An adaptive power allocation method and processor-readable medium

Abstract

The application discloses a kind of adaptive power distribution method and processor readable medium for backscattering system.The method proposes a kind of selection factor of label cluster that rate factor and fair factor are combined for the multi-label burst access scene in backscattering system, label is combined with cluster as a unit with similar channel signal-to-noise ratio, and label cluster combination is sequentially accessed according to the size of selection factor.The method effectively improves the throughput of system by maintaining the fairness of label access through two steps of label grouping and power distribution.

Description

Technical Field

[0001] This invention relates to signal processing technology, and more particularly to an adaptive power allocation method for backscattering systems and a processor-readable medium. Background Technology

[0002] Current backscatter systems generally employ Time Division Multiple Access (TDMA) orthogonal access for multi-tag access. However, in practice, the reader ignores the power differences between tags and does not multiplex tag signals in the power domain. Only one tag can be accessed at a time, and if multiple tags respond simultaneously, tag collisions occur, reducing system access efficiency. Backscatter systems using Non-Orthogonal Multiple Access (NOMA), on the other hand, can utilize the power differences between tags, allowing multiple tag signals to be superimposed in the power domain, enabling simultaneous access to multiple tags and significantly improving system access efficiency.

[0003] Power allocation is the most critical issue in the design of non-orthogonal multiple access (NMO) systems. For backscatter systems using NMO, total tag rate and tag fairness cannot be simultaneously satisfied. Traditional proportional fairness scheduling algorithms group users based on the ratio of their instantaneous rate to their average rate and compare the proportional fairness ratios of all candidate user combinations to find the user combination that maximizes both user fairness and system rate, along with its corresponding power allocation factor. While this algorithm can maximize system throughput while satisfying user fairness, its computational complexity is extremely high because it requires calculating and comparing the proportional fairness factors for all candidate user groups. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this application proposes an adaptive power allocation method for backscattering systems. This algorithm, through two steps—tag grouping and power allocation—effectively improves system throughput while maintaining fairness in tag access.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] An adaptive power allocation method is proposed for a backscattering system comprising: a reader and multiple tags within its access range; the reader can simultaneously access multiple tag clusters via multiple beams; all tags can be divided into M clusters, each cluster containing m tags. j There are (j = 1, 2, ..., M) tags, and the distance from the j-th tag cluster to the reader is d. j The method is characterized by comprising:

[0007] Step S1. Obtain the number M of tag clusters within the reader's access range, and let Let represent the set of biclusters formed by arbitrarily selecting two different label clusters from M label clusters.

[0008] Among them, u i This represents the i-th bicluster combination.

[0009] Step S2. Initialize candidate combinations And i=1;

[0010] Step S3. Select the i-th bicluster combination u i Obtain the channel signal-to-noise ratio Γ of its two clusters. i1 and Γ i2 , let Γ i1 >Γ i2 Calculate the ratio of the channel signal-to-noise ratios of the two clusters.

[0011] Step S4. Calculate and select the i-th bicluster combination u i The ratio of unvisited tags in the two inner clusters: q i1 =n i1 / m i1 and q i2 =n i2 / m i2 , where n i1 and n i2 m represents the number of tags to be accessed in each of the two clusters. i1 and m i2 This represents the total number of labels in each of the two clusters;

[0012] Step S5. For the i-th bicluster combination u i The selection strategy for the inner two clusters can be described as follows:

[0013] Judgment condition q i1 / q i2 ≥1 or condition Does one of the two conditions apply?

[0014] If satisfied, then let u i Cluster selection factor Otherwise, let the candidate combination V = V∪u i And calculate u i Average proportion of tags to be accessed in the middle Let u i Cluster selection factor

[0015] Step S6. Continue traversing the next bicluster combination until all bicluster combinations have been traversed.

[0016] Step S7 selects the power allocation mode, namely, maximum rate principle power allocation or weighted maximum rate principle power allocation. This method effectively reduces algorithm complexity and improves system throughput.

[0017] Preferably, after step S7, the method further includes: step S8 using a continuous interference cancellation method to access the two assigned tag clusters, and step S9 ending the assignment.

[0018] Preferably, if there are still tags to be accessed in step S9, the process returns to step S2 until the allocation is complete. Preferably, step S7 includes:

[0019] If the combination to be selected Then for all cluster selection factors ξ in U i Sort and select ξ i The largest binary cluster combination u i Power allocation is performed using the maximum rate principle;

[0020] Otherwise, with and As a weighting factor, power allocation is performed using the weighted maximum rate principle.

[0021] Preferably, the maximum rate principle power allocation method includes:

[0022] The two tag clusters are assigned power factors α1 = 1 - α0 and α2 = α0, respectively.

[0023] in, R TH (Unit: bps / Hz) is the minimum achievable rate of tag cluster 2, defined as...

[0024] in is the path fading factor, with a value between 1 and 4, d is the distance from the tag cluster to the reader, h is the channel coefficient, and N0 is the observation noise.

[0025] Preferably, the weighted maximum rate principle power allocation method includes:

[0026] Assign power factors α1 = α to the two tag clusters respectively. w0 α2=1-α w0 ,

[0027] in,

[0028] This application provides a processor-readable medium storing a computer program thereon, characterized in that the computer storage medium includes a computer program that executes the above-described method.

[0029] Compared with existing solutions, the advantages of this application are:

[0030] Compared to existing solutions, the adaptive power allocation method provided by this invention combines the advantages of the maximum rate power allocation scheme and the maximum fair allocation scheme. By grouping tags with similar channel signal-to-noise ratios into clusters, and accessing the tag clusters sequentially according to the size of the selection factor, it is suitable for backscatter systems with a large number of tags and usually burst access. The algorithm has low complexity and can effectively improve the system throughput. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0032] Figure 1 This is a schematic diagram of the backscattering system according to an embodiment of the present invention;

[0033] Figure 2 This invention provides a comparison of the adaptive power allocation method of this embodiment with other power allocation methods at different signal-to-noise ratios to the maximum system speed. Detailed Implementation

[0034] The above-described solution will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are illustrative of this application and not intended to limit its scope. The implementation conditions used in the embodiments may be further adjusted according to the specific conditions of a particular manufacturer, and implementation conditions not specified are generally those used in routine experiments. To better illustrate this disclosure, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that this disclosure can be implemented even without certain specific details.

[0035] This application proposes an adaptive power allocation method for backscatter systems. Specifically, for multi-tag burst access scenarios in backscatter systems, this method employs two steps: tag grouping and power allocation. Specifically, it uses a tag cluster selection factor that combines a rate factor and a fairness factor, and groups tags with similar channel signal-to-noise ratios into clusters, accessing the dual-cluster combinations sequentially according to the selection factor. This effectively improves system throughput while maintaining fairness in tag access.

[0036] In one specific implementation, the power allocation method includes the following steps:

[0037] Step S1. Obtain the number M of tag clusters within the reader's access range, and let Let represent the set of biclusters formed by arbitrarily selecting two different label clusters from M label clusters.

[0038] Among them, u i This represents the i-th bicluster combination.

[0039] Step S2. Initialize candidate combinations And i=1;

[0040] Step S3. Select the i-th bicluster combination u i To obtain the channel signal-to-noise ratio (SNR) of the two clusters it contains, Γ i1 and Γ i2 Let Γ i1 >Γ i2 Calculate the ratio of the channel signal-to-noise ratios of the two clusters.

[0041] Step S4. Calculate and select the i-th bicluster combination u i The ratio of unvisited tags in the two inner clusters:

[0042] q i1 =n i1 / m i1 and q i2 =n i2 / m i2 ,

[0043] Where, n i1 and n i2 m represents the number of tags to be accessed in each of the two clusters. i1 and m i2 This indicates the total number of labels for each of the two clusters.

[0044] Step S5. For the i-th bicluster combination u i The selection strategy for the inner two clusters can be described as follows:

[0045] Judgment condition q i1 / q i2 ≥1 or Does it meet the requirements?

[0046] If the condition is satisfied, then let u i Cluster selection factor

[0047] Otherwise, let the candidate combination V = V∪u i ,

[0048] And calculate u i Average proportion of tags to be accessed in the middle

[0049] Let u i Cluster selection factor

[0050] Step S6. Continue traversing the next bicluster combination. Specifically, by using i = i + 1, if... Proceed to step S3.

[0051] Step S7

[0052] If, the candidate combination Then for all cluster selection factors ξ in U i Sort and select ξ i The largest binary cluster combination u i In this case, the maximum rate principle is used for power allocation;

[0053] Otherwise, with and As a weighting factor, power allocation is performed using the weighted maximum rate principle.

[0054] Step S8 uses the continuous interference cancellation method to access the two assigned tag clusters.

[0055] If there are still tags to be visited in step S9, return to step S2; otherwise, the algorithm has finished executing.

[0056] The maximum rate principle power allocation method includes:

[0057] The power factors assigned to the two tag clusters are: α1 = 1 - α0, α2 = α0,

[0058] in, R TH (Unit: bps / Hz) is the minimum achievable rate of tag cluster 2, defined as... in is the path fading factor, with a value between 1 and 4, d is the distance from the tag cluster to the reader, h is the channel coefficient, and N0 is the observation noise.

[0059] The method proposed in this application will be verified through simulation below.

[0060] This embodiment uses computer experiments (such as those based on MATLAB) to compare the performance differences of the adaptive power allocation scheme proposed in this application with other schemes at different signal-to-noise ratios for the overall system speed.

[0061] In the simulation, it is assumed that the distances between the two tags and the reader are 1 meter and 4 meters respectively, the path fading factor is 2, the small-scale fading channel between the tag and the receiver antenna is assumed to follow Rayleigh flat fading, and the total power transmitted by the transmitter is 33 dBm. Figure 1As shown, the backscattering system includes: a reader and multiple tags within the access range. The reader can simultaneously access multiple tag clusters through multiple beams. All tags can be divided into M clusters, and each cluster contains m tags. j There are (j = 1, 2, ..., M) tags, and the distance from the j-th tag cluster to the reader is d. j .

[0062] After initialization, the experimental parameters are executed sequentially according to steps S1 to S9. Based on Shannon's formula, the achievable speed of the system can be expressed by the following formula.

[0063]

[0064] Simulation results are as follows Figure 2 As shown, from Figure 2 The study found that, under different initial signal-to-noise ratios, the adaptive power allocation method proposed in this application has significant advantages in terms of system achievable speed compared with the maximum fair power allocation method and the time-division multiplexing method.

[0065] This application also provides a processor-readable medium comprising a computer program that performs the methods described above.

[0066] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer (processor) readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0067] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above embodiments are only for illustrating the technical concept and features of this application, and are intended to enable those skilled in the art to understand the content of this application and implement it accordingly. They should not be used to limit the scope of protection of this application. All equivalent changes or modifications made in accordance with the spirit and essence of this application should be included within the scope of protection of this application.

Claims

1. An adaptive power allocation method for a backscattering system, characterized in that, The backscattering system comprises: a reader and multiple tags within its access range. The reader simultaneously accesses multiple tag clusters via multiple beams. All tags are divided into M clusters, and each cluster contains m tags. j There are 3 tags, j = 1, 2, ..., M, and the distance from the j-th tag cluster to the reader is d. j The power of each tag cluster can be allocated according to the following algorithm, including: Step S1. Obtain the number M of tag clusters within the reader's access range, and let Let represent the set of biclusters formed by arbitrarily selecting two different label clusters from M label clusters. Among them, u i This represents the i-th bicluster combination. Step S2. Initialize the candidate combinations. And i=1; Step S3. Select the i-th bicluster combination u i Obtain the channel signal-to-noise ratio Γ of its two clusters. i1 and Γ i2 , let Γ i1 >Γ i2 Calculate the ratio of the channel signal-to-noise ratios of the two clusters. Step S4. Calculate and select the i-th bicluster combination u i The ratio of unvisited tags in the two inner clusters: q i1 =n i1 / m i1 and q i2 =n i2 / m i2 , where n i1 and n i2 m represents the number of tags to be accessed in each of the two clusters. i1 and m i2 This represents the total number of labels in each of the two clusters; Step S5. For the i-th bicluster combination u i The selection strategy for the inner two clusters is described as follows: Judgment condition q i1 / q i2 ≥1 or condition Does one of the two conditions apply? If satisfied, then let u i Cluster selection factor Otherwise, let the candidate combination V = V∪u i And calculate u i Average proportion of tags to be accessed in the middle Let u i Cluster selection factor Step S6. Iterate through the next binary cluster combination until all binary cluster combinations have been traversed. Step S7. Select the power allocation mode, i.e., select maximum rate principle power allocation or weighted maximum rate principle power allocation, including if there are candidate combinations Then for all cluster selection factors ξ in U i Sort and select ξ i The largest binary cluster combination u i Power allocation is performed using the maximum rate principle; Otherwise, with and As a weighting factor, power allocation is performed using the weighted maximum rate principle.

2. The adaptive power allocation method according to claim 1, characterized in that, Following step S7, the following is also included: Step S8. Access the two assigned tag clusters using the continuous interference cancellation method. Step S9. Allocation complete.

3. The adaptive power allocation method according to claim 2, characterized in that, If there are still tags to be accessed in step S9, return to step S2 until the allocation is completed.

4. The adaptive power allocation method according to claim 1, characterized in that, The maximum rate principle for power allocation includes: The power factors assigned to the two tag clusters are: α1 = 1 - α0, α2 = α0, in, R TH The minimum achievable rate for a tag cluster, in bps / Hz, is defined as follows: in is the path fading factor, with a value between 1 and 4, d is the distance from the tag cluster to the reader, h is the channel coefficient, and N0 is the observation noise.

5. The adaptive power allocation method according to claim 1, characterized in that, The power allocation based on the weighted maximum rate principle includes: The power factor is assigned to the two tag clusters as follows: α1 = α w0 α2=1-α w0 , in, 6. A processor-readable medium having a computer program stored thereon, characterized in that, The computer program performs the method as described in any one of claims 1-5.

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