Game theory based energy harvesting cognitive radio d2d assisted relay method and apparatus

Abstract

The application discloses a game theory-based energy collection cognitive radio D2D auxiliary relay method and device, which comprises the following steps: determining the signal-to-noise ratios of multiple target users in a target user set in a cell corresponding to a base station, and dividing the multiple target users in the target user set into cellular users and edge users according to the signal-to-noise ratios of the target users; according to a preset coalition formation strategy, forming multiple pre-formed coalitions from the cellular users and the edge users; judging whether a non-supercalition exists in each pre-formed coalition; when it is judged that a non-supercalition exists in each pre-formed coalition, obtaining a coalition utility value corresponding to the non-supercalition, taking the non-supercalition corresponding to the maximum coalition utility value as a target-formed coalition, and determining a relay relationship between the cellular users and the edge users according to the target-formed coalition. It can be seen that the application proposes a coalition formation strategy, can realize dynamic spectrum sharing, improves the communication spectrum utilization rate, and further improves the communication efficiency.

Description

Technical Field

[0001] This invention relates to the field of cognitive radio technology, and in particular to a game theory-based cognitive radio D2D assisted relay method and apparatus for energy harvesting. Background Technology

[0002] With the continuous development of wireless communication technology in recent years, the number of wireless communication devices is constantly increasing, and the corresponding wireless communication spectrum has become an increasingly scarce resource.

[0003] The current spectrum allocation method is static and fixed, which means that the spectrum is spaced at fixed intervals and fixed-size spectrum blocks are allocated to different licensed operators for a certain period of time, and then reallocated after the period expires. Although the management mode of static and fixed spectrum allocation is simple, the spectrum utilization rate is relatively low, resulting in a large waste of spectrum resources and reduced communication efficiency.

[0004] Therefore, it is particularly important to propose a dynamic spectrum sharing strategy to improve the utilization of communication spectrum and thus improve communication efficiency. Summary of the Invention

[0005] The technical problem to be solved by this invention is to provide a game theory-based energy harvesting cognitive radio D2D assisted relay method and device, which can improve the utilization rate of communication spectrum and thus improve communication efficiency.

[0006] To address the aforementioned technical problems, the first aspect of this invention discloses a game theory-based energy harvesting cognitive radio D2D-assisted relay method, the method comprising:

[0007] Determine the signal-to-noise ratio (SNR) of multiple target users in the target user set within the cell corresponding to the base station, and divide the multiple target users in the target user set into cellular users and edge users based on the SNR of the target users, wherein the SNR of the cellular users is greater than the SNR of the edge users;

[0008] According to a preset alliance composition strategy, the cellular users and the edge users are formed into multiple pre-composed alliances, and each pre-composed alliance includes at least one cellular user and at least one edge user;

[0009] Determine whether each of the pre-formed alliances is a non-super alliance. When it is determined that each of the pre-formed alliances is a non-super alliance, obtain the alliance utility value corresponding to the non-super alliance.

[0010] The non-super alliance corresponding to the largest alliance utility value is selected as the target alliance, and the relay relationship between the cellular user and the edge user is determined based on the target alliance.

[0011] As an optional implementation, in the first aspect of the present invention, determining the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station includes:

[0012] A set of target users within the cell corresponding to the base station in a time slot T is determined. From this set, the m-th target user is randomly selected as the first target user, and the n-th target user is randomly selected as the second target user. The signal-to-noise ratio (SNR) of the first target user in the time slot T is determined using a first formula.

[0013] The first formula includes:

[0014]

[0015] Among them, P s Indicates the signal transmission power of the base station; g mB ρ represents the channel gain coefficient between the first target user and the base station; ρ represents the path loss coefficient. This represents the straight-line distance between the first target user and the second target user; This represents the straight-line distance between the first target user and the base station; Represents Gaussian noise; h mn This represents the channel gain coefficient between the first target user and the second target user; θ represents the transmit power of the first target user; m,n Indicates the channel multiplexing flag, and θ m,n =1, the channel multiplexing means that the second target user uses the channel of the first target user.

[0016] As an optional implementation, in the first aspect of the present invention, the step of forming multiple pre-formed alliances of the cellular users and the edge users according to a preset alliance formation strategy includes:

[0017] According to the preset alliance composition strategy (L,v), the cellular users and the edge users are arranged and combined to obtain multiple pre-composed alliances;

[0018] Where L represents the set of cellular users M = {Cu1, Cu2, ..., Cu...} m The set of edge users K = {Du1,Du2,…,Du} k Let L be the maximum set of users that can form a pre-formed alliance, and L = {M∪K}, where m ≥ 1 and k ≥ 1.

[0019] As an optional implementation, in the first aspect of the invention, the alliance utility value of the pre-formed alliance is determined by a second formula, the second formula comprising:

[0020]

[0021] Where i represents the i-th pre-formed alliance, and i ≤ min(m,k); R i c R represents the data transmission rate of the cellular user in the i-th pre-formed alliance. i c The calculation formula is:

[0022]

[0023] as well as, The signal-to-noise ratio of the cellular user in the i-th pre-formed alliance under the time slot T is represented by the following: The calculation formula is the first formula;

[0024] This represents the data transmission rate of the edge user in the i-th pre-formed alliance. The calculation formula is:

[0025]

[0026] as well as, ω represents the energy value collected by the cellular user; β represents the energy collection coefficient; i The cellular user represents the percentage of time they assist the edge user in transmitting data during time slot T; α represents the percentage of time slots used for energy harvesting; Q represents the percentage of time slots used for energy harvesting. k This represents the set of users in the pre-formed alliance; This represents the signal-to-noise ratio of the kth edge user when the mth cellular user assists the kth edge user in transmitting data;

[0027] Furthermore, when the m-th cellular user assists the k-th edge user in transmitting data, the signal-to-noise ratio of the k-th edge user... The calculation formula is:

[0028]

[0029] as well as, g represents the transmit power of the m-th edge user; km This represents the channel gain coefficient between the k-th edge user and the m-th cellular user; This represents the distance between the k-th cellular user and the base station; This represents the distance between the k-th edge user and the m-th cellular user; The Gaussian white noise is represented by h. kB P represents the channel gain coefficient between the k-th edge user and the base station; s Indicates the base station's transmit power; θ m,n Indicates the channel multiplexing flag, and θ m,n =1, the channel multiplexing means that the second target user uses the channel of the first target user.

[0030] As an optional implementation, in the first aspect of the present invention, the step of arranging and combining the cellular users and the edge users to obtain multiple pre-formed alliances according to a preset alliance composition strategy (L,v) includes:

[0031] According to the preset alliance composition strategy (L,v), at least one cellular user and at least one edge user are randomly selected from the set L to form a pre-composed alliance with two alliance combination forms.

[0032] And, the first pre-formed alliance is P1 = {{Du} i},{Cu j The second pre-formed alliance is P2 = {Du} i Cu j};

[0033] According to the second formula, the utility value of the first pre-formed alliance is determined as follows:

[0034]

[0035] Based on the second formula, the alliance utility value of the second prospective alliance user is determined as follows:

[0036]

[0037] Where i and j represent the numbers of cellular users and edge users in each pre-formed alliance, and i≤k, j≤m.

[0038] As an optional implementation, in the first aspect of the present invention, determining whether any of the pre-formed alliances are non-super alliances includes:

[0039] Comparing the utility value of the second pre-formed alliance with the utility value of the first pre-formed alliance, we obtain:

[0040]

[0041] when When, then v(Cu) m ∪Duk ) <v(Cu m )+v(Du k ), thus determining that each of the pre-formed alliances contains a non-super alliance.

[0042] As an optional implementation, in the first aspect of the present invention, after forming multiple pre-formed alliances of cellular users and edge users according to a preset alliance formation strategy, the method further includes:

[0043] Generate energy harvesting control parameters and control the cellular users to harvest energy from the base station's N frequency band signals.

[0044] as well as,

[0045]

[0046] Where, β i The α represents the percentage of time a cellular user in the i-th pre-formed alliance assists the edge user in transmitting data in time slot T; α represents the percentage of time slots used for energy harvesting; η represents the energy harvesting efficiency; P s Indicates the signal transmission power of the base station; g i This represents the channel gain coefficient between the base station and the cellular user; This indicates the distance between the base station and the cellular user.

[0047] A second aspect of this invention discloses a game theory-based energy harvesting cognitive radio D2D-assisted relay device, the device comprising:

[0048] The determination module is used to determine the signal-to-noise ratio (SNR) of multiple target users in the target user set within the cell corresponding to the base station, and to divide the multiple target users in the target user set into cellular users and edge users based on the SNR of the target users, wherein the SNR of the cellular users is greater than the SNR of the edge users;

[0049] The composition module is used to form multiple pre-composed alliances of the cellular users and the edge users according to a preset alliance composition strategy, wherein each pre-composed alliance includes at least one cellular user and at least one edge user;

[0050] The judgment module is used to determine whether any of the pre-formed alliances are non-super alliances;

[0051] The acquisition module is used to acquire the alliance utility value corresponding to the non-super alliance when it is determined that there is a non-super alliance in each of the pre-formed alliances.

[0052] The determining module is further configured to select the non-super alliance corresponding to the largest alliance utility value as the target alliance, and determine the relay relationship between the cellular user and the edge user based on the target alliance.

[0053] As an optional implementation, in a second aspect of the present invention, the method by which the determining module determines the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station includes:

[0054] A set of target users within the cell corresponding to the base station in a time slot T is determined. From this set, the m-th target user is randomly selected as the first target user, and the n-th target user is randomly selected as the second target user. The signal-to-noise ratio (SNR) of the first target user in the time slot T is determined using a first formula.

[0055] The first formula includes:

[0056]

[0057] Among them, P s Indicates the signal transmission power of the base station; g mB ρ represents the channel gain coefficient between the first target user and the base station; ρ represents the path loss coefficient. This represents the straight-line distance between the first target user and the second target user; This represents the straight-line distance between the first target user and the base station; Represents Gaussian noise; h mn This represents the channel gain coefficient between the first target user and the second target user; θ represents the transmit power of the first target user; m,n Indicates the channel multiplexing flag, and θ m,n =1, the channel multiplexing means that the second target user uses the channel of the first target user.

[0058] As an optional implementation, in a second aspect of the present invention, the method by which the component module forms multiple pre-composed alliances of the cellular users and the edge users according to a preset alliance composition strategy includes:

[0059] According to the preset alliance composition strategy (L,v), the cellular users and the edge users are arranged and combined to obtain multiple pre-composed alliances;

[0060] Where L represents the set of cellular users M = {Cu1, Cu2, ..., Cu...} m The set of edge users K = {Du1,Du2,…,Du} kLet L be the maximum set of users that can form a pre-formed alliance, and L = {MUK}, where m ≥ 1 and k ≥ 1.

[0061] As an optional implementation, in a second aspect of the invention, the component module determines the alliance utility value of the pre-formed alliance using a second formula, the second formula comprising:

[0062]

[0063] Where i represents the i-th pre-formed alliance, and i ≤ min(m,k); R i c R represents the data transmission rate of the cellular user in the i-th pre-formed alliance. i c The calculation formula is:

[0064]

[0065] as well as, The signal-to-noise ratio of the cellular user in the i-th pre-formed alliance under the time slot T is represented by the following: The calculation formula is the first formula;

[0066] This represents the data transmission rate of the edge user in the i-th pre-formed alliance. The calculation formula is:

[0067]

[0068] as well as, ω represents the energy value collected by the cellular user; β represents the energy collection coefficient; i The cellular user represents the percentage of time they assist the edge user in transmitting data during time slot T; α represents the percentage of time slots used for energy harvesting; Q represents the percentage of time slots used for energy harvesting. k This represents the set of users in the pre-formed alliance; This represents the signal-to-noise ratio of the kth edge user when the mth cellular user assists the kth edge user in transmitting data;

[0069] Furthermore, when the m-th cellular user assists the k-th edge user in transmitting data, the signal-to-noise ratio of the k-th edge user... The calculation formula is:

[0070]

[0071] as well as, g represents the transmit power of the m-th edge user; kmThis represents the channel gain coefficient between the k-th edge user and the m-th cellular user; This represents the distance between the k-th cellular user and the base station; This represents the distance between the k-th edge user and the m-th cellular user; The Gaussian white noise is represented by h. kB P represents the channel gain coefficient between the k-th edge user and the base station; s Indicates the base station's transmit power; θ m,n Indicates the channel multiplexing flag, and θ m,n =1, the channel multiplexing means that the second target user uses the channel of the first target user.

[0072] As an optional implementation, in a second aspect of the present invention, the method by which the composition module arranges and combines the cellular users and the edge users to obtain multiple pre-composed alliances according to a preset alliance composition strategy (L,v) includes:

[0073] According to the preset alliance composition strategy (L,v), at least one cellular user and at least one edge user are randomly selected from the set L to form a pre-composed alliance with two alliance combination forms.

[0074] And, the first pre-formed alliance is P1 = {{Du} i},{Cu j The second pre-formed alliance is P2 = {Du} i Cu j};

[0075] According to the second formula, the utility value of the first pre-formed alliance is determined as follows:

[0076]

[0077] Based on the second formula, the alliance utility value of the second prospective alliance user is determined as follows:

[0078]

[0079] Where i and j represent the numbers of cellular users and edge users in each pre-formed alliance, and i≤k, j≤m.

[0080] As an optional implementation, in a second aspect of the invention, the method by which the determining module determines whether any of the pre-formed alliances are non-super alliances includes:

[0081] Comparing the utility value of the second pre-formed alliance with the utility value of the first pre-formed alliance, we obtain:

[0082]

[0083] when When, then v(Cu) m UDu k ) <v(Cu m )+v(Du k ), thus determining that each of the pre-formed alliances contains a non-super alliance.

[0084] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0085] The generation module is used to generate energy harvesting control parameters after the composition module forms multiple pre-composed alliances of the cellular users and the edge users according to a preset alliance composition strategy.

[0086] The control module is used to control the energy of the cellular user in collecting signals from the base station across N frequency bands.

[0087] as well as,

[0088]

[0089] Where, β i The α represents the percentage of time a cellular user in the i-th pre-formed alliance assists the edge user in transmitting data in time slot T; α represents the percentage of time slots used for energy harvesting; η represents the energy harvesting efficiency; P s Indicates the signal transmission power of the base station; g i This represents the channel gain coefficient between the base station and the cellular user; This indicates the distance between the base station and the cellular user.

[0090] A third aspect of this invention discloses another game theory-based energy harvesting cognitive radio D2D-assisted relay device, the device comprising:

[0091] Memory containing executable program code;

[0092] A processor coupled to the memory;

[0093] The processor calls the executable program code stored in the memory to execute the game theory-based cognitive radio D2D assisted relay method for energy harvesting disclosed in the first aspect of the present invention.

[0094] The fourth aspect of the present invention discloses a computer-storable medium storing computer instructions, which, when invoked, are used to execute the game theory-based cognitive radio D2D assisted relay method for energy harvesting disclosed in the first aspect of the present invention.

[0095] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0096] This invention, in its embodiments, determines the signal-to-noise ratio (SNR) of multiple target users within a target user set within a cell corresponding to a base station. Based on the SNR of the target users, these users are divided into cellular users and edge users, with the SNR of cellular users being greater than that of edge users. According to a preset alliance composition strategy, cellular users and edge users are grouped into multiple pre-formed alliances, each pre-formed alliance including at least one cellular user and at least one edge user. It is determined whether any pre-formed alliance contains a non-super alliance. When a non-super alliance is found, the alliance utility value corresponding to the non-super alliance is obtained. The non-super alliance corresponding to the highest alliance utility value is selected as the target alliance, and the relay relationship between cellular users and edge users is determined based on the target alliance. Therefore, this invention can divide all users into cellular users and edge users based on the user SNR within the current target range and utilize cellular users to provide relay support for data transmission to edge users. Meanwhile, in order to verify that cellular users provide relay support for data transmission to edge users with the highest efficiency, a coalition formation strategy is proposed, and it is verified whether the pre-formed coalition is a non-super-additive coalition. The non-super-additive coalition formation scheme with the highest coalition utility value is determined as the final scheme, thereby realizing dynamic spectrum sharing, improving communication spectrum utilization, and thus improving communication efficiency. Attached Figure Description

[0097] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0098] Figure 1 This is a flowchart illustrating a game theory-based cognitive radio D2D assisted relay method for energy harvesting disclosed in an embodiment of the present invention.

[0099] Figure 2 This is a flowchart illustrating another D2D-assisted relay method for energy harvesting cognitive radio based on game theory disclosed in an embodiment of the present invention.

[0100] Figure 3 This is a schematic diagram of the structure of a game theory-based cognitive radio D2D assisted relay device for energy harvesting disclosed in an embodiment of the present invention;

[0101] Figure 4This is a schematic diagram of another D2D-assisted relay device for energy harvesting cognitive radio based on game theory disclosed in an embodiment of the present invention;

[0102] Figure 5 This is a schematic diagram of another energy harvesting cognitive radio D2D-assisted relay device based on game theory disclosed in an embodiment of the present invention. Detailed Implementation

[0103] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0104] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0105] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0106] This invention discloses a game theory-based energy harvesting cognitive radio D2D assisted relay method and device. It can classify all users into cellular users and edge users based on the signal-to-noise ratio (SNR) within the current target range, and utilize cellular users to provide relay support for data transmission to edge users. Simultaneously, to verify that cellular users provide the most efficient relay support for edge users, a coalition formation strategy is proposed, and it is verified whether the pre-formed coalitions are non-super-additive coalitions. The non-super-additive coalition formation scheme with the highest coalition utility value is determined as the final scheme, thereby achieving dynamic spectrum sharing, improving communication spectrum utilization, and ultimately enhancing communication efficiency. Detailed explanations follow.

[0107] Example 1

[0108] Please see Figure 1 , Figure 1 This is a flowchart illustrating a game theory-based cognitive radio D2D assisted relay method for energy harvesting disclosed in an embodiment of the present invention. Figure 1 The described game theory-based cognitive radio D2D assisted relay method for energy harvesting can be applied to spectrum sharing devices with cognitive radio capabilities, wireless LAN systems with cognitive functions, or mesh networks, MIMO systems, military equipment, and cloud / network platforms with the aforementioned capabilities. This invention does not limit the application of this method. Figure 1 As shown, this game theory-based energy harvesting cognitive radio D2D assisted relay method may include the following operations:

[0109] 101. Determine the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station.

[0110] 102. Based on the signal-to-noise ratio (SNR) of the target users, the target users in the target user set are divided into cellular users and edge users, with the SNR of cellular users being greater than that of edge users.

[0111] 103. According to the preset alliance composition strategy, cellular users and edge users are divided into multiple pre-composed alliances, and each pre-composed alliance includes at least one cellular user and at least one edge user.

[0112] 104. Determine whether any of the pre-formed alliances are non-super alliances.

[0113] 105. When it is determined that there are non-super alliances in each pre-formed alliance, obtain the alliance utility value corresponding to the non-super alliance.

[0114] 106. Form alliances by targeting the non-super alliances with the highest alliance utility value, and determine the relay relationship between cellular users and edge users based on the alliances formed by the targets.

[0115] Steps 101-106 are implemented in underlay cognitive radio. The fact that the signal-to-noise ratio (SNR) of the cellular user is greater than that of the edge user indicates that the communication quality of the cellular user is better than that of the edge user. Furthermore, when cellular users and edge users form a pre-formed alliance, the cellular user can also be called a relay user. This means the cellular user provides relay support for data transmission to the edge users in the pre-formed alliance, thereby improving the communication efficiency of the edge users and ultimately improving the communication efficiency of the target users within the cell corresponding to the base station. Before providing relay transmission to the edge users, the cellular user needs to harvest energy from the base station to enable relay transmission.

[0116] As can be seen, the embodiments of the present invention can classify all users into cellular users and edge users based on the signal-to-noise ratio of users within the current target range, and utilize cellular users to provide relay support for data transmission to edge users. Simultaneously, to verify that the efficiency of cellular users providing relay support for data transmission to edge users is maximized, an alliance formation strategy is proposed, and it is verified whether the pre-formed alliances are non-super-additive alliances. The non-super-additive alliance formation scheme with the highest alliance utility value is determined as the final scheme, thereby achieving dynamic spectrum sharing, improving communication spectrum utilization, and ultimately improving communication efficiency.

[0117] In this embodiment of the invention, as an optional implementation, determining the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station may include:

[0118] A set of target users within the cell corresponding to the base station in a time slot T is determined. From this set, the m-th target user is randomly selected as the first target user, and the n-th target user is randomly selected as the second target user. The signal-to-noise ratio (SNR) of the first target user in time slot T is determined using a first formula.

[0119] The first formula includes:

[0120]

[0121] Among them, P s Indicates the signal transmission power of the base station; g mB ρ represents the channel gain coefficient between the first target user and the base station; ρ represents the path loss coefficient. This represents the straight-line distance between the first target user and the second target user; This represents the straight-line distance between the first target user and the base station; Represents Gaussian noise; h mn This represents the channel gain coefficient between the first target user and the second target user; θ represents the transmit power of the first target user; m,n Indicates the channel multiplexing flag, and θ m,n =1, channel multiplexing means that the second target user uses the channel of the first target user.

[0122] Furthermore, the aforementioned first and second target users are two target users randomly selected within the cell corresponding to the base station. Before calculating their signal-to-noise ratio (SNR), it is not confirmed whether the two target users are cellular users or edge users. Additionally, when calculating the SNR of a randomly selected target user, the influence of surrounding users and the base station on its SNR must be considered. Therefore, the first formula above proposes a proportionality coefficient related to the influence between users, as well as a proportionality coefficient affecting the SNR calculation of the target user in the event of channel reuse between users.

[0123] As can be seen, the embodiments of the present invention propose a method for calculating the signal-to-noise ratio (SNR) of a target user within a cell corresponding to a base station. By considering the influence of surrounding users and the base station on the SNR of the target user, the first formula above proposes a proportional coefficient for the influence between users and a proportional coefficient for the influence on the SNR calculation of the target user in the case of channel reuse between users. This method can accurately calculate the SNR of the target user and provide strong data support for subsequent classification of the target user into cellular users or edge users based on the SNR.

[0124] In this embodiment of the invention, as another optional implementation, the above-mentioned method of forming multiple pre-formed alliances of cellular users and edge users according to a preset alliance formation strategy may include:

[0125] Based on the preset alliance composition strategy (L,v), cellular users and edge users are arranged and combined to obtain multiple pre-composed alliances;

[0126] Where L represents the set of cellular users M = {Cu1, Cu2, ..., Cu...} m The set of edge users K = {Du1,Du2,…,Du} k Let L be the maximum set of users that can form a pre-formed alliance, and L = {MUK}.

[0127] Furthermore, the aforementioned preset alliance formation strategy is a pre-formed alliance formation strategy, providing a formation strategy capable of traversing all cases of cellular users and edge users within the cell corresponding to the current base station forming a pre-formed alliance strategy. Additionally, the number of cellular user sets m ≥ 1 and the number of edge user sets k ≥ 1.

[0128] As can be seen, the embodiments of the present invention provide a composition strategy that can traverse all cases of cellular users and edge users in the cell corresponding to the current base station forming a pre-composed alliance strategy. This can prevent different actual user situations from occurring according to different application scenarios. The method proposed in this invention lacks universality, thus providing support for subsequent calculation of the utility value of the pre-composed alliance and verification that the pre-composed alliance is a non-super-additive alliance.

[0129] In another optional implementation of this invention, the utility value of the pre-formed alliance can be determined by a second formula, which includes:

[0130]

[0131] Where i represents the i-th pre-formed alliance, and i ≤ min(m,k); R i c R represents the data transmission rate of cellular users in the i-th pre-formed alliance. i The formula for calculating c is:

[0132]

[0133] as well as, This represents the signal-to-noise ratio of cellular users in the i-th pre-formed alliance under time slot T. The calculation formula is the first formula;

[0134] This represents the data transmission rate of the edge users in the i-th pre-formed alliance. The calculation formula is:

[0135]

[0136] as well as, ω represents the energy collected by cellular users; β represents the energy collection coefficient; i The α represents the percentage of time a cellular user assists an edge user in transmitting data during time slot T; α represents the percentage of time slots used for energy harvesting; Q k This represents a pre-formed alliance of users; This represents the signal-to-noise ratio of the k-th edge user when the m-th cellular user assists the k-th edge user in transmitting data;

[0137] Furthermore, when the m-th cellular user assists the k-th edge user in transmitting data, the signal-to-noise ratio of the k-th edge user is... The calculation formula is:

[0138]

[0139] as well as, g represents the transmit power of the m-th edge user; km This represents the channel gain coefficient between the k-th edge user and the m-th cellular user; This represents the distance between the k-th cellular user and the base station; This represents the distance between the k-th edge user and the m-th cellular user; Represents Gaussian white noise; h kBP represents the channel gain coefficient between the k-th edge user and the base station; s Indicates the base station's transmit power; θ m,n Indicates the channel multiplexing flag, and θ m,n =1, channel multiplexing means that the second target user uses the channel of the first target user.

[0140] In the aforementioned formula for calculating the alliance utility value, similar to the calculation of the signal-to-noise ratio (SNR) of a randomly selected target user, the influence of surrounding users and base stations on the SNR of the target user needs to be considered. Therefore, the formula needs to include a proportional coefficient for the influence between users, as well as a proportional coefficient for the influence on the SNR calculation of the target user in the case of channel reuse between users.

[0141] As can be seen, the embodiments of the present invention can calculate the alliance utility value of each pre-formed alliance, and considering that during the relay transmission process, there are still issues such as the impact of surrounding users, base stations, and channel multiplexing on the calculation of the alliance utility value, the accuracy of the alliance utility value calculation can be improved.

[0142] In an optional embodiment, the above-described method of arranging and combining cellular users and edge users to obtain multiple pre-formed alliances according to a preset alliance composition strategy (L,v) may include:

[0143] According to the preset alliance composition strategy (L,v), at least one cellular user and at least one edge user are randomly selected from the set L to form a pre-composed alliance with two alliance combination forms.

[0144] And, the first pre-formed alliance is P1 = {{Du} i},{Cu j The second pre-formed alliance is P2 = {Du} i Cu j};

[0145] According to the second formula, the utility value of the first pre-formed alliance is determined as follows:

[0146]

[0147] According to the second formula, the alliance utility value of the second prospective alliance user is determined as follows:

[0148]

[0149] Where i and j represent the numbers of cellular users and edge users in each pre-formed alliance, and i≤k, j≤m.

[0150] In this optional embodiment, a preset alliance composition strategy is proposed, and at least one cellular user and at least one edge user randomly selected from the above permutations and combinations are formed into a pre-composed alliance. The pre-composed alliance is then split to obtain the alliance utility value before and after the split.

[0151] As an optional embodiment, the alliance formation strategy proposed in this invention is not limited to the way of forming an alliance between a cellular user and an edge user. The above-mentioned alliance formation method is only one method of formation. Depending on the specific application scenario, the number of users forming the alliance can be stacked. However, the purpose of the alliance formation method proposed in this invention is to improve the communication spectrum utilization of all users in the application scenario, thereby improving the communication efficiency of all users.

[0152] As can be seen, the alliance utility values ​​obtained before and after the split in this optional embodiment provide a basis for verifying whether the alliance is a super-additive alliance, thus providing a basis for the present invention to improve communication spectrum utilization and thereby improve communication efficiency.

[0153] In this optional embodiment, as an optional implementation, the above-mentioned determination of whether each pre-formed alliance has a non-super alliance may include:

[0154] Comparing the utility value of the second pre-formed coalition with that of the first pre-formed coalition, we obtain:

[0155]

[0156] when When, then v(Cu) m ∪Du k ) <v(Cu m )+v(Du k ), thus determining that there are non-super alliances in each pre-formed alliance.

[0157] when When, then v(Cu) m ∪Du k )>v(Cu m )+v(Du k ), thus confirming that each pre-formed alliance has a super alliance.

[0158] As can be seen, this optional embodiment verifies that the pre-formed alliance exists as a non-super-additive alliance, and verifies that P1 = {{Du} i},{Cu j The alliance with the highest utility value is P1 = {{Du}, so in this verification scenario, the final choice is to put P1 = {{Du}. i},{Cu j The alliance formation strategy was determined as the final alliance formation strategy.

[0159] Example 2

[0160] Please see Figure 2 , Figure 2 This is a flowchart illustrating a game theory-based cognitive radio D2D assisted relay method for energy harvesting disclosed in an embodiment of the present invention. Figure 2 The described game theory-based cognitive radio D2D assisted relay method for energy harvesting can be applied to spectrum sharing devices with cognitive radio capabilities, wireless LAN systems with cognitive functions, or mesh networks, MIMO systems, military equipment, and cloud / network platforms with the aforementioned capabilities. This invention does not limit the application of this method. Figure 2 As shown, this game theory-based energy harvesting cognitive radio D2D assisted relay method may include the following operations:

[0161] 201. Determine the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station.

[0162] 202. Based on the signal-to-noise ratio (SNR) of the target users, the target users in the target user set are divided into cellular users and edge users, with the SNR of cellular users being greater than that of edge users.

[0163] 203. Based on the preset alliance composition strategy, cellular users and edge users are grouped into multiple pre-composed alliances.

[0164] 204. Generate energy harvesting control parameters.

[0165] 205. Controlling the energy of cellular user acquisition base station signals across N frequency bands.

[0166] 206. Determine whether any of the pre-formed alliances are non-super alliances.

[0167] 207. When it is determined that there are non-super alliances in each pre-formed alliance, obtain the alliance utility value corresponding to the non-super alliance.

[0168] 208. Form alliances by targeting the non-super alliances corresponding to the largest alliance utility value, and determine the relay relationship between cellular users and edge users based on the alliances formed by the targets.

[0169] In this embodiment of the invention, for other descriptions of steps 201-203 and steps 206-208, please refer to the detailed description of steps 101-106 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0170] Among them, the energy of N frequency band signals collected by cellular user base stations The formula for determining it is:

[0171]

[0172] And, β i α represents the percentage of time a cellular user in the i-th pre-formed alliance assists an edge user in transmitting data in time slot T; α represents the percentage of time slots used for energy harvesting; η represents the energy harvesting efficiency; P s Indicates the signal transmission power of the base station; g i This represents the channel gain coefficient between the base station and the cellular user; This indicates the distance between the base station and the cellular user.

[0173] In this embodiment of the invention, the aforementioned cellular user needs to first collect energy from the base station before providing relay transmission to the edge user in order to provide relay transmission to the edge user.

[0174] As can be seen, the embodiments of the present invention provide a calculation formula for the energy collected by cellular users as relay users to provide relay transmission to edge users, which improves the accuracy of energy collection when cellular users provide relay transmission to edge users, and thus lays the foundation for the subsequent formation of pre-formed alliances and the provision of relay transmission.

[0175] In an optional embodiment, within the target user set corresponding to the aforementioned base station cell, a target user set L = {Du1, Cu1, Cu2} has been determined, along with a cellular user set M = {Cu1, Cu2} and an edge user set K = {Du1}. Based on a preset alliance formation strategy (L, v), a first pre-formed alliance is formed as P1 = {Q1, Q2}, where Q1 = {Du1, Cu1} and Q2 = {Cu2}. A second pre-formed alliance is formed as P2 = {Du1, Cu2, Cu3}. Energy harvesting control parameters are generated to control the energy harvested by the cellular users participating in assisting edge user relay transmission for the base station's N frequency band signals. This was intended to lay the foundation for energy consumption in assisting edge users with relay transmission later.

[0176] At this point, the alliance utility values ​​v(P1) = v(Q1) + v(Q2) and v(P2) for the two pre-formed alliances are calculated.

[0177] When v(P2)-v(P1)<0, it is determined that each pre-formed alliance has a non-super-additive alliance, that is, a non-super alliance. The non-super alliance corresponding to the largest alliance utility value is determined as the target alliance. The relay relationship between cellular users and edge users is determined according to the target alliance. That is, the pre-formed alliance composed of P1={Q1,Q2}, where Q1={Du1,Cu1} and Q2={Cu2} is the final alliance formation strategy for cellular users in the cell corresponding to the base station to assist edge users in relay transmission.

[0178] As can be seen, this optional embodiment illustrates that a large alliance composed of all users is not necessarily the optimal strategy for the alliance. There must exist an alliance segment whose alliance benefits are greater than those of a large alliance composed of all users. By arranging and combining all cellular users and edge users into a pre-formed alliance, it is determined whether the utility value of the pre-formed alliance can reach the maximum alliance utility value within the cell, that is, whether the communication efficiency of all users within the cell reaches the maximum. This can effectively improve the communication efficiency of all users within the cell, and there is no omission in the judgment. This effectively achieves the technical problem of low spectrum resource utilization and inability to achieve dynamic spectrum sharing, as described in this invention.

[0179] Example 3

[0180] Please see Figure 3 , Figure 3 This is a schematic diagram of a game theory-based energy harvesting cognitive radio D2D assisted relay device disclosed in an embodiment of the present invention. Figure 3 The described game theory-based energy harvesting cognitive radio D2D assisted relay device can be applied to spectrum sharing equipment with cognitive radio functionality, wireless LAN systems with cognitive functions, or mesh networks, MIMO systems, military equipment, and cloud / network platforms with the aforementioned functions. This invention does not limit the application to these applications. Figure 3 As shown, the game theory-based energy harvesting cognitive radio D2D-assisted relay device may include:

[0181] The determination module 301 is used to determine the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station.

[0182] The determination module 301 is also used to divide multiple target users in the target user set into cellular users and edge users according to the signal-to-noise ratio of the target users, wherein the signal-to-noise ratio of the cellular users is greater than that of the edge users.

[0183] The composition module 302 is used to form multiple pre-composed alliances of cellular users and edge users according to a preset alliance composition strategy. Each pre-composed alliance includes at least one cellular user and at least one edge user.

[0184] The judgment module 303 is used to determine whether there is a non-super alliance in each pre-formed alliance.

[0185] The acquisition module 304 is used to acquire the utility value of the non-super alliance when it is determined that there is a non-super alliance in each pre-formed alliance.

[0186] The determination module 301 is also used to form an alliance by taking the non-super alliance corresponding to the largest alliance utility value as the target, and to determine the relay relationship between cellular users and edge users based on the alliance formed by the target.

[0187] Steps 101-106 are implemented in underlay cognitive radio. The fact that the signal-to-noise ratio (SNR) of the cellular user is greater than that of the edge user indicates that the communication quality of the cellular user is better than that of the edge user. Furthermore, when cellular users and edge users form a pre-formed alliance, the cellular user can also be called a relay user. This means the cellular user provides relay support for data transmission to the edge users in the pre-formed alliance, thereby improving the communication efficiency of the edge users and ultimately improving the communication efficiency of the target users within the cell corresponding to the base station. Before providing relay transmission to the edge users, the cellular user needs to harvest energy from the base station to enable relay transmission.

[0188] As can be seen, the embodiments of the present invention can classify all users into cellular users and edge users based on the signal-to-noise ratio of users within the current target range, and utilize cellular users to provide relay support for data transmission to edge users. Simultaneously, to verify that the efficiency of cellular users providing relay support for data transmission to edge users is maximized, an alliance formation strategy is proposed, and it is verified whether the pre-formed alliances are non-super-additive alliances. The non-super-additive alliance formation scheme with the highest alliance utility value is determined as the final scheme, thereby achieving dynamic spectrum sharing, improving communication spectrum utilization, and ultimately improving communication efficiency.

[0189] In this embodiment of the invention, as an optional implementation, the method by which the determining module 301 determines the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station includes:

[0190] A set of target users within the cell corresponding to the base station in a time slot T is determined. From this set, the m-th target user is randomly selected as the first target user, and the n-th target user is randomly selected as the second target user. The signal-to-noise ratio (SNR) of the first target user in time slot T is determined using a first formula.

[0191] The first formula includes:

[0192]

[0193] Among them, P s Indicates the signal transmission power of the base station; g mB ρ represents the channel gain coefficient between the first target user and the base station; ρ represents the path loss coefficient. This represents the straight-line distance between the first target user and the second target user; This represents the straight-line distance between the first target user and the base station; Represents Gaussian noise; h mn This represents the channel gain coefficient between the first target user and the second target user; θ represents the transmit power of the first target user; m,n Indicates the channel multiplexing flag, and θ m,n =1, channel multiplexing means that the second target user uses the channel of the first target user.

[0194] Furthermore, the aforementioned first and second target users are two target users randomly selected within the cell corresponding to the base station. Before calculating their signal-to-noise ratio (SNR), it is not confirmed whether the two target users are cellular users or edge users. Additionally, when calculating the SNR of a randomly selected target user, the influence of surrounding users and the base station on its SNR must be considered. Therefore, the first formula above proposes a proportionality coefficient related to the influence between users, as well as a proportionality coefficient affecting the SNR calculation of the target user in the event of channel reuse between users.

[0195] As can be seen, the embodiments of the present invention propose a method for calculating the signal-to-noise ratio (SNR) of a target user within a cell corresponding to a base station. By considering the influence of surrounding users and the base station on the SNR of the target user, the first formula above proposes a proportional coefficient for the influence between users and a proportional coefficient for the influence on the SNR calculation of the target user in the case of channel reuse between users. This method can accurately calculate the SNR of the target user and provide strong data support for subsequent classification of the target user into cellular users or edge users based on the SNR.

[0196] In this embodiment of the invention, as another optional implementation, the above-mentioned component module 302, according to a preset alliance composition strategy, forms multiple pre-composed alliances of cellular users and edge users in the following ways:

[0197] Based on the preset alliance composition strategy (L,v), cellular users and edge users are arranged and combined to obtain multiple pre-composed alliances;

[0198] Where L represents the set of cellular users M = {Cu1, Cu2, ..., Cu...} m The set of edge users K = {Du1,Du2,…,Du} k Let L be the maximum set of users that can form a pre-formed alliance, and L = {MUK}.

[0199] Furthermore, the aforementioned preset alliance formation strategy is a pre-formed alliance formation strategy, providing a formation strategy capable of traversing all cases of cellular users and edge users within the cell corresponding to the current base station forming a pre-formed alliance strategy. Additionally, the number of cellular user sets m ≥ 1 and the number of edge user sets k ≥ 1.

[0200] As can be seen, the embodiments of the present invention provide a composition strategy that can traverse all cases of cellular users and edge users in the cell corresponding to the current base station forming a pre-composed alliance strategy. This can prevent different actual user situations from occurring according to different application scenarios. The method proposed in this invention lacks universality, thus providing support for subsequent calculation of the utility value of the pre-composed alliance and verification that the pre-composed alliance is a non-super-additive alliance.

[0201] In another optional implementation of this invention, the aforementioned component module 302 determines the alliance utility value of the pre-formed alliance using a second formula, the second formula including:

[0202]

[0203] Where i represents the i-th pre-formed alliance, and i ≤ min(m,k); R i c R represents the data transmission rate of cellular users in the i-th pre-formed alliance. i c The calculation formula is:

[0204]

[0205] as well as, This represents the signal-to-noise ratio of cellular users in the i-th pre-formed alliance under time slot T. The calculation formula is the first formula;

[0206] This represents the data transmission rate of the edge users in the i-th pre-formed alliance. The calculation formula is:

[0207]

[0208] as well as, ω represents the energy collected by cellular users; β represents the energy collection coefficient; i The α represents the percentage of time a cellular user assists an edge user in transmitting data during time slot T; α represents the percentage of time slots used for energy harvesting; Q k This represents a pre-formed alliance of users; This represents the signal-to-noise ratio of the k-th edge user when the m-th cellular user assists the k-th edge user in transmitting data;

[0209] Furthermore, when the m-th cellular user assists the k-th edge user in transmitting data, the signal-to-noise ratio of the k-th edge user is... The calculation formula is:

[0210]

[0211] as well as, g represents the transmit power of the m-th edge user; km This represents the channel gain coefficient between the k-th edge user and the m-th cellular user; This represents the distance between the k-th cellular user and the base station; This represents the distance between the k-th edge user and the m-th cellular user; Represents Gaussian white noise; h kB P represents the channel gain coefficient between the k-th edge user and the base station; s Indicates the base station's transmit power; θ m,n Indicates the channel multiplexing flag, and θ m,n =1, channel multiplexing means that the second target user uses the channel of the first target user.

[0212] In the aforementioned formula for calculating the alliance utility value, similar to the calculation of the signal-to-noise ratio (SNR) of a randomly selected target user, the influence of surrounding users and base stations on the SNR of the target user needs to be considered. Therefore, the formula needs to include a proportional coefficient for the influence between users, as well as a proportional coefficient for the influence on the SNR calculation of the target user in the case of channel reuse between users.

[0213] As can be seen, the embodiments of the present invention can calculate the alliance utility value of each pre-formed alliance, and considering that during the relay transmission process, there are still issues such as the impact of surrounding users, base stations, and channel multiplexing on the calculation of the alliance utility value, the accuracy of the alliance utility value calculation can be improved.

[0214] In an optional embodiment, the composition module 302, according to a preset alliance composition strategy (L,v), arranges and combines cellular users and edge users to obtain multiple pre-composed alliances in the following ways:

[0215] According to the preset alliance composition strategy (L,v), at least one cellular user and at least one edge user are randomly selected from the set L to form a pre-composed alliance with two alliance combination forms.

[0216] And, the first pre-formed alliance is P1 = {{Du} i},{Cu j The second pre-formed alliance is P2 = {Du} i Cu j};

[0217] According to the second formula, the utility value of the first pre-formed alliance is determined as follows:

[0218]

[0219] According to the second formula, the alliance utility value of the second prospective alliance user is determined as follows:

[0220]

[0221] Where i and j represent the numbers of cellular users and edge users in each pre-formed alliance, and i≤k, j≤m.

[0222] In this optional embodiment, a preset alliance composition strategy is proposed, and at least one cellular user and at least one edge user randomly selected from the above permutations and combinations are formed into a pre-composed alliance. The pre-composed alliance is then split to obtain the alliance utility value before and after the split.

[0223] As an optional embodiment, the alliance formation strategy proposed in this invention is not limited to the way of forming an alliance between a cellular user and an edge user. The above-mentioned alliance formation method is only one method of formation. Depending on the specific application scenario, the number of users forming the alliance can be stacked. However, the purpose of the alliance formation method proposed in this invention is to improve the communication spectrum utilization of all users in the application scenario, thereby improving the communication efficiency of all users.

[0224] As can be seen, the alliance utility values ​​obtained before and after the split in this optional embodiment provide a basis for verifying whether the alliance is a super-additive alliance, thus providing a basis for the present invention to improve communication spectrum utilization and thereby improve communication efficiency.

[0225] In this optional embodiment, as an optional implementation, the determination module 303's determination of whether each pre-formed alliance has a non-super alliance may include:

[0226] Comparing the utility value of the second pre-formed coalition with that of the first pre-formed coalition, we obtain:

[0227]

[0228] when When, then v(Cu) m UDu k ) <v(Cu m )+v(Du k ), thus determining that there are non-super alliances in each pre-formed alliance.

[0229] when When, then v(Cu)m ∪Du k )>v(Cu m )+v(Du k ), thus confirming that each pre-formed alliance has a super alliance.

[0230] As can be seen, this optional embodiment verifies that the pre-formed alliance exists as a non-super-additive alliance, and verifies that P1 = {{Du} i},{Cu j The alliance with the highest utility value is P1 = {{Du}, so in this verification scenario, the final choice is to put P1 = {{Du}. i},{Cu j The alliance formation strategy was determined as the final alliance formation strategy.

[0231] In another alternative embodiment, such as Figure 4 As shown, the aforementioned game theory-based energy harvesting cognitive radio D2D-assisted relay device may further include:

[0232] The generation module 305 is used to generate energy harvesting control parameters after the composition module 302 forms multiple pre-composed alliances of cellular users and edge users according to a preset alliance composition strategy.

[0233] Control module 306 is used to control the energy of cellular users collecting signals from base stations on N frequency bands.

[0234] as well as,

[0235]

[0236] Where, β i α represents the percentage of time a cellular user in the i-th pre-formed alliance assists an edge user in transmitting data in time slot T; α represents the percentage of time slots used for energy harvesting; η represents the energy harvesting efficiency; P s Indicates the signal transmission power of the base station; g i This represents the channel gain coefficient between the base station and the cellular user; This indicates the distance between the base station and the cellular user.

[0237] In this embodiment of the invention, the aforementioned cellular user needs to first collect energy from the base station before providing relay transmission to the edge user in order to provide relay transmission to the edge user.

[0238] As can be seen, the embodiments of the present invention provide a calculation formula for the energy collected by cellular users as relay users to provide relay transmission to edge users, which improves the accuracy of energy collection when cellular users provide relay transmission to edge users, and thus lays the foundation for the subsequent formation of pre-formed alliances and the provision of relay transmission.

[0239] In an optional embodiment, within the target user set corresponding to the aforementioned base station cell, a target user set L = {Du1, Cu1, Cu2} has been determined, along with a cellular user set M = {Cu1, Cu2} and an edge user set K = {Du1}. Based on a preset alliance formation strategy (L, v), a first pre-formed alliance is formed as P1 = {Q1, Q2}, where Q1 = {Du1, Cu1} and Q2 = {Cu2}. A second pre-formed alliance is formed as P2 = {Du1, Cu2, Cu3}. Energy harvesting control parameters are generated to control the energy harvested by the cellular users participating in assisting edge user relay transmission for the base station's N frequency band signals. This was intended to lay the foundation for energy consumption in assisting edge users with relay transmission later.

[0240] At this point, the alliance utility values ​​v(P1) = v(Q1) + v(Q2) and v(P2) for the two pre-formed alliances are calculated.

[0241] When v(P2)-v(P1)<0, it is determined that each pre-formed alliance has a non-super-additive alliance, that is, a non-super alliance. The non-super alliance corresponding to the largest alliance utility value is determined as the target alliance. The relay relationship between cellular users and edge users is determined according to the target alliance. That is, the pre-formed alliance composed of P1={Q1,Q2}, where Q1={Du1,Cu1} and Q2={Cu2} is the final alliance formation strategy for cellular users in the cell corresponding to the base station to assist edge users in relay transmission.

[0242] As can be seen, this optional embodiment illustrates that a large alliance composed of all users is not necessarily the optimal strategy for the alliance. There must exist an alliance segment whose alliance benefits are greater than those of a large alliance composed of all users. By arranging and combining all cellular users and edge users into a pre-formed alliance, it is determined whether the utility value of the pre-formed alliance can reach the maximum alliance utility value within the cell, that is, whether the communication efficiency of all users within the cell reaches the maximum. This can effectively improve the communication efficiency of all users within the cell, and there is no omission in the judgment. This effectively achieves the technical problem of low spectrum resource utilization and inability to achieve dynamic spectrum sharing, as described in this invention.

[0243] Example 4

[0244] Please see Figure 5 , Figure 5 This is a schematic diagram of another D2D-assisted relay device for energy harvesting cognitive radio based on game theory disclosed in an embodiment of the present invention. Figure 5 As shown, the game theory-based energy harvesting cognitive radio D2D-assisted relay device may include:

[0245] Memory 401 storing executable program code;

[0246] Processor 402 coupled to memory 401;

[0247] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the game theory-based cognitive radio D2D assisted relay method for energy harvesting described in Embodiment 1 or Embodiment 2 of the present invention.

[0248] Example 5

[0249] This invention discloses a computer-storable medium storing computer instructions. When invoked, these computer instructions are used to execute steps in the game theory-based cognitive radio D2D-assisted relay method for energy harvesting described in Embodiment 1 or Embodiment 2 of this invention.

[0250] Example 6

[0251] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the game theory-based energy harvesting cognitive radio D2D assisted relay method described in Embodiment 1 or Embodiment 2.

[0252] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0253] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0254] Finally, it should be noted that the D2D-assisted relay method and apparatus for energy harvesting cognitive radio based on game theory disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A game-theory-based energy harvesting cognitive radio D2D-assisted relay method, characterized in that, The method includes: Determine the signal-to-noise ratio (SNR) of multiple target users in the target user set within the cell corresponding to the base station, and divide the multiple target users in the target user set into cellular users and edge users based on the SNR of the target users, wherein the SNR of the cellular users is greater than the SNR of the edge users; According to a preset alliance composition strategy, the cellular users and the edge users are formed into multiple pre-composed alliances, and each pre-composed alliance includes at least one cellular user and at least one edge user; Determine whether each of the pre-formed alliances has a non-super alliance. The non-super alliance is a non-super-additive alliance, which indicates that the pre-formed alliance has an alliance combination where the alliance utility value after alliance splitting is greater than the alliance utility value before alliance splitting. When it is determined that each of the pre-formed alliances has a non-super alliance, obtain the alliance utility value corresponding to the non-super alliance. The non-super alliance corresponding to the largest alliance utility value is selected as the target alliance, and the relay relationship between the cellular user and the edge user is determined according to the target alliance. The cellular user in the target alliance has the function of providing relay support to the edge user in the target alliance.

2. The energy harvesting cognitive radio D2D-assisted relay method based on game theory according to claim 1, characterized in that, Determining the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station includes: Determined in a time slot The set of target users within the cell corresponding to the base station is defined, and from the set of target users, the m-th target user is randomly selected as the first target user, and the n-th target user is randomly selected as the second target user; the first target user is determined in the time slot by the first formula. Signal-to-noise ratio ; The first formula includes: in, Indicates the signal transmission power of the base station; This represents the channel gain coefficient between the first target user and the base station; Indicates the path loss coefficient; This represents the straight-line distance between the first target user and the second target user; This represents the straight-line distance between the first target user and the base station; Indicates Gaussian noise; This represents the channel gain coefficient between the first target user and the second target user; This indicates the transmit power of the second target user; Indicates the channel multiplexing flag, and The channel multiplexing indicates that the second target user uses the channel of the first target user.

3. The game theory-based energy harvesting cognitive radio D2D-assisted relay method according to claim 2, characterized in that, The step of forming multiple pre-formed alliances between the cellular users and the edge users according to a preset alliance formation strategy includes: According to the preset alliance formation strategy The cellular users and the edge users are arranged and combined to obtain multiple pre-formed alliances; in, Represents the set of cellular users With the set of edge users The maximum set of users that can form a pre-formed alliance, and ,in, , , Used to represent the alliance utility value of the pre-formed alliance.

4. The game theory-based energy harvesting cognitive radio D2D-assisted relay method according to claim 3, characterized in that, The utility value of the pre-formed alliance is determined by a second formula, which includes: ， in, Indicates the first The aforementioned pre-formed alliance, and ; Indicates the first The data transmission rate of the cellular users in the pre-formed alliance, the The calculation formula is: ， as well as, Indicates the first The cellular users in the pre-formed alliance in the time slot The signal-to-noise ratio at the following levels, the The calculation formula is the first formula; Indicates the first The data transmission rate of the edge users in the pre-formed alliance, the The calculation formula is: ， as well as, This represents the energy value collected by the cellular user; Indicates the energy harvesting coefficient; This indicates that the cellular user is in a time slot. The percentage of time spent assisting edge users in transmitting data; Indicates the percentage of energy harvesting time slots; This represents the set of users in the pre-formed alliance; Indicates the first The aforementioned cellular user assistance When the edge user transmits data, the first The signal-to-noise ratio of the edge users; Furthermore, the first The aforementioned cellular user assistance When the edge user transmits data, the first Signal-to-noise ratio of the edge users The calculation formula is: ， as well as, This represents the transmit power of the m-th cellular user; This represents the channel gain coefficient between the k-th edge user and the m-th cellular user; This represents the distance between the k-th cellular user and the base station; This represents the distance between the k-th edge user and the m-th cellular user; Indicates Gaussian white noise; This represents the channel gain coefficient between the k-th edge user and the base station; Indicates the base station's transmit power; Indicates the channel multiplexing flag, and The channel multiplexing indicates that the second target user uses the channel of the first target user.

5. The game theory-based cognitive radio D2D-assisted relay method for energy harvesting according to claim 4, characterized in that, The method based on the preset alliance formation strategy The cellular users and the edge users are arranged and combined to obtain multiple pre-formed alliances, including: According to the preset alliance formation strategy In the set At least one cellular user and at least one edge user are randomly selected to form a pre-formed alliance with two alliance combination forms. And, the first pre-formed alliance is The second pre-formed alliance is ; According to the second formula, the utility value of the first pre-formed alliance is determined as follows: ， According to the second formula, the utility value of the second pre-formed alliance is determined as follows: ， in, and This indicates the IDs of edge users and cellular users in each pre-formed alliance, where, , , Used to indicate the first The edge users in the time slot The signal-to-noise ratio is below. Used to indicate the first The cellular users in the time slot The signal-to-noise ratio is below. , The calculation formula is the first formula. Used to indicate the first The aforementioned cellular user assistance When the edge user transmits data, the first The signal-to-noise ratio of each edge user.

6. The game theory-based energy harvesting cognitive radio D2D-assisted relay method according to claim 5, characterized in that, The determination of whether any of the pre-formed alliances are non-super alliances includes: Comparing the utility value of the second pre-formed alliance with the utility value of the first pre-formed alliance, we obtain: ， when At that time, ,Right now, It was determined that each of the pre-formed alliances contained a non-super alliance.

7. The game theory-based energy harvesting cognitive radio D2D-assisted relay method according to any one of claims 1-6, characterized in that, After forming multiple pre-formed alliances between the cellular users and the edge users according to a preset alliance formation strategy, the method further includes: Generate energy harvesting control parameters and control the cellular users to harvest energy from the base station. Energy of each frequency band signal ; as well as, in, Indicates the first Cellular users in the aforementioned pre-formed alliance in time slots The percentage of time spent assisting edge users in transmitting data; Indicates the percentage of energy harvesting time slots; Indicates energy harvesting efficiency; This indicates the signal transmission power of the base station; This represents the channel gain coefficient between the base station and the cellular user; This indicates the distance between the base station and the cellular user.

8. A game-theory-based energy harvesting cognitive radio D2D-assisted relay device, characterized in that, The device includes: The determination module is used to determine the signal-to-noise ratio of multiple target users in the target user set within the cell corresponding to the base station; The determining module is further configured to divide multiple target users in the target user set into cellular users and edge users according to the signal-to-noise ratio of the target users, wherein the signal-to-noise ratio of the cellular users is greater than that of the edge users; The composition module is used to form multiple pre-composed alliances of the cellular users and the edge users according to a preset alliance composition strategy, wherein each pre-composed alliance includes at least one cellular user and at least one edge user; The judgment module is used to determine whether each of the pre-formed alliances has a non-super alliance. The non-super alliance is a non-super-additive alliance, which indicates that the pre-formed alliance has an alliance combination mode where the alliance utility value after alliance splitting is greater than the alliance utility value before alliance splitting. The acquisition module is used to acquire the alliance utility value corresponding to the non-super alliance when it is determined that there is a non-super alliance in each of the pre-formed alliances. The determining module is further configured to select the non-super alliance corresponding to the largest alliance utility value as the target alliance, and determine the relay relationship between the cellular user and the edge user based on the target alliance. The cellular user in the target alliance has the function of providing relay support to the edge user in the target alliance.

9. A game-theory-based energy harvesting cognitive radio D2D-assisted relay device, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the game theory-based cognitive radio D2D assisted relay method for energy harvesting as described in any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the game theory-based cognitive radio D2D assisted relay method for energy harvesting as described in any one of claims 1-7.

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