Smart home network communication method and apparatus, electronic device, and readable storage medium

Abstract

Embodiments of the present application provide a smart home network communication method and device, electronic equipment and readable storage medium, wherein the smart home devices in the smart home network communicate based on channels in the smart home network, and the method comprises: determining channel usage of channels in a specified channel range in the smart home network; collecting device information of the smart home devices in the smart home network; selecting a target channel from the channels according to the channel usage and the device information; performing channel aggregation on the target channel to form an aggregated channel; and controlling the smart home devices in the smart home network to communicate through the aggregated channel. Embodiments of the present application can improve the throughput of the smart home network.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of Internet of Things (IoT) technology, and in particular to a smart home network communication method, a smart home network communication device, an electronic device, and a computer-readable storage medium. Background Technology

[0002] With the development of Internet of Things (IoT) technology, the types and number of smart home devices are constantly increasing, including smart light bulbs, door locks, cameras, sensors, speakers, and other smart home devices. These smart home devices require stable and high-speed network connections to achieve real-time data transmission, device control, and automated services. As a result, smart home networks are facing increasingly higher data transmission demands and more complex network management challenges.

[0003] To improve data transmission rates and network capacity, channel aggregation technology has been proposed. Channel aggregation allows multiple independent channels to be combined into a wider channel through software configuration or hardware design. However, the decision-making process for channel aggregation in smart home networks is currently imperfect, making it difficult to select suitable channels from the smart home network's channels for aggregation, thereby failing to improve the network's throughput based on the aggregated channels. Summary of the Invention

[0004] This invention provides a smart home network communication method, device, electronic device, and computer-readable storage medium to address the problem that the decision-making process for channel aggregation in smart home networks is currently imperfect, resulting in the inability to select suitable channels from the smart home network channels for aggregation to form aggregated channels, thereby improving the throughput of the smart home network based on aggregated channels.

[0005] This invention discloses a smart home network communication method, wherein smart home devices in the smart home network communicate based on channels in the smart home network, and the method includes:

[0006] Determine the channel usage status of channels within a specified channel range in the smart home network;

[0007] Collect device information of smart home devices in the smart home network;

[0008] Target channels are selected from the channels based on the channel usage and the device information;

[0009] The target channels are aggregated to form aggregated channels;

[0010] The system controls smart home devices in the smart home network to communicate through the aggregation channel.

[0011] Optionally, the step of filtering target channels from the channels based on channel usage and device information includes:

[0012] Candidate channels are selected from the channels based on the channel usage data;

[0013] The target channel is selected from the candidate channels based on the device information.

[0014] Optionally, the step of filtering candidate channels from the channel based on the channel usage includes:

[0015] Determine the channel selection parameters used to filter the channels;

[0016] Candidate channels are selected from the channels based on the channel selection parameters and the channel usage.

[0017] Optionally, determining the channel selection parameters used to filter the channels includes:

[0018] Obtain channel information of the channel in the smart home network; the channel information includes at least the interference situation, signal strength and compatibility with the smart home devices of the channel;

[0019] Based on the channel information, channel selection parameters for the channel in the smart home network are determined; wherein the channel selection parameters include at least the channel state information, signal-to-noise ratio, channel interference, bandwidth, channel utilization, and latency thresholds for the channel.

[0020] Optionally, the channel usage information includes at least the current channel state information and the current signal-to-noise ratio of the channel; the step of filtering candidate channels from the channel based on the channel usage information includes:

[0021] Channels whose current channel state information reaches a threshold and whose current signal-to-noise ratio reaches a threshold are selected as candidate channels.

[0022] Optionally, the channel usage information includes at least the channel's current channel interference, current bandwidth, current channel utilization, and current latency; the step of filtering candidate channels from the channel based on the channel usage information includes:

[0023] The data transmission rate of the channel is determined based on the current channel state information, the current signal-to-noise ratio, the current channel interference, the current bandwidth, the current channel utilization, and the current delay.

[0024] Channels whose data transmission rate exceeds a preset data transmission rate are selected as candidate channels.

[0025] Optionally, the device information includes at least the signal strength information, device type, and data transmission requirements of the smart home device for each of the channels; the step of filtering the target channel from the candidate channels based on the device information includes:

[0026] The signal strength information, device type, and data transmission requirements are input into a preset network demand prediction model to obtain the usage pattern and traffic model of the smart home device; wherein, the usage pattern is used to characterize the activity status of the smart home device in various time periods in the future, and the traffic model is used to characterize the data transmission volume of the smart home device in various time periods in the future.

[0027] Target channels are selected from the candidate channels based on the usage pattern and the traffic model.

[0028] Optionally, after controlling the smart home devices in the smart home network to communicate through the aggregation channel, the method further includes:

[0029] Monitor the network status of the smart home network;

[0030] Based on the network status, determine whether to re-determine the new channel selection parameters used to filter the channels;

[0031] A new target channel is selected from the channels based on the new channel selection parameters;

[0032] The new target channel is aggregated to form a new aggregated channel;

[0033] Control the smart home devices in the smart home network to communicate through the new aggregation channel.

[0034] Optionally, the network status includes at least whether a new source of interference has been detected, and determining whether to re-determine new channel selection parameters for filtering the channel based on the network status includes:

[0035] If a new source of interference is detected in the smart home network, new channel selection parameters for filtering the channels are determined.

[0036] This invention also discloses a smart home network communication device, wherein smart home devices in the smart home network communicate based on channels in the smart home network, and the device includes:

[0037] The channel usage determination module is used to determine the channel usage of channels within a specified channel range in the smart home network.

[0038] The device information acquisition module is used to collect device information of smart home devices in the smart home network;

[0039] The target channel filtering module is used to filter target channels from the channels based on the channel usage and the device information;

[0040] The channel aggregation module is used to aggregate the target channels to form aggregated channels;

[0041] The device communication module is used to control smart home devices in the smart home network to communicate through the aggregation channel.

[0042] Optionally, the target channel filtering module is used to:

[0043] Candidate channels are selected from the channels based on the channel usage data;

[0044] The target channel is selected from the candidate channels based on the device information.

[0045] In one embodiment of the present invention, the target channel filtering module is configured to:

[0046] Determine the channel selection parameters used to filter the channels;

[0047] Candidate channels are selected from the channels based on the channel selection parameters and the channel usage.

[0048] Optionally, the target channel filtering module is used to:

[0049] Obtain channel information of the channel in the smart home network; the channel information includes at least the interference situation, signal strength and compatibility with the smart home devices of the channel;

[0050] Based on the channel information, channel selection parameters for the channel in the smart home network are determined; wherein the channel selection parameters include at least the channel state information, signal-to-noise ratio, channel interference, bandwidth, channel utilization, and latency thresholds for the channel.

[0051] Optionally, the channel usage information includes at least the current channel state information and the current signal-to-noise ratio of the channel; the target channel filtering module is used for:

[0052] Channels whose current channel state information reaches a threshold and whose current signal-to-noise ratio reaches a threshold are selected as candidate channels.

[0053] Optionally, the channel usage information includes at least the channel's current channel interference, current bandwidth, current channel utilization, and current latency; the target channel filtering module is used to:

[0054] The data transmission rate of the channel is determined based on the current channel state information, the current signal-to-noise ratio, the current channel interference, the current bandwidth, the current channel utilization, and the current delay.

[0055] Channels whose data transmission rate exceeds a preset data transmission rate are selected as candidate channels.

[0056] Optionally, the device information includes at least the signal strength information, device type, and data transmission requirements of the smart home device for each of the channels; the target channel filtering module is used for:

[0057] The signal strength information, device type, and data transmission requirements are input into a preset network demand prediction model to obtain the usage pattern and traffic model of the smart home device; wherein, the usage pattern is used to characterize the activity status of the smart home device in various time periods in the future, and the traffic model is used to characterize the data transmission volume of the smart home device in various time periods in the future.

[0058] Target channels are selected from the candidate channels based on the usage pattern and the traffic model.

[0059] Optionally, the device further includes: an update module, configured to:

[0060] Monitor the network status of the smart home network;

[0061] Based on the network status, determine whether to re-determine the new channel selection parameters used to filter the channels;

[0062] A new target channel is selected from the channels based on the new channel selection parameters;

[0063] The new target channel is aggregated to form a new aggregated channel;

[0064] Control the smart home devices in the smart home network to communicate through the new aggregation channel.

[0065] Optionally, the network status includes at least whether a new interference source has been detected, and the update module is used to:

[0066] If a new source of interference is detected in the smart home network, new channel selection parameters for filtering the channels are determined.

[0067] This invention also discloses an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0068] The memory is used to store computer programs;

[0069] When the processor executes a program stored in the memory, it implements the method described in the embodiments of the present invention.

[0070] This invention also discloses a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in this invention.

[0071] This invention also discloses a computer-readable storage medium storing instructions that, when executed by one or more processors, cause the processors to perform the methods described in this invention.

[0072] The embodiments of the present invention have the following advantages:

[0073] In this embodiment of the invention, smart home devices in a smart home network communicate based on channels within the smart home network. During communication, the channel usage within a specified channel range in the smart home network is determined, and device information of the smart home devices in the network is collected. Based on the channel usage and device information, target channels are selected from the channels, and these target channels are aggregated to form aggregated channels. This allows control over communication between smart home devices in the smart home network through these aggregated channels. This embodiment of the invention can select target channels from multiple channels based on channel usage and device information, choosing those with superior performance and suitability for smart home devices, such as those that are underutilized or have less interference. Communication can then be performed using the aggregated channels formed by aggregating these target channels. Since smart home devices can communicate through aggregated channels, the throughput of the smart home network can be increased, supporting simultaneous high-speed communication by more smart home devices. Attached Figure Description

[0074] Figure 1 This is a flowchart illustrating the steps of a smart home network communication method provided in an embodiment of the present invention;

[0075] Figure 2 This is a schematic diagram of a smart home network optimization method provided in an embodiment of the present invention;

[0076] Figure 3 This is a structural block diagram of a smart home network communication device provided in an embodiment of the present invention;

[0077] Figure 4 This is a schematic diagram of the hardware structure of an electronic device that implements various embodiments of the present invention. Detailed Implementation

[0078] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0079] Reference Figure 1 This diagram illustrates a flowchart of a smart home network communication method provided in an embodiment of the present invention. The smart home devices in the smart home network communicate based on channels within the smart home network, and the method may specifically include the following steps:

[0080] Step 101: Determine the channel usage status of channels within the specified channel range in the smart home network.

[0081] In practical implementation, the Internet of Things (IoT) can include smart home networks. Smart home devices in these networks can include smart light bulbs, door locks, cameras, sensors, speakers, air conditioners, fans, refrigerators, rice cookers, water heaters, etc. These smart home devices can interconnect through wireless communication technologies such as Wi-Fi (Wireless Fidelity), Bluetooth, and cellular networks. Smart home devices typically communicate using channels in the range of 2.4 GHz to 10.6 GHz.

[0082] The specified channel range can be channels within the range of 2.4 GHz to 10.6 GHz. In this embodiment of the invention, during the communication process of smart home devices in a smart home network, spectrum analysis techniques such as Fast Fourier Transform (FFT) can be used to determine the channel usage within the 2.4 GHz to 10.6 GHz range in the smart home network. For example, channel usage may include, but is not limited to, channel state information, signal-to-noise ratio (SNR), channel interference, bandwidth, channel utilization, and latency. Specifically, channel state information (CSI) is a set of parameters describing the characteristics of a wireless channel, which may include channel gain, phase, and latency; signal-to-noise ratio (SNR) is the ratio of signal strength to noise strength, usually expressed in decibels (dB); the higher the SNR, the better the channel quality; channel interference refers to signal interference from other wireless devices; channels with less interference are generally considered to be a better choice; bandwidth refers to the frequency range of the channel, usually measured in Hertz (Hz). The wider the bandwidth, the stronger the transmission capacity of the channel; channel utilization refers to the proportion of the channel occupied by other devices, and channels with lower utilization are usually more suitable for selection; latency refers to the time required for a signal to be transmitted from the transmitting end to the receiving end, and channels with lower latency are usually more suitable for real-time applications.

[0083] In one example of this invention, the spectrum analysis process can be as follows: For the 2.4GHz band: check the usage of channels 1-11, taking care to avoid overlapping interference between adjacent channels; For the 5GHz band: check the usage of channels 36-165, as the 5GHz band has more available channels, and be aware of the limitations of DFS (Dynamic Frequency Selection) channel usage. It is important to note that in the 2.4GHz band, non-overlapping channels (1, 6, 11) are used to reduce interference, while in the 5GHz band, the channel spacing is larger, generally making overlap less likely. Additionally, based on the identified interference sources in the smart home network, channels farther from the interference sources can be selected.

[0084] Step 102: Collect device information of smart home devices in the smart home network.

[0085] In this embodiment of the invention, device information of each smart home device in the smart home network can be collected. The device information can include at least the signal strength information of the smart home device for each channel, the device type, and the data transmission requirements. Specifically, the signal strength information can refer to the Received Signal Strength Indicator (RSSI), the device type can refer to the type of smart home device such as smart light bulb, door lock, camera, sensor, and speaker, and the data transmission requirements refer to the quantity and type of data transmitted by the smart home device. The type can include text, images, video, and control commands.

[0086] Step 103: Select the target channel from the channels based on the channel usage and the device information.

[0087] Step 104: Aggregate the target channels to form aggregated channels.

[0088] Step 105: Control the smart home devices in the smart home network to communicate through the aggregation channel.

[0089] In practical implementation, channel bonding is a wireless communication technology that allows smart home devices in a smart home network to use multiple channels simultaneously for data transmission, thereby increasing the bandwidth of the smart home network and improving the data transmission rate.

[0090] In this embodiment of the invention, a target channel can be selected from multiple channels based on the channel usage of the channels in the smart home network and the device information of the smart home devices. The target channel is then aggregated to form an aggregated channel. Subsequently, the smart home devices in the smart home network can be controlled to communicate through the aggregated channel. Communication based on the aggregated channel can improve the throughput of the smart home network.

[0091] It should also be noted that, in order to better support channel aggregation, embodiments of the present invention can also perform synchronous optimization on the communication protocols in the smart home network. Specifically, this may include optimizing the MAC layer protocol, for example, by using Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA) technologies to reduce collisions and retransmissions, thereby supporting more efficient data transmission and error correction mechanisms; and optimizing the network layer protocol to provide better packet routing and priority management, for example, by using efficient routing algorithms at the network layer, such as QoS (Quality of Service) based routing selection, to ensure the priority transmission of critical data.

[0092] Optionally, embodiments of the present invention may also set the number of target channels for channel aggregation. For example, the number of target channels needs to be greater than or equal to a preset number, so as to ensure that the aggregated channel formed by the aggregation of target channels can provide the best network performance.

[0093] In this embodiment of the invention, smart home devices in a smart home network communicate based on channels within the smart home network. During communication, the channel usage within a specified channel range in the smart home network is determined, and device information of the smart home devices in the network is collected. Based on the channel usage and device information, target channels are selected from the channels, and these target channels are aggregated to form aggregated channels. This allows control over communication between smart home devices in the smart home network through these aggregated channels. This embodiment of the invention can select target channels from multiple channels based on channel usage and device information, choosing those with superior performance and suitability for smart home devices, such as those that are underutilized or have less interference. Communication can then be performed using the aggregated channels formed by aggregating these target channels. Since smart home devices can communicate through aggregated channels, the throughput of the smart home network can be increased, supporting simultaneous high-speed communication by more smart home devices.

[0094] In one embodiment of the present invention, step 103, filtering target channels from the channels based on the channel usage and the device information, includes:

[0095] Candidate channels are selected from the channels based on the channel usage data;

[0096] The target channel is selected from the candidate channels based on the device information.

[0097] In this embodiment of the invention, candidate channels can be first selected from the channels in the smart home network based on the channel usage of the channels in the smart home network. Then, target channels can be further selected from the candidate channels based on the device information of the smart home devices. The selected channels are channels with better performance in the smart home network and are suitable for smart home devices. The smart home devices communicate based on the aggregated channels formed by the aggregation of target channels, which can improve the performance of the smart home network and the user experience.

[0098] In one embodiment of the present invention, the step of filtering candidate channels from the channel based on the channel usage includes:

[0099] Determine the channel selection parameters used to filter the channels;

[0100] Candidate channels are selected from the channels based on the channel selection parameters and the channel usage.

[0101] The channel selection parameters may include at least thresholds for channel state information, signal-to-noise ratio (SNR), channel interference, bandwidth, channel utilization, and latency. Channel usage information may include, but is not limited to, current channel state information, current SNR, current channel interference, current bandwidth, current channel utilization, and current latency.

[0102] In this embodiment of the invention, channel selection parameters for filtering channels can be determined, and then candidate channels can be filtered from the channels in the smart home network based on the channel selection parameters and channel usage.

[0103] In one embodiment of the present invention, determining the channel selection parameters for filtering the channels includes:

[0104] Obtain channel information of the channel in the smart home network; the channel information includes at least the interference situation, signal strength and compatibility with the smart home devices of the channel;

[0105] Based on the channel information, channel selection parameters for the channel in the smart home network are determined; wherein the channel selection parameters include at least the channel state information, signal-to-noise ratio, channel interference, bandwidth, channel utilization, and latency thresholds for the channel.

[0106] In specific implementations, channel information includes at least the channel's interference situation, signal strength, and compatibility with smart home devices. The channel's interference situation refers to the type and intensity of interference sources in the smart home network, the signal strength refers to the RSSI (Received Signal Strength Indication), and the compatibility with smart home devices refers to the smart home devices in the smart home network supported by the channel.

[0107] In this embodiment of the invention, channel selection parameters for channels in a smart home network can be determined based on channel information. These parameters may include at least thresholds for channel state information, signal-to-noise ratio (SNR), channel interference, bandwidth, channel utilization, and latency. The thresholds in this embodiment serve as the minimum performance criteria to be considered when selecting a channel. For example, if the SNR of a channel is lower than the threshold, that channel will not be considered as a candidate channel.

[0108] In one embodiment of the present invention, the channel usage information includes at least the current channel state information and the current signal-to-noise ratio of the channel; the step of filtering candidate channels from the channel based on the channel usage information includes:

[0109] Channels whose current channel state information reaches a threshold and whose current signal-to-noise ratio reaches a threshold are selected as candidate channels.

[0110] In this embodiment of the invention, the quality of each channel can be determined using Current Channel State Information (CSI), and the channel with the highest current Signal-to-Noise Ratio (SNR) can be selected for channel aggregation. Specifically, channels whose Current Channel State Information (CSI) reaches the threshold of the Channel State Information in the channel selection parameters, and whose Current Signal-to-Noise Ratio (SNR) reaches the threshold of the SNR in the channel selection parameters, are selected as candidate channels.

[0111] In one embodiment of the present invention, the channel usage information includes at least the channel's current channel interference, current bandwidth, current channel utilization, and current latency; the step of filtering candidate channels from the channel based on the channel usage information includes:

[0112] The data transmission rate of the channel is determined based on the current channel state information, the current signal-to-noise ratio, the current channel interference, the current bandwidth, the current channel utilization, and the current delay.

[0113] Channels whose data transmission rate exceeds a preset data transmission rate are selected as candidate channels.

[0114] In this embodiment of the invention, the data transmission rate of each channel can be calculated based on parameters of channel usage, such as the current channel state information, current signal-to-noise ratio, current channel interference, current bandwidth, current channel utilization, and current latency. Then, channels with data transmission rates exceeding a preset data transmission rate are selected as candidate channels. This embodiment of the invention avoids channel aggregation of channels with low data transmission rates, thus ensuring a higher data transmission rate based on aggregated channels and improving the data transmission performance of the smart home network.

[0115] In one embodiment of the present invention, the device information includes at least the signal strength information, device type, and data transmission requirements of the smart home device for each of the channels; the step of filtering the target channel from the candidate channels based on the device information includes:

[0116] The signal strength information, device type, and data transmission requirements are input into a preset network demand prediction model to obtain the usage pattern and traffic model of the smart home device; wherein, the usage pattern is used to characterize the activity status of the smart home device in various time periods in the future, and the traffic model is used to characterize the data transmission volume of the smart home device in various time periods in the future.

[0117] Target channels are selected from the candidate channels based on the usage pattern and the traffic model.

[0118] Among them, the network demand prediction model is based on the LSTM (Long Short-Term Memory) algorithm model, which can predict the future network demand of smart home devices.

[0119] Specifically, usage patterns refer to the behavioral patterns and operating modes of smart home devices in daily use. By analyzing these usage patterns, we can predict the activity of smart home devices in a future time period. For example, a smart camera might start recording video when it detects motion and remain in standby mode otherwise. Its behavior pattern might show more motion detections during the day and fewer at night. Traffic models describe the data transmission needs of smart home devices under different usage patterns. Using traffic models, we can predict the amount of data transmission by smart home devices in a future time period. For example, a smart camera might send a status packet once per hour when in standby mode and continuously transmit video data when recording video, thus its data transmission needs differ.

[0120] In this embodiment of the invention, after obtaining device information of smart home devices such as signal strength information, device type, and data transmission requirements, the information can be input into the network demand prediction model. This allows the network demand prediction model to output the usage patterns and traffic models of smart home devices. Based on these usage patterns and traffic models, the future network demands of smart home devices can be predicted. Target channels are then selected from candidate channels based on these usage patterns and traffic models. This ensures that the selected target channels match the activity status and data transmission volume of smart home devices in various future time periods. By rationally selecting channels and avoiding overload on any particular channel, efficient utilization of smart home network channels is achieved, providing users with a more stable and responsive smart home experience.

[0121] In one embodiment of the present invention, after the smart home devices in the smart home network communicate through the aggregation channel, the method further includes:

[0122] Monitor the network status of the smart home network;

[0123] Based on the network status, determine whether to re-determine the new channel selection parameters used to filter the channels;

[0124] A new target channel is selected from the channels based on the new channel selection parameters;

[0125] The new target channel is aggregated to form a new aggregated channel;

[0126] Control the smart home devices in the smart home network to communicate through the new aggregation channel.

[0127] In this embodiment of the invention, during the operation of the smart home network, a network congestion detection algorithm (e.g., a model based on queuing theory) can be used to continuously monitor the network performance and environmental changes of the smart home network. If network congestion or a new source of interference is detected, the channel aggregation strategy will be dynamically adjusted. For example, based on the network status, it can be determined whether to re-determine the new channel selection parameters for filtering channels. According to the new channel selection parameters, new target channels are selected from the channels for channel aggregation to form a new aggregated channel. The smart home devices in the smart home network are then controlled to communicate through the new aggregated channel. In this way, by dynamically switching the communication channels of smart home devices to a more suitable aggregated channel based on the network status, the communication of smart home devices can always be kept in a better state.

[0128] In one embodiment of the present invention, the network state includes at least whether a new interference source is detected, and the step of determining whether to re-determine new channel selection parameters for filtering the channel based on the network state includes:

[0129] If a new source of interference is detected in the smart home network, new channel selection parameters for filtering the channels are determined.

[0130] In practice, interference sources can include Bluetooth devices, microwave ovens, wireless cameras, and neighboring Wi-Fi networks. Specifically, Bluetooth devices such as Bluetooth headsets, keyboards, and mice can compete with smart home networks that are Wi-Fi networks for the 2.4GHz frequency band. Microwave ovens in the kitchen can interfere with nearby Wi-Fi signals when they are working. If multiple wireless cameras are installed in the home, they may cause interference in the 2.4GHz frequency band. If a neighbor's Wi-Fi network uses the same or adjacent channels, it can also interfere with the smart home network.

[0131] In this embodiment of the invention, the network status includes at least whether a new interference source is detected. If network congestion or a new interference source is detected, the channel aggregation strategy will be dynamically adjusted. For example, new channel selection parameters for filtering the channels can be redefined. If the network is normal or no new interference source is detected, no operation is required.

[0132] This invention proposes a smart home network optimization method based on ultra-wideband channel aggregation technology, aiming to improve the performance of smart home networks through intelligent channel selection and aggregation, dynamic adjustment and communication protocol optimization.

[0133] To enable those skilled in the art to better understand the embodiments of the present invention, a complete example is described below. (Refer to...) Figure 2 This is a schematic diagram of a smart home network optimization method provided in an embodiment of the present invention. The main steps for implementing smart home network optimization may include:

[0134] 1. Network Environment Analysis: The smart home system analyzes the current network environment of the smart home network, mainly including the following aspects: using spectrum analysis techniques such as Fast Fourier Transform (FFT) to detect the current channel usage in the 2.4GHz to 10.6GHz range; collecting signal strength information of each smart home device (e.g., by receiving signal strength index RSSI), as well as the device type and data transmission requirements of smart home devices, and then using network demand prediction models to analyze the usage patterns and traffic models of smart home devices to predict future network demands; in addition, the smart home system can analyze surrounding radio interference sources and further determine the optimal channel selection scheme based on the radio interference sources.

[0135] 2. Channel Selection and Aggregation: Based on the analysis results, the smart home system selects the optimal wireless channel (target channel) and aggregates multiple selected channels to form a broadband channel to increase data throughput. Channel aggregation can be implemented through software configuration. The smart home system optimizes channel selection parameters by considering channel interference, signal strength, and compatibility with smart home devices. According to the IEEE 802.15.4a / z standard, non-overlapping frequency bands are selected, and the bandwidth is dynamically adjusted according to network requirements. For example, Channel State Information (CSI) can be used to determine the quality of each channel, and the channel with the highest Signal-to-Noise Ratio (SNR) can be selected for aggregation. Furthermore, thresholds can be set for parameters such as CSI, SNR, channel interference, bandwidth, channel utilization, and latency, for example, a data transmission rate greater than 20 Mbps (megabits per second) can be used as a standard for channel aggregation.

[0136] 3. Dynamic Adjustment: During the operation of the smart home network, the smart home system can continuously monitor network performance and environmental changes using network congestion detection algorithms. For example, if network congestion or new interference sources are detected, the smart home system will dynamically adjust its channel aggregation strategy, switching to a more suitable channel combination to maintain optimal smart home network performance.

[0137] 4. Communication Protocol Optimization: To better support channel aggregation, the communication protocols in smart home networks also need optimization. This includes optimizing the MAC layer protocol, employing Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA) technologies to reduce collisions and retransmissions, thus supporting more efficient data transmission and error correction mechanisms; optimizing the network layer protocol to provide better packet routing and priority management. Employing efficient routing algorithms at the network layer, such as QoS (Quality of Service) based routing, ensures priority transmission of critical data.

[0138] In summary, this embodiment of the invention performs network environment analysis on the smart home network and predicts the network requirements of smart home devices. Then, it selects and aggregates channels, enabling smart home devices to communicate based on aggregated channels to improve throughput. Furthermore, during the operation of the smart home network, the smart home system will dynamically adjust the channel aggregation strategy to ensure optimal network performance.

[0139] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0140] Reference Figure 3 This diagram illustrates a structural block diagram of a smart home network communication device provided in an embodiment of the present invention. The smart home devices in the smart home network communicate based on channels within the smart home network. Specifically, the device may include the following modules:

[0141] The channel usage determination module 301 is used to determine the channel usage of channels within a specified channel range in the smart home network;

[0142] Device information acquisition module 302 is used to collect device information of smart home devices in the smart home network;

[0143] The target channel filtering module 303 is used to filter target channels from the channels based on the channel usage and the device information;

[0144] Channel aggregation module 304 is used to aggregate the target channels to form aggregated channels;

[0145] The device communication module 305 is used to control the smart home devices in the smart home network to communicate through the aggregation channel.

[0146] In one embodiment of the present invention, the target channel filtering module 303 is used for:

[0147] Candidate channels are selected from the channels based on the channel usage data;

[0148] The target channel is selected from the candidate channels based on the device information.

[0149] In one embodiment of the present invention, the target channel filtering module 303 is used for:

[0150] Determine the channel selection parameters used to filter the channels;

[0151] Candidate channels are selected from the channels based on the channel selection parameters and the channel usage.

[0152] In one embodiment of the present invention, the target channel filtering module 303 is used for:

[0153] Obtain channel information of the channel in the smart home network; the channel information includes at least the interference situation, signal strength and compatibility with the smart home devices of the channel;

[0154] Based on the channel information, channel selection parameters for the channel in the smart home network are determined; wherein the channel selection parameters include at least the channel state information, signal-to-noise ratio, channel interference, bandwidth, channel utilization, and latency thresholds for the channel.

[0155] In one embodiment of the present invention, the channel usage information includes at least the current channel state information and the current signal-to-noise ratio of the channel; the target channel filtering module 303 is configured to:

[0156] Channels whose current channel state information reaches a threshold and whose current signal-to-noise ratio reaches a threshold are selected as candidate channels.

[0157] In one embodiment of the present invention, the channel usage information includes at least the channel's current channel interference, current bandwidth, current channel utilization, and current latency; the target channel filtering module 303 is configured to:

[0158] The data transmission rate of the channel is determined based on the current channel state information, the current signal-to-noise ratio, the current channel interference, the current bandwidth, the current channel utilization, and the current delay.

[0159] Channels whose data transmission rate exceeds a preset data transmission rate are selected as candidate channels.

[0160] In one embodiment of the present invention, the device information includes at least the signal strength information, device type, and data transmission requirements of the smart home device for each of the channels; the target channel filtering module 303 is used for:

[0161] The signal strength information, device type, and data transmission requirements are input into a preset network demand prediction model to obtain the usage pattern and traffic model of the smart home device; wherein, the usage pattern is used to characterize the activity status of the smart home device in various time periods in the future, and the traffic model is used to characterize the data transmission volume of the smart home device in various time periods in the future.

[0162] Target channels are selected from the candidate channels based on the usage pattern and the traffic model.

[0163] In one embodiment of the present invention, the apparatus further includes: an update module, configured to:

[0164] Monitor the network status of the smart home network;

[0165] Based on the network status, determine whether to re-determine the new channel selection parameters used to filter the channels;

[0166] A new target channel is selected from the channels based on the new channel selection parameters;

[0167] The new target channel is aggregated to form a new aggregated channel;

[0168] Control the smart home devices in the smart home network to communicate through the new aggregation channel.

[0169] In one embodiment of the present invention, the network state includes at least whether a new interference source has been detected, and the update module is configured to:

[0170] If a new source of interference is detected in the smart home network, new channel selection parameters for filtering the channels are determined.

[0171] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0172] In addition, this invention also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the various processes of the above-described smart home network communication method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here.

[0173] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the above-described smart home network communication method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0174] This invention also provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described smart home network communication method embodiments, and can achieve the same technical effects. To avoid repetition, it will not be described again here.

[0175] Figure 4 A schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0176] The electronic device 400 includes, but is not limited to, components such as: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, a processor 410, and a power supply 411. Those skilled in the art will understand that... Figure 4 The electronic device structures shown are not intended to limit the electronic device. An electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements. In embodiments of the present invention, the electronic device includes, but is not limited to, mobile phones, tablet computers, laptops, PDAs, in-vehicle terminals, wearable devices, and pedometers.

[0177] It should be understood that, in this embodiment of the invention, the radio frequency unit 401 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink data from the base station and processes it with the processor 410; additionally, it transmits uplink data to the base station. Typically, the radio frequency unit 401 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier, a duplexer, etc. Furthermore, the radio frequency unit 401 can also communicate with networks and other devices through a wireless communication system.

[0178] The electronic device provides users with wireless broadband internet access through network module 402, such as helping users send and receive emails, browse web pages, and access streaming media.

[0179] The audio output unit 403 can convert audio data received by the radio frequency unit 401 or the network module 402 or stored in the memory 409 into audio signals and output them as sound. Furthermore, the audio output unit 403 can also provide audio output related to specific functions performed by the electronic device 400 (e.g., call signal reception sound, message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, and a receiver, etc.

[0180] Input unit 404 is used to receive audio or video signals. Input unit 404 may include a graphics processing unit (GPU) 4041 and a microphone 4042. The GPU 4041 processes image data of still images or videos acquired by an image capture device (such as a camera) in video capture mode or image capture mode. The processed image frames can be displayed on display unit 406. The image frames processed by GPU 4041 can be stored in memory 409 (or other storage medium) or transmitted via radio frequency unit 401 or network module 402. Microphone 4042 can receive sound and process such sound into audio data. The processed audio data can be converted into a format that can be transmitted to a mobile communication base station via radio frequency unit 401 in telephone call mode.

[0181] The electronic device 400 also includes at least one sensor 405, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 4061 according to the ambient light level, and the proximity sensor can turn off the display panel 4061 and / or backlight when the electronic device 400 is moved to the ear. As a type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used to identify the posture of the electronic device (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. The sensor 405 may also include a fingerprint sensor, pressure sensor, iris sensor, molecular sensor, gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc., which will not be described in detail here.

[0182] The display unit 406 is used to display information input by the user or information provided to the user. The display unit 406 may include a display panel 4061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0183] User input unit 407 can be used to receive input numerical or character information, and generate key signal inputs related to user settings and function control of electronic devices. Specifically, user input unit 407 includes a touch panel 4071 and other input devices 4072. Touch panel 4071, also known as a touch screen, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near touch panel 4071). Touch panel 4071 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 410, which receives and executes commands from the processor 410. In addition, touch panel 4071 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. Besides touch panel 4071, user input unit 407 may also include other input devices 4072. Specifically, other input devices 4072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, joysticks, etc., which will not be described in detail here.

[0184] Furthermore, the touch panel 4071 can cover the display panel 4061. When the touch panel 4071 detects a touch operation on or near it, it transmits the information to the processor 410 to determine the type of touch event. Subsequently, the processor 410 provides corresponding visual output on the display panel 4061 based on the type of touch event. Although in Figure 4 In this embodiment, the touch panel 4071 and the display panel 4061 are two independent components to realize the input and output functions of the electronic device. However, in some embodiments, the touch panel 4071 and the display panel 4061 can be integrated to realize the input and output functions of the electronic device. The specific implementation is not limited here.

[0185] Interface unit 408 serves as an interface for connecting external devices to electronic device 400. For example, external devices may include a wired or wireless headphone port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, and so on. Interface unit 408 can be used to receive input from external devices (e.g., data, power, etc.) and transmit the received input to one or more components within electronic device 400, or it can be used to transmit data between electronic device 400 and external devices.

[0186] The memory 409 can be used to store software programs and various data. The memory 409 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback, image playback, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). Furthermore, the memory 409 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0187] The processor 410 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 409, and by calling data stored in the memory 409, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. The processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 410.

[0188] The electronic device 400 may also include a power supply 411 (such as a battery) for supplying power to various components. Preferably, the power supply 411 can be logically connected to the processor 410 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system.

[0189] In addition, the electronic device 400 includes some functional modules not shown, which will not be described in detail here.

[0190] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0191] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0192] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

[0193] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0194] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0195] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0196] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0197] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0198] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0199] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A smart home network communication method, characterized in that, The smart home devices in the smart home network communicate based on channels within the smart home network, and the method includes: Determine the channel usage status of channels within a specified channel range in the smart home network; Collect device information of smart home devices in the smart home network. The device information includes at least the signal strength information of the smart home devices for each channel, device type, and data transmission requirements of the smart home devices. Candidate channels are selected from the channels based on the channel usage data; The signal strength information, device type, and data transmission requirements are input into a preset network demand prediction model to obtain the usage pattern and traffic model of the smart home device; wherein, the usage pattern is used to characterize the activity status of the smart home device in various time periods in the future, and the traffic model is used to characterize the data transmission volume of the smart home device in various time periods in the future. Target channels are selected from the candidate channels based on the usage pattern and the traffic model; The target channels are aggregated to form aggregated channels, and the communication protocols in the smart home network are synchronously optimized. The system controls smart home devices in the smart home network to communicate through the aggregation channel.

2. The method according to claim 1, characterized in that, The step of filtering candidate channels from the channel based on the channel usage includes: Determine the channel selection parameters used to filter the channels; Candidate channels are selected from the channels based on the channel selection parameters and the channel usage.

3. The method according to claim 2, characterized in that, The determination of the channel selection parameters used to filter the channels includes: Obtain channel information of the channel in the smart home network; the channel information includes at least the interference situation, signal strength and compatibility with the smart home devices of the channel; Based on the channel information, channel selection parameters for the channel in the smart home network are determined; wherein the channel selection parameters include at least the channel state information, signal-to-noise ratio, channel interference, bandwidth, channel utilization, and latency thresholds for the channel.

4. The method according to claim 3, characterized in that, The channel usage information includes at least the current channel state information and the current signal-to-noise ratio of the channel; the step of filtering candidate channels from the channel based on the channel usage information includes: Channels whose current channel state information reaches a threshold and whose current signal-to-noise ratio reaches a threshold are selected as candidate channels.

5. The method according to claim 4, characterized in that, The channel usage information includes at least the channel's current channel interference, current bandwidth, current channel utilization, and current latency; the step of filtering candidate channels from the channel based on the channel usage information includes: The data transmission rate of the channel is determined based on the current channel state information, the current signal-to-noise ratio, the current channel interference, the current bandwidth, the current channel utilization, and the current delay. Channels whose data transmission rate exceeds a preset data transmission rate are selected as candidate channels.

6. The method according to claim 1, characterized in that, After the smart home devices in the controlled smart home network communicate via the aggregation channel, the method further includes: Monitor the network status of the smart home network; Based on the network status, determine whether to re-determine the new channel selection parameters used to filter the channels; A new target channel is selected from the channels based on the new channel selection parameters; The new target channel is aggregated to form a new aggregated channel; Control the smart home devices in the smart home network to communicate through the new aggregation channel.

7. The method according to claim 6, characterized in that, The network status includes at least whether a new source of interference has been detected, and determining whether to re-determine the new channel selection parameters for filtering the channels based on the network status includes: If a new source of interference is detected in the smart home network, new channel selection parameters for filtering the channels are determined.

8. A smart home network communication device, characterized in that, The smart home devices in the smart home network communicate based on channels within the smart home network, and the device includes: The channel usage determination module is used to determine the channel usage of channels within a specified channel range in the smart home network. The device information acquisition module is used to collect device information of smart home devices in the smart home network. The device information includes at least the signal strength information of the smart home devices for each channel, device type, and data transmission requirements of the smart home devices. The target channel filtering module is used to filter candidate channels from the channels based on the channel usage; input the signal strength information, device type, and data transmission requirements into a preset network demand prediction model to obtain the usage pattern and traffic model of the smart home device; wherein, the usage pattern is used to characterize the activity status of the smart home device in various time periods in the future, and the traffic model is used to characterize the data transmission volume of the smart home device in various time periods in the future; and filter target channels from the candidate channels based on the usage pattern and the traffic model. The channel aggregation module is used to aggregate the target channels to form aggregated channels and to synchronously optimize the communication protocols in the smart home network. The device communication module is used to control smart home devices in the smart home network to communicate through the aggregation channel.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory is used to store computer programs; When the processor executes a program stored in the memory, it implements the method as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon that, when executed by one or more processors, cause the processors to perform the method as described in any one of claims 1-7.

Images