A method, device, electronic device and medium for optimizing communication link quality

Abstract

The present invention provides a communication link quality optimization method, device, electronic device and medium, including: determining the service type carried by the sensor in the initial network; re-determining the value of the spreading factor of the sensor in the multi-hop network according to the service type carried by the sensor and the STSSA algorithm, so that the sensor joins the corresponding target network. The optimization method provided by the present invention can reduce the network deployment cost, achieve full network coverage, and is simple and easy to implement, thereby ensuring the service quality of various perception services and improving the user experience.

Description

Technical Field

[0001] The present invention relates to the field of machine control technology, and in particular to a communication link quality optimization method, device, electronic equipment and medium. Background Art

[0002] The power Internet of Things is a complex multi-network flow system that takes the power system as the core and combines communication networks, smart terminal sensors, artificial intelligence and other technologies. It is necessary to widely deploy intelligent sensing devices with certain sensing, computing and execution capabilities in all aspects of power production, transmission, consumption and management to achieve panoramic and holographic perception, interconnection and seamless integration of the entire process of power grid operation and enterprise management.

[0003] At present, the typical application scenario of the power Internet of Things is the urban integrated underground pipeline corridor. The power system is an important part of the integrated pipeline corridor. In order to ensure its efficient operation, it is necessary to achieve full-area perception of the underground pipeline corridor. As a low-power wide area network technology, LoRa has become the main communication technology for achieving full-area perception of underground pipeline corridors due to its low hardware cost, high availability, and high flexibility (i.e., it can establish an independent dedicated network on an unlicensed spectrum).

[0004] In the prior art, in order to achieve full coverage of the power communication network, patent CN109699033A discloses two different communication methods based on the power information collection service and the end-to-end service in the LoRaWAN network. Although the number of deployed base stations is reduced and the network construction cost can be effectively reduced, it is only suitable for large-scale deployment of base stations in the power system Internet of Things. Another example is patent CN213935175U, which involves a power networking system, which reduces the network deployment cost of the power networking system, but the overall network throughput is low, and the network as a whole adopts a cluster architecture. For the concentrator, it is necessary to undertake the data forwarding of the node equipment. The concentrator generally requires a larger battery capacity or adopts a direct power supply method. Another example is patent CN113453302A, which discloses a self-organizing power wireless LoRa communication method, device, system and storage medium. The LoRa communication device running this method has both terminal node function and relay function. There is no need to add gateway equipment to expand the network. It is simple and easy to implement and has low cost. However, since LoRa in this solution is connected in accordance with the traditional wireless network rather than the low-power wide area network, each data packet is marked with a clear destination rather than flooding. This method is a huge test for the computing power, storage capacity and energy consumption of the LoRa device. Therefore, there is a need for a power grid system that can achieve full coverage while ensuring the service quality of each perception service, reduce network deployment costs, and balance energy consumption. Summary of the invention

[0005] The present invention provides a communication link quality optimization method, device, electronic device and medium, which are used to solve the technical problems of incomplete coverage of power networking systems and poor user experience in the prior art, and to achieve the purpose of expanding the power grid system while ensuring the quality of each service.

[0006] In a first aspect, the present invention provides a method for optimizing communication link quality, comprising:

[0007] Determine the service type carried by the sensors in the initial network;

[0008] According to the service type carried by the sensor and the STSSA algorithm, the spreading factor value of the sensor in the multi-hop network is re-determined so that the sensor joins the corresponding target network.

[0009] Further, according to the communication link quality optimization method provided by the present invention, the spreading factor value of the sensor in the multi-hop network is re-determined according to the service type carried by the sensor and the STSSA algorithm, so that the sensor joins the corresponding target network, including:

[0010] Determining a spreading factor of the sensor and a corresponding number of hops;

[0011] Obtaining a data transmission rate of the sensor according to a spreading factor of the sensor and a corresponding hop number;

[0012] According to the service type carried by the sensor, determine the lower limit of the data rate on the sensor, obtain the upper limit of the spreading factor and the upper limit of the number of hops, and determine the interval range of the spreading factor and the interval range of the number of hops;

[0013] According to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops and the STSSA algorithm, the spreading factor value in the multi-hop network is re-determined for the sensor, so that the sensor is migrated out of the atomic network and joined the corresponding target network.

[0014] Further, according to the communication link quality optimization method provided by the present invention, obtaining the data transmission rate of the sensor according to the spreading factor of the sensor and the corresponding hop number includes:

[0015] Determining the number of times the data packet is forwarded on the sensor according to the type of service carried by the sensor;

[0016] A uniformly distributed random delay and a complementary delay are set for the data packet to determine the transmission time required for the data packet to be forwarded on the sensor; wherein the uniformly distributed random delay is:

[0017]

[0018] in, represents the uniformly distributed random delay of the nth forwarding of the i-th relay node; x represents the first randomly distributed delay, i represents the relay node, n represents that the relay node will forward the message for the nth time; μ represents uniform distribution;

[0019] A data transmission rate of the sensor is determined according to the transmission time.

[0020] Further, according to the communication link quality optimization method provided by the present invention, obtaining the upper limit value of the spreading factor and the upper limit value of the number of hops according to the service type carried by the sensor, and determining the interval range of the spreading factor and the interval range of the number of hops, includes:

[0021] Determine uplink instantaneous signal-to-noise ratio;

[0022] It is confirmed that at least one sensor is allocated to each channel, an upper limit value of a spreading factor and an upper limit value of a hop number are obtained according to the uplink instantaneous signal-to-noise ratio, and an interval range of the spreading factor and an interval range of the hop number are determined.

[0023] Further, according to the communication link quality optimization method provided by the present invention, the spreading factor value in the multi-hop network is re-determined for the sensor according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the STSSA algorithm, so that the sensor is migrated out of the atomic network and joins the corresponding target network, including:

[0024] Determine a corresponding range of spreading factors and a range of hop counts for each service node on the sensor;

[0025] The sensor is migrated to a corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor.

[0026] Further, according to the communication link quality optimization method provided by the present invention, the migrating the sensor to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor includes:

[0027] When the service node corresponding to the sensor is of a guarantee type and the service node on the sensor has a subnode, the subnode is allocated to other service nodes, or the subnode and the service node are migrated to the corresponding target network together when the capacity of the target network allows.

[0028] Further, according to the communication link quality optimization method provided by the present invention, the migrating the sensor to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor includes:

[0029] Determine the boundary of multiple spreading factors and priority information of each spreading factor;

[0030] When the service node on the sensor is a data service, the service node is preferentially migrated to a channel with a spreading factor of SF8;

[0031] When the service node on the sensor is a data packet delivery rate type service, the service node is preferentially migrated to a channel where a minimum allowed spreading factor is located.

[0032] Further, according to the communication link quality optimization method provided by the present invention, the sensor is migrated to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor, and further includes:

[0033] The service node on the sensor is forward migrated or reverse migrated to the corresponding target network.

[0034] In a second aspect, the present invention further provides a communication link quality optimization device, comprising:

[0035] A determination module, used to determine the service type carried by the sensor in the initial network;

[0036] The redetermining module is used to redetermine the spreading factor value of the sensor in the multi-hop network according to the service type of the sensor and the STSSA algorithm, so that the sensor joins the corresponding target network.

[0037] In a third aspect, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-described methods for optimizing the quality of a communication link are implemented.

[0038] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-described methods for optimizing the quality of a communication link.

[0039] In a fifth aspect, the present invention further provides a computer program product, comprising computer executable instructions, which, when executed, are used to implement the steps of the communication link quality optimization method as described in any one of the above items.

[0040] The present invention provides a communication link quality optimization method, device, electronic device and medium, including: determining the service type carried by the sensor in the initial network; re-determining the value of the spreading factor of the sensor in the multi-hop network according to the service type carried by the sensor and the STSSA algorithm, so that the sensor joins the corresponding target network. The optimization method provided by the present invention can reduce the network deployment cost, achieve full network coverage, and is simple and easy to implement, thereby ensuring the service quality of various perception services and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 It is a flow chart of the communication link quality optimization method provided by the present invention;

[0043] Figure 2 It is a schematic diagram of the expected effect achieved by the communication link quality optimization method provided by the present invention;

[0044] Figure 3 It is a schematic diagram of the process flow of the service node processing of the guarantee type provided by the present invention;

[0045] Figure 4 is a schematic diagram of an initial network of other service nodes provided by the present invention;

[0046] Figure 5 It is a schematic diagram of the process of performing migration processing on other service nodes provided by the present invention;

[0047] Figure 6 It is a schematic diagram of the reverse migration provided by the present invention;

[0048] Figure 7 It is a schematic diagram of the total communication time of various algorithms provided by the present invention in a square space;

[0049] Figure 8 It is a schematic diagram of the total communication time of various algorithms provided by the present invention in a narrow and long space;

[0050] Fig. 9 It is a schematic diagram of the results of the square space service support rate of various algorithms provided by the present invention;

[0051] Fig.10It is a schematic diagram of the results of the various algorithms provided by the present invention in narrow and long space service support rates;

[0052] Fig.11 It is a structural schematic diagram of a communication link quality optimization device provided by the present invention;

[0053] Fig.12 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Figure 1 A communication link quality optimization method provided by the present invention, such as Figure 1 As shown, the communication link quality optimization method provided by the present invention includes:

[0056] Step 101: Determine the service type carried by the sensor in the initial network.

[0057] In this embodiment, it is necessary to determine the service type carried by each sensor in the initial network, and divide the initial network into a system with multiple different subnets according to different service types, wherein each subnet type corresponds to a spreading factor. In a multi-hop network, there are multiple subnet types, that is, there are multiple spreading factors. The spreading factor (SF) refers to the number of chips into which each symbol is converted, and the ratio of the chip rate after spreading to the signal rate before spreading reflects the spreading gain.

[0058] It should be noted that this embodiment is to divide an initial network with a single spreading factor into a multi-hop network with multiple different spreading factors. Figure 2 As shown, there are Figure 1 and points Figure 2 In this embodiment, Figure 1 The initial network connected by SF7 is divided into Figure 2 There are six subnets with different spreading factors in the multi-hop network. The SFs are orthogonal to each other. Each sensor corresponds to one SF. The gateway (root) can realize parallel transmission of six SFs, and each subnet operates independently.

[0059] Step 102: According to the service type carried by the sensor and the STSSA algorithm, the spreading factor value of the sensor in the multi-hop network is re-determined so that the sensor joins the corresponding target network.

[0060] In this embodiment, it is necessary to re-determine the subnet type of the sensor in the multi-hop network according to the service type of the sensor and the STSSA algorithm, so that the service node on the sensor is added to the corresponding target network. In this embodiment, the link is constructed from the data packet delivery rate and data rate. The function of SF and hop number, and then the uplink spreading factor (SF) and the range of hop number are determined for the sensor corresponding to the service node according to the service requirements of different service types. Among them, the STSSA algorithm (Service-oriented Tree-based SF Allocation Algorithm) is a service-oriented tree-based SF allocation algorithm.

[0061] It should be noted that in the embodiment of the present invention, the original single root uplink data acquisition network is divided into six subnets with the same root but not intersecting, and a spreading factor (SF) is assigned to each subnet, so that multiple spreading factors (SF) are transmitted in parallel. This embodiment is a tree-based clustering algorithm, and each sensor is migrated to the corresponding subnet according to the service type, data volume, priority and other information of the service node, and joins the target network. Among them, the physical implementation model of this embodiment is CT-LoRa.

[0062] According to the communication link quality optimization method provided by the present invention, by determining the service type carried by the sensor in the initial network, according to the service type carried by the sensor and the STSSA algorithm, the spreading factor value of the sensor in the multi-hop network is re-determined, so that the sensor joins the corresponding target network. The optimization method provided by the present invention can reduce the network deployment cost, achieve full network coverage, and is simple and easy to implement, thereby ensuring the service quality of various perception services and improving the user experience.

[0063] Based on any of the above embodiments, in this embodiment, re-determining the channel type of the sensor in the multi-hop network according to the service type of the sensor and the STSSA algorithm so that the service node on the sensor joins the corresponding target network includes:

[0064] Determine the spreading factor of the sensor and the corresponding number of hops;

[0065] According to the spreading factor of the sensor and the corresponding hop number, the data transmission rate of the sensor is obtained;

[0066] According to the service type carried by the sensor, determine the lower limit of the data rate on the sensor, obtain the upper limit of the spreading factor and the upper limit of the number of hops, and determine the interval range of the spreading factor and the interval range of the number of hops;

[0067] Based on the STSSA algorithm, according to the data transmission rate, the interval range of the spreading factor and the interval range of the number of hops, the spreading factor value in the multi-hop network is re-determined for the sensor, so that the sensor is migrated out of the atomic network and joined the corresponding target network.

[0068] In this embodiment, it is necessary to determine the transmission time of the data packet of the service node on the sensor according to the service type and node type of the sensor, and then obtain the transmission rate of the sensor; further determine the data packet delivery rate of the service node, including the upper limit value of the spreading factor and the upper limit value of the number of hops, and finally, according to the data transmission rate and the interval range of the spreading factor and the interval range of the number of hops, and the STSSA algorithm, re-determine the subnet type in the multi-hop network for the sensor, determine the corresponding spreading factor value according to the subnet type, and enable the service node on the sensor to join the corresponding target network. The joined target network can be any channel of SF7, SF8, SF9, SF10, SF11 and SF12.

[0069] It should be noted that, unlike the traditional star network, in the star network, when the bandwidth is fixed, the transmission rate is only related to SF, while in the multi-hop network, the rate is related to both SF and the number of hops. Under the same SF, the more hops, the slower the transmission rate. The physical implementation mechanism of LoRa adopted by the present invention is CT-LoRa. Specifically, the offset-CT improvement method is adopted. The implementation process of this method is specifically shown in the following embodiment, which will not be described in detail here.

[0070] It should be noted that in the narrow space of the underground pipe gallery, the problem between interference and data packet delivery rate is also a point considered by the present invention. From the trend analysis, the larger the SF, the greater the transmission success rate, which is different from the star-type LoRa network. The traditional star-type LoRa network adopts the ALOHA protocol. The larger the SF, the slower the data transmission speed. If the number of data packets sent is the same, the longer the transmission time of each data packet, the greater the possibility of conflict. Therefore, the larger the SF, the lower the transmission success rate. However, in the multi-hop LoRa network, the MAC layer mechanism ensures that there is no problem of decreased transmission success rate due to packet conflicts. The transmission success rate depends on the anti-interference ability, that is, the SF12 channel is interfered by the five channels of SF7, SF8, SF9, SF10, and SF11. The SF12 channel has the strongest anti-interference ability and the greater the transmission success rate.

[0071] According to the communication link quality optimization method provided by the present invention, by calculating the determined data transmission rate, spreading factor and hop number interval according to the STSSA algorithm, the spreading factor value in the multi-hop network is re-determined for the sensor, so that the service node on the sensor joins the corresponding target network. It is possible to expand the network without adding gateway equipment, reduce network deployment costs, achieve full network coverage, be simple and easy to implement, ensure the service quality of various perception services, and improve user experience.

[0072] Based on any of the foregoing embodiments, in this embodiment, obtaining the data transmission rate of the sensor according to the spreading factor of the sensor and the corresponding hop number includes:

[0073] Determining the number of times the data packet is forwarded on the sensor according to the type of service carried by the sensor;

[0074] A uniformly distributed random delay and a complementary delay are set for the data packet to determine the transmission time required for the data packet to be forwarded on the sensor; wherein the uniformly distributed random delay is:

[0075]

[0076] in, represents the uniformly distributed random delay of the nth forwarding of the i-th relay node; x represents the first randomly distributed delay, i represents the relay node, n represents that the relay node will forward the message for the nth time; μ represents uniform distribution;

[0077] A transmission rate of the sensor is determined based on the transmission time.

[0078] In this embodiment, the transmission rate in the multi-hop network is determined based on the offset-CT improved method. This method needs to insert two parts of delay before each relay packet retransmission. The delay mainly consists of two parts. One part is that each part a delay is an independent uniformly distributed random delay, which is used to generate a time offset between messages. The delay has a five-digit field and there are thirty-two possibilities; the other part is a complementary delay, which is the same as the complementary delay in the prior art and will not be introduced in detail here.

[0079] For example, assume that a data packet has been forwarded n-1 times before reaching relay node i. When the data packet is forwarded from relay node i to relay node j for the nth time, the first randomly distributed delay is set to x in this embodiment. represents the nth forwarding of the i-th relay node, and the second complementary delay is y. The statement is as before.

[0080]

[0081]

[0082] The transmission time of the data packet of the relay node for the nth time is:

[0083]

[0084]

[0085]

[0086] Among them, T S is the unit symbol time, T P It is the propagation time of the LoRa data packet itself. This part is consistent with the representation of the traditional LoRa network and can be expressed as:

[0087]

[0088]

[0089] T packet =T preamble +T payload

[0090] In this embodiment, each time a hop is added, the time is fixedly increased by T. P +T S , Indicates the random backoff time of this jump, which is uniformly distributed between 0 and T S random variable; T for each hop P It is closely related to the spreading factor (SF) of the subnet.

[0091] It should be noted that, in this embodiment, the node type refers to whether the service node on the sensor is a child node or a parent node, and the service type refers to whether the data packet to be transmitted is a data-type service or a data packet delivery rate-type service, wherein the transmission rate is determined based on the transmission time of the data packet, and the transmission rate can be obtained by using the calculation method in the prior art, which will not be introduced in detail here.

[0092] According to the communication link quality optimization method provided by the present invention, by determining the number of times a data packet is forwarded on the sensor according to the service type of the sensor, setting a uniformly distributed random delay and a complementary delay for the data packet, determining the transmission time required for the data packet to be forwarded on the sensor, and obtaining the transmission rate, it is possible to achieve accurate perception of the perception service, improve the quality of the service perception service, and enhance the user experience.

[0093] Based on any of the above embodiments, in this embodiment, obtaining the upper limit value of the spreading factor and the upper limit value of the number of hops according to the service type carried by the sensor, and determining the interval range of the spreading factor and the interval range of the number of hops, includes:

[0094] Determine uplink instantaneous signal-to-noise ratio;

[0095] It is confirmed that at least one sensor is allocated to each channel, and an upper limit value of a spreading factor and an upper limit value of a hop number are determined according to the uplink instantaneous signal-to-noise ratio, and an interval range of the spreading factor and an interval range of the hop number are determined.

[0096] In this embodiment, the uplink instantaneous signal-to-noise ratio needs to be determined. Assume that the uplink instantaneous signal-to-noise ratio is Y. nm , for a relay node i, when the spreading factor (SF) is u:

[0097]

[0098] Among them, P max is the power value, h i is the channel gain, r i α is the distance between the two, is the deterministic loss, f c is the carrier frequency, σ is the path loss exponent, is additive white Gaussian noise.

[0099] In this embodiment, when only one device is allocated to one spreading factor (SF), the device is interfered by other SFs, which can be expressed as:

[0100]

[0101] Among them, I -i =I\{i},u -u =u\{u},s a，b is a binary variable indicating whether the SF of relay node a is b.

[0102]

[0103] When multiple sensors are assigned to one spreading factor (SF), they are subject to interference from both the same SF and other SFs. The interference from the same SF is much greater than that from other SFs. The interference from the same SF can be expressed as:

[0104]

[0105] It should be noted that, in this embodiment, is used to represent the probability of successful data packet transmission. Since each SF is assigned to at least one sensor, the transmission success rate only considers the case of interference from the same SF.

[0106]

[0107] Among them, θ co is the capture threshold value, transmission success rate It can also be expressed as:

[0108]

[0109] When it comes to an n-hop link, the packet transmission success rate can be expressed as:

[0110]

[0111] Moreover, for terminal i, using an n-hop link with SF=u, this embodiment uses a two-tuple to evaluate this link, which are the unit transmission time and the transmission success rate, and is specifically expressed as follows:

[0112]

[0113] According to the communication link quality optimization method provided by the present invention, by determining the instantaneous signal-to-noise ratio of the uplink, and then confirming that each channel is assigned at least one sensor, the upper limit value of the spreading factor and the upper limit value of the number of hops are obtained according to the instantaneous signal-to-noise ratio of the uplink, and the interval range of the spreading factor and the interval range of the number of hops are determined, the data packet delivery success rate can be accurately calculated, and a basis is provided for the service node on the sensor to re-determine the target network.

[0114] Based on any of the above embodiments, in this embodiment, the step of re-determining the spreading factor value in the multi-hop network for the sensor according to the transmission rate and the data transmission rate, the interval range of the spreading factor, and the interval range of the number of hops based on the STSSA algorithm, so that the sensor is migrated out of the atomic network and joins the corresponding target network, includes:

[0115] Determine a corresponding range of spreading factors and a range of hop counts for each service node on the sensor;

[0116] The service node on the sensor is migrated to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor.

[0117] In this embodiment, it is necessary to determine the corresponding spreading factor and the range of hops for each service node. Before the service node is migrated to the network, it is necessary to determine the capacity of the subnet corresponding to each channel type. In this embodiment, the channels in the multi-hop network are divided into six channels: SF7, SF8, SF9, SF10, SF11 and SF12. The capacity of each channel is determined to be n*0.3, n*0.25, n*0.2, n*0.15, n*0.1, and n*0.07, respectively, where n is the total number of sensors, and then the priority and security type are added to each spreading factor.

[0118] service(i)={range(i),Priority i , Ensure i}

[0119] It should be noted that, in this embodiment, the hop count interval range refers to the channel range to which the service node can migrate. For example, service node 1 can migrate from SF7 to SF10 in sequence, but cannot migrate to SF12. The specific range can be set according to the actual needs of the user and is not specifically limited here.

[0120] According to the communication link quality optimization method provided by the present invention, the corresponding spreading factor and hop count range are determined for each service node on the sensor according to the data packet delivery success rate, and then the service nodes on the sensor can be accurately migrated to the corresponding target network according to the capacity of each spreading factor, thereby improving the service quality of the perception service.

[0121] Based on any of the foregoing embodiments, in this embodiment, migrating the sensor to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor includes:

[0122] When the service node corresponding to the sensor is of a guarantee type and the service node on the sensor has a subnode, the subnode is allocated to other service nodes, or the subnode and the service node are migrated to the corresponding target network together when the capacity of the target network allows.

[0123] In this embodiment, from the perspective of the protection type, for the ensured services, if there are child nodes, the child nodes are allocated to other service nodes. If they cannot be allocated to other service nodes, the service node and the child nodes are migrated to the corresponding SF and added to the target network.

[0124] For guarantee type business, such as Figure 3As shown, assuming that the service node G is a guaranteed data packet delivery rate service, when considering migrating the child nodes M and N of the service node G to other service nodes, such as F and H, assuming that the service node M cannot be migrated to other service nodes in the manner of SF7 due to various reasons, then the child nodes M and N will be migrated to SF10 with the G service node. If the capacity of SF10 is full or SF10 cannot meet the data packet delivery rate requirements, they will be migrated to SF12, where the M node is referred to as a migrated node in this embodiment, and this part of the migrated nodes will be reversely migrated in the subsequent links.

[0125] It should be noted that in the process of outward and inward migration, there is a phenomenon that the child nodes of a certain service node need to rely on other service nodes at the same level of the service node to communicate, which is called mounting. After mounting, the branches of the tree become unbalanced. This phenomenon only occurs in the network with a spreading factor of SF7. Therefore, when inserting a service node in the SF8-12 spreading factor, link balancing needs to be considered, that is, the service nodes using SF7 need to be reconstructed.

[0126] It should be noted that, in the process of migrating service nodes from small SF to large SF, when the number of nodes in each subnet meets the iteration condition, that is, the SF8 to SF12 subnets have reached the expected capacity, or when the algorithm searches all service nodes included in SF7 and still no node can be migrated outward, the iteration terminates. For processing the accompanying nodes, that is, the process of SF from large to small, this embodiment only traverses all the accompanying nodes once and then terminates.

[0127] According to the communication link quality optimization method provided by the present invention, when the service type of the sensor is a guarantee type and there are sub-nodes on the service node of the sensor, the sub-nodes can be assigned to other service nodes, and the sub-nodes and the service nodes can be migrated to the corresponding target network together, thereby ensuring that each service node can be accurately migrated to the SF and join the corresponding target network, thereby improving the service quality of the perception service.

[0128] Based on any of the foregoing embodiments, in this embodiment, migrating the sensor to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor includes:

[0129] Determine the boundary of multiple channel types and priority information of each channel type;

[0130] When the service node on the sensor is a data service, the service node is preferentially migrated to a channel type of SF8;

[0131] When the service node on the sensor is a data packet delivery rate type service, the service node is preferentially migrated to the minimum allowed channel type.

[0132] In this embodiment, considering the service priority, processing is performed according to the priority. Under the same priority, all service nodes are classified according to the available interval, and SF9 is determined as the dividing line. The lower limit is SF7. The services corresponding to SF8 are data-type services, and the rest are data packet delivery rate services. When the service node on the sensor processes data-type services, it is preferentially migrated to SF8. When the service node processes data packet delivery rate services, it starts to migrate from the minimum SF allowed by the service node. If the capacity of the subnet to be migrated is full, it is adjusted upward.

[0133] It should be noted that for the same priority, the reason for post-processing packet delivery rate-type services is that the coverage area of ​​SF is different, and the network diagram formed is also different. The larger the SF, the easier it is to connect, and each service node is only allowed to be allocated to one subnet. Therefore, nodes with larger SF have greater selectivity.

[0134] It should be noted that for other types of services, the initial network distribution is as follows: Figure 4 The migration process is as follows: Figure 5 As shown, when facing nodes of different priorities, migration is performed according to the determined priority order information, when facing different types of services, data type services are prioritized, and when facing the same level and type, the present invention starts migration from the node farthest from the gateway.

[0135] like Figure 5 As shown, assuming that all services in the SF7 subnet are of the same type and level, and there is still vacant space in the SF8 subnet, and it is hoped that the P node will migrate to SF8, the P node will first try to connect directly to SF8. If it can be connected, it will connect directly. If not, it is found that there are N, R, T, and S nodes that are as far away from the gateway as P. These four nodes will try to migrate to SF8 in sequence. If the migration is successful and SF8 is full, it will start to migrate to SF9, that is, SF will migrate in order from small to large. If all four service nodes cannot be connected to the SF8 subnet, then it is necessary to search upward with breadth first to try whether point H can be connected.

[0136] If the P node cannot connect to other nodes, its connectivity is maintained and the H point cannot migrate outward, such as Figure 5 Points in Figure 1 As shown in Figure 1, if the P node can connect to the F point and the H point can migrate to the SF8 subnet, then the H point successfully migrates out and the round ends. The next round starts with the P point again, trying to migrate to the SF8 subnet. If the P point can connect to the H point, then the migration is successful, as shown in Figure 1. Figure 5 Points in Figure 2As shown in the figure, after point P migrates, the next node to migrate is N, and so on. The purpose of checking connectivity is to ensure that after a node is extracted, the original SF network still guarantees connectivity. If it cannot be guaranteed, for guaranteed services, these nodes need to be migrated together as accompanying nodes; for best-effort services, they cannot be migrated out of the current SF, that is, the child nodes of a node must be able to migrate to other parent nodes, otherwise they cannot be migrated.

[0137] According to the communication link quality optimization method provided by the present invention, by migrating the service nodes on the sensor to the corresponding target network according to the transmission rate, channel type, hop number range, and capacity of each spreading factor, it is possible to ensure that each service node is accurately migrated to the target subnet of the multi-hop network, thereby improving the service quality of the perception service.

[0138] Based on any of the above embodiments, in this embodiment, the step of migrating the sensor to the corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor further includes:

[0139] The service node on the sensor is forward migrated or reverse migrated to the corresponding target network.

[0140] In this embodiment, the service nodes on the sensor can be forward migrated or reverse migrated to migrate the service nodes to the corresponding target network, wherein the forward migration can be divided into two steps, namely, extracting nodes and inserting nodes. The process of inserting nodes is relatively simple. When the node service requirements are met, the node is inserted into the branch (tree branch) that minimizes the overall transmission time of the subnet. The process of extracting nodes is relatively complex and is divided into two methods, guaranteed service extraction and other service extraction. The specific processing process is shown in the above embodiment.

[0141] Figure 6 The figure is a schematic diagram of the node migration process from high SF to low SF. For the same link, SF cannot be adjusted from high to low. For the M node, it migrates due to the migration of the G node. Since the G node migrated very early (high priority), the E node has not been assigned to SF9 and cannot communicate with the M node using SF7, but can communicate with SF9. Therefore, after the overall forward migration, the accompanying nodes will be reversely migrated. Through this step, the communication delay can be reduced, and the energy consumption of the M node and the G node is also reduced. The order of reverse migration starts from the accompanying node to which the SF with the longest subnet communication time belongs, that is, the four subnets SF9, SF10, SF11, and SF12 are reversely migrated.

[0142] According to the communication link quality optimization method provided by the present invention, the service node is migrated to the corresponding target network through forward migration or reverse migration, which can ensure that each service node is accurately migrated to the target subnet of the multi-hop network, thereby improving the service quality of the perceived service.

[0143] Based on any of the above embodiments, in this embodiment, in view of the problem that the current LoRa multi-hop network cannot meet the differentiated needs of urban underground pipe gallery services, the present invention proposes a multi-service power communication network link quality optimization mechanism based on LoRa multi-hop, which includes a transmission rate model and a data packet delivery rate model, and uses SF and hop count to represent the transmission rate and data packet delivery rate. The service corresponds to the SF and hop count of the link according to the requirements of the transmission rate and data packet delivery rate, that is, the network partitioning problem is understood as a K-coloring problem, and the STSAA (Service-oriented Tree-based SFAllocation Algorithm) algorithm is proposed, which is used to assign an SF to each sensor in the LoRa multi-hop network, and divide the entire network into six subnets from SF7 to SF12. The algorithm determines different sensors according to the service type (i.e., guaranteed type or best effort type), and extracts the process of joining the initial network to the new subnet. Under the condition of ensuring connectivity, the present invention supports the differentiated needs of the service and improves the overall throughput of the network.

[0144] In this embodiment, Figure 7 It is a schematic diagram of the effects of various algorithms in the square space, reflecting the processing effects of the STSAA algorithm and the TSCA algorithm under the first business model of the square space, wherein the horizontal axis represents the number of sensors, the vertical axis represents the total communication time, and the number of sensors increases from 200 to 500. When the node density is low (the number of nodes is 200), in order to meet the needs of various businesses, the time saving ratio of the STSAA algorithm is not as large as that of the high density; when the node density is high, the STSAA algorithm performs better than the TSCA algorithm.

[0145] In this embodiment, Figure 8 It reflects the communication time in the narrow and long space. It can be seen that compared with the square space, the overall communication time of the two algorithms has increased significantly, and the advantages of the two algorithms have become less obvious. The performance of the STSAA algorithm is mainly affected by two aspects. One is connectivity. Second, in a square environment, the height of the tree (i.e., the number of hops) is significantly reduced, and the overall communication time is also reduced. In a narrow and long environment, even after SF7 is reconstructed, the decrease in the height of the tree is still far less than that in a square environment. However, when the number of nodes is large, the STSAA algorithm has certain advantages over the TSCA algorithm. Overall, the effect of the STSAA algorithm in a narrow and long space is not as stable as in a square space. Fig. 9 The service support rate of the STSAA algorithm in a square is demonstrated. The guaranteed service support rate cannot be guaranteed at a lower node density, but it can be guaranteed in a high-density space.

[0146] In this embodiment, Fig.10 The service support rate of the STSAA algorithm in a narrow space is shown. Overall, the best-effort service is less affected by the space, while the guaranteed tasks, especially the control services, cannot be migrated to the designated SF under low-density conditions due to the narrow service constraint interval. Even at high density, the support rate cannot be guaranteed. When the sensor density is low, the best-effort service support rate will be higher because the SF and hop count interval of such services are large, and since the guaranteed service support cannot be completed, there is no need to migrate out of its own interval for the guaranteed task.

[0147] According to the communication link quality optimization method provided by the present invention, the entire initial network is divided into six non-intersecting subnets to improve the overall network throughput and achieve effective support for differentiated services while ensuring coverage and business needs.

[0148] Fig.11 A schematic diagram of the structure of a communication link quality optimization device provided by the present invention is shown in FIG. Fig.11 As shown, the present invention provides a communication link quality optimization device, comprising:

[0149] The determination module 1101 is used to determine the channel type and service type corresponding to the sensor in the initial network; wherein each channel type corresponds to a spreading factor;

[0150] The redetermining module 1102 is used to redetermine the channel type of the sensor in the multi-hop network according to the service type of the sensor and the STSSA algorithm, so that the service node on the sensor joins the corresponding target network.

[0151] According to the communication link quality optimization device provided by the present invention, by determining the channel type and service type corresponding to the sensor in the initial network; according to the service type of the sensor and the STSSA algorithm, the channel type of the sensor in the multi-hop network is re-determined, so that the service node on the sensor joins the corresponding target network. The optimization device provided by the present invention can reduce the network deployment cost and achieve full network coverage without adding gateway equipment when expanding the network. It is simple and easy to implement, ensures the service quality of various perception services, and improves the user experience.

[0152] Since the principle of the device described in the embodiment of the present invention is the same as that of the method described in the above embodiment, a more detailed explanation will not be repeated here.

[0153] Fig.12 Schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention. Fig.12 As shown, the present invention provides an electronic device, including: a processor (processor) 1201, a memory (memory) 1202 and a bus 1203;

[0154] The processor 1201 and the memory 1202 communicate with each other via the bus 1203;

[0155] The processor 1201 is used to call the program instructions in the memory 1202 to execute the methods provided in the above-mentioned method embodiments, for example, including: determining the channel type and service type corresponding to the sensor in the initial network; wherein each channel type corresponds to a spreading factor; based on the service type of the sensor and the STSSA algorithm, re-determining the channel type of the sensor in the multi-hop network, so that the service node on the sensor joins the corresponding target network.

[0156] In addition, the logic instructions in the above-mentioned memory 1203 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0157] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided by the above methods, and the methods include: determining the channel type and service type corresponding to the sensor in the initial network; wherein each channel type corresponds to a spreading factor; and based on the service type of the sensor and the STSSA algorithm, re-determining the channel type of the sensor in the multi-hop network, so that the service node on the sensor joins the corresponding target network.

[0158] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform the above-mentioned methods, the method comprising: determining the channel type and service type corresponding to the sensor in the initial network; wherein each channel type corresponds to a spreading factor; and based on the service type of the sensor and the STSSA algorithm, re-determining the channel type of the sensor in the multi-hop network so that the service node on the sensor joins the corresponding target network.

[0159] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative effort.

[0160] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing communication link quality, characterized in that: include: Determine the service type carried by the sensors in the initial network; Re-determine the spreading factor value of the sensor in the multi-hop network according to the service type carried by the sensor and the STSSA algorithm, so that the sensor joins the corresponding target network; The re-determining the spreading factor value of the sensor in the multi-hop network according to the service type carried by the sensor and the STSSA algorithm so that the sensor joins the corresponding target network includes: Determining a spreading factor of the sensor and a corresponding number of hops; Obtaining a data transmission rate of the sensor according to a spreading factor of the sensor and a corresponding hop number; According to the service type carried by the sensor, determine the lower limit of the data rate on the sensor, obtain the upper limit of the spreading factor and the upper limit of the number of hops, and determine the interval range of the spreading factor and the interval range of the number of hops; Based on the STSSA algorithm, according to the data transmission rate, the interval range of the spreading factor and the interval range of the number of hops, the spreading factor value of the sensor in the multi-hop network is re-determined, so that the sensor is migrated out of the atomic network and joins the corresponding target network; The obtaining, according to the spreading factor of the sensor and the corresponding hop number, a data transmission rate of the sensor includes: Determining the number of times a data packet is forwarded on the sensor according to the type of service carried by the sensor; A uniformly distributed random delay and a complementary delay are set for the data packet to determine the transmission time required for the data packet to be forwarded on the sensor; wherein the uniformly distributed random delay is: in, represents the uniformly distributed random delay of the nth forwarding of the i-th relay node; x represents the first randomly distributed delay, i represents the relay node, n represents that the relay node will forward the message for the nth time; μ represents uniform distribution; Determining a data transmission rate of the sensor according to the transmission time; The step of obtaining an upper limit value of a spreading factor and an upper limit value of a hop count according to a service type carried by the sensor, and determining an interval range of the spreading factor and an interval range of the hop count includes: Determine uplink instantaneous signal-to-noise ratio; It is confirmed that at least one sensor is allocated to each channel, an upper limit value of a spreading factor and an upper limit value of a hop number are obtained according to the uplink instantaneous signal-to-noise ratio, and an interval range of the spreading factor and an interval range of the hop number are determined.

2. The method for optimizing the quality of a communication link according to claim 1, characterized in that: The method of re-determining the spreading factor value of the sensor in the multi-hop network based on the STSSA algorithm according to the data transmission rate, the interval range of the spreading factor and the interval range of the number of hops, so that the sensor is migrated out of the atomic network and joins the corresponding target network, includes: Determine a corresponding range of spreading factors and a range of hop counts for each service node on the sensor; The sensor is migrated to a corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor.

3. The method for optimizing the quality of a communication link according to claim 2, characterized in that: The step of migrating the sensor to a corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor includes: When the service node corresponding to the sensor is of a guarantee type and the service node on the sensor has a subnode, the subnode is allocated to other service nodes, or the subnode and the service node are migrated to the corresponding target network together when the capacity of the target network allows.

4. The method for optimizing the quality of a communication link according to claim 2, characterized in that: The step of migrating the sensor to a corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor includes: Determine the boundary of multiple spreading factors and priority information of each spreading factor; When the service node on the sensor is a data service, the service node is preferentially migrated to a channel with a spreading factor of SF8; When the service node on the sensor is a data packet delivery rate type service, the service node is preferentially migrated to a channel where a minimum allowed spreading factor is located.

5. The method for optimizing the quality of a communication link according to claim 2, characterized in that: The step of migrating the sensor to a corresponding target network according to the data transmission rate, the interval range of the spreading factor, the interval range of the number of hops, and the capacity of each spreading factor further includes: The service node on the sensor is forward migrated or reverse migrated to the corresponding target network.

6. A communication link quality optimization device, characterized in that: include: A determination module, used to determine the service type carried by the sensor in the initial network; A redetermining module, used to redetermine the spreading factor value of the sensor in the multi-hop network according to the service type of the sensor and the STSSA algorithm, so that the sensor joins the corresponding target network; The re-determining the spreading factor value of the sensor in the multi-hop network according to the service type carried by the sensor and the STSSA algorithm so that the sensor joins the corresponding target network includes: Determining a spreading factor of the sensor and a corresponding number of hops; Obtaining a data transmission rate of the sensor according to a spreading factor of the sensor and a corresponding hop number; According to the service type carried by the sensor, determine the lower limit of the data rate on the sensor, obtain the upper limit of the spreading factor and the upper limit of the number of hops, and determine the interval range of the spreading factor and the interval range of the number of hops; Based on the STSSA algorithm, according to the data transmission rate, the interval range of the spreading factor and the interval range of the number of hops, the spreading factor value of the sensor in the multi-hop network is re-determined, so that the sensor is migrated out of the atomic network and joins the corresponding target network; The obtaining, according to the spreading factor of the sensor and the corresponding hop number, a data transmission rate of the sensor includes: Determining the number of times a data packet is forwarded on the sensor according to the type of service carried by the sensor; A uniformly distributed random delay and a complementary delay are set for the data packet to determine the transmission time required for the data packet to be forwarded on the sensor; wherein the uniformly distributed random delay is: in, represents the uniformly distributed random delay of the nth forwarding of the i-th relay node; x represents the first randomly distributed delay, i represents the relay node, n represents that the relay node will forward the message for the nth time; μ represents uniform distribution; Determining a data transmission rate of the sensor according to the transmission time; The step of obtaining an upper limit value of a spreading factor and an upper limit value of a hop count according to a service type carried by the sensor, and determining an interval range of the spreading factor and an interval range of the hop count includes: Determine uplink instantaneous signal-to-noise ratio; It is confirmed that at least one sensor is allocated to each channel, an upper limit value of a spreading factor and an upper limit value of a hop number are obtained according to the uplink instantaneous signal-to-noise ratio, and an interval range of the spreading factor and an interval range of the hop number are determined.

7. An electronic device, characterized in that: include: processor, memory and bus, wherein, The processor and the memory communicate with each other via the bus; The memory stores program instructions executable by the processor, and the processor can execute the steps of the communication link quality optimization method according to any one of claims 1 to 5 by calling the program instructions.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to execute the steps of the communication link quality optimization method according to any one of claims 1 to 5.

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