Unmanned aerial vehicle communication spectrum allocation method, device and equipment based on interference

Abstract

The invention discloses an unmanned aerial vehicle communication spectrum allocation method, device and equipment based on interference, and belongs to the technical field of wireless communication. The method comprises the following steps: acquiring information of two spectrum transaction parties; setting an incentive mechanism for the operator according to the information to obtain a utility function of the operator; according to a preset number of operator renting channels, a preset number of unmanned aerial vehicles and constraint conditions corresponding to QoS requirements of the operators and the unmanned aerial vehicles, constructing a nonlinear optimization problem, and optimizing a utility function of the operators; and solving the nonlinear optimization problem by adopting an allocation rule and a coloring rule to obtain a spectrum allocation scheme which enables the effectiveness of an operator to be maximum. According to the method, the excitation mechanism is set for the operator, the nonlinear optimization problem about the utility function of the operator is constructed, the allocation rule and the coloring rule are adopted for solving, and the optimal spectrum allocation scheme is obtained, so that the spectrum utilization rate is improved under the condition that the QoS requirements of the operator and the unmanned aerial vehicle are met.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communication, and particularly relates to a method, device and equipment for allocating communication spectrum of unmanned aerial vehicles based on interference. Background Art

[0002] In recent years, unmanned aerial vehicle (UAV) technology has developed rapidly and has been widely used in many fields such as science and industry. As an important part of the Internet of Things technology, UAVs play an important role in many scenarios such as logistics distribution, agricultural plant protection, surveying and mapping, emergency rescue, and power inspection. With the increasingly wide application of UAVs, their communication requirements are also growing continuously, and spectrum resources, as a key element of UAV communication, are particularly important. However, due to the shortage of spectrum resources and the lack of dedicated spectrum for UAVs, UAVs lack real-time supervision of security during communication and are vulnerable to interference. In order to alleviate the problem of tight spectrum resources, spectrum sharing has been proposed in the prior art, but there is a lack of a spectrum allocation method that can not only meet the QoS requirements of operators and UAVs but also improve the spectrum utilization rate. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method, device and equipment for allocating communication spectrum of unmanned aerial vehicles based on interference. By setting an incentive mechanism for operators, constructing a non-linear optimization problem about the utility function of operators, and using allocation rules and coloring rules to solve it, an optimal spectrum allocation scheme is obtained, so as to improve the spectrum utilization rate while meeting the QoS requirements of operators and UAVs.

[0004] To achieve the above purpose, the present invention is implemented by the following technical solutions:

[0005] In the first aspect, the present invention provides a method for allocating communication spectrum of unmanned aerial vehicles based on interference, and the method includes:

[0006] Obtain information of both sides of the spectrum transaction;

[0007] Set an incentive mechanism for operators according to the information to obtain the utility function of operators;

[0008] Construct a non-linear optimization problem according to the constraints corresponding to the preset number of channels leased by operators, the number of UAVs, and the QoS requirements of operators and UAVs, and optimize the utility function of operators;

[0009] Use allocation rules and coloring rules to solve the non-linear optimization problem to obtain a spectrum allocation scheme that maximizes the utility of operators.

[0010] On the one hand, further, the information of both parties in spectrum trading includes: the spectrum leased by the operator to the UAV, the lease price provided by the UAV to the operator, the transmission powers of the operator and the UAV, and the geographical locations.

[0011] On the one hand, further, solving the non-linear optimization problem by using the allocation rule and the coloring rule to obtain a spectrum allocation scheme that maximizes the operator's utility includes:

[0012] Generating a conflict relationship according to the transmission powers, geographical locations and QoS requirements of the operator and the UAV, and constructing a conflict graph;

[0013] Allocating the spectrum leased by the operator to the UAV by using the allocation rule;

[0014] Coloring the allocation result on the conflict graph by using the coloring rule;

[0015] Judging whether the spectrum leased by the operator has been allocated completely. In response to the leased spectrum being allocated completely, solving for the maximum operator utility and the corresponding optimal spectrum allocation scheme; in response to not being allocated completely, judging whether there is a UAV that has not leased the spectrum;

[0016] In response to there being a UAV that has not leased the spectrum, repeating the above steps to continue the next round of allocation and coloring; in response to there not being one, solving for the maximum operator utility and the corresponding optimal spectrum allocation scheme.

[0017] On the one hand, further, the conflict relationship is generated through the calculation of the path loss model; wherein, the path loss model includes: the communication link path loss model between the operator and the UAV and the communication link path loss model between the UAV and the UAV;

[0018] The expression of the communication link path loss model between the operator and the UAV is:

[0019] ,

[0020] wherein,

[0021] ,

[0022] ,

[0023] ,

[0024] ,

[0025] In the formula, is the communication link path loss between the operator and the UAV, is the distance between the operator and the UAV; and are the LOS path loss and the NLOS path loss respectively; and are the probabilities that the communication link is the LOS path and the NLOS path respectively; is the speed of light; is the carrier frequency; and are the average additional losses of the LOS path and the NLOS path respectively; and are both constants related to the environment; is the included angle between the operator device and the UAV;

[0026] The expression of the communication link path loss model between UAVs is:

[0027] ,

[0028] In the formula, is the communication link path loss between UAVs, is the distance between UAVs; is the path loss exponent; is the reference distance.

[0029] On the one hand, further, the allocation rule for allocating the spectrum leased by the operator to the UAVs includes:

[0030] Sort the lease prices provided by the UAVs to the operator from high to low, and number the UAVs in ascending order;

[0031] Judge whether there is an idle channel in the spectrum leased by the operator; in response to the existence, allocate the idle channel to the UAV according to the UAV number; otherwise, allocate the occupied channel to the UAV according to the UAV number;

[0032] In response to allocating an idle channel to the UAV, judge whether the UAVs to be allocated do not conflict with the UAVs in the idle channel coexistence group, and whether the cumulative interference received by the UAVs in the idle channel coexistence group is less than the preset interference threshold;

[0033] In response to both non-conflicting and less than the interference threshold, the UAVs to be allocated can join the idle channel coexistence group and be allocated the idle channel; otherwise, judge whether the UAV numbers have been traversed;

[0034] In response to not having traversed, repeat the above steps and continue to judge the next UAV to be allocated; otherwise, complete one round of allocation;

[0035] In response to allocating an occupied channel to a drone, determine whether there is a conflict between the drone to be allocated and the operator equipment in the occupied channel;

[0036] In response to a conflict, determine whether all drone numbers have been traversed; otherwise, determine whether there is no conflict between the drone to be allocated and the drones in the coexistence group of the occupied channel, and whether the cumulative interference received by the drones in the coexistence group of the occupied channel is less than a preset interference threshold;

[0037] In response to there being no conflict and being less than the interference threshold, the drone to be allocated can join the coexistence group of the occupied channel and be allocated the occupied channel; otherwise, determine whether all drone numbers have been traversed;

[0038] In response to not having traversed all, repeat the above steps and continue to judge the next drone to be allocated; otherwise, complete one round of allocation.

[0039] In combination with one aspect, further, the coloring of the allocation result on the conflict graph using the coloring rule includes:

[0040] Assign the same color to the drones and operator equipment allocated on the same channel;

[0041] Assign different colors to the drones and operator equipment allocated on different channels.

[0042] In combination with one aspect, further, the utility function of the operator includes: the service income, rental income and interference impact of the operator, and the expression is:

[0043] ,

[0044] In the formula, is the utility function of the operator; is the service fee obtained by the operator; is the service fee paid by each drone when obtaining a spectrum license; is the number of drones that have successfully leased the spectrum; is the income obtained by the operator from leasing the spectrum; is the th price for a drone to lease the spectrum; ; is the benefit loss caused by the interference when the operator leases the spectrum; is the weighting coefficient; is the number of channels leased by the operator.

[0045] In combination with one aspect, further, the expression of the non-linear optimization problem is:

[0046] ,

[0047] In the formula, represents whether the channel is allocated to the UAV , represents the channel allocated to the UAV , represents the channel not allocated to the UAV ; is the utility function of the operator; is the service fee obtained by the operator; is the service fee paid by each UAV when obtaining a spectrum license; is the number of UAVs that successfully lease the spectrum; is the income obtained by the operator from leasing the spectrum; is the th price for a UAV to lease the spectrum; ; is the benefit loss caused by the interference when the operator leases the spectrum; is the weighting coefficient; is the number of channels leased by the operator;

[0048] The expression of the constraint condition is:

[0049] ,

[0050] ,

[0051] ,

[0052] ,

[0053] In the formula, is the set of the number of channels, ; is the set of the number of UAVs; represents that the UAV is affected by co-channel conflict interference; is the set of the number of conflict relationships, ; represents that the UAV is affected by the operator ; is the set of the number of operators, ; is the preset interference threshold for the UAV; represents whether the operator leases the channel , represents the operator Leased channel , indicating that the operator does not lease the channel ; is the minimum interference tolerable by the preset operator; indicating that the operator occupies the channel , indicating that the operator is occupying the channel , indicating that the operator does not occupy the channel .

[0054] In a second aspect, the present invention further provides an interference-based UAV communication spectrum allocation device, including:

[0055] An information collection module: used to obtain information of both parties in the spectrum transaction;

[0056] An incentive setting module: used to set an incentive mechanism for the operator according to the information to obtain the utility function of the operator;

[0057] A problem construction module: used to construct a non-linear optimization problem according to the constraints corresponding to the preset number of channels leased by the operator, the number of UAVs, and the QoS requirements of the operator and the UAV, and optimize the utility function of the operator;

[0058] An optimization solving module: used to solve the non-linear optimization problem by using the allocation rule and the coloring rule to obtain a spectrum allocation scheme that maximizes the operator's utility.

[0059] In a third aspect, the present invention further provides a computer device, including a storage medium and a processor;

[0060] The storage medium is used to store instructions;

[0061] The processor is used to operate according to the instructions to execute the steps of the method described in any item of the first aspect.

[0062] Compared with the prior art, the present invention can at least achieve the following beneficial effects:

[0063] 1. The interference-based UAV communication spectrum allocation method provided by the present invention sets an incentive mechanism for the operator, constructs a non-linear optimization problem about the operator's utility function, and uses the allocation rule and the coloring rule to solve it, obtaining an optimal spectrum allocation scheme, thereby improving the spectrum utilization rate while meeting the QoS requirements of the operator and the UAV;

[0064] 2. The present invention first generates conflict relationships and constructs a conflict graph to describe the interference situations among various devices; then uses allocation rules to allocate spectrum resources to the drones; finally uses coloring rules to color the allocation results, thereby completing one round of spectrum resource allocation; through multiple rounds of allocation and coloring, a spectrum allocation scheme that maximizes the operator's utility is obtained, which not only meets the QoS requirements of the operator and the drones, but also effectively improves the spectrum utilization rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0066] Figure 1 is a flowchart of a method for allocating drone communication spectrum based on interference provided by an embodiment of the present invention;

[0067] Figure 2 is a flowchart of an optimization solution method provided by an embodiment of the present invention;

[0068] Figure 3 is a flowchart of a method for allocation rules provided by an embodiment of the present invention;

[0069] Figure 4 is a conflict graph provided by an embodiment of the present invention;

[0070] Figure 5 is a conflict graph with coloring provided by an embodiment of the present invention;

[0071] Figure 6 is a comparison graph of the operator's utility and the success rate of drone leased spectrum between the method provided by an embodiment of the present invention and a comparison method under different interference thresholds;

[0072] Figure 7 is a comparison graph of the operator's utility and the success rate of drone leased spectrum between the method provided by an embodiment of the present invention and a comparison method under different numbers of drones;

[0073] Figure 8 is a comparison graph of the operator's utility and the success rate of drone leased spectrum between the method provided by an embodiment of the present invention and a comparison method under different numbers of channels;

[0074] Figure 9 is a schematic structural diagram of a device for allocating drone communication spectrum based on interference provided by an embodiment of the present invention;

[0075] Figure 10It is an internal structure diagram of a computer device provided by an embodiment of the present invention. Detailed implementation manners

[0076] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and cannot be used to limit the protection scope of the present invention.

[0077] Embodiment 1:

[0078] This embodiment provides a method for allocating UAV communication spectrum based on interference. As Figure 1 shown, it is a flowchart of the method provided in this embodiment, mainly including the following steps:

[0079] Step S100: Obtain information of both parties in spectrum trading, including: the spectrum leased by the operator to the UAV, the lease price provided by the UAV to the operator, the transmission powers of the operator and the UAV, and the geographical locations;

[0080] Step S200: Set an incentive mechanism for the operator according to the information to obtain the utility function of the operator. Among them, setting the incentive mechanism is to maximize the utility function, improve the operator's revenue, and thus encourage more operators to share the spectrum and lease channels;

[0081] Step S300: Construct a non-linear optimization problem according to the constraints corresponding to the preset number of channels leased by the operator, the number of UAVs, and the QoS requirements of the operator and the UAV, and optimize the utility function of the operator. Among them, the preset number of channels leased by the operator needs to be greater than zero;

[0082] Step S400: Solve the non-linear optimization problem by using the allocation rule and the coloring rule to obtain a spectrum allocation scheme that maximizes the operator's utility.

[0083] It should be noted that the method provided in this embodiment can be applied to a communication system that executes this method. The system includes operators and UAVs. Before the UAVs execute communication services, they need to first lease and obtain the allocated spectrum from the operator through this method before they can continue to execute their services.

[0084] The method for allocating UAV communication spectrum based on interference provided in this embodiment sets an incentive mechanism for the operator, constructs a non-linear optimization problem regarding the utility function of the operator, and uses the allocation rule and the coloring rule to solve it, obtaining an optimal spectrum allocation scheme, so as to improve the spectrum utilization rate while meeting the QoS requirements of the operator and the UAV.

[0085] In this embodiment, as Figure 2As shown in the figure, it is the flowchart of the optimization solution method provided in this embodiment. The following combines Figure 2 , and further details on how to use the allocation rule and the coloring rule to solve the non-linear optimization problem and obtain the spectrum allocation scheme that maximizes the operator's utility:

[0086] Step S401: Generate a conflict relationship based on the transmission power, geographical location, and QoS requirements of the operator and the UAV, and construct a conflict graph;

[0087] Step S402: Use the allocation rule to allocate the spectrum leased by the operator to the UAV;

[0088] Step S403: Use the coloring rule to color the allocation result on the conflict graph;

[0089] Step S404: Determine whether the spectrum leased by the operator has been allocated. In response to the leased spectrum being allocated, solve for the maximum operator utility and the corresponding optimal spectrum allocation scheme; in response to not being allocated, determine whether there is a UAV that has not leased the spectrum;

[0090] Step S405: In response to there being a UAV that has not leased the spectrum, repeat the above steps to continue the next round of allocation and coloring; in response to there not being any, solve for the maximum operator utility and the corresponding optimal spectrum allocation scheme.

[0091] Specifically, before allocating the leased spectrum to the UAV, it is necessary to construct a conflict relationship and a conflict graph to describe the interference situation between various devices. The conflict relationship is the interference range generated based on the transmission power, geographical location, and QoS requirements of the operator and the UAV, and mainly includes the following types:

[0092] Type 1: The interference ranges between any two devices do not overlap; this type indicates that there is no interference between the two devices;

[0093] Type 2: The interference ranges between any two devices overlap, and the overlapping part does not include the devices themselves; this type indicates that there is interference between the two devices, but the interference is relatively small and does not exceed the interference threshold;

[0094] Type 3: The interference ranges between any two devices overlap, and the overlapping part includes the devices themselves; this type indicates that the interference between the two devices is very serious, exceeding the interference threshold and affecting the QoS of the devices.

[0095] Further, a conflict graph needs to be constructed based on the conflict relationships. The construction rules of the conflict graph are as follows: No edge is assigned between any two devices with a conflict relationship of type one; An edge is assigned between any two devices with a conflict relationship of type two, and the edge is a dashed line; An edge is assigned between any two devices with a conflict relationship of type three, and the edge is a solid line. As Figure 4 shown, it is the conflict graph provided by this embodiment; among them, there are conflict relationships of type three between device A2 of operator A and drone U5, and between drone U2 and drone U3; while there are conflict relationships of type two between drone U1 and drone U4, between drone U4 and drone U5, and between device B2 of operator B and drone U2.

[0096] As an alternative embodiment, as Figure 3 shown, it is the method flowchart of the allocation rule provided by this embodiment. Referring to Figure 3 , the allocation rule mainly includes the following steps:

[0097] Step S4021: Sort the rental prices provided by the drones to the operator from high to low, and number the drones in ascending order;

[0098] Step S4022: Determine whether there is an idle channel in the spectrum leased by the operator; in response to the existence, allocate an idle channel to the drone according to the drone number; otherwise, allocate an occupied channel to the drone according to the drone number;

[0099] Step S4023: In response to allocating an idle channel to the drone, determine whether the drone to be allocated conflicts with none of the drones in the idle channel coexistence group, and whether the cumulative interference received by the drones in the idle channel coexistence group is less than a preset interference threshold;

[0100] Step S4024: In response to no conflict and being less than the interference threshold, the drone to be allocated can join the idle channel coexistence group and be allocated an idle channel; otherwise, determine whether the drone numbers have been traversed;

[0101] In response to not having traversed, repeat the above steps to continue judging the next drone to be allocated; otherwise, complete one round of allocation;

[0102] Step S4025: In response to allocating an occupied channel to the drone, determine whether the drone to be allocated conflicts with the operator device in the occupied channel;

[0103] Step S4026: In response to a conflict, determine whether the drone numbers have been traversed; otherwise, determine whether the drone to be allocated conflicts with none of the drones in the occupied channel coexistence group, and whether the cumulative interference received by the drones in the occupied channel coexistence group is less than a preset interference threshold;

[0104] Step S4027: In response to neither conflicting and both being less than the interference threshold, the UAV to be allocated can join the occupied channel coexistence group and be allocated the occupied channel; otherwise, determine whether all UAV numbers have been traversed;

[0105] In response to not having traversed all, repeat the above steps to continue judging the next UAV to be allocated; otherwise, complete one round of allocation.

[0106] It should be noted that the non - conflict between each device in the above steps refers to two situations: the dotted line and no line in the conflict graph. Refer to Figure 4 , assume that operator A leases two channels: one idle channel and one occupied channel with devices A1 and A2, operator B leases one occupied channel with devices B1 and B2; and the number of devices that can be accommodated in each channel is three. When using the allocation rule, UAV U1 will give priority to joining the idle channel; there is no conflict between UAV U2 and UAV U1, so it joins the idle channel; there is a conflict between UAV U3 and UAV U2, so it does not join the idle channel; there is no conflict between UAV U4 and either UAV U1 or UAV U2, so it joins the idle channel; at the end of the first round of allocation, UAV U1, UAV U2 and UAV U4 are allocated to the same channel. There is no conflict between UAV U3 and either device A1 or A2 of operator A, so it joins the occupied channel of operator A; at the end of the second round of allocation, devices A1, A2 and UAV U3 are allocated to the same channel. There is no conflict between UAV U5 and either device B1 or B2 of operator B, so it joins the occupied channel of operator B; at the end of the third round of allocation, devices B1, B2 and UAV U5 are allocated to the same channel.

[0107] Furthermore, the coloring rule mainly includes the following steps: assign the same color to the UAVs and operator devices allocated on the same channel; assign different colors to the UAVs and operator devices allocated on different channels. Specifically, as Figure 5 shown, it is the conflict graph of coloring provided by the embodiment of the present invention. UAV U1, UAV U2 and UAV U4 are all allocated to the idle channel of operator A, so they are all yellow; devices A1, A2 and UAV U3 are all allocated to the occupied channel of operator A, so they are all purple; devices B1, B2 and UAV U5 are all allocated to the occupied channel of operator B, so they are all blue. Thus, the allocation of the spectrum leased by the operator for the UAVs is realized, and at the same time, the interference effect is avoided.

[0108] The method for allocating the communication spectrum of drones based on interference provided in this embodiment first generates conflict relationships and constructs a conflict graph to describe the interference situations among various devices; then uses allocation rules to allocate spectrum resources to the drones; and finally uses coloring rules to color the allocation results, thereby completing one round of spectrum resource allocation; through multiple rounds of allocation and coloring, a spectrum allocation scheme that maximizes the operator's utility is obtained, which not only meets the QoS requirements of the operator and the drones, but also effectively improves the spectrum utilization rate.

[0109] Figures 1 to 3 Only the logical order of the method described in this embodiment is shown. On the premise of no conflict, in other possible embodiments of the present invention, the steps shown or described can be completed in a different order from Figures 1 to 3 the order shown. The method for allocating the communication spectrum of drones based on interference provided in this embodiment can be applied to terminals and can be executed by a device for allocating the communication spectrum of drones based on interference. This device can be implemented in software and / or hardware, and this device can be integrated in a terminal, for example: any smart phone, tablet computer or computer device with a communication function.

[0110] Embodiment 2:

[0111] The method for allocating the communication spectrum of drones based on interference provided in this embodiment is different from that in Embodiment 1 in that, in order to generate the conflict relationships among various devices, it is necessary to calculate the interference situation through a path loss model. Assuming that the communication links between the operator and the drones and between the drones are different, the path loss models corresponding to the conflict relationships mainly include: the path loss model of the communication link between the operator and the drones and the path loss model of the communication link between the drones;

[0112] The expression of the path loss model of the communication link between the operator and the drones is:

[0113] ,

[0114] where

[0115] ,

[0116] ,

[0117] ,

[0118] ,

[0119] In the formula, is the path loss of the communication link between the operator and the drones, is the distance between the operator and the drones; and are the LOS path loss and the NLOS path loss respectively; and are the probabilities that the communication link is the LOS path and the NLOS path respectively; is the speed of light; is the carrier frequency; and are the average additional losses of the LOS path and the NLOS path respectively; and are both constants related to the environment; is the angle between the operator's equipment and the UAV;

[0120] The expression of the communication link path loss model between UAVs is:

[0121] ,

[0122] In the formula, is the communication link path loss between UAVs, is the distance between UAVs; is the path loss exponent; is the reference distance.

[0123] Embodiment III:

[0124] This embodiment provides a method for allocating UAV communication spectrum based on interference. The difference from Embodiment I is that the utility function of the operator includes: the service revenue, rental revenue and interference impact of the operator, and the expression is:

[0125] ,

[0126] In the formula, is the utility function of the operator; is the service fee obtained by the operator; is the service fee paid by each UAV when obtaining a spectrum license; is the number of UAVs that successfully lease the spectrum; is the revenue obtained by the operator from leasing the spectrum; is the th price of the UAV leasing the spectrum; ; is the benefit loss brought by the interference suffered by the operator when leasing the spectrum; is the weighting coefficient; is the number of channels leased by the operator.

[0127] Furthermore, the expression of the non-linear optimization problem regarding the operator's utility function is:

[0128] ,

[0129] In the formula, represents whether the channel is allocated to the drone , represents the channel allocated to the drone , represents the channel not allocated to the drone .

[0130] It should be noted that is the service fee obtained by the operator; is the income obtained by the operator from leasing the spectrum; is the benefit loss caused by the interference when the operator leases the spectrum. The more successful the number of drone leases is for the first two items, the higher the income obtained by the operator; while for the last item, the more successful the number of drone leases is, the more channels are leased, and the greater the impact of the interference. Therefore, the non-linear optimization problem of the operator's utility function is how to allocate the leased channels so as to connect more drones with as few channels as possible.

[0131] Specifically, the constraint condition expression of the non-linear optimization problem is:

[0132] ,

[0133] ,

[0134] ,

[0135] ,

[0136] In the formula, is the set of channel numbers, ; is the set of drone numbers; represents that the drone is affected by co-channel conflict interference; is the set of conflict relationship numbers, ; represents that the drone is affected by the operator 's interference; is the set of operator numbers, ; is the preset interference threshold for the drone; represents whether the operator leases the channel , Indicates the operator Leased channel , Indicates the operator Does not lease the channel ; Is the minimum interference tolerable by the preset operator; Indicates the operator Whether to occupy the channel , Indicates the operator Is occupying the channel , Indicates the operator Is not occupying the channel .

[0137] It should be noted that the first constraint condition is to ensure that each drone can only lease one channel; the second constraint condition is to ensure that the cumulative interference received by each drone from the same channel should be less than or equal to the preset interference threshold; the third constraint condition is to ensure that the cumulative interference received by each operator from the same channel should be less than or equal to the preset minimum interference; the fourth constraint condition is to ensure that the drone can only lease the channel leased by the operator.

[0138] To verify the performance of the allocation method proposed in the embodiments of the present invention, the method in this paper is compared with the comparative method here: "There is no coexistence group in the scenario, using traditional binary conflict, not considering aggregated interference, only considering whether the interference ranges of the two overlap".

[0139] As Figure 6 shown, it is a comparison chart of the operator utility and the drone leased spectrum success rate of the method provided in the embodiments of the present invention and the comparative method under different interference thresholds. As can be seen from Figure 6 , as the interference threshold decreases, the ability of each device to tolerate interference decreases, and it is difficult for the devices to coexist. Therefore, both the operator utility and the drone leased spectrum success rate are decreasing. In addition, since the comparative method uses binary conflict, for the drone U4 in Figure 4 being interfered by the drones U1 and U5, it is determined that the drone U4 cannot be allocated; but the method in this paper uses aggregated interference, and the actual cumulative interference received by the drone U4 does not exceed the interference threshold and does not affect the QoS, which is tolerable interference. Therefore, the method in this paper is significantly better than the comparative method.

[0140] As Figure 7 shown, it is a comparison chart of the operator utility and the drone leased spectrum success rate of the method provided in the embodiments of the present invention and the comparative method under different numbers of drones. As can be seen from Figure 7It can be seen that the method in this paper is significantly better than the comparative method. In addition, as the number of UAVs increases, the number of UAVs that can be accommodated in the channel increases. While the operator's utility continues to increase, the channel's ability to accommodate UAVs gradually decreases; therefore, the success rate of UAVs leasing spectrum gradually decreases. Moreover, due to the limited number of channels, the aggregate interference received by the device is closer to the interference threshold, so the growth rate of the operator's utility slows down.

[0141] As Figure 8 shown, it is a comparison diagram of the operator's utility and the success rate of UAVs leasing spectrum between the method provided in the embodiment of the present invention and the comparative method under different numbers of channels. From Figure 8 it can be seen that the method in this paper is significantly better than the comparative method. In addition, as the number of channels increases, more UAVs can be accommodated. Therefore, both the operator's utility and the success rate of UAVs leasing spectrum increase. However, after all the idle channels are allocated, the channels already occupied by the operator's devices will be allocated. Compared with the idle channels, the number of UAVs that can be accommodated in the occupied channels decreases, and the performance of the operator's devices cannot be interfered. Therefore, the growth rates of the operator's utility and the success rate of UAVs leasing spectrum slow down.

[0142] Embodiment 4:

[0143] This embodiment provides a UAV communication spectrum allocation device based on interference. As Figure 9 shown, the device includes:

[0144] An information collection module: used to obtain information of both parties in the spectrum transaction;

[0145] An incentive setting module: used to set an incentive mechanism for the operator according to the information to obtain the utility function of the operator;

[0146] A problem construction module: used to construct a non-linear optimization problem according to the constraints corresponding to the preset number of channels leased by the operator, the number of UAVs, and the QoS requirements of the operator and UAVs, and optimize the utility function of the operator;

[0147] An optimization and solution module: used to solve the non-linear optimization problem by using the allocation rule and the coloring rule to obtain a spectrum allocation scheme that maximizes the operator's utility.

[0148] The UAV communication spectrum allocation device based on interference provided in this embodiment can execute the UAV communication spectrum allocation method based on interference provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0149] Embodiment 5:

[0150] This embodiment also provides a computer device, which can be a server, and its internal structure diagram can be asFigure 10 As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface.

[0151] Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the data obtained and generated in the method for a robot to autonomously enter a packaging container. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements the methods of the foregoing Embodiments 1 to 3.

[0152] Those skilled in the art can understand that Figure 10 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0153] The computer device provided by the embodiment of the present invention can execute the method for allocating the communication spectrum of an unmanned aerial vehicle based on interference provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0154] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0155] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or a means for implementing the functions specified in one or more of the blocks.

[0156] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including an instruction means that implements the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or a means for implementing the functions specified in one or more of the blocks.

[0157] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or a means for implementing the functions specified in one or more of the blocks.

[0158] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the present invention and the claims. All of these fall within the protection scope of the present invention.

Claims

1. A spectrum allocation method for UAV communication based on interference, characterized in that: The method comprises: Obtain information about both parties in spectrum transactions; Setting an incentive mechanism for the operator based on the information to obtain a utility function of the operator; According to the preset number of leased channels of the operator, the number of drones, and the constraints corresponding to the QoS requirements of the operator and the drones, a nonlinear optimization problem is constructed to optimize the utility function of the operator; The nonlinear optimization problem is solved by using allocation rules and coloring rules to obtain a spectrum allocation scheme that maximizes the utility of the operator.

2. The interference-based spectrum allocation method for UAV communication according to claim 1 is characterized in that: The information of both parties of the spectrum transaction includes: the spectrum leased by the operator to the drone, the lease price provided by the drone to the operator, the transmission power and geographical location of the operator and the drone.

3. The interference-based spectrum allocation method for UAV communication according to claim 1 is characterized in that: The adopting of allocation rules and coloring rules to solve the nonlinear optimization problem to obtain a spectrum allocation scheme that maximizes the utility of the operator includes: Based on the transmission power, geographic location, and QoS requirements of operators and drones, conflict relationships are generated and a conflict graph is constructed; Adopting allocation rules to allocate spectrum for drone operators to lease; Using a coloring rule to color the allocation result on the conflict graph; Determine whether the spectrum leased by the operator has been allocated. In response to the spectrum being allocated, find the maximum operator utility and the corresponding optimal spectrum allocation plan. In response to the spectrum not being allocated, determine whether there is a drone that has not leased the spectrum. In response to the existence of drones that have not leased spectrum, repeat the above steps and continue to the next round of allocation and coloring; in response to the absence of drones, solve the maximum operator utility and the corresponding optimal spectrum allocation plan.

4. The interference-based spectrum allocation method for UAV communication according to claim 3 is characterized in that: The conflict relationship is generated by calculating a path loss model; wherein the path loss model includes: a communication link path loss model between an operator and a UAV and a communication link path loss model between UAVs; The expression of the communication link path loss model between the operator and the drone is: ， in, ， ， ， ， In the formula, is the communication link path loss between the operator and the UAV, is the distance between the operator and the drone; and They are line-of-sight path loss and non-line-of-sight path loss; and The probabilities that the communication link is a line-of-sight path and a non-line-of-sight path, respectively; is the speed of light; is the carrier frequency; and The average additional losses for line-of-sight and non-line-of-sight paths, respectively; and All of them are constants related to the environment; is the angle between the operator’s equipment and the drone; The expression of the communication link path loss model between the UAVs is: ， In the formula, is the communication link path loss between UAVs, is the distance between drones; is the path loss index; is the reference distance.

5. The interference-based spectrum allocation method for UAV communication according to claim 3 is characterized in that: The allocation rules used to allocate spectrum for operators to lease to drones include: Sort the rental prices offered by drones to operators from high to low, and number the drones in ascending order; Determine whether there is an idle channel in the spectrum leased by the operator; in response to the existence of an idle channel, allocate an idle channel to the drone according to the drone number; otherwise, allocate an occupied channel to the drone according to the drone number; In response to allocating an idle channel to a drone, determining whether the drone to be allocated does not conflict with any drone in the idle channel coexistence group, and whether the accumulated interference suffered by the drones in the idle channel coexistence group is less than a preset interference threshold; In response to no conflict and both being less than the interference threshold, the drone to be allocated can join the idle channel coexistence group and allocate an idle channel; otherwise, it is determined whether the drone numbers have been traversed; In response to the traversal not being completed, repeat the above steps to continue to determine the next drone to be assigned; otherwise, one round of assignment is completed; In response to allocating an occupied channel to the drone, determining whether the drone to be allocated conflicts with an operator device in the occupied channel; In response to the conflict, determine whether the traversal of the drone numbers has been completed; otherwise, determine whether the drone to be assigned does not conflict with the drones in the occupied channel coexistence group, and whether the accumulated interference suffered by the drones in the occupied channel coexistence group is less than a preset interference threshold; In response to no conflict and both being less than the interference threshold, the drone to be allocated can join the occupied channel coexistence group and allocate the occupied channel; otherwise, it is determined whether the drone numbers have been traversed; In response to the traversal not being completed, the above steps are repeated to continue to determine the next drone to be assigned; otherwise, a round of assignment is completed.

6. The interference-based spectrum allocation method for UAV communication according to claim 3 is characterized in that: The step of using a coloring rule to color the allocation result on the conflict graph includes: Assign the same color to drones and operator equipment assigned to the same channel; Assign different colors to drones and operator equipment assigned to different channels.

7. The interference-based spectrum allocation method for UAV communication according to claim 1 is characterized in that: The utility function of the operator includes: the operator's service income, rental income and interference impact, and the expression is: ， In the formula, is the utility function of the operator; Service fees received by operators; A service fee paid for obtaining a spectrum license for each drone; The number of drones that have successfully leased spectrum; Revenue from leasing spectrum to operators; For the the price of leasing spectrum for each drone; ; The loss of benefits caused by interference when leasing spectrum to operators; is the weighting coefficient; The number of channels leased to operators.

8. The interference-based spectrum allocation method for UAV communication according to claim 1 is characterized in that: The nonlinear optimization problem expression is: ， In the formula, Indicates channel Is it assigned to a drone? , Indicates channel Assign to drone , Indicates channel Not assigned to drone ; is the utility function of the operator; Service fees received by operators; A service fee paid for obtaining a spectrum license for each drone; The number of drones that have successfully leased spectrum; Revenue from leasing spectrum to operators; For the the price of leasing spectrum for each drone; ; The loss of benefits caused by interference when leasing spectrum to operators; is the weighting coefficient; The number of channels leased to operators; The constraint condition expression is: ， ， ， ， In the formula, is the set of channel numbers, ; is the number of drones; Indicates drone Affected by the conflict of the same channel; is the set of conflict relationship numbers, ; Indicates drone By operator interference; is the set of operator numbers, ; The interference threshold to which the drone is subjected is preset; Indicates the operator Whether to rent the channel , Indicates the operator Lease Channel , Indicates the operator No channel rental ; The minimum interference that can be tolerated by the preset operator; Indicates the operator Is the channel occupied? , Indicates the operator Occupying the channel , Indicates the operator No channel occupied .

9. An interference-based UAV communication spectrum allocation device, characterized in that: include: Information collection module: used to obtain information of both parties of spectrum transaction; Incentive setting module: used to set an incentive mechanism for the operator according to the information to obtain the utility function of the operator; Problem construction module: used to construct a nonlinear optimization problem according to the preset number of operator leased channels, the number of drones, and the constraints corresponding to the QoS requirements of the operator and the drones, and optimize the utility function of the operator; Optimization solution module: used to solve the nonlinear optimization problem by using allocation rules and coloring rules to obtain a spectrum allocation solution that maximizes the utility of the operator.

10. A computer device, characterized in that: including storage media and processors; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 8.

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