of RAT module.

6. The method of any of claims 1 to 5, further comprising: periodically updating the individual SAR budgets during successive monitoring windows based on changes in the operational context data.

7. The method of claim 6, further comprising: predicting future SAR utilization for each RAT module of the plurality of RAT modules based on historical SAR utilization data and current operating conditions, and wherein computing the individual SAR budget for each RAT module of the plurality of RAT modules comprises: reallocating SAR budgets among the plurality of RAT modules based on the predicted future SAR utilization.

8. The method of claim 7, wherein reallocating the SAR budgets comprises: transferring at least a portion of unused SAR budget from a first RAT module having a predicted SAR utilization below a first threshold to a second RAT module having a predicted SAR utilization above a second threshold.

9. The method of any of claims 1 to 8, further comprising: responsive to determining antenna-specific SAR contributions, separately managing SAR budgets based on the determined antenna-specific SAR contributions and at least one of antenna location or grouping within the UE.

10. The method of any of claims 1 to 9, further comprising: predicting future SAR utilization for each RAT module of the plurality of RAT modules based on historical SAR utilization data and anticipated operational conditions; and updating the computed SAR budget for each RAT module based on the predicted future SAR utilization.

11. The method of claim 10, wherein predicting the future SAR utilization comprises: estimating anticipated airtime utilization based on predicted traffic demand and predicted link availability; estimating anticipated emissions based on predicted airtime utilization and predicted transmission power levels; and calculating normalized SAR contributions for each RAT module of the plurality of RAT modules based on the estimated anticipated emissions.

12. A user equipment (UE), comprising: a plurality of radio access technology (RAT) modules; at least one processor coupled to the plurality of RAT modules; and at least one memory storing executable instructions that, when executed by the at least one processor, cause at least one of the one or more of the plurality of RAT modules or the at least one processor to perform the method of any of claims 1 to 11 : compute an individual specific absorption rate (SAR) budget for each RAT module of the plurality of RAT modules based on operational context data associated with the UE; send each individual SAR budget to a corresponding RAT module of the plurality of RAT modules; and adjust, at one or more RAT modules of the plurality of RAT modules, transmission parameters of the corresponding RAT module based on the corresponding individual SAR budget.

13. A computer-readable storage medium embodying a set of executable instructions, the set of executable instructions to manipulate a user equipment to perform the method of any of claims 1 to 11 .

Images