A wireless channel measurement time slot scheduling method under multi-wearable device concurrency

Abstract

The present application relates to the technical field of wireless communication, in particular to a wireless channel measurement time slot scheduling method under multi-wearable device concurrency. The present application periodically acquires the state and distance information of the intelligent wearable device through the base station, dynamically allocates the measurement priority, and determines the total measurement time slot quantity according to the priority. Time slot allocation is adopted, combined with the priority polling mechanism, to allocate non-overlapping AoA / CS measurement time slots for each device, and the starting time and duration are issued through the wireless control channel to guide the device to transmit the measurement signal in the corresponding time slot. The present application solves the wireless channel measurement conflict problem when multiple nodes concurrently access, and through orthogonal allocation and dynamic resource configuration, the balance between high-precision spatial perception and low-power consumption of small-sized wearable devices is considered while reducing the air interface signal collision.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, specifically to a method for scheduling wireless channel measurement time slots under concurrent use of multiple wearable devices. Background Technology

[0002] With the widespread application of Bluetooth Low Energy technology in wireless personal area networks (WLANs), novel wireless channel measurement technologies based on phase ranging and angle of arrival (AOA) have become a core means to achieve high-precision spatial awareness. In smart home wireless coverage environments, multiple wireless wearable nodes make high-frequency channel probe requests with access points (base stations) to maintain the positioning accuracy and data synchronization of the air interface link.

[0003] However, in complex indoor environments with multiple wearable devices communicating concurrently, existing technologies face the following communication layer challenges:

[0004] When multiple concurrent wireless wearable devices exist in a system, each device needs to frequently perform channel measurements with the base station to maintain high-precision positioning and gesture recognition. Existing random access or fixed-period scheduling methods are prone to wireless frame collisions and interference when faced with the sudden surge of high-frequency sampling demands from multiple devices, leading to a decrease in channel measurement success rate and an increase in interaction latency. To ensure sub-meter positioning accuracy and millisecond-level response latency, wearable devices typically need to maintain high-frequency channel probing. However, in a multi-node environment, blindly increasing the measurement frequency will significantly increase the power consumption of the wireless link and shorten the standby time of miniaturized wearable devices. How to balance measurement accuracy and power consumption for multiple devices within the limited wireless channel capacity by optimizing the time slot scheduling scheme is a pressing problem in the field of wireless communication.

[0005] To address this, a time slot scheduling method for wireless channel measurement under concurrent use of multiple wearable devices is proposed. Summary of the Invention

[0006] The purpose of this invention is to provide a wireless channel measurement time slot scheduling method under multiple wearable devices concurrent access. By orthogonally allocating wireless probe reference signals in the time domain and dynamically configuring asymmetric channel resources based on service status, the problem of wireless channel measurement conflict and air interface resource waste caused by multiple nodes concurrent access is solved.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for scheduling wireless channel measurement time slots under concurrent use of multiple wearable devices includes:

[0009] The base station periodically receives and acquires the current application status information of each smart wearable device and / or the distance information between the smart wearable device and the base station, and dynamically assigns each smart wearable device to a preset measurement priority based on the status information and / or distance information.

[0010] The base station maintains an overall scheduling cycle and determines the total number of measurement time slots required based on the measurement priorities of all smart wearable devices that currently need to perform channel measurements.

[0011] The base station employs a time slot allocation combined with priority polling mechanism to allocate a non-overlapping AoA / CS measurement time slot to each smart wearable device within the scheduling period; the base station sends the start time and duration of the AoA / CS measurement time slot to each smart wearable device via a wireless control channel.

[0012] Each of the smart wearable devices transmits an AoA / CS channel measurement signal within the AoA / CS measurement time slot according to the received start time.

[0013] Preferably, the preset measurement priority includes high priority, medium priority, and low priority, including:

[0014] When the smart wearable device is at the entrance / exit boundary of the presence gate and / or is performing gesture interaction, it is assigned to the high priority; when the smart wearable device is in a stable state within the presence gate, it is assigned to the medium priority; when the smart wearable device is in an off-site state and / or in sleep mode, it is assigned to the low priority.

[0015] Preferably, when the number of smart wearable devices is too large, causing the total capacity requirement of the scheduling period to exceed the scheduling period, the base station reduces the measurement rate of the medium-priority and / or low-priority smart wearable devices to ensure the real-time measurement needs of the high-priority smart wearable devices.

[0016] When any of the aforementioned smart wearable devices causes the confidence level of continuous measurement results to fall below a preset threshold due to environmental changes and / or occlusion, the base station allocates a reserved emergency time slot for rapid recalibration, and resumes normal time slot scheduling after successful recalibration.

[0017] Preferably, the mechanism of time slot allocation combined with priority polling includes:

[0018] The base station prioritizes allocating non-overlapping AoA / CS measurement time slots to the high-priority smart wearable devices;

[0019] Within the same priority level, the base station uses a polling method to allocate time slots to smart wearable devices to ensure fair measurement opportunities for smart wearable devices of the same level.

[0020] The base station will allocate the remaining time slot resources within the scheduling period to the low-priority smart wearable device for periodic heartbeat detection.

[0021] Preferably, the presence gate entry / exit boundary refers to: the smart wearable device being within the edge range of a preset distance threshold and an angle threshold, and the continuous ranging residual satisfying a preset switching judgment condition; the stable state within the presence gate refers to: the smart wearable device being located within the visible sector defined by the distance threshold and the angle threshold, and the rate of change of the six-axis IMU sensor being lower than a preset static threshold; the absence state and / or sleep mode refers to: the smart wearable device being outside the visible sector and / or being in a low-power mode with no displacement and no gesture event triggered within a preset time period.

[0022] Preferably, the base station dynamically determines the duration of the scheduling period based on the following dimensions:

[0023] The base station adjusts the scheduling cycle based on the number of smart wearable devices currently establishing connections and sets the minimum measurement duration required for a single device, wherein the scheduling cycle is greater than or equal to the number of smart wearable devices multiplied by the minimum measurement duration;

[0024] When a base station determines that any smart wearable device has entered a high-priority state, the base station switches the measurement frequency of that device from a first preset frequency to a second preset frequency, wherein the second preset frequency is greater than the first preset frequency. At the same time, the base station adjusts the scheduling period to meet the target duration of one-half of the second preset frequency by reducing the proportion of idle time slots of inactive devices within the scheduling period. When the confidence level of continuous measurement results is lower than a preset threshold, the base station increases the number of pulse repetitions for a single AoA / CS measurement and increases the value of the scheduling period by a preset step size until the confidence level recovers to above the preset threshold.

[0025] Preferably, the second preset frequency is between 100Hz and 200Hz to meet the real-time requirements of gesture interaction; the first preset frequency is between 20Hz and 25Hz to meet the low power consumption requirements of on-site status monitoring.

[0026] Preferably, the base station performs the priority polling in the following manner:

[0027] Within the same priority queue, the base station presets the access sequence for each smart wearable device, allocates measurement time slots sequentially according to the access sequence, and automatically jumps to the first device in the sequence for cyclic execution after completing the allocation of the last device in the current sequence.

[0028] When a new smart wearable device jumps to high priority due to triggering gesture interaction and / or entering the presence gate boundary, the base station suspends the current medium and low priority polling progress and inserts the high priority device into the next pending start time slot;

[0029] During the polling process, the base station allocates a higher frequency of polling positions to high-priority devices compared to medium- and low-priority devices; within the scheduling cycle, high-priority devices are polled more often than medium-priority devices, and medium-priority devices are polled more often than low-priority devices.

[0030] The base station will allocate the remaining time slots that are not occupied by high or medium priority devices during the scheduling cycle to devices in the off-site state or dormant mode at the lowest cyclic frequency in order to perform periodic heartbeat connection detection.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0032] 1. This invention effectively solves the air interface signal collision problem caused by multiple wearable devices accessing the network concurrently by uniformly maintaining the scheduling cycle of the base station and adopting a time-domain orthogonal time slot allocation mechanism. By allocating non-overlapping AoA / CS measurement time slots to each device, the exclusivity of the channel sounding signal during physical layer transmission is ensured, avoiding measurement data packet loss and retransmission caused by co-channel interference, and significantly improving the robustness and measurement confidence of the wireless link in complex indoor environments.

[0033] 2. This invention introduces a dynamic prioritization mechanism based on application status and distance information. The base station can sense sudden service demands such as gesture interaction, and ensure that key interaction nodes obtain sufficient bandwidth resources to achieve millisecond-level response by dynamically shrinking the idle time slots of inactive devices and adjusting the scheduling cycle frequency in real time; at the same time, when there are too many devices, channel congestion is prevented by reducing the measurement rate of low-priority nodes, thereby maximizing the utilization of air interface resources.

[0034] 3. This invention achieves precise control of the duty cycle of the RF front-end of wearable devices through an event-triggered mechanism and a multi-level polling strategy. Devices in a stable presence or sleep mode are allocated only low-frequency keep-alive detection time slots, significantly reducing RF power consumption during inactivity. Simultaneously, by dynamically increasing the number of pulse repetitions and coordinating with emergency time slot recalibration when the channel environment deteriorates, the system ensures that it can obtain high-precision positioning results when necessary without constantly maintaining high-power transmission, effectively extending the standby time of miniaturized wearable devices. Attached Figure Description

[0035] Figure 1 This is a flowchart of a wireless channel measurement time slot scheduling method under multiple wearable devices concurrently proposed in this invention;

[0036] Figure 2 This is a flowchart of a wireless channel measurement time slot scheduling method for concurrent multiple wearable devices proposed in this invention.

[0037] Figure 3 This is a flowchart of the priority polling mechanism proposed in this invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example 1

[0040] Please see Figures 1 to 3 This invention provides a method for scheduling wireless channel measurement time slots under concurrent use of multiple wearable devices, the technical solution of which is as follows:

[0041] A method for scheduling wireless channel measurement time slots under concurrent use of multiple wearable devices, such as Figure 1 - Figure 2 As shown, it includes:

[0042] The base station periodically receives and acquires the current application status information of each smart wearable device and / or the distance information between the smart wearable device and the base station, and dynamically assigns each smart wearable device to a preset measurement priority based on the status information and / or distance information.

[0043] The base station maintains an overall scheduling cycle and determines the total number of measurement time slots required based on the measurement priorities of all smart wearable devices that currently need to perform channel measurements.

[0044] The base station employs a time slot allocation combined with priority polling mechanism to allocate a non-overlapping AoA / CS measurement time slot to each smart wearable device within the scheduling period; the base station sends the start time and duration of the AoA / CS measurement time slot to each smart wearable device via a wireless control channel.

[0045] Each of the smart wearable devices transmits an AoA / CS channel measurement signal within the AoA / CS measurement time slot according to the received start time.

[0046] The AoA / CS measurement time slots employ a "data + sensing" composite frame structure. Within each allocated time slot, the first part is a 128-bit service data payload area used to transmit sensor readings; this is followed by the measurement signal segment. This design ensures that data backhaul is completed simultaneously with channel measurement, avoiding additional consumption of the effective air interface bandwidth by measurement actions, and prioritizing the integrity of the measurement pulse by compressing the payload length in scenarios where total capacity exceeds limits.

[0047] Furthermore, the preset measurement priorities include high priority, medium priority, and low priority, including:

[0048] When the smart wearable device is at the entrance / exit boundary of the presence gate and / or is performing gesture interaction, it is assigned to the high priority; when the smart wearable device is in a stable state within the presence gate, it is assigned to the medium priority; when the smart wearable device is in an off-site state and / or in sleep mode, it is assigned to the low priority.

[0049] The dynamic allocation process employs a state-weighted decision algorithm:

[0050] Base station preset motion weights and position weight The system first calculates the motion score based on the rate of change of values ​​from the six-axis IMU sensor. (If the score is below the static threshold, it is recorded as 0 points; if it is above, it is mapped to a score of 1-100 proportionally.) Then, the position score is calculated based on the distance and angle residuals. (Being in the center of the gate scores 50 points, while being near the edge increases to 100 points). Final priority score. .like If gesture interaction exists, it will be forcibly assigned to high priority; if If, it is classified as medium priority; If the exit criteria are met, it is classified as a low priority.

[0051] Specifically, the sports score A piecewise linear mapping function is used for calculation to ensure filtering of minute movements and rapid response to violent movements. The real-time acceleration modulus change rate calculated by the six-axis IMU sensor is assumed to be... (unit: The preset static threshold is (e.g., 0.05) The preset threshold for saturation during strenuous exercise is... (e.g., 2.0) ),against Different numerical ranges, sports scores The calculation logic is as follows:

[0052] When the rate of change Between the lower threshold and the upper threshold (i.e.) < < When the motion score is calculated, the base station uses the following linear normalization formula:

[0053] ;

[0054] When the rate of change Less than the lower threshold When the device is determined to be completely stationary, a value is directly assigned. =0;

[0055] When the rate of change Greater than or equal to the upper limit threshold When the device is determined to be in a state of high-frequency, violent motion, a value is directly assigned. =100.

[0056] Specifically, the position score Based on the current distance d of the device and the radius of the visible sector edge of the base station The ratio (e.g., 3.0m) is used for calculation. Wherein, To prevent stationary devices located in the central area from being incorrectly downgraded due to excessively low total scores, this embodiment sets the baseline score for the central safety zone at 75 points, with the edge areas approaching 100 points. The calculation formula is as follows:

[0057] ;

[0058] The base station first calculates the magnitude using the acceleration and angular velocity vectors transmitted from the six-axis IMU sensor. If the magnitude is continuously below a preset stationary threshold (e.g., 0.05) for 500ms, the base station will then determine the magnitude. If the distance d and angle are both 0.1 rad / s, then it is marked as a stable state. Subsequently, the base station will use the real-time measured distance d and angle... With respect to the preset on-site gate area (e.g., distance from the base station) ,angle ) for comparison.

[0059] When state conflicts occur, the system arbitrates according to the principle of "business sensitivity first." Specifically, if a smart wearable device triggers a gesture interaction event, regardless of whether its distance information is within the out-of-field range, the base station forcibly assigns it to high priority and maps its device ID to the first reserved time slot within the scheduling cycle. If the device does not trigger a gesture and is in sleep mode, the base station detects its distance by sending low-frequency query frames. If the distance exceeds the gate edge threshold (e.g., 3.5m) and the continuous ranging residual fluctuation is less than 10cm, it is removed from the high / medium priority queue and moved to the end of the low-priority circular list. Through the above-mentioned clear threshold limits and conflict arbitration logic, the base station can stably and uniquely execute priority reallocation actions in complex and ever-changing application scenarios.

[0060] This invention achieves precise and dynamic configuration of wearable device priorities by introducing a multi-dimensional state-weighted judgment algorithm and a "business sensitivity priority" arbitration logic. Its benefits include: leveraging the deep coupling of IMU motion features and spatial location information to effectively improve the robustness and uniqueness of priority identification in complex environments; ensuring millisecond-level hard real-time response for critical services such as gesture interaction through a conflict arbitration mechanism; and taking into account low-power maintenance of inactive devices through low-frequency detection, thus achieving efficient and refined scheduling of air interface resources among different service requirements.

[0061] Furthermore, when the number of smart wearable devices is too large, causing the total capacity requirement of the scheduling cycle to exceed the scheduling cycle, the base station reduces the measurement rate of the medium-priority and / or low-priority smart wearable devices to ensure the real-time measurement needs of the high-priority smart wearable devices.

[0062] When any of the aforementioned smart wearable devices causes the confidence level of continuous measurement results to fall below a preset threshold due to environmental changes and / or occlusion, the base station allocates a reserved emergency time slot for rapid recalibration, and resumes normal time slot scheduling after successful recalibration.

[0063] When a base station determines that priority adjustment or emergency time slot allocation is necessary, the base station's scheduling module triggers scheduling vector reconfiguration. The base station fills the IDs of high-priority devices into the first consecutive time slots of the scheduling frame, fills the middle interleaved time slots with the IDs of medium-priority devices, and fixes the emergency recalibration time slots to point to the specified values ​​for each cycle. Time period. If the total capacity is exceeded, the base station modifies the polling mask of the medium-priority devices, causing them to transmit signals only in even-numbered cycles on the physical link, thereby freeing up 50% of the medium-priority time slots for high-priority devices to use at high frequencies.

[0064] To ensure link stability during the scheduling vector reconfiguration process, the base station includes a synchronization counter when sending control frames containing new timeslot information. Upon receiving the reconfiguration command, each wearable device maintains the current time slot scheme. Each cycle, and at the start of the superframe when the counter returns to zero, synchronously switch to the reconstructed scheduling vector.

[0065] In scenarios where total capacity is exceeded, the 50% of released medium-priority time slots are redirected to high-priority devices in gesture interaction mode via the base station's scheduling mask. At this time, the base station allocates two independent AoA / CS start times to the high-priority device, located in the original service time slot interval and the original medium-priority idle interval, respectively. This physically doubles the sampling frequency of critical devices without changing the total scheduling cycle's physical length, ensuring millisecond-level response times for gesture interactions.

[0066] During the aforementioned scheduling process, the base station maintains a global clock synchronization reference. When a scheduling vector reconfiguration occurs, the control message sent by the base station not only includes the new start time of each smart wearable device but also a mapping mask for each device ID. For high-priority devices assigned double the sampling frequency, their mapping mask corresponds to two physical layer transmission windows. After receiving the reconfiguration command, the wearable device's local RF controller switches from the original single-pulse transmission logic to a double-pulse burst mode based on the zeroing point of the synchronization counter. The interval between the two bursts is dynamically determined by the base station based on the reconfigured central interleaved time slot position, thereby ensuring real-time alignment between physical layer resource allocation and logical layer priority requirements during dynamic system adjustments.

[0067] The mapping mask is a 16-bit binary field, where the first 8 bits correspond to the starting time slot number within the scheduling period, bits 9 to 12 define the transmission mode (e.g., 0001 represents a double-pulse burst), and the last 4 bits define the time slot offset K. When the device detects the double-pulse burst mode, its RF controller immediately executes the first AoA / CS signal transmission after receiving the starting time slot, and calculates the waiting time based on the offset K. This waiting time is equal to K multiplied by the minimum single measurement time. After the counter returns to zero, the second pulse transmission is executed at the middle interleaved time slot of the reconstructed signal, thereby doubling the sampling frequency at the physical layer.

[0068] The confidence level is determined based on the phase standard deviation of five consecutive AoA measurements. When the phase standard deviation exceeds a preset threshold of 15 degrees, the confidence level is considered low. The rapid recalibration process includes: the base station using a reserved Tlast emergency time slot to send 10 calibration packets with fixed phase reference values ​​to the target device; after receiving the packets, the target device calculates the average deviation between the local received phase and the reference phase, and writes it as a compensation bias into the phase register of the RF front end to complete the realignment of the phase reference until the phase standard deviation of subsequent measurements recovers to within 10 degrees.

[0069] This invention achieves a doubling of the sampling frequency of key devices without changing the total cycle length through scheduling vector reconstruction and a physical layer dual-pulse burst mechanism, ensuring millisecond-level real-time response for gesture interactions. Simultaneously, the introduction of quantized confidence determination and an emergency recalibration process effectively combats environmental occlusion interference, significantly improving measurement robustness in dynamic scenarios. Combined with a masking control mechanism, it enables flexible allocation and efficient utilization of air interface resources during multi-node concurrency, maximizing system spectral efficiency and sensing accuracy while ensuring the real-time performance of high-priority services.

[0070] Furthermore, leveraging the physical reciprocity of the wireless channel, the base station simultaneously extracts the uplink frequency deviation characteristics when receiving measurement packets uploaded by the smart wearable device. Based on this deviation, the base station predicts the clock drift trend of the wearable device's crystal oscillator in the next scheduling cycle and carries a frequency pre-compensation value for a specific ID in the control frame. Upon receiving this value, the wearable device fine-tunes the frequency by adjusting its local tuning voltage, ensuring precise alignment between the physical center frequency of the AoA measurement pulse and the base station's receiving bandwidth. This frequency pre-compensation at the base station significantly reduces the phase shift error caused by crystal oscillator temperature drift in inexpensive wearable devices. This mechanism improves frequency synchronization accuracy in dynamic environments without requiring a hardware-compensated crystal oscillator, further ensuring the stability of spatial perception results under high-frequency gesture interaction.

[0071] Furthermore, the mechanism of combining time slot allocation with priority polling includes:

[0072] The base station prioritizes allocating non-overlapping AoA / CS measurement time slots to the high-priority smart wearable devices;

[0073] Within the same priority level, the base station uses a polling method to allocate time slots to smart wearable devices to ensure fair measurement opportunities for smart wearable devices of the same level.

[0074] The base station will allocate the remaining time slot resources within the scheduling period to the low-priority smart wearable device for periodic heartbeat detection.

[0075] When the device is in a low-priority heartbeat detection mode, the six-axis IMU sensor on the wearable device maintains high-frequency (no less than 100Hz) local monitoring. Once the IMU detects that the modulus change rate exceeds a preset static threshold, the device will no longer wait for polling by the base station, but will send a "priority jump request" through contention for access slots, enabling the base station to immediately sense its position change and trigger scheduling vector reconstruction, thereby eliminating the perception delay under low-frequency sampling.

[0076] This invention achieves efficient and fair resource allocation and high real-time response through the synergy of priority polling and IMU triggering mechanisms. Low-priority devices utilize local high-frequency monitoring to compensate for low-frequency air interface sampling, ensuring instantaneous perception of state transitions and eliminating perception latency. While guaranteeing the resource needs of high-priority services, it significantly reduces the overall standby power consumption of the system and substantially improves perception sensitivity and resource scheduling flexibility in multi-device concurrent scenarios.

[0077] Furthermore, the "in-situation gate entry / exit boundary" refers to: the smart wearable device being located within the edge range of a preset distance threshold and an angle threshold, and the continuous ranging residual satisfying the preset switching judgment condition; the "stable state within the in-situ gate" refers to: the smart wearable device being located within the visible sector defined by the distance threshold and the angle threshold, and the rate of change of the six-axis IMU sensor value being lower than the preset static threshold; the "out-of-situation state" and / or "sleep mode" refers to: the smart wearable device being outside the visible sector and / or being in a low-power mode with no displacement and no gesture event triggered within a preset time period.

[0078] This invention achieves accurate identification of device status by combining refined region delineation with multi-dimensional criteria. Utilizing ranging residual judgment and IMU threshold filtering, it effectively avoids logic jitter and false triggering when the device switches between entry and exit boundaries. Simultaneously, based on automatic sensing of departure and sleep modes, it dynamically shuts down unnecessary high-frequency detection tasks, significantly reducing air interface resource usage and terminal RF power consumption. While ensuring spatial perception accuracy, it achieves a dynamic optimal balance between system performance and power consumption control.

[0079] Furthermore, the base station dynamically determines the duration of the scheduling period based on the following dimensions:

[0080] The base station adjusts the scheduling cycle based on the number of smart wearable devices currently establishing connections and sets the minimum measurement duration required for a single device, wherein the scheduling cycle is greater than or equal to the number of smart wearable devices multiplied by the minimum measurement duration;

[0081] When a base station determines that any smart wearable device has entered a high-priority state, the base station switches the measurement frequency of that device from a first preset frequency to a second preset frequency, wherein the second preset frequency is greater than the first preset frequency. At the same time, the base station adjusts the scheduling period to meet the target duration of one-half of the second preset frequency by reducing the proportion of idle time slots of inactive devices within the scheduling period. When the confidence level of continuous measurement results is lower than a preset threshold, the base station increases the number of pulse repetitions for a single AoA / CS measurement and increases the value of the scheduling period by a preset step size until the confidence level recovers to above the preset threshold.

[0082] Specifically, the 'inactive device' is strictly defined in the scheduling algorithm as: a device that is currently in a low-priority queue and has not sent a "Payload non-empty" data packet through contention slots in the past M consecutive scheduling cycles (e.g., M=3).

[0083] When the confidence level of continuous measurement results is lower than a preset threshold, the base station increases the number of pulse repetitions for a single AoA / CS measurement (from 1 to 4-8 times) to improve the signal accumulation gain. Simultaneously, it increases the total value of the scheduling cycle in steps of a single time slot to accommodate the extended single-device occupancy time caused by the increase in the number of pulse repetitions. It sacrifices time resolution to improve spatial perception accuracy in weak signal or strong interference environments until the confidence level is restored.

[0084] This invention ensures the fundamental physical support for resource allocation by establishing a dynamic mapping relationship between the number of devices and the scheduling cycle. It employs a measurement frequency elastic switching mechanism, compressing inactive idle time slots to achieve extremely rapid response for high-priority services. By introducing confidence-based adaptive pulse gain and cycle adjustment logic, it flexibly sacrifices temporal resolution for extremely high reliability in spatial awareness under complex interference environments, achieving a deep dynamic balance between system real-time performance and robustness, significantly improving the user experience when multiple devices are running concurrently.

[0085] Furthermore, the second preset frequency is between 100Hz and 200Hz to meet the real-time requirements of gesture interaction; the first preset frequency is between 20Hz and 25Hz to meet the low power consumption requirements of on-site status monitoring.

[0086] By scientifically setting two frequency ranges, the system accurately matches business scenarios: the high-frequency band ensures millisecond-level zero-latency response for gesture interaction, greatly improving the smoothness of interaction; while the low-frequency band effectively reduces the active proportion of the radio frequency front end, significantly extending the battery life of wearable devices while ensuring basic perception.

[0087] Furthermore, such as Figure 3 As shown, the base station performs the priority polling in the following manner:

[0088] Within the same priority queue, the base station presets the access sequence for each smart wearable device, allocates measurement time slots sequentially according to the access sequence, and automatically jumps to the first device in the sequence for cyclic execution after completing the allocation of the last device in the current sequence.

[0089] When a new smart wearable device jumps to high priority due to triggering gesture interaction and / or entering the presence gate boundary, the base station suspends the current medium and low priority polling progress and inserts the high priority device into the next pending start time slot;

[0090] During the polling process, the base station allocates a higher frequency of polling positions to high-priority devices compared to medium- and low-priority devices; within the scheduling cycle, high-priority devices are polled more often than medium-priority devices, and medium-priority devices are polled more often than low-priority devices.

[0091] The base station will allocate the remaining time slots that are not occupied by high or medium priority devices during the scheduling cycle to devices in the off-site state or dormant mode at the lowest cyclic frequency in order to perform periodic heartbeat connection detection.

[0092] This polling mechanism ensures rapid response for high-priority services and preemptive allocation of resources through differentiated frequency allocation and emergency insertion strategies. At the same time, the round-robin polling ensures access fairness among devices of the same level, effectively balancing the system's real-time response, logical fairness, and long-term connection stability.

[0093] This invention effectively solves the air interface signal collision problem caused by concurrent access of multiple wearable devices by unifying the base station's maintenance and scheduling cycle and adopting a time-domain orthogonal time slot allocation mechanism. By allocating non-overlapping AoA / CS measurement time slots to each device, the exclusivity of the channel probe signal during physical layer transmission is ensured, avoiding measurement data packet loss and retransmission due to co-channel interference, significantly improving the robustness of the wireless link. Simultaneously, combined with dynamic priority allocation based on state and distance information, on-demand resource configuration is achieved, ensuring high-precision spatial awareness while balancing communication efficiency and low power consumption in multi-device environments.

[0094] Example 2

[0095] This embodiment describes a typical smart home living room environment where a base station simultaneously connects to and manages three smart rings worn by a user: smart ring A, smart ring B, and smart ring C. All three devices are miniaturized, power-sensitive wearable nodes, and all possess AoA / CS wireless sensing capabilities.

[0096] In the initial operating state, the user wearing ring A walks and swings their hand normally, approximately 1.5m away from the base station and located in the center of the visible sector. The base station calculates a motion score based on the six-axis IMU data transmitted from ring A, and a position score based on its distance residual. The weighted score P is between 30 and 80, and the base station assigns it to medium priority. Ring B is placed by the user on a stationary coffee table, and its IMU modulus is below 0.05m / s² for 500ms, indicating a stable state, and it is also assigned to medium priority. Ring C is on the user's drooping finger, with no significant movement at the moment, and is also assigned to medium priority.

[0097] When a user suddenly raises the finger wearing ring C to perform an "air click" gesture, ring C's IMU sensor detects a sudden change in modulus. The base station recognizes the gesture interaction event and, regardless of its current location, forcibly elevates ring C to high priority, triggering a scheduling vector reconfiguration. To ensure millisecond-level accuracy in gesture recognition, the base station sends a control message with a mapping mask and a synchronization counter. Device C recognizes the double-pulse burst mode. After the synchronization counter returns to zero, ring C, within a single scheduling cycle, utilizes the existing service time slots and the interleaved time slots released by the reconfiguration to perform two pulse transmissions, causing its measurement frequency to jump from 25Hz to 200Hz, capturing high-frequency dynamic gestures.

[0098] During gesture execution, the user's body or another hand inadvertently obstructs the direct line of sight between ring C and the base station. The base station detects that the standard deviation of the AoA measurement phase of ring C reaches 18 degrees for five consecutive times, exceeding the 15-degree threshold, and determines the confidence level to be low. The base station immediately uses the reserved Tlast emergency time slot at the end of the cycle to send 10 fixed-phase calibration packets to ring C. Ring C calculates the average deviation between the received phase and the reference value and writes the compensation bias into the phase register of its RF front-end. Simultaneously, the base station increases the number of pulse repetitions of ring C to 8 times, and, in conjunction with an increased cycle delay, uses signal accumulation gain to counteract obstruction interference, ensuring that the gesture control logic does not fail due to signal jitter.

[0099] When a user wearing ring A leaves the living room and enters the bedroom, the base station detects a distance exceeding 3.5 meters. Since ring A is outside the visible sector and no gesture trigger is detected, the base station marks it as out of service and moves it to a low-priority circular list. Ring A then enters an extremely low-power mode, performing periodic heartbeat detection only at a frequency of 20Hz. During this low-frequency polling, the IMU sensor inside ring A maintains local monitoring at 100Hz. Once the user wears the ring again and enters the living room, generating valid movement, ring A will send a "priority jump request" through contention for access slots, requesting the base station to reallocate high-frequency measurement resources.

[0100] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for scheduling wireless channel measurement time slots under concurrent use of multiple wearable devices, characterized in that, include: The base station periodically receives and acquires the current application status information of each smart wearable device and / or the distance information between the smart wearable device and the base station, and dynamically assigns each smart wearable device to a preset measurement priority based on the status information and / or distance information. The base station maintains an overall scheduling cycle and determines the total number of measurement time slots required based on the measurement priorities of all smart wearable devices that currently need to perform channel measurements. The base station uses a time slot allocation mechanism combined with priority polling to allocate a non-overlapping AoA / CS measurement time slot to each smart wearable device within the scheduling period; the base station sends the start time and duration of the AoA / CS measurement time slot to each smart wearable device through a wireless control channel. Each of the smart wearable devices transmits an AoA / CS channel measurement signal within the AoA / CS measurement time slot according to the received start time.

2. The wireless channel measurement time slot scheduling method under concurrent multi-wearable device operation according to claim 1, characterized in that, The preset measurement priorities include high priority, medium priority, and low priority, including: When the smart wearable device is at the entrance / exit boundary of the presence gate and / or is performing gesture interaction, it is assigned to the high priority; when the smart wearable device is in a stable state within the presence gate, it is assigned to the medium priority; when the smart wearable device is in an off-site state and / or in sleep mode, it is assigned to the low priority.

3. The wireless channel measurement time slot scheduling method under concurrent multi-wearable device operation according to claim 2, characterized in that: When the number of smart wearable devices is too large, causing the total capacity requirement of the scheduling cycle to exceed the scheduling cycle, the base station reduces the measurement rate of the medium-priority and / or low-priority smart wearable devices to ensure the real-time measurement needs of the high-priority smart wearable devices. When any of the aforementioned smart wearable devices causes the confidence level of continuous measurement results to fall below a preset threshold due to environmental changes and / or occlusion, the base station allocates a reserved emergency time slot for rapid recalibration, and resumes normal time slot scheduling after successful recalibration.

4. The wireless channel measurement time slot scheduling method under concurrent multi-wearable device operation according to claim 3, characterized in that: The time slot allocation, combined with a priority-based round-robin mechanism, includes: The base station prioritizes allocating non-overlapping AoA / CS measurement time slots to the high-priority smart wearable devices; Within the same priority level, the base station uses a polling method to allocate time slots to smart wearable devices to ensure fair measurement opportunities for smart wearable devices of the same level. The base station will allocate the remaining time slot resources within the scheduling period to the low-priority smart wearable devices.

5. The wireless channel measurement time slot scheduling method under multiple wearable devices concurrently according to claim 2, characterized in that: The "on-site gate entry / exit boundary" refers to the following: the smart wearable device is located within the edge range of a preset distance threshold and an angle threshold, and the continuous ranging residual meets the preset switching judgment condition; the "stable state within the on-site gate" refers to the following: the smart wearable device is located within the visible sector defined by the distance threshold and the angle threshold, and the rate of change of the six-axis IMU sensor value is lower than the preset static threshold; the "off-site state" and / or "sleep mode" refers to the following: the smart wearable device is outside the visible sector and / or is in a low-power mode with no displacement and no gesture event triggered within a preset time period.

6. The wireless channel measurement time slot scheduling method under concurrent use of multiple wearable devices according to claim 3, characterized in that, The base station dynamically determines the duration of the scheduling period based on the following dimensions: The base station adjusts the scheduling cycle based on the number of smart wearable devices currently establishing connections and sets the minimum measurement duration required for a single device, wherein the scheduling cycle is greater than or equal to the number of smart wearable devices multiplied by the minimum measurement duration; When the base station determines that any smart wearable device has entered a high-priority state, the base station switches the measurement frequency of the device from a first preset frequency to a second preset frequency, wherein the second preset frequency is greater than the first preset frequency; at the same time, the base station adjusts the scheduling period to meet the target duration of one-half of the second preset frequency by reducing the proportion of idle time slots of inactive devices within the scheduling period. When the confidence level of continuous measurement results is lower than the preset threshold, the base station increases the number of pulse repetitions for a single AoA / CS measurement and increases the value of the scheduling period according to the preset step size until the confidence level recovers to above the preset threshold.

7. The wireless channel measurement time slot scheduling method under concurrent use of multiple wearable devices according to claim 6, characterized in that, The second preset frequency is between 100Hz and 200Hz to meet the real-time requirements of gesture interaction; the first preset frequency is between 20Hz and 25Hz to meet the low power consumption requirements of on-site status monitoring.

8. A method for scheduling wireless channel measurement time slots under concurrent use of multiple wearable devices according to claim 4, characterized in that, The base station performs the priority polling in the following manner: Within the same priority queue, the base station presets the access sequence for each smart wearable device, allocates measurement time slots sequentially according to the access sequence, and automatically jumps to the first device in the sequence for cyclic execution after completing the allocation of the last device in the current sequence. When a new smart wearable device jumps to high priority due to triggering gesture interaction and / or entering the presence gate boundary, the base station suspends the current medium and low priority polling progress and inserts the high priority device into the next pending start time slot; During the polling process, the base station allocates a higher frequency of polling positions to high-priority devices compared to medium- and low-priority devices; Within the scheduling period, high-priority devices are polled more often than medium-priority devices, and medium-priority devices are polled more often than low-priority devices. The base station will allocate the remaining time slots that were not occupied by high or medium priority devices during the scheduling cycle to devices in the off-site state and / or sleep mode in turn at the lowest cyclic frequency.

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