Adaptive random-walk scheduling for BLE beacon transmissions

Abstract

A method for Bluetooth Low Energy (BLE) advertising includes determining, by a controller of a BLE device, a next transmission time for advertising content using a bounded mean-reverting random-walk process. The determination is based on a next drift variable (Δtn+1), a base interval value (T0), and a random jitter component (J). The next drift variable is determined based on a current drift variable (Δtn), a first parameter (λ), a random variable (ξn) and a scaling factor (σ) set to determine a standard deviation. The current drift variable and the next drift variable are constrained within boundaries (-Δmax, Δmax). The method further includes transmitting the advertising content, by a transmitter of the BLE device, autonomously at the next transmission time without external coordination. The bounded mean-reverting random-walk process may provide collision avoidance in dense beacon environments by enabling autonomous desynchronization between multiple BLE devices operating in proximity.

Description

10088-10094ADAPTIVE RANDOM- WALK SCHEDULING FOR BLE BEACON TRANSMISSIONSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority of U.S. Provisional patent Application No. 63 / 716,208, titled Method for Improved Beacon-Based Communication Reliability and Distance, filed November 4, 2024, which is hereby incorporated by reference in its entirety.

[0002] This application claims priority of U.S. Provisional patent Application No. 63 / 716,174, titled Method and System for Suboptimal BLE Beacon Detection in Challenging Environments, filed November 4, 2024, which is hereby incorporated by reference in its entirety.FIELD OF INVENTION

[0003] The present disclosure relates to Bluetooth Low Energy (BLE) communication systems, and more particularly to transmitter-only scheduling mechanisms that autonomously time transmission intervals using a bounded randomwalk process and probabilistic congestion avoidance to improve reliability in dense beacon environments.BACKGROUND

[0004] Bluetooth Low Energy (BLE) technology has become widely adopted for short-range wireless communication applications, particularly in Internet of Things (loT) deployments, asset tracking, and proximity-based services. BLE beacons operate by periodically transmitting advertising packets across three designated advertising channels, allowing nearby receivers to detect their presence and collect transmitted data.

[0005] In conventional BLE implementations, each beacon transmits at a fixed interval with minimal random jitter, typically ranging from 0 to 10 milliseconds between transmission events. This approach works adequately in sparse network environments where few beacons operate within the same communication range. However, as the density of BLE devices increases, particularly in industrial, commercial, and urban environments, the likelihood of simultaneous transmissions from multiple beacons increases substantially.10088-10094

[0006] When multiple beacons transmit simultaneously or with overlapping timing, packet collisions occur on the shared advertising channels. These collisions result in corrupted or lost advertising packets, reducing the reliability of data collection and proximity detection systems. The memoryless nature of conventional BLE advertising timing means that beacons that experience timing overlap may continue to interfere with each other across multiple transmission cycles, forming stable clusters of synchronized devices that persistently collide.

[0007] Dense beacon deployments are becoming increasingly common in various applications, including warehouse management systems, smart building infrastructure, vehicle fleet monitoring, and large-scale asset tracking networks. In such environments, hundreds or even thousands of beacons may operate within overlapping communication ranges, creating substantial challenges for reliable data collection and system performance.

[0008] Traditional approaches to addressing collision issues in dense wireless networks often rely on centralized coordination, receiver-side scheduling, or connection- oriented protocols that require bidirectional communication. However, these solutions introduce additional complexity, increase power consumption, and may not be suitable for simple beacon applications where devices are designed to operate autonomously with minimal computational overhead and extended battery life.

[0009] The challenge of managing transmission timing in dense beacon environments while maintaining the simplicity and low power characteristics of BLE technology represents an ongoing area of development in wireless communication systems.

[0010] Gateway and CRC issues

[0011] Bluetooth Low Energy (BLE) technology has become widely adopted for wireless communication in applications ranging from Internet of Things (loT) devices to location tracking systems. BLE beacons operate by periodically transmitting advertisement packets on designated advertising channels, specifically channels 37, 38, and 39. These advertisement packets contain information such as device identifiers, sensor data, or other payload information that receiving devices can process.10088-10094

[0012] In many deployment scenarios, BLE beacons operate in dense wireless environments where multiple devices compete for the same spectrum resources. Such environments are characterized by high levels of interference, signal fading, and packet collisions that can degrade communication reliability. When BLE advertisement packets experience bit errors due to these environmental factors, the standard BLE protocol employs cyclic redundancy check (CRC) validation to detect corrupted packets. Packets that fail CRC validation are typically discarded by the BLE link layer, making them unavailable to upper protocol layers.

[0013] The loss of advertisement packets in dense environments can substantially reduce the effectiveness of BLE-based systems. Traditional approaches to improving BLE communication reliability include techniques such as channel hopping, retransmission scheduling, and connection-oriented retry mechanisms. However, these approaches generally require modifications to transmitter firmware or changes to BLE stack behavior, which may not be feasible in many deployment scenarios where existing beacon hardware cannot be modified.

[0014] Dense wireless environments present particular challenges for BLE beacon systems because beacons typically operate in a transmit-only mode without establishing connections or implementing retransmission protocols. This operational mode, while power-efficient, provides limited opportunities for error recovery when packets are corrupted during transmission. The standard approach of discarding CRC-failed packets means that potentially recoverable information contained in partially corrupted frames is not utilized.

[0015] Gateway devices that receive BLE advertisements often collect multiple copies of the same advertisement over time, including both valid packets and those that fail CRC validation. These multiple receptions may contain different error patterns due to the varying nature of wireless channel conditions, interference sources, and temporal variations in the communication environment. The availability of multiple packet copies presents opportunities for improving data recovery that are not exploited by conventional BLE processing approaches.SUMMARY10088-10094

[0016] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0017] According to an aspect of the present disclosure, a method for Bluetooth Low Energy (BLE) advertising is provided.

[0018] The method comprises determining, by a controller of a BLE device, a next transmission time for advertising content using a bounded mean-reverting random-walk process and based on a next drift variable (Atn+i), a base interval value (To), and a random jitter component (J). The next drift variable is determined based on a current drift variable (Atn), a first parameter (X), a random variable ( n) and a scaling factor (c) set to determine a standard deviation. The current drift variable and the next drift variable are constrained within boundaries (-Amax, Amax). The method further comprises transmitting the advertising content, by a transmitter of the BLE device, autonomously at the next transmission time without external coordination.

[0019] According to another aspect of the present disclosure, a non-transitory computer-readable medium storing instructions is provided. When executed by a processor of a BLE device, the instructions cause the processor to perform a method comprising determining a next transmission time for advertising content using a bounded mean-reverting random- walk process and based on a next drift variable (Atn+i), a base interval value (To), and a random jitter component (J). The next drift variable is determined based on a current drift variable (Atn), a first parameter (A), a random variable ( n) and a scaling factor (c) set to determine a standard deviation. The current drift variable and the next drift variable are constrained within boundaries (-Amax, Amax). The method further comprises controlling transmission of the advertising content autonomously at the next transmission time without external coordination.

[0020] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.

[0021] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not10088-10094 intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0022] According to an aspect of the present disclosure, a method for recovering Bluetooth Low Energy (BLE) advertising data in a dense wireless environment is provided. The method comprises receiving, by a gateway, and during a period of time, BLE advertising packets associated with a common advertiser identifier. The method comprises applying a cyclic-redundancy-check (CRC) validation process on payloads of the BLE advertising packets and finding faulty BLE advertising packets and non-faulty BLE advertising packets. The method comprises generating a reconstructed payload, based at least on payloads of the faulty BLE advertising packets and a bitwise majority voting process. The method comprises applying the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid. The method comprises outputting by the gateway one or more reconstructed BLE advertising packets having the reconstructed payload.

[0023] According to another aspect of the present disclosure, a gateway system for recovering Bluetooth Low Energy (BLE) advertising data is provided. The gateway system comprises a receiver configured to receive BLE advertising packets associated with a common advertiser identifier during a period of time. The gateway system comprises a memory configured to store the BLE advertising packets. The gateway system comprises a CRC calculator configured to apply a cyclic-redundancy-check (CRC) validation process on payloads of the BLE advertising packets to identify faulty BLE advertising packets and non-faulty BLE advertising packets. The gateway system comprises a payload reconstruction unit configured to generate a reconstructed payload based at least on payloads of the faulty BLE advertising packets and a bitwise majority voting process, wherein the CRC calculator is further configured to apply the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid.

[0024] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform operations is provided. The operations comprise receiving BLE advertising packets associated with a common advertiser10088-10094 identifier during a period of time. The operations comprise applying a cyclic-redundancy- check (CRC) validation process on payloads of the BLE advertising packets to identify faulty BLE advertising packets and non-faulty BLE advertising packets. The operations comprise generating a reconstructed payload based at least on payloads of the faulty BLE advertising packets and a bitwise majority voting process. The operations comprise applying the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid. The operations comprise outputting one or more reconstructed BLE advertising packets having the reconstructed payload.

[0025] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.BRIEF DESCRIPTION OF FIGURES

[0026] Non-limiting and non- exhaustive examples are described with reference to the following figures.

[0027] FIG. 1 illustrates a flowchart of a method for determining and transmitting advertising content in a BLE device, according to aspects of the present disclosure.

[0028] FIG. 2 illustrates a flowchart of a method for BLE advertising with congestion sensing, according to aspects of the present disclosure.

[0029] FIG. 3 illustrates a block diagram of a BLE device and a BLE receiver, according to aspects of the present disclosure.

[0030] FIG. 4 illustrates a system diagram of a BLE communication environment with multiple beacons and a gateway, according to aspects of the present disclosure.

[0031] FIG. 5 illustrates a flowchart of a method for reconstructing BLE advertisement payloads from multiple received packets, according to aspects of the present disclosure.

[0032] FIG. 6 illustrates a flowchart of a process for recovering BLE advertisement packets using majority voting across multiple gateways, according to aspects of the present disclosure.

[0033] FIG. 7 illustrates a flowchart of a method for recovering BLE advertising data in a dense wireless environment, according to aspects of the present disclosure10088-10094DETAILED DESCRIPTIONAdaptive random-walk scheduling for ble beacon transmissions

[0034] The present disclosure relates to an adaptive random-walk scheduling method for Bluetooth Low Energy (BLE) beacon transmissions that addresses collision problems occurring in dense beacon environments. In conventional BLE systems, beacons may transmit advertising packets at fixed intervals with minimal random jitter, which can lead to persistent synchronization and repeated packet collisions when multiple devices operate in proximity. Such collisions may result in packet loss and reduced reliability of proximity or telemetry data collection, particularly in industrial environments where beacon starting times may not follow uniform distribution patterns.

[0035] The adaptive random-walk scheduling method provides autonomous transmitter- only timing control using bounded stochastic processes to mitigate these collision issues. Each BLE beacon may independently determine transmission intervals through a bounded mean-reverting random-walk process that introduces gradual timing drift while maintaining compliance with BLE protocol requirements. The random-walk process may incorporate a drift variable that evolves according to mathematical relationships involving mean-reversion factors, random variables, and scaling parameters, causing beacon transmission phases to gradually separate over time.

[0036] The method may reduce packet collisions and improve communication reliability without requiring external coordination, gateway feedback, or receiver-side scheduling mechanisms. The autonomous nature of the approach allows each beacon to operate independently while contributing to overall network performance improvement through distributed timing optimization. The bounded nature of the random- walk process may ensure that transmission intervals remain within acceptable ranges for BLE compliance while providing sufficient variability to prevent phase-locking between devices.

[0037] In some cases, the method may incorporate additional congestion avoidance mechanisms through energy sensing capabilities that allow beacons to probabilistically skip transmissions when channel congestion is detected. Such enhancements may further reduce overall channel utilization and collision rates in high-density deployment scenarios.10088-10094

[0038] The following sections provide detailed examples and specific implementations of the adaptive random-walk scheduling method, including mathematical formulations, system architectures, and operational procedures for BLE beacon devices implementing the described techniques.

[0039] Referring to FIG. 3, a BLE device 150 may include multiple components configured to implement the adaptive random-walk scheduling method. The BLE device 150 may comprise a controller 151, a transmitter 152, a memory 153, and an energy sensing circuit 154. These components may work together to enable autonomous transmission timing control using the bounded mean-reverting random-walk process described herein.

[0040] The controller 151 may be configured to determine a next transmission time for advertising content using the bounded mean-reverting random-walk process. The controller 151 may base the determination on a next drift variable (Atn+i), a base interval value (To), and a random jitter component (J). The next drift variable may be determined based on a current drift variable (Atn), a first parameter (X), a random variable ( n) and a scaling factor (c) set to determine a standard deviation. In some cases, the current drift variable and the next drift variable may be constrained within boundaries (-Amax, Amax).

[0041] The controller 151 may be configured to multiply (1-X) by the current drift variable (Atn) to provide a first product, multiply the random variable (§n) by the scaling factor (c) to provide a second product, and add the first product to the second product to provide the next drift variable. In some cases, the random variable (§n) may be a zeromean Gaussian random variable. The random jitter component (J) may be drawn from a Gamma distribution.

[0042] Examples of values of X:10088-10094

[0043] The controller 151 may be further configured to enforce a minimum guard interval (8min) between consecutive transmissions to prevent overlap. The controller 151 may also be configured to reflect a value of the next drift variable to a range within the boundaries by an amount equal to a potential out-of-range value when the drift variable exceeds the specified boundaries.

[0044] As further shown in FIG. 3, the transmitter 152 may be configured to transmit the advertising content autonomously at the next transmission time without external coordination. The transmitter 152 may operate under control of the controller 151 to execute transmission events according to the calculated timing intervals. The autonomous operation of the transmitter 152 may eliminate the need for gateway coordination or receiver feedback mechanisms.

[0045] The memory 153 may be configured to store the boundaries (Amax), first parameter (X), and scaling factor (c). The stored parameters may be kept unchanged during normal operation of the BLE device 150, providing consistent operational characteristics for the random-walk process. The memory 153 may provide the controller 151 with access to these parameters during transmission time calculations.

[0046] The energy sensing circuit 154 may be configured to measure received signal strength (RS SI) prior to transmission. The controller 151 may be configured to probabilistically skip transmission when the RS SI exceeds a threshold, providing congestion avoidance capabilities. In some cases, a probability of skipping transmission may be proportional to a level of detected congestion as measured by the energy sensing circuit 154.

[0047] With continued reference to FIG. 3, the BLE device 150 may transmit a message 159 to a BLE receiver 160. The message 159 may contain the advertising content transmitted according to the adaptive timing schedule determined by the controller 151. The BLE receiver 160 may be configured to receive and process messages10088-10094 from multiple instances of the BLE device 150, as indicated by the stacked representation in the diagram.

[0048] In deployment scenarios, the BLE device 150 may be one of 10-10000 BLE devices in a truck that communicate with one or few BLE receivers 160. Such large-scale deployments may benefit from the collision reduction capabilities provided by the adaptive random-walk scheduling method. The autonomous operation of each BLE device 150 may allow the system to scale effectively without requiring centralized coordination mechanisms, making the approach suitable for dense beacon environments where traditional fixed-interval scheduling may result in excessive collision rates.

[0049] Referring to FIG. 1 , a method 100 for Bluetooth Low Energy (BLE) advertising may provide autonomous transmission timing control through a bounded mean-reverting random- walk process. The method 100 may comprise multiple repetitions of determining transmission times and transmitting advertising content, with each repetition corresponding to a transmission cycle for the advertising content.

[0050] The method 100 may include a step 110 for determining a next transmission time for advertising content using the bounded mean-reverting random-walk process. The step 110 may be performed by the controller 151 of the BLE device 150 and may be based on a next drift variable (Atn+i), a base interval value (To), and a random jitter component (J). Anh example of a mathematical formula for determining the next transmission time may be expressed as: Tn+i=Tn+ T0+ Atn+ J

[0051] Other mathematical formulas may be applied.

[0052] In the mathematical formula, Tn+i represents the next transmission time, Tn represents the current transmission time, To represents the base interval value, Atn represents the current drift variable, and J represents the random jitter component. The base interval value (To) may provide a nominal advertising interval that serves as the foundation for transmission timing. The drift variable (Atn) may introduce controlled timing variations that evolve according to the random- walk process. The random jitter component (J) may add short-term variability to prevent synchronization between devices.10088-10094

[0053] As further shown in FIG. 1, the bounded mean-reverting random- walk process may govern the evolution of the drift variable through the mathematical expression: tn+1= (1- )4tn+ ^n

[0054] In this expression, the next drift variable (Atn+i) may be determined based on the current drift variable (Atn), a first parameter (X), a random variable (§n), and a scaling factor (G) set to determine a standard deviation. The first parameter (X) may serve as a mean-reversion factor that controls the tendency of the drift variable to return toward zero, preventing the timing from drifting excessively from the base interval value. The scaling factor (o) may determine the magnitude of random variations introduced at each step of the process.

[0055] The random variable (§n) may be a zero-mean Gaussian random variable that provides the stochastic component of the random-walk process. The zero-mean characteristic may ensure that the random variations do not introduce systematic bias in the timing evolution. The Gaussian distribution may provide appropriate statistical properties for the random-walk behavior while maintaining mathematical tractability.

[0056] With continued reference to FIG. 1, the current drift variable and the next drift variable may be constrained within boundaries (-Amax, Amax). These boundaries may ensure that the drift variable remains within acceptable ranges for BLE protocol compliance while providing sufficient variability to achieve desynchronization between devices. The bounded nature of the process may prevent the transmission intervals from becoming excessively long or short, maintaining compatibility with BLE timing requirements.

[0057] The method 100 may further include a step 120 for transmitting the advertising content. The step 120 may be performed by the transmitter 152 of the BLE device 150 and may involve transmitting the advertising content autonomously at the next transmission time without external coordination. The autonomous transmission may eliminate the need for centralized scheduling, gateway coordination, or receiver feedback mechanisms, allowing each BLE device 150 to operate independently while contributing to overall collision reduction.10088-10094

[0058] The method 100 may be implemented through instructions stored on a non- transitory computer-readable medium that, when executed by a processor of the BLE device 150, cause the processor to perform the described operations. The instructions may cause the processor to determine the next transmission time for advertising content using the bounded mean-reverting random-walk process based on the next drift variable (Atn+i), base interval value (To), and random jitter component (J). The instructions may further cause the processor to control transmission of the advertising content autonomously at the next transmission time without external coordination, providing software-based implementation of the adaptive scheduling method.

[0059] Referring to FIG. 1, the step 110 may comprise detailed computational substeps that implement the bounded mean-reverting random-walk process for determining the next drift variable. The computational process may be divided into discrete mathematical operations that can be executed sequentially by the controller 151 to calculate the next drift variable (Atn+i) from the current drift variable (Atn) and associated parameters.

[0060] As shown in FIG. 1, a step 111 may involve multiplying ( I - A) by the current drift variable (Atn) to provide a first product. The step 111 may represent the meanreversion component of the random- walk process, where the first parameter (X) controls the rate at which the drift variable tends to return toward zero. The multiplication operation may be expressed mathematically as:

[0061] P1= (l-A) x 4tn

[0062] where Pi represents the first product. In some cases, when X = 0.1 and the current drift variable Atn = 50 milliseconds, the first product may be calculated as Pi = (1 - 0.1) x 50 = 0.9 x 50 = 45 milliseconds.

[0063] With continued reference to FIG. 1, a step 112 may involve multiplying the random variable ( n) by the scaling factor (c) to provide a second product. The step 112 may introduce the stochastic component of the random-walk process, where the scaling factor (G) determines the magnitude of random variations added to the drift variable evolution. The multiplication operation may be expressed as:10088-10094

[0064] Where P2 represents the second product. In some cases, when o = 10 milliseconds and the random variable= -0.3 (drawn from a zero-mean Gaussian distribution), the second product may be calculated as P2 = 10 x (-0.3) = -3 milliseconds.

[0065] As further shown in FIG. 1, a step 113 may involve adding the first product to the second product to provide the next drift variable. The step 113 may combine the mean-reversion component from the step 111 with the stochastic component from the step 112 to determine the next drift variable (Atn+i). The addition operation may be expressed as:

[0066] Continuing the numerical example, the next drift variable may be calculated as Atn+i = 45 + (-3) = 42 milliseconds. The resulting value may then be subject to boundary constraints to ensure the next drift variable remains within the specified range (-Amax, Amax).

[0067] The computational sequence of the step 111, the step 112, and the step 113 may be repeated for each transmission cycle to continuously evolve the drift variable according to the bounded mean-reverting random- walk process. The controller 151 may execute these computational steps in sequence, storing intermediate results such as the first product and the second product in temporary memory locations before performing the final addition operation in the step 113.

[0068] In alternative numerical examples, different parameter values may produce varying drift variable evolution patterns. When X = 0.2, o = 15 milliseconds, Atn = -30 milliseconds, and= 0.8, the first product may be calculated as Pi = (1 - 0.2) x (-30) = 0.8 x (-30) = -24 milliseconds. The second product may be calculated as P2 = 15 x 0.8 = 12 milliseconds. The next drift variable may then be determined as Atn+i = -24 + 12 = -12 milliseconds.

[0069] The computational approach implemented through the step 111, the step 112, and the step 113 may provide a systematic method for implementing the bounded meanreverting random-walk process in software or hardware implementations. The discrete nature of the computational steps may facilitate implementation in digital signal processors, microcontrollers, or other computational platforms used in BLE beacon devices. The mathematical operations may be performed using fixed-point or floating-10088-10094 point arithmetic depending on the computational capabilities and precision requirements of the BLE device 150.

[0070] With continued reference to FIG. 1, the method 100 may include additional constraint enforcement mechanisms to ensure proper operation within BLE protocol requirements and maintain the drift variable within specified boundaries. These constraint enforcement mechanisms may be implemented through dedicated processing steps that operate on the calculated drift variable and transmission timing parameters to prevent violations of system limitations.

[0071] As shown in FIG. 1, a step 114 may involve enforcing a minimum guard interval (8min) between consecutive transmissions to prevent overlap. The step 114 may ensure that the calculated transmission intervals comply with BLE timing requirements by establishing a lower bound on the time spacing between consecutive advertising events. The minimum guard interval (5min) may be set to a value that prevents transmission overlap while maintaining compatibility with BLE protocol specifications.

[0072] The step 114 may be performed by the controller 151 after the calculation of the next drift variable in the step 113. The controller 151 may compare the calculated transmission interval against the minimum guard interval (5min) and adjust the timing if the calculated interval falls below the minimum threshold. In some cases, when the sum of the base interval value (To), the drift variable (Atn), and the random jitter component (J) results in an interval shorter than 8min, the controller 151 may extend the transmission interval to meet the minimum guard interval requirement.

[0073] The mathematical implementation of the step 114 may involve a conditional adjustment where the actual transmission interval is set to the maximum of the calculated interval and the minimum guard interval. In some cases, when 8min = 20 milliseconds, To = 100 milliseconds, Atn = -85 milliseconds, and J = 2 milliseconds, the calculated interval may be 100 + (-85) + 2 = 17 milliseconds. Since 17 milliseconds is less than the minimum guard interval of 20 milliseconds, the step 114 may adjust the transmission interval to 20 milliseconds to ensure BLE compliance.

[0074] As further shown in FIG. 1, a step 115 may involve reflecting a value of the next drift variable to a range within the boundaries by an amount equal to a potential out- of-range value. The step 115 may implement boundary enforcement for the drift variable10088-10094 evolution to ensure that the next drift variable (Atn+i) remains within the specified boundaries (-Amax, Amax) even when the random-walk process would otherwise cause the drift variable to exceed these limits.

[0075] The step 115 may be performed by the controller 151 after the calculation of the next drift variable in the step 113 and may operate in parallel with or sequentially after the step 114. The controller 151 may evaluate whether the calculated next drift variable (Atn+i) exceeds the upper boundary (Amax) or falls below the lower boundary (- Amax), and apply reflection operations to bring the drift variable back within the acceptable range.

[0076] For upper boundary violations where Atn+i > Amax, the step 115 may apply a reflection operation. In some cases, when Amax = 200 milliseconds and the calculated next drift variable Atn+i = 250 milliseconds, the reflection operation may yield Atn+i(reflected)= 200 - (250 - 200) = 200 - 50 = 150 milliseconds.

[0077] For lower boundary violations where Atn+i < -Amax, the step 115 may apply a corresponding reflection operation. In some cases, when Amax = 200 milliseconds and the calculated next drift variable Atn+i = -230 milliseconds, the reflection operation may yield Atn+i(reflected)= -200 - (-230 - (-200)) = -200 - (-230 + 200) = -200 - (-30) = -200 + 30 = - 170 milliseconds.

[0078] The reflection mechanism implemented in the step 115 may maintain the statistical properties of the random-walk process while ensuring that the drift variable remains within the specified boundaries. The reflection operation may preserve the energy of the random-walk by redirecting out-of-bounds values back into the acceptable range rather than simply clamping the values at the boundary limits. This approach may prevent the drift variable from becoming stuck at the boundary values and maintain the desired variability in transmission timing.

[0079] The combination of the step 114 and the step 115 may provide comprehensive constraint enforcement for the adaptive random-walk scheduling method. The step 114 may ensure BLE protocol compliance through minimum guard interval enforcement, while the step 115 may maintain the bounded nature of the random- walk process through drift variable reflection. The controller 151 may execute both constraint enforcement steps for each transmission cycle to ensure reliable operation within system10088-10094 limitations while preserving the collision reduction benefits of the adaptive timing approach.

[0080] Referring to FIG. 2, a method 101 for Bluetooth Low Energy (BLE) advertising may extend the method 100 with congestion avoidance capabilities that enable adaptive transmission control based on channel conditions. The method 101 may incorporate energy sensing mechanisms that allow BLE devices to detect channel congestion and probabilistically adjust transmission behavior to reduce overall channel utilization in high-traffic environments.

[0081] The method 101 may include the step 110 for determining a next transmission time for advertising content using the bounded mean-reverting random- walk process, as described in connection with the method 100. The step 110 may provide the foundation for adaptive timing control through the drift variable evolution and boundary enforcement mechanisms that enable autonomous desynchronization between multiple BLE devices operating in proximity.

[0082] As shown in FIG. 2, the method 101 may include a step 130 for measuring received signal strength (RSSI) prior to transmission. The step 130 may be performed by the energy sensing circuit 154 of the BLE device 150 as a micro-sensing operation that provides brief channel assessment before each transmission event. The energy sensing circuit 154 may perform the RSSI measurement over a short time interval to detect the presence of other transmissions or interference sources that may indicate channel congestion conditions.

[0083] The step 130 may involve sampling the received signal strength across one or more of the BLE advertising channels to assess the current level of channel activity. In some cases, the energy sensing circuit 154 may measure RSSI values over a time period of 1-10 milliseconds immediately before the scheduled transmission time to capture recent channel conditions. The measured RSSI values may be compared against a predetermined threshold to determine whether channel congestion is present.

[0084] The micro-sensing operation performed in the step 130 may consume minimal power and time compared to the overall transmission process, allowing the congestion detection mechanism to operate efficiently without significantly impacting the power consumption characteristics of the BLE device 150. The brief nature of the RSSI10088-10094 measurement may enable real-time congestion assessment while maintaining compatibility with the autonomous timing control provided by the bounded meanreverting random-walk process.

[0085] With continued reference to FIG. 2, the method 101 may include a step 132 for applying a probabilistic process to determine whether to skip transmission when the RSSI exceeds a threshold. The step 132 may be performed by the controller 151 based on the RSSI measurements obtained from the energy sensing circuit 154 in the step 130. The probabilistic process may evaluate the measured RSSI values against the predetermined threshold and calculate a probability of skipping the current transmission event based on the level of detected congestion.

[0086] The step 132 may implement a congestion-responsive transmission control mechanism where the probability of skipping transmission may be proportional to the level of detected congestion as indicated by the RSSI measurements. When the measured RSSI values exceed the threshold, the step 132 may calculate a skip probability that increases with higher RSSI levels, providing more aggressive congestion avoidance when channel activity is high and less intervention when channel activity is moderate.

[0087] In some cases, the probabilistic process in the step 132 may use a linear relationship between RSSI levels and skip probability, where the probability of skipping transmission increases linearly with RSSI values above the threshold. For example, when the RSSI threshold is set to -70 dBm and the measured RSSI is -60 dBm, the step 132 may calculate a skip probability of 0.2 (20%). When the measured RSSI increases to -50 dBm, the skip probability may increase to 0.4 (40%), providing stronger congestion avoidance response to higher interference levels.

[0088] As further shown in FIG. 2, the step 132 may lead to two possible outcomes based on the probabilistic determination. When the probabilistic process determines that transmission should be skipped, the method 101 may follow a "Skip" path that terminates the current transmission cycle without executing the step 120. When the probabilistic process determines that transmission should proceed, the method 101 may follow a "Transmit" path that leads to the step 120 for transmitting the advertising content.

[0089] The "Skip" path may provide immediate congestion relief by reducing the number of simultaneous transmissions when channel activity is high. The skipped10088-10094 transmission events may reduce overall channel utilization without requiring coordination between BLE devices, allowing the distributed congestion avoidance mechanism to operate autonomously across multiple devices in dense deployment scenarios.

[0090] The "Transmit" path may lead to the step 120 where the advertising content is transmitted by the transmitter 152 of the BLE device 150 autonomously at the next transmission time without external coordination. The step 120 in the method 101 may operate identically to the step 120 in the method 100, providing the same autonomous transmission capabilities while incorporating the congestion-aware timing control enabled by the step 130 and the step 132.

[0091] The adaptive transmission mechanism implemented through the step 130 and the step 132 may provide significant benefits in high-density deployment scenarios where multiple BLE devices compete for channel access. In some cases, when 500 BLE devices operate in proximity with conventional fixed-interval scheduling, collision rates may exceed 40% during peak transmission periods. The method 101 may reduce collision rates to 25-30% by enabling devices to probabilistically skip transmissions when channel congestion is detected, providing substantial improvement in communication reliability.

[0092] The congestion avoidance capabilities of the method 101 may be particularly beneficial in industrial environments where large numbers of BLE devices may be deployed in confined spaces such as shipping containers, warehouses, or manufacturing facilities. The adaptive transmission control may allow these deployments to maintain acceptable communication performance even when beacon densities reach 1000 devices per coverage area, where conventional approaches may experience excessive collision rates and communication failures.

[0093] The combination of the bounded mean-reverting random-walk process from the method 100 with the congestion sensing capabilities of the method 101 may provide comprehensive collision avoidance that operates on multiple time scales. The randomwalk process may provide long-term desynchronization between devices, while the congestion sensing may provide immediate response to short-term channel congestion events. The dual-mechanism approach may achieve collision reduction performance that exceeds the capabilities of either mechanism operating independently.10088-10094

[0094] The adaptive random-walk scheduling method may provide substantial performance improvements in high-density deployment scenarios where large numbers of BLE beacons operate within overlapping coverage areas. Dense network environments with 200-1000 beacons may present significant challenges for conventional BLE timing approaches, where fixed- interval scheduling with minimal jitter may result in persistent synchronization patterns and excessive collision rates that degrade communication reliability.

[0095] In deployment scenarios involving 200-1000 BLE devices, the bounded mean-reverting random- walk process may achieve a 25-35% decrease in full-event collision rates compared to standard BLE timing mechanisms. The collision reduction may be attributed to the autonomous desynchronization capabilities provided by the evolving drift variable, which may cause beacon transmission phases to gradually separate over multiple transmission cycles. The statistical properties of the random-walk process may ensure that beacons maintain sufficient timing variability to avoid persistent overlaps while remaining within BLE protocol compliance boundaries.

[0096] The performance improvement achieved through the adaptive scheduling method may be particularly pronounced in scenarios where conventional BLE timing approaches experience phase-locking phenomena. Standard BLE operation with fixed intervals and minimal random jitter may allow multiple beacons to synchronize their transmission timing, forming stable clusters of devices that repeatedly transmit simultaneously. The memoryless nature of conventional jitter mechanisms may fail to break these synchronization patterns once they are established, leading to persistent collision clusters that maintain high collision rates over extended periods.

[0097] The bounded mean-reverting random-walk process may prevent phaselocking and stable cluster formation by introducing memory into the timing evolution through the drift variable persistence. The mean-reversion factor (X) may control the balance between timing persistence and randomness, allowing beacons to maintain sufficient correlation between consecutive transmission intervals to gradually drift away from collision patterns while preventing excessive timing deviation that could violate BLE compliance requirements.10088-10094

[0098] The adaptive random-walk scheduling method may be deployed across diverse industrial environments where conventional assumptions about beacon timing distribution may not apply. In industrial settings such as manufacturing facilities, shipping containers, and warehouse operations, BLE beacons may be activated simultaneously during system initialization or power restoration events, creating synchronized starting conditions that violate the uniform distribution assumptions underlying standard BLE timing protocols. These synchronized starting conditions may lead to persistent phase-locking patterns that conventional random jitter mechanisms may be unable to resolve effectively.

[0099] Industrial deployment scenarios may involve hundreds or thousands of BLE beacons operating within confined spaces where electromagnetic interference, metal structures, and dense device populations create challenging communication environments. The bounded mean-reverting random-walk process may provide autonomous desynchronization capabilities that operate effectively in these environments without requiring external coordination infrastructure or centralized timing control systems. The method may maintain BLE protocol compliance while adapting to the non- uniform starting time distributions commonly encountered in industrial applications.

[0100] In manufacturing environments, BLE beacons may be integrated into production equipment, inventory tracking systems, and worker safety monitoring applications where simultaneous system startup may occur during shift changes or equipment maintenance cycles. The adaptive scheduling method may enable these beacons to autonomously establish distributed timing patterns that reduce collision rates and improve data collection reliability for production monitoring and quality control systems.

[0101] The adaptive random-walk scheduling method may find application across multiple industry sectors where dense beacon deployments present communication reliability challenges. In retail environments, the method may be applied to proximity marketing systems, inventory management networks, and customer analytics platforms where hundreds of beacons may operate within shopping centers, department stores, and retail chains. The collision reduction capabilities may improve the accuracy of customer10088-10094 location tracking and product interaction monitoring while maintaining low power consumption characteristics for battery-operated beacon deployments.

[0102] Healthcare applications may benefit from the adaptive scheduling method in hospital asset tracking systems, patient monitoring networks, and medical equipment management platforms. Healthcare facilities may deploy large numbers of BLE beacons for tracking wheelchairs, medical devices, and patient identification systems where communication reliability may be critical for patient safety and operational efficiency. The autonomous timing control may reduce the risk of missed transmissions and improve the responsiveness of emergency alert systems and patient monitoring applications.

[0103] Transportation industry applications may include fleet management systems, cargo tracking networks, and passenger information systems where BLE beacons may be deployed across vehicles, shipping containers, and transportation hubs. The method may improve the reliability of location tracking and telemetry data collection in environments where large numbers of mobile beacons may create dynamic interference patterns. The autonomous operation may be particularly beneficial for applications where centralized coordination infrastructure may be unavailable or impractical to implement.

[0104] Smart city deployments may incorporate the adaptive scheduling method in traffic monitoring systems, environmental sensing networks, and public infrastructure management applications. Urban environments may present dense beacon deployment scenarios where hundreds of devices may operate within overlapping coverage areas across traffic intersections, parking facilities, and public transportation systems. The collision reduction capabilities may improve the accuracy of traffic flow monitoring and environmental data collection while reducing the infrastructure requirements for beacon coordination systems.

[0105] Industrial automation applications may utilize the method in process monitoring systems, equipment tracking networks, and safety management platforms where BLE beacons may be integrated into machinery, tools, and personnel monitoring systems. The autonomous timing control may improve the reliability of real-time data collection for predictive maintenance systems and safety alert mechanisms while maintaining compatibility with existing industrial communication protocols and infrastructure.10088-10094

[0106] Event management applications may deploy the adaptive scheduling method in conference tracking systems, attendee monitoring networks, and venue management platforms where temporary beacon installations may create high-density communication environments. The method may improve the accuracy of attendee location tracking and interaction monitoring during large-scale events where conventional beacon timing approaches may experience excessive collision rates due to simultaneous deployment and activation procedures.

[0107] Educational institution applications may include campus navigation systems, student tracking networks, and facility management platforms where BLE beacons may be deployed across classrooms, laboratories, and common areas. The collision reduction capabilities may improve the reliability of location-based services and attendance monitoring systems while maintaining low power consumption for long-term deployments in educational environments.

[0108] Museum and cultural institution applications may utilize the method in visitor guidance systems, exhibit interaction tracking, and facility management networks where BLE beacons may provide location-based information services and visitor behavior analytics. The adaptive timing control may improve the accuracy of visitor flow monitoring and exhibit engagement tracking while reducing the maintenance requirements for beacon coordination infrastructure.

[0109] The bounded random-walk scheduling approach may be extended and adapted to other wireless communication technologies beyond BLE, demonstrating broader applicability for collision avoidance in dense device deployments. The mathematical principles underlying the mean-reverting random-walk process may be applied to Wi-Fi communication systems where access point coordination and device scheduling may benefit from autonomous timing control mechanisms that reduce channel contention and improve network throughput.

[0110] Wi-Fi applications may incorporate the adaptive scheduling method in dense access point deployments, mesh networking systems, and device-to-device communication scenarios where conventional carrier sense multiple access protocols may experience performance degradation due to hidden node problems and excessive collision rates. The bounded random-walk process may be adapted to control transmission timing10088-10094 for Wi-Fi beacon frames, probe requests, and data transmission scheduling to reduce interference between overlapping networks and improve overall system performance.

[0111] Zigbee protocol implementations may benefit from the adaptive scheduling method in sensor network deployments, home automation systems, and industrial monitoring applications where large numbers of low-power devices may compete for channel access. The autonomous timing control may be adapted to Zigbee superframe structures and beacon scheduling mechanisms to reduce collision rates in dense sensor networks while maintaining compatibility with existing Zigbee protocol specifications and power management requirements.

[0112] The extensibility of the bounded random-walk scheduling approach to multiple wireless technologies may be facilitated by the protocol-agnostic nature of the mathematical framework underlying the method. The drift variable evolution equations, boundary enforcement mechanisms, and congestion sensing capabilities may be adapted to different communication protocols by adjusting the timing parameters, boundary constraints, and transmission scheduling interfaces to match the specific requirements of each wireless technology.

[0113] Internet of Things (loT) communication protocols may incorporate the adaptive scheduling method to address scalability challenges in large-scale device deployments where thousands of connected devices may operate within overlapping coverage areas. The autonomous timing control may provide collision reduction benefits for LoRaWAN networks, cellular loT systems, and proprietary loT protocols where conventional scheduling approaches may experience performance limitations due to device density and interference patterns.

[0114] The broad applicability of the bounded random-walk scheduling approach across multiple wireless technologies and industry applications may position the method as a foundational technique for addressing collision avoidance challenges in dense communication environments. The scalability characteristics of the autonomous timing control may support the growing demands of loT ecosystems where device density and communication reliability requirements continue to increase across diverse application domains.10088-10094

[0115] The following description sets forth exemplary aspects of the present disclosure. It should be recognized, however, that such description is not intended as a limitation on the scope of the present disclosure. Rather, the description also encompasses combinations and modifications to those exemplary aspects described herein.

[0116] Bluetooth Low Energy (BLE) beacon systems face challenges in dense deployment environments where multiple beacons transmit advertising packets simultaneously, leading to packet collisions and reduced communication reliability. Conventional BLE advertising operates with fixed transmission intervals plus small random jitter, which may result in persistent timing overlaps between devices, particularly in industrial environments where beacon starting times are not uniformly distributed.

[0117] The adaptive random-walk scheduling method described herein addresses these collision problems through autonomous transmitter-only timing control. Each BLE beacon independently determines transmission intervals using a bounded mean-reverting random-walk process that introduces gradual timing drift while maintaining compliance with BLE specifications. The bounded stochastic process prevents phase-locking between devices by causing transmission times to evolve independently across multiple beacons in the same environment.

[0118] The method operates without external coordination or receiver feedback, making the approach suitable for large-scale deployments where centralized control may be impractical. Each beacon maintains local timing parameters and updates transmission intervals based on mathematical relationships that incorporate random variables and mean-reversion factors. The autonomous nature of the scheduling eliminates dependencies on gateway coordination or synchronization signals from external sources.

[0119] Packet collision reduction occurs through the gradual desynchronization of beacon transmission phases over time. The bounded random-walk process ensures that beacons do not drift to extremely long or short intervals while providing sufficient variability to break up synchronized transmission patterns. The method may incorporate optional congestion sensing capabilities that allow beacons to probabilistically skip transmissions when channel activity exceeds predetermined thresholds.10088-10094

[0120] Communication reliability improvements result from the reduced likelihood of simultaneous transmissions among multiple beacons. The stochastic timing approach distributes transmission events more evenly across time, decreasing the probability that multiple beacons will attempt to transmit during overlapping time periods. The method maintains BLE compliance through guard intervals and boundary constraints that prevent violations of standard timing requirements.

[0121] Gateway-side majority-voting reconstruction of bluetooth low energy advertisements

[0122] The disclosed approach provides a gateway-side reconstruction method for recovering Bluetooth Low Energy (BLE) advertising data in challenging wireless environments. The system may operate by collecting multiple receptions of BLE advertising packets from the same advertiser, including packets that fail cyclic redundancy check (CRC) validation due to interference, noise, or signal degradation. Rather than discarding corrupted packets as conventional BLE receivers do, the gateway may store and analyze these partially corrupted transmissions to extract useful information.

[0123] The reconstruction process may employ bitwise majority voting techniques to determine the most probable bit values across multiple packet receptions. In some cases, the system aggregates packets received within a defined time window and aligns the bitstreams according to standard BLE packet structure. Each bit position may be evaluated across all collected packets, with the final bit value determined by statistical analysis of the received data. The voting process may incorporate weighting factors based on signal quality metrics such as received signal strength indicator (RS SI), signal-to- noise ratio (SNR), or log-likelihood ratio (LLR) values to improve reconstruction accuracy.

[0124] The gateway-side approach may offer advantages in dense deployment scenarios where multiple BLE beacons operate simultaneously and packet collisions or interference frequently occur. The system may reconstruct valid advertisement payloads without requiring any modifications to existing BLE beacon hardware, firmware, or transmission protocols. In some cases, the reconstruction process maintains full10088-10094 compatibility with standard BLE specifications while enhancing reception reliability through statistical processing of multiple corrupted receptions.

[0125] The reconstructed payload may undergo validation through CRC computation using the standard BLE CRC-24 polynomial. When the computed CRC matches the expected value, the gateway may output the reconstructed packet as a valid advertisement. The process may continue iteratively, collecting additional packet receptions until either a valid reconstruction is achieved, or a predetermined maximum number of attempts is reached. This approach may provide improved detection rates in noisy environments while preserving the existing BLE ecosystem infrastructure.

[0126] Referring to FIG. 4, a BLE communication environment may include multiple BLE beacons configured to transmit advertising packets in a wireless network. The environment may comprise a BLE beacon 201, a BLE beacon 202, and a BLE beacon 203, each of which may transmit wireless signals as indicated by wave symbols emanating from each beacon. The BLE beacons 201, 202, and 203 may transmit BLE advertising packets on specific advertising channels (such as channels 37, 38, and 39) according to standard BLE protocol specifications.

[0127] The BLE beacons 201, 202, and 203 may communicate with a gateway 210 configured to receive and process the transmitted advertising packets. The gateway 210 may include an antenna symbol indicating wireless reception capability for capturing signals from the multiple BLE beacons. In some cases, the gateway 210 may function as a receiver configured to receive BLE advertising packets associated with a common advertiser identifier during a period of time.

[0128] As shown in FIG. 4, the gateway 210 may include several internal components for processing received BLE advertising packets. The gateway 210 may comprise a gateway CRC calculator 211, a gateway memory 212, and a gateway pay load reconstruction unit 213. The gateway memory 212 may be configured to store the BLE advertising packets received from the BLE beacons 201, 202, and 203. In some cases, the gateway CRC calculator 211 may be configured to apply a cyclic-redundancy-check (CRC) validation process on payloads of the BLE advertising packets to identify faulty BLE advertising packets and non-faulty BLE advertising packets.10088-10094

[0129] The gateway CRC calculator 211 and the gateway memory 212 may be connected with bidirectional arrows indicating data exchange between these components. The gateway memory 212 and the gateway payload reconstruction unit 213 may also be connected, with the gateway payload reconstruction unit 213 positioned below the gateway memory 212 in the system architecture. The gateway payload reconstruction unit 213 may be configured to generate a reconstructed payload based at least on pay loads of the faulty BLE advertising packets and a bitwise majority voting process. In some cases, the gateway CRC calculator 211 may be further configured to apply the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid.

[0130] The gateway payload reconstruction unit 213 may be configured to prevent generation of the reconstructed payload when a number of the faulty BLE advertising packets is below a threshold. In some cases, the gateway payload reconstruction unit 213 may be configured to exclude packets from the bitwise majority voting process when the packets have a number of bits that disagree with other packets above a predetermined disagreement limit.

[0131] The voting logic implemented by the gateway payload reconstruction unit 213 may be implemented in software, firmware, or dedicated hardware. The gateway system may operate in real-time or post-processing operation modes depending on the specific application requirements and processing capabilities of the gateway 210.

[0132] With continued reference to FIG. 4, a BLE advertising packet 220 may be structured according to standard BLE protocol specifications and may comprise four sequential fields arranged in a specific order. The BLE advertising packet 220 may represent the data structure transmitted by the BLE beacons 201, 202, and 203 to the gateway 210 during wireless communication.

[0133] The BLE advertising packet 220 may include an access address 221 positioned as the first field in the packet structure. The access address 221 may contain a specific value of 0x8E89BED6, which may serve as a synchronization pattern for BLE receivers to identify and align with incoming advertising packets. In some cases, the access address 221 may provide a standardized identifier that allows receiving devices to10088-10094 distinguish BLE advertising packets from other wireless transmissions operating in the same frequency band.

[0134] Following the access address 221, the BLE advertising packet 220 may include an advertiser address 222 positioned as the second field in the sequential arrangement. The advertiser address 222 may contain identification information that allows receiving devices to associate multiple packet receptions with the same transmitting beacon. In some cases, the advertiser address 222 may enable the gateway 210 to group packets from the same source for aggregation and reconstruction processing.

[0135] The BLE advertising packet 220 may further comprise a payload 223 positioned as the third field following the advertiser address 222. The payload 223 may contain the actual data being transmitted by the BLE beacons, which may include sensor readings, status information, or other application-specific data. In some cases, the payload 223 may represent the primary information content that the gateway payload reconstruction unit 213 seeks to recover through the majority voting process when packets are corrupted during transmission.

[0136] The BLE advertising packet 220 may conclude with a CRC field 224 positioned as the fourth and final field in the packet structure. The CRC field 224 may contain a cyclic redundancy check value computed over the preceding fields of the packet using the standard BLE CRC-24 polynomial. In some cases, the CRC field 224 may enable the gateway CRC calculator 211 to validate the integrity of received packets and determine whether reconstruction efforts have successfully recovered the original transmitted data.

[0137] Referring to FIG. 5, a method 230 may provide a systematic approach for reconstructing valid BLE advertisement payloads from multiple received packets that may include corrupted transmissions. The method 230 may operate through a sequence of processing steps designed to aggregate and analyze multiple packet receptions to recover valid data from partially corrupted BLE advertising packets.

[0138] The method 230 may begin with a step 232 for collecting advertising packets within a configurable aggregation window. The step 232 may involve gathering BLE advertising packets that share the same advertiser address within a defined time period. In10088-10094 some cases, the aggregation window for collecting BLE advertising packets may be configured to a specific time range of 50-20000 milliseconds, allowing the gateway 210 to capture multiple transmissions of the same advertisement data. The step 232 may enable the gateway memory 212 to store multiple receptions of BLE advertising packets associated with a common advertiser identifier during the specified period of time.

[0139] Following packet collection, the method 230 may proceed to a step 234 for aligning the collected packets to ensure consistent bit positions across multiple copies. The step 234 may involve de-whitening and alignment processes applied to the BLE advertising packets to prepare them for statistical analysis. In some cases, the BLE advertising packets may undergo de-whitening and alignment processes to ensure consistent bit positions across copies, removing the whitening sequence applied during BLE transmission and synchronizing the packet structures for accurate bit-by-bit comparison.

[0140] The method 230 may then advance to a step 236 for performing majority voting across the aligned packets to determine the most probable bit value at each position. The step 236 may implement a bitwise majority voting process that analyzes each bit position across all collected packet copies. The majority voting process may be expressed mathematically as bi majority’ bi,k, where a>krepresents weights derived from reliability metrics such as RS SI, SNR, or LLR values, and bi krepresents bit number i in the kth received packet ( where bi kvalues are ±1). The reconstructed bit value may be determined using bL rec= sign b majority), where the sign function returns 1 if the argument is greater than or equal to zero, and returns zero otherwise.

[0141] The step 236 may handle packets with missing or unreliable bits by treating them as erasures and excluding them from the count during majority voting. In some cases, packets may be excluded from majority voting when they have more than an UN AGREEMENT LI MIT of bits that disagree with other packets, allowing the system to filter out transmissions that are too corrupted to contribute meaningfully to the reconstruction process. The maximum number of packet copies processed may be typically set to N = 5-7 packets to balance reconstruction accuracy with processing efficiency.10088-10094

[0142] After the majority voting process, the method 230 may advance to a step 238 for validity checking where a CRC is computed over the reconstructed payload and compared to determine if the reconstruction is valid. The step 238 may involve applying the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid. The CRC validation may use the standard BLE CRC-24 polynomial for computation, ensuring compatibility with standard BLE protocol specifications. In some cases, the reconstructed CRC may be tested against all CRC values of the aggregated packets with a requirement that the computed CRC should agree with more than a certain number of aggregated packets, providing a double qualification process for enhanced validation reliability.

[0143] At the decision point in the step 238, if the validity check indicates that the reconstructed packet is valid, the method 230 may proceed to a step 240 for outputting the reconstructed packet as a valid advertisement. The step 240 may involve outputting by the gateway 210 one or more reconstructed BLE advertising packets having the reconstructed payload. In some cases, the system may provide over 30% improvement in recovery probability compared to conventional BLE reception through this reconstruction approach.

[0144] If the validity check in the step 238 indicates that the packet is not valid, the method 230 may return to the step 232 to collect additional advertising packets for further processing. This iterative nature of the method 230 may allow continued attempts at reconstruction until either a valid payload is recovered or a predetermined termination condition is reached. The method 230 may demonstrate an approach where the bitwise majority voting process is an equal weight bitwise majority voting process, or alternatively may implement a weighted bitwise majority voting process where each bitwise observation is assigned a weight derived from a reliability metric.

[0145] The method 230 may accommodate scenarios where the payloads of the BLE advertising packets are ideally equal to each other during the period of time, enabling the use of a value of the CRC field 224 of one of the non-faulty BLE advertising packets as a reference CRC value during the applying of the CRC validation process on the reconstructed payload. Alternatively, the method 230 may generate a reconstructed CRC10088-10094 based at least on CRC values of the faulty BLE advertising packets and the bitwise majority voting process when the pay loads are expected to remain constant.

[0146] In cases where the pay loads of the BLE advertising packets are variable within the period of time, the method 230 may adapt by using a value of the CRC field 224 of one of the non-faulty BLE advertising packets as a reference CRC value, or by applying the bitwise majority voting process to determine a reference CRC value during the CRC validation process. The method 230 may also accommodate pay load variability by using a value of the CRC field 224 of one of the non-faulty BLE advertising packets and an allowable variability over the period time of the payloads to generate a set of values that represent allowable values of reference CRCs to be used during the CRC validation process.

[0147] Referring to FIG. 6, a process 250 may provide an enhanced approach for recovering BLE advertisement packets using majority voting across multiple gateways in a distributed network architecture. The process 250 may implement a weighted and multi-gateway embodiment where geographically diverse receivers contribute to the reconstruction of corrupted BLE advertising packets. In some cases, the process 250 may exploit spatial diversity to improve independence between bit errors that may occur at different geographic locations due to varying interference patterns, signal propagation conditions, and local noise sources.

[0148] The process 250 may begin with a step 252 for receiving multiple copies of a packet from multiple gateways distributed across different geographic locations. The step 252 may involve collecting BLE advertising packet receptions from a plurality of gateway systems, where each gateway may be positioned at a different physical location to capture the same BLE advertising transmissions under varying channel conditions. In some cases, multiple gateways may forward receptions to a cloud-based aggregator for performing the voting process using geographically diverse receivers, enabling the system to leverage spatial diversity for improved reconstruction accuracy.

[0149] Following the collection of multiple packet copies, the process 250 may proceed to a step 254 for identifying corresponding bits across the received packet copies from the different gateway locations. The step 254 may involve aligning and synchronizing the packet structures received from multiple gateways to ensure that10088-10094 corresponding bit positions are properly matched across all receptions. In some cases, the step 254 may account for timing differences and synchronization variations that may occur when the same BLE advertising packet is received by geographically separated gateway systems.

[0150] The process 250 may then advance to a step 256 for applying weighted majority voting where each packet's contribution depends on signal quality metrics measured at the respective gateway locations. The step 256 may implement a weighted bitwise majority voting process where each packet reception is assigned a weight based on reliability indicators specific to the receiving gateway. In some cases, the bitwise majority voting process may be a weighted bitwise majority voting process where the gateway payload reconstruction unit 213 may be configured to assign to each bitwise observation a weight derived from a reliability metric.

[0151] The weighting factors applied in the step 256 may be derived from various signal quality measurements captured by each participating gateway. In some cases, the reliability metric may be derived from at least one of a received-signal-strength indicator (RSSI), a signal-to-noise ratio (SNR), or a log-likelihood ratio (LLR) measured at each gateway location. The weighted voting approach may enable packets received under better signal conditions to have greater influence on the final bit decisions, while packets received under poor conditions may contribute proportionally less to the reconstruction process.

[0152] After applying the weighted majority voting across all participating gateways, the process 250 may proceed to a step 258 for determining the recovered packet version based on the weighted statistical analysis of all received copies. The step 258 may generate a reconstructed payload by combining the weighted contributions from all gateway locations, producing a final bit sequence that represents the most probable transmitted data based on the collective evidence from multiple receivers.

[0153] The process 250 may conclude with a step 259 for outputting the recovered packet after successful reconstruction through the multi-gateway weighted voting approach. The step 259 may provide the final reconstructed BLE advertising packet that has been validated through CRC checking, similar to the validation process described in the method 230. In some cases, the cloud-based aggregation approach implemented in the10088-10094 process 250 may provide enhanced reconstruction capabilities compared to singlegateway systems by leveraging the statistical independence of errors occurring at different geographic locations.

[0154] The spatial diversity exploited by the process 250 may improve independence between bit errors because interference patterns, multipath fading, and noise characteristics may vary significantly across different geographic locations. This geographic separation may result in different bits being corrupted in packet receptions at different gateways, enabling the weighted majority voting process to recover the original transmitted data even when individual gateway receptions contain multiple bit errors.

[0155] Referring to FIG. 7, a method 300 may provide a comprehensive approach for recovering Bluetooth Low Energy (BLE) advertising data in dense wireless environments through systematic processing of multiple packet receptions. The method 300 may operate through sequential processing steps that enable reconstruction of valid payloads from corrupted BLE advertising transmissions while maintaining compatibility with existing BLE infrastructure.

[0156] The method 300 may begin with a step 302 for receiving, by the gateway 210, BLE advertising packets associated with a common advertiser identifier during a period of time. The step 302 may involve capturing multiple transmissions from the same BLE beacon source within a defined temporal window, allowing the gateway 210 to collect sufficient packet samples for statistical analysis. In some cases, the step 302 may be repeated across multiple periods of time to continuously process BLE advertising data from various beacon sources operating in the wireless environment. The common advertiser identifier may correspond to the advertiser address 222 contained within each BLE advertising packet 220, enabling the gateway 210 to group packets from the same transmitting source for aggregation processing.

[0157] Following packet reception, the method 300 may proceed to a step 304 for applying a cyclic-redundancy-check (CRC) validation process on payloads of the BLE advertising packets and finding faulty BLE advertising packets and non-faulty BLE advertising packets. The step 304 may utilize the gateway CRC calculator 211 to evaluate the integrity of each received packet by computing CRC values using the standard BLE CRC-24 polynomial and comparing the computed values against the CRC field 224 of10088-10094 each packet. In some cases, the step 304 may categorize received packets into two groups: packets that pass CRC validation and are considered non-faulty, and packets that fail CRC validation due to bit errors introduced during wireless transmission and are classified as faulty BLE advertising packets.

[0158] The method 300 may then advance to a step 306 for generating a reconstructed payload based at least on pay loads of the faulty BLE advertising packets and a bitwise majority voting process. The step 306 may employ the gateway payload reconstruction unit 213 to perform statistical analysis across the faulty packet receptions, applying bitwise majority voting techniques to determine the most probable bit values at each position within the packet structure. In some cases, the bitwise majority voting process implemented in the step 306 may be a weighted bitwise majority voting process where each bitwise observation is assigned a weight derived from a reliability metric. The reliability metric may be derived from at least one of a received-signal-strength indicator (RSSI), a signal-to-noise ratio (SNR), or a log-likelihood ratio (LLR) measured during packet reception.

[0159] The step 306 may accommodate various scenarios regarding pay load consistency across the period of time. When the payloads of the BLE advertising packets are ideally equal to each other during the period of time, the step 306 may use a value of the CRC field 224 of one of the non-faulty BLE advertising packets as a reference CRC value during subsequent validation processes. Alternatively, the step 306 may generate a reconstructed CRC based at least on CRC values of the faulty BLE advertising packets and the bitwise majority voting process when payload consistency is expected.

[0160] In cases where the pay loads of the BLE advertising packets are variable within the period of time, the step 306 may adapt the reconstruction approach accordingly. The step 306 may use a value of the CRC field 224 of one of the non-faulty BLE advertising packets as a reference CRC value, or may apply the bitwise majority voting process to determine a reference CRC value during the validation process. In some cases, the step 306 may use a value of the CRC field 224 of one of the non-faulty BLE advertising packets and an allowable variability over the period time of the payloads to generate a set of values that represent allowable values of reference CRCs to be used during subsequent validation processes.10088-10094

[0161] After payload reconstruction, the method 300 may proceed to a step 308 for applying the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid. The step 308 may utilize the gateway CRC calculator 211 to compute a CRC value over the reconstructed payload using the standard BLE CRC-24 polynomial and compare the computed result against the reference CRC value determined during the step 306. In some cases, the step 308 may implement a double qualification process where the computed CRC is tested against all CRC values of the aggregated packets, with a requirement that the computed CRC should agree with more than a certain number of aggregated packets to enhance validation reliability.

[0162] The method 300 may conclude with a step 310 for outputting by the gateway 210 one or more reconstructed BLE advertising packets having the reconstructed pay load. The step 310 may provide the final reconstructed packets when the step 308 determines that the reconstructed payload is valid based on successful CRC validation. In some cases, the step 310 may output reconstructed BLE advertising packets that maintain the original packet structure including the access address 221, the advertiser address 222, the reconstructed payload 223, and the validated CRC field 224.

[0163] The method 300 may implement multiple repetitions of the sequential processing flow across different periods of time to continuously handle BLE advertising data from various beacon sources in the wireless environment. Each repetition of the method 300 may process packets associated with different common advertiser identifiers or may handle subsequent transmissions from previously processed beacon sources. In some cases, the method 300 may prevent generation of the reconstructed payload when a number of the faulty BLE advertising packets is below a threshold, ensuring that sufficient statistical samples are available for reliable reconstruction.

[0164] The method 300 may be implemented through a non-transitory computer- readable storage medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising the steps described above. The computer- readable storage medium may contain program code for receiving BLE advertising packets associated with a common advertiser identifier during a period of time, applying the CRC validation process to identify faulty and non-faulty packets, generating the reconstructed pay load using the bitwise majority voting process, applying CRC10088-10094 validation on the reconstructed payload, and outputting the reconstructed BLE advertising packets. In some cases, the instructions stored on the non-transitory computer-readable storage medium may implement the weighted bitwise majority voting process where each bitwise observation is assigned a weight derived from the reliability metric based on RSSI, SNR, or LLR measurements.

[0165] The BLE beacons may transmit BLE advertising packets wirelessly to the gateway through standard radio frequency communication protocols operating on designated advertising channels. The transmission process may occur at regular intervals determined by the beacon's advertising schedule, with each beacon broadcasting its advertising data across multiple channels to maximize reception probability. In some cases, the BLE beacons may transmit on advertising channels 37, 38, and 39 according to standard BLE specifications, enabling the gateway to receive multiple copies of the same advertisement data across different frequency channels.

[0166] The gateway may capture these wireless transmissions through its antenna system and radio front-end circuitry, which may convert the received radio frequency signals into digital data streams for processing. The gateway may operate continuously to monitor the advertising channels and capture both valid and corrupted packet receptions from multiple BLE beacons operating within its reception range. In some cases, the gateway may timestamp each received packet to enable temporal correlation and grouping of packets from the same advertiser within defined aggregation windows.

[0167] The coordinated operation of the gateway's internal components may enable systematic processing of the received BLE advertising packets through a multi-stage validation and reconstruction pipeline. The gateway memory may serve as the primary storage component for received packets, maintaining both valid and corrupted packet receptions for subsequent analysis. The gateway memory may organize stored packets according to their advertiser identifiers and reception timestamps, enabling efficient retrieval and grouping of related packet receptions during the reconstruction process.

[0168] The gateway CRC calculator may perform initial validation of received packets by computing cyclic redundancy check values over the packet payloads and comparing these computed values against the transmitted CRC fields. The gateway CRC calculator may categorize each received packet as either valid or corrupted based on the10088-10094CRC validation results. In some cases, the gateway CRC calculator may store both the validation results and the computed CRC values in the gateway memory for use during subsequent reconstruction processes.

[0169] When corrupted packets are identified through CRC validation failure, the gateway payload reconstruction unit may retrieve the relevant packet group from the gateway memory for statistical analysis. The gateway payload reconstruction unit may access multiple corrupted packet receptions associated with the same advertiser identifier and apply bitwise majority voting algorithms to determine the most probable bit values at each position within the packet structure. The reconstruction process may involve iterative analysis of the stored packet data, with the gateway payload reconstruction unit coordinating with the gateway memory to access additional packet receptions as needed.

[0170] The gateway payload reconstruction unit may implement filtering mechanisms to exclude packets that are too corrupted to contribute meaningfully to the reconstruction process. The filtering may involve analyzing the degree of disagreement between individual packets and the collective group, removing packets that exceed predetermined disagreement thresholds. In some cases, the gateway payload reconstruction unit may dynamically adjust the reconstruction parameters based on the quality and quantity of available packet receptions stored in the gateway memory.

[0171] Following the majority voting process, the gateway payload reconstruction unit may generate a reconstructed payload and coordinate with the gateway CRC calculator to validate the reconstruction results. The gateway CRC calculator may compute a new CRC value over the reconstructed payload and compare this computed value against reference CRC values to determine reconstruction validity. The validation process may involve multiple comparison operations, including verification against CRC values from non-corrupted packets and statistical analysis of CRC agreement across the packet group.

[0172] The system may operate in real-time processing mode where packet reception, validation, and reconstruction occur continuously as BLE advertising packets are received from the wireless environment. Real-time operation may enable immediate processing of corrupted packets and rapid output of reconstructed advertisements with minimal latency. The real-time mode may be suitable for applications requiring10088-10094 immediate response to BLE advertising data or time-sensitive processing of beacon transmissions.

[0173] Alternatively, the system may operate in post-processing mode where received packets are stored for batch analysis during designated processing intervals. Post-processing operation may enable more comprehensive statistical analysis by allowing the system to collect larger groups of packet receptions before initiating the reconstruction process. In some cases, post-processing mode may provide enhanced reconstruction accuracy by enabling analysis of extended packet collections and more sophisticated filtering of corrupted receptions.

[0174] The coordinated operation of the gateway components may achieve over 30% improvement in recovery probability compared to conventional BLE reception systems that discard corrupted packets. This improvement may result from the statistical advantage gained by analyzing multiple corrupted receptions rather than relying solely on individual packet validation. The majority voting approach may recover valid data even when individual packet receptions contain multiple bit errors, provided that the errors occur at different bit positions across the collected packet group.

[0175] The enhanced recovery performance may be achieved without requiring any modifications to beacon transmitters or BLE protocol parameters. The BLE beacons may continue operating according to standard advertising schedules and packet formats, with no changes to transmission timing, power levels, or data encoding. The gateway-side processing approach may maintain full compatibility with existing BLE infrastructure while providing improved reception reliability through statistical analysis of multiple packet receptions.

[0176] The system may adapt to varying environmental conditions and interference patterns by adjusting the aggregation window duration and the number of packet receptions included in each reconstruction attempt. Dynamic parameter adjustment may enable the system to balance reconstruction accuracy with processing latency based on the current wireless environment conditions. In some cases, the system may monitor reconstruction success rates and automatically optimize processing parameters to maintain performance across different deployment scenarios.10088-10094

[0177] A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.

[0178] Because some aspects of the illustrated embodiments of the present disclosure may, for the most part, be implemented using electronic components and circuits known to those skilled in the art, details will not be explained in any greater extent than that considered necessary as illustrated above, for the understanding and appreciation of the underlying concepts of the present invention and in order not to obfuscate or distract from the teachings of the present invention.

[0179] Any combination of any steps of any method illustrated in the specification and / or drawings may be provided. Any combination of any subject matter of any of claims may be provided. Any combinations of systems, units, components, processors, sensors, illustrated in the specification and / or drawings may be provided. Any combination of any module or unit listed in any of the figures, any part of the specification and / or any claims may be provided.

[0180] Any reference in the specification to a method should be applied mutatis mutandis to a device or system capable of executing the method and / or to a non- transitory computer readable medium that stores instructions for executing the method. Any reference in the specification to a system or device should be applied mutatis mutandis to a method that may be executed by the system, and / or may be applied mutatis mutandis to non-transitory computer readable medium that stores instructions executable by the system.

[0181] Any reference in the specification to a non-transitory computer readable medium should be applied mutatis mutandis to a device or system capable of executing instructions stored in the non-transitory computer readable medium and / or may be applied mutatis mutandis to a method for executing the instructions.

[0182] In the foregoing specification, the invention has been described with reference to specific examples of embodiments of the invention. It will, however, be evident that various modifications and changes may be made therein without departing from the broader spirit and scope of the invention as set forth in the appended claims. The10088-10094 specifications and drawings are, accordingly, to be regarded in an illustrative rather than in a restrictive sense.

[0183] Those skilled in the art will recognize that the boundaries between logic blocks are merely illustrative and that alternative embodiments may merge logic blocks or circuit elements or impose an alternate decomposition of functionality upon various logic blocks or circuit elements. Thus, it is to be understood that the architectures depicted herein are merely exemplary, and that in fact many other architectures may be implemented which achieve the same functionality.

[0184] Those skilled in the art will recognize that boundaries between the abovedescribed operations merely illustrative. The multiple operations may be combined into a single operation, a single operation may be distributed in additional operations and operations may be executed at least partially overlapping in time. Moreover, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be altered in various other embodiments.

[0185] Any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality may be seen as "associated with" each other such that the desired functionality is achieved, irrespective of the underlying architecture or intermedial components. Likewise, any two components so associated can also be viewed as being "operably connected," or "operably coupled," to each other to achieve the desired functionality.

[0186] It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference numerals may be repeated among the figures to indicate corresponding or analogous elements.

[0187] In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word ‘comprising’ does not exclude the presence of other elements or steps then those listed in a claim. Furthermore, the terms “a” or “an,” as used herein, are defined as one or more than one. Also, the use of introductory phrases such as “at least one” and “one or more” in the claims should not be construed to imply10088-10094 that the introduction of another claim element by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim element to inventions containing only one such element, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an." The same holds true for the use of definite articles. Unless stated otherwise, terms such as “first" and “second” are used to arbitrarily distinguish between the elements such terms describe. Thus, these terms are not necessarily intended to indicate temporal or other prioritization of such elements. The mere fact that certain measures are recited in mutually different claims does not indicate that a combination of these measures cannot be used to advantage.

[0188] It is appreciated that various features of the embodiments of the disclosure which are, for clarity, described in the contexts of separate embodiments may also be provided in combination in a single embodiment. Conversely, various features of the embodiments of the disclosure which are, for brevity, described in the context of a single embodiment may also be provided separately or in any suitable sub-combination.

[0189] It will be appreciated by persons skilled in the art that the embodiments of the disclosure are not limited by what has been particularly shown and described hereinabove. Thus, the scope of the embodiments of the disclosure is defined by the appended claims and equivalents thereof. While certain features of the disclosure have been illustrated and described herein, many modifications, substitutions, changes, and equivalents will now occur to those of ordinary skill in the art. It is therefore to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.

Claims

10088-10094CLAIMS1. A method for Bluetooth Low Energy (BLE) advertising, comprising: determining, by a controller of a BLE device, a next transmission time for advertising content using a bounded mean-reverting random-walk process and based on a next drift variable (At_n+1), a base interval value (TO), and a random jitter component (J), the next drift variable being determined based on a current drift variable (At_n), a first parameter (X), a random variable (c,_n ) and a scaling factor (c) set to determine a standard deviation; wherein the current drift variable and the next drift variable are constrained within boundaries (-A max, A max); and transmitting the advertising content, by a transmitter of the BLE device, autonomously at the next transmission time without external coordination.

2. The method of claim 1, wherein the determining comprises: multiplying ( I -A) by the current drift variable (At_n) to provide a first product; multiplying the random variable (c,_n) by the scaling factor (o) to provide a second product; and adding the first product to the second product to provide the next drift variable.

3. The method of claim 2, wherein the random variable (c,_n) is a zero-mean Gaussian random variable.

4. The method of claim 2, wherein the random jitter component (J) is drawn from a Gamma distribution.

5. The method of claim 1, further comprising enforcing a minimum guard interval (8_min) between consecutive transmissions to prevent overlap.

6. The method of claim 1, comprising reflecting a value of the next drift variable to a range within the boundaries by an amount equal to a potential out-of-range value.

7. The method of claim 1 , wherein the boundaries (A max), first parameter (X), and scaling factor (c) are stored in a memory of the BLE device and are kept unchanged during a normal operation of the BLE device.

8. The method of claim 1, further comprising measuring, by an energy sensing circuit of the BLE device, received signal strength (RS SI) prior to transmission and probabilistically skipping transmission when the RS SI exceeds a threshold.10088-100949. The method of claim 8, wherein a probability of skipping transmission is proportional to a level of detected congestion.

10. A BLE device, comprising: a controller configured to determine a next transmission time for advertising content using a bounded mean-reverting random-walk process and based on a next drift variable (At_n+1), a base interval value (TO), and a random jitter component (J), the next drift variable being determined based on a current drift variable (At_n), a first parameter (X), a random variable ( c,_n ) and a scaling factor (G) set to determine a standard deviation; wherein the current drift variable and the next drift variable are constrained within boundaries (-A max, A max); and a transmitter configured to transmit the advertising content autonomously at the next transmission time without external coordination.

11. The BLE device of claim 10, wherein the controller is configured to: multiply (1- X) by the current drift variable (At_n) to provide a first product; multiply the random variable (c,_ n) by the scaling factor (o) to provide a second product; and add the first product to the second product to provide the next drift variable.

12. The BLE device of claim 11, wherein the random variable (c,_n) is a zero-mean Gaussian random variable.

13. The BLE device of claim 11, wherein the random jitter component (J) is drawn from a Gamma distribution.

14. The BLE device of claim 10, wherein the controller is further configured to enforce a minimum guard interval (8_min) between consecutive transmissions to prevent overlap.

15. The BLE device of claim 10, wherein the controller is configured to reflect a value of the next drift variable to a range within the boundaries by an amount equal to a potential out-of-range value.

16. The BLE device of claim 10, further comprising a memory configured to store the boundaries (A max), first parameter (X), and scaling factor (c), wherein the stored parameters are kept unchanged during a normal operation of the BLE device.

17. The BLE device of claim 10, further comprising an energy sensing circuit configured to measure received signal strength (RS SI) prior to transmission, wherein the10088-10094 controller is configured to probabilistically skip transmission when the RS SI exceeds a threshold.

18. The BLE device of claim 17, wherein a probability of skipping transmission is proportional to a level of detected congestion.

19. A non-transitory computer-readable medium storing instructions that, when executed by a processor of a BLE device, cause the processor to perform a method comprising: determining a next transmission time for advertising content using a bounded mean-reverting random- walk process and based on a next drift variable (At_n+1), a base interval value (TO), and a random jitter component (J), the next drift variable being determined based on a current drift variable (At_n), a first parameter (X), a random variable (c,_ n )and a scaling factor (c) set to determine a standard deviation; wherein the current drift variable and the next drift variable are constrained within boundaries (-A max, A max); and controlling transmission of the advertising content autonomously at the next transmission time without external coordination.

20. The non-transitory computer-readable medium of claim 19, wherein the determining comprises: multiplying ( 1 -A) by the current drift variable (At_n) to provide a first product; multiplying the random variable (c,_n ) by the scaling factor (o) to provide a second product; and adding the first product to the second product to provide the next drift variable.

21. A method for recovering Bluetooth Low Energy (BLE) advertising data in a dense wireless environment, comprising: receiving, by a gateway, and during a period of time, BLE advertising packets associated with a common advertiser identifier; applying a cyclic-redundancy-check (CRC) validation process on payloads of the BLE advertising packets and finding faulty BLE advertising packets and non-faulty BLE advertising packets; generating a reconstructed payload, based at least on payloads of the faulty BLE advertising packets and a bitwise majority voting process; applying the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid; and outputting by the gateway one or more reconstructed BLE advertising packets having the reconstructed payload.

22. The method according to claim 21, wherein the bitwise majority voting process is an equal weight bitwise majority voting process.10088-1009423. The method according to claim 21, wherein the payloads of the BLE advertising packets are ideally equal to each other during the period of time, and wherein the method comprises using a value of a CRC field of one of the non-faulty BLE advertising packets as a reference CRC value during the applying of the CRC validation process on the reconstructed payload.

24. The method according to claim 21, wherein the payloads of the BLE advertising packets are ideally equal to each other during the period of time, and wherein the method comprises generating a reconstructed CRC, based at least on CRC values of the faulty BLE advertising packets and the bitwise majority voting process.

25. The method according to claim 21, wherein the payloads of the BLE advertising packets are variable within the period of time, and wherein the method comprises using a value of a CRC field of one of the non-faulty BLE advertising packets as a reference CRC value during the applying of the CRC validation process on the reconstructed payload.

26. The method according to claim 21, wherein the payloads of the BLE advertising packets are variable within the period of time, and wherein the method comprises using a value of a CRC field of one of the non-faulty BLE advertising packets and an allowable variability over the period time of the payloads to generate a set of values that represent allowable values of reference CRCs to be used during the applying of the CRC validation process on the reconstructed payload.

27. The method according to claim 21, wherein the payloads of the BLE advertising packets are variable within the period of time, and wherein the method comprises applying the bitwise majority voting process to determine a reference CRC value during the applying of the CRC validation process on the reconstructed payload.

28. The method according to claim 21, comprising preventing from generating the reconstructed payload when a number of the faulty BLE advertising packets is below a threshold.

29. The method according to claim 1, wherein the bitwise majority voting process is a weighted bitwise majority voting process.

30. The method of claim 29, wherein each bitwise observation is assigned a weight derived from a reliability metric.10088-1009431. The method of claim 30, further comprising generating the reliability metric based on consistency of bit decisions.

32. The method of claim 29, wherein weights of the weighted bitwise majority voting process are derived from at least one of a received-signal-strength indicator (RSSI), a signal-to-noise ratio (SNR), or a log-likelihood ratio (LLR).

33. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to perform operations comprising: receiving BLE advertising packets associated with a common advertiser identifier during a period of time; applying a cyclic-redundancy-check (CRC) validation process on pay loads of the BLE advertising packets to identify faulty BLE advertising packets and non-faulty BLE advertising packets; generating a reconstructed payload based at least on pay loads of the faulty BLE advertising packets and a bitwise majority voting process; applying the CRC validation process on the reconstructed payload to determine whether the reconstructed payload is valid; and outputting one or more reconstructed BLE advertising packets having the reconstructed payload.

34. The non-transitory computer-readable storage medium of claim 33, wherein the bitwise majority voting process is a weighted bitwise majority voting process.

35. The non-transitory computer-readable storage medium of claim 34, wherein each bitwise observation is assigned a weight derived from a reliability metric.

36. The non-transitory computer- readable storage medium of claim 35, wherein the reliability metric is derived from at least one of a received-signal-strength indicator (RSSI), a signal-to-noise ratio (SNR), or a log-likelihood ratio (LLR).

37. The non-transitory computer- readable storage medium of claim 33, wherein the operations further comprise preventing generation of the reconstructed payload when a number of the faulty BLE advertising packets is below a threshold.

38. The non-transitory computer-readable storage medium of claim 33, wherein the payloads of the BLE advertising packets are ideally equal to each other during the period of time, and wherein the operations comprise using a value of a CRC field of one of the non-faulty BLE advertising packets as a reference CRC value during the applying of the CRC validation process on the reconstructed payload.10088-1009439. The non-transitory computer- readable storage medium of claim 33, wherein the payloads of the BLE advertising packets are variable within the period of time, and wherein the operations comprise applying the bitwise majority voting process to determine a reference CRC value during the applying of the CRC validation process on the reconstructed payload.

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