CN115734252A - Cognitive wireless power supply network optimization method based on backscatter relay transmission - Google Patents

Cognitive wireless power supply network optimization method based on backscatter relay transmission Download PDF

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CN115734252A
CN115734252A CN202211516401.3A CN202211516401A CN115734252A CN 115734252 A CN115734252 A CN 115734252A CN 202211516401 A CN202211516401 A CN 202211516401A CN 115734252 A CN115734252 A CN 115734252A
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backscatter
energy harvesting
energy
data transmission
receiver
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CN115734252B (en
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刘晓莹
蔺中葳
王家红
郑可琛
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Zhejiang University of Technology ZJUT
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Abstract

本发明公开了一种基于反向散射中继传输的认知无线供能网络优化方法，将认知无线供能网络的工作时隙分为中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段，在中继阶段主发射机发送数据给主接收机，反向散射单元发射机采用反向散射模式中继主用户数据给主接收机，能量捕获单元发射机进行能量捕获；在反向散射数据传输阶段，主发射机发送数据给主接收机，反向散射单元发射机采用反向散射模式发送数据给反向散射接收机，能量捕获单元发射机进行能量捕获；在能量捕获数据传输阶段，主发射机休眠，能量捕获单元发射机利用捕获的能量传输数据给能量捕获接收机。本发明优化了各个阶段的持续时间，提高了数据传输的吞吐量。

Figure 202211516401

The invention discloses a cognitive wireless energy supply network optimization method based on backscatter relay transmission, which divides the working time slot of the cognitive wireless energy supply network into a relay stage, a backscatter data transmission stage and energy capture data In the transmission phase, in the relay phase, the main transmitter sends data to the main receiver, the backscatter unit transmitter uses the backscatter mode to relay the main user data to the main receiver, and the energy capture unit transmitter performs energy capture; In the scatter data transmission stage, the main transmitter sends data to the main receiver, the backscatter unit transmitter uses the backscatter mode to send data to the backscatter receiver, and the energy capture unit transmitter performs energy capture; in the energy capture data transmission stage , the main transmitter is dormant, and the energy harvesting unit transmitter uses the captured energy to transmit data to the energy harvesting receiver. The invention optimizes the duration of each stage and improves the throughput of data transmission.

Figure 202211516401

Description

基于反向散射中继传输的认知无线供能网络优化方法Cognitive wireless power supply network optimization method based on backscatter relay transmission

技术领域technical field

本申请属于认知无线供能通信技术领域，尤其涉及一种基于反向散射中继传输的认知无线供能网络优化方法。The present application belongs to the technical field of cognitive wireless power supply communication, and in particular relates to a cognitive wireless power supply network optimization method based on backscatter relay transmission.

背景技术Background technique

在认知无线供能网络中，通常包含主用户和次级用户。主用户拥有频谱的授权，可以随时接入频谱。次级用户没有授权频谱，只能在授权频谱空闲时段伺机接入授权频谱。主用户通常有恒定的电源供电，例如电视、手机等。次级用户通常没有固定的电源供能，因此需要从周围环境中捕获能量，并将捕获到的能量存储到次级用户的可充电电池中。次级用户存储的能量供其在传输数据时使用。In a cognitive wireless power supply network, there are usually primary users and secondary users. The primary user has spectrum authorization and can access the spectrum at any time. Secondary users do not have licensed spectrum and can only opportunistically access the licensed spectrum during the idle period of the licensed spectrum. Primary users usually have a constant power supply, such as TV, mobile phone, etc. Secondary users usually do not have a fixed source of energy, so energy needs to be captured from the surrounding environment and stored in the secondary user's rechargeable battery. The energy stored by the secondary user is used when transmitting data.

此外，近年来反向散射技术由于其功耗低，已经在认知无线供能网络中得到广泛的研究。配备反向散射单元的设备可以通过反向散射网络中的射频信号来传输自己的数据，也可以做为反向散射中继设备，通过反向散射来进行中继。In addition, backscatter technology has been extensively studied in cognitive wireless powering networks due to its low power consumption in recent years. A device equipped with a backscatter unit can transmit its own data through the radio frequency signal in the backscatter network, or it can be used as a backscatter relay device to relay through backscatter.

在该网络中，如何分配次级用户何时进行反向散射中继、能量捕获和次级数据传输，以及分配多长时间给次级用户进行反向散射中继、能量捕获和次级数据传输以实现网络吞吐量最大化是需要考虑的主要问题。In this network, how to allocate when secondary users perform backscatter relay, energy harvesting, and secondary data transmission, and how long to allocate to secondary users for backscatter relay, energy harvesting, and secondary data transmission To maximize network throughput is the main issue that needs to be considered.

发明内容Contents of the invention

为了提升现有基于反向散射中继的认知无线供能网络中的吞吐量，本申请的目的是提供一种基于反向散射中继传输的认知无线供能网络吞吐量优化方法。该方法通过次级用户中继主用户数据，有效解决了网络的吞吐量最大化问题，提升了网络的频谱利用率，并且采用能量捕获技术和反向散射技术大大节省了网络的能耗。In order to improve the throughput of the existing cognitive wireless power supply network based on backscatter relay, the purpose of this application is to provide a throughput optimization method of the cognitive wireless power supply network based on backscatter relay transmission. This method relays primary user data through secondary users, effectively solves the problem of network throughput maximization, improves network spectrum utilization, and uses energy harvesting technology and backscattering technology to greatly save network energy consumption.

为了实现上述目的，本申请的技术方案如下：In order to achieve the above object, the technical scheme of the present application is as follows:

一种基于反向散射中继传输的认知无线供能网络优化方法，所述认知无线供能网络包括对应主用户的主发射机和主接收机，以及对应第一次级用户的配备能量捕获单元的次级发射机和能量捕获接收机，以及对应第二次级用户的配备反向散射单元的次级发射机和反向散射接收机，所述基于反向散射中继传输的认知无线供能网络优化方法，包括：A cognitive wireless energy supply network optimization method based on backscatter relay transmission, the cognitive wireless energy supply network includes a main transmitter and a main receiver corresponding to the main user, and an equipped energy corresponding to the first secondary user The secondary transmitter and energy harvesting receiver of the acquisition unit, and the secondary transmitter and backscatter receiver equipped with the backscatter unit corresponding to the second secondary user, said knowledge based on backscatter relay transmission A method for optimizing a wireless energy supply network, including:

将所述认知无线供能网络的工作时隙分为中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段；Dividing the working time slots of the cognitive wireless energy supply network into a relay stage, a backscatter data transmission stage and an energy harvesting data transmission stage;

其中，在中继阶段主发射机发送数据给主接收机，配备反向散射单元的次级发射机采用反向散射模式中继主用户数据给主接收机，配备能量捕获单元的次级发射机进行能量捕获；Among them, in the relay stage, the main transmitter sends data to the main receiver, the secondary transmitter equipped with backscatter unit adopts the backscatter mode to relay the primary user data to the main receiver, and the secondary transmitter equipped with energy harvesting unit perform energy capture;

在反向散射数据传输阶段，主发射机发送数据给主接收机，配备反向散射单元的次级发射机采用反向散射模式发送数据给反向散射接收机，配备能量捕获单元的次级发射机进行能量捕获；In the backscatter data transmission phase, the primary transmitter sends data to the primary receiver, the secondary transmitter equipped with a backscatter unit sends data to the backscatter receiver in backscatter mode, and the secondary transmitter equipped with an energy harvesting unit machine for energy capture;

在能量捕获数据传输阶段，主发射机休眠，配备能量捕获单元的次级发射机利用捕获的能量传输数据给能量捕获接收机。In the energy harvesting data transmission stage, the primary transmitter is dormant, and the secondary transmitter equipped with an energy harvesting unit uses the captured energy to transmit data to the energy harvesting receiver.

进一步的，所述基于反向散射中继传输的认知无线供能网络优化方法，还包括：Further, the cognitive wireless power supply network optimization method based on backscatter relay transmission also includes:

将中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时间分别表 示为：

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,
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和
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，在满足主用户目标吞吐量的前提下，以实现次级用户的总吞吐量最大化为 目标构建优化模型
Figure 223812DEST_PATH_IMAGE004
： Denote the durations of the relay phase, the backscatter data transmission phase, and the energy harvesting data transmission phase as:
Figure 318676DEST_PATH_IMAGE001
,
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and
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, under the premise of satisfying the target throughput of the primary user, an optimization model is constructed with the goal of maximizing the total throughput of the secondary user
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:

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；
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;

满足如下约束条件：

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；
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； Satisfy the following constraints:
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;
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;

其中，

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表示在能量捕获数据传输阶段，第
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个配备能量捕获单元的次级发射机产 生的吞吐量，
Figure 238091DEST_PATH_IMAGE010
表示在反向散射数据传输阶段，第
Figure 992420DEST_PATH_IMAGE011
个配备反向散射单元的次级发射机产 生的吞吐量，M表示配备反向散射单元的次级发射机数量，N表示配备能量捕获单元的次级 发射机数量，
Figure 791749DEST_PATH_IMAGE012
；
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表示在能量捕获数据传输阶段，第
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个配备能量捕获单 元的次级发射机被分配到的时间； in,
Figure 762799DEST_PATH_IMAGE008
Indicates that in the energy harvesting data transmission stage, the first
Figure 431678DEST_PATH_IMAGE009
Throughput produced by secondary transmitters equipped with energy harvesting units,
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Indicates that in the backscatter data transmission stage, the first
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Throughput produced by secondary transmitters equipped with backscatter elements, M is the number of secondary transmitters equipped with backscatter elements, N is the number of secondary transmitters equipped with energy harvesting elements,
Figure 791749DEST_PATH_IMAGE012
;
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Indicates that in the energy harvesting data transmission stage, the first
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The time at which secondary transmitters equipped with energy harvesting units are assigned;

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，表示在能量捕获数据传输阶段，第
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个配备能量捕获单 元的次级发射机产生的吞吐量；
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, which means that in the stage of energy harvesting data transmission, the first
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Throughput produced by secondary transmitters equipped with energy harvesting units;

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，表示在反向散射数据传输阶段，第
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个配备反向散 射单元的次级发射机产生的吞吐量，
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反向散射系数，
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表示主发射机的发射功率；
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, which means that in the backscatter data transmission stage, the first
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Throughput produced by secondary transmitters equipped with backscatter elements,
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backscatter coefficient,
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Indicates the transmit power of the main transmitter;

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，表示在中继阶段，主接收机处实现的吞 吐量；
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, represents the throughput achieved at the master receiver during the relay phase;

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，表示在反向散射数据传输阶段，主接收机处实现的吞 吐量；
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, represents the throughput achieved at the main receiver during the backscatter data transmission phase;

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表示主用户在每个时隙内的目标吞吐量；
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Indicates the target throughput of the primary user in each time slot;

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表示信道带宽；
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Indicates the channel bandwidth;

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表示环境噪声功率；
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Indicates the ambient noise power;

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，表示第
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个配备能量捕获单元的次级发射机在授权频谱忙碌 时捕获到的能量，
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表示能量捕获效率；
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, indicating the first
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The energy captured by a secondary transmitter equipped with an energy harvesting unit when the licensed spectrum is busy,
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Indicates the energy capture efficiency;

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表示从第
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个配备能量捕获单元的次级发射机到能量捕获接收机的信道增益；
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means from the
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The channel gain from a secondary transmitter equipped with an energy harvesting unit to an energy harvesting receiver;

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表示从第
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个配备反向散射单元的次级发射机到反向散射接收机的信道增益；
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means from the
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channel gain from a secondary transmitter equipped with a backscatter unit to a backscatter receiver;

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表示从主发射机到第
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个配备反向散射单元的次级发射机的信道增益；
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Indicates from the main transmitter to the second
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channel gain of a secondary transmitter equipped with backscatter elements;

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表示从主发射机到第
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个配备能量捕获单元的次级发射机的信道增益；
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Indicates from the main transmitter to the second
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The channel gain of a secondary transmitter equipped with an energy harvesting unit;

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表示从第
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个配备反向散射单元的次级发射机到主接收机的信道增益；
Figure 272798DEST_PATH_IMAGE029
means from the
Figure 524788DEST_PATH_IMAGE009
channel gain from a secondary transmitter equipped with a backscatter unit to the primary receiver;

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表示从主发射机到主接收机的信道增益；
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Indicates the channel gain from the main transmitter to the main receiver;

求解优化模型的最优解，得到中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时间。The optimal solution of the optimized model is solved for the duration of the relay phase, the backscatter data transmission phase, and the energy harvesting data transmission phase.

进一步的，所述求解优化模型的最优解，包括：Further, said solving the optimal solution of the optimization model includes:

将优化变量

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转化为
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，带入到优化模型，得到优化模型
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： will optimize the variable
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Converted to
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, into the optimization model to obtain the optimization model
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:

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；
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;

列出

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的拉格朗日函数，如下： list
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The Lagrange function of is as follows:

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Figure 493290DEST_PATH_IMAGE034

其中：in:

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；
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;

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；
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;

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；
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;

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，为拉格朗日乘子；
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, is the Lagrangian multiplier;

通过对拉格朗日函数求关于

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的一阶偏导数，令该一阶偏导数为零，得到
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的表达 式，如下： By finding the Lagrangian function about
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The first-order partial derivative of , let the first-order partial derivative be zero, get
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The expression of is as follows:

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； （1）
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; (1)

其中

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表示若
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，则
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，否则，
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； in
Figure 35819DEST_PATH_IMAGE040
express if
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,but
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,otherwise,
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;

通过对拉格朗日函数求关于

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一阶偏导数，令该一阶偏导数为零，得
Figure 676753DEST_PATH_IMAGE013
的表达式， 如下：By finding the Lagrangian function about
Figure 366995DEST_PATH_IMAGE013
The first-order partial derivative, let the first-order partial derivative be zero, get
Figure 676753DEST_PATH_IMAGE013
The expression of is as follows:

Figure 560527DEST_PATH_IMAGE044
Figure 560527DEST_PATH_IMAGE044

其中

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； in
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;

拉格朗日乘子更新的表达式，如下：The expression of Lagrange multiplier update is as follows:

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； （3）
Figure 516030DEST_PATH_IMAGE046
; (3)

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； （4）
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;(4)

然后求解优化模型

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，包括： Then solve the optimization model
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,include:

步骤4.1：设置初始化

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，
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的值，并且都大于等于0，初始化迭代次数
Figure 679027DEST_PATH_IMAGE049
； Step 4.1: Setup initialization
Figure 520130DEST_PATH_IMAGE002
,
Figure 214417DEST_PATH_IMAGE048
value, and are greater than or equal to 0, the number of initialization iterations
Figure 679027DEST_PATH_IMAGE049
;

步骤4.2：判断

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超过N，若否，则采用二分搜索算法更新
Figure 181870DEST_PATH_IMAGE051
，通过固定
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，
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的 值，
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，然后跳到步骤4.2；否则，跳到步骤4.3； Step 4.2: Judgment
Figure 724344DEST_PATH_IMAGE050
Exceeds N, if not, use binary search algorithm to update
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, fixed by
Figure 730663DEST_PATH_IMAGE002
,
Figure 124430DEST_PATH_IMAGE052
the value of
Figure 391463DEST_PATH_IMAGE053
, then skip to step 4.2; otherwise, skip to step 4.3;

步骤4.3：通过固定

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基于公式(1)更新
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的值； Step 4.3: Fix by
Figure 652680DEST_PATH_IMAGE054
Update based on formula (1)
Figure 55979DEST_PATH_IMAGE002
value;

步骤4.4：通过固定

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，
Figure 944618DEST_PATH_IMAGE055
基于公式(3)更新
Figure 681630DEST_PATH_IMAGE056
； Step 4.4: Fix by
Figure 127972DEST_PATH_IMAGE002
,
Figure 944618DEST_PATH_IMAGE055
Update based on formula (3)
Figure 681630DEST_PATH_IMAGE056
;

步骤4.5：通过固定

Figure 516600DEST_PATH_IMAGE002
，
Figure 946444DEST_PATH_IMAGE057
基于公式(4)更新
Figure 984807DEST_PATH_IMAGE058
； Step 4.5: Fix by
Figure 516600DEST_PATH_IMAGE002
,
Figure 946444DEST_PATH_IMAGE057
Update based on formula (4)
Figure 984807DEST_PATH_IMAGE058
;

步骤4.6：判断所有的变量是否收敛，若是，则跳到步骤4.7；否则，跳到步骤4.2；Step 4.6: Judging whether all variables are convergent, if so, skip to step 4.7; otherwise, skip to step 4.2;

步骤4.7：输出最优解

Figure 338559DEST_PATH_IMAGE059
，最优解
Figure 982030DEST_PATH_IMAGE060
。 Step 4.7: Output the optimal solution
Figure 338559DEST_PATH_IMAGE059
,Optimal solution
Figure 982030DEST_PATH_IMAGE060
.

进一步的，所述采用二分搜索算法更新

Figure 379513DEST_PATH_IMAGE051
，包括： Further, the update using the binary search algorithm
Figure 379513DEST_PATH_IMAGE051
,include:

步骤3.1：输入一个上界值

Figure 108435DEST_PATH_IMAGE061
，设置下界值
Figure 498834DEST_PATH_IMAGE062
，将
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替代
Figure 565196DEST_PATH_IMAGE051
带入到拉格朗日函数 对
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的一阶偏导数中，得到解
Figure 476968DEST_PATH_IMAGE064
； Step 3.1: Enter an upper bound value
Figure 108435DEST_PATH_IMAGE061
, set the lower bound value
Figure 498834DEST_PATH_IMAGE062
,Will
Figure 996811DEST_PATH_IMAGE063
replace
Figure 565196DEST_PATH_IMAGE051
into the Lagrange function pair
Figure 781414DEST_PATH_IMAGE051
In the first partial derivative of , the solution is obtained
Figure 476968DEST_PATH_IMAGE064
;

步骤3.2：设置循环次数为

Figure 829452DEST_PATH_IMAGE065
，初始值为1，判断解
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是否小于
Figure 583836DEST_PATH_IMAGE067
，
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为一个很小的数， 若是，则跳到步骤3.5，否则跳到步骤3.3，
Figure 539340DEST_PATH_IMAGE068
； Step 3.2: Set the number of cycles to
Figure 829452DEST_PATH_IMAGE065
, the initial value is 1, and the judgment solution
Figure 834317DEST_PATH_IMAGE066
Is it less than
Figure 583836DEST_PATH_IMAGE067
,
Figure 4453DEST_PATH_IMAGE067
is a very small number, if so, go to step 3.5, otherwise go to step 3.3,
Figure 539340DEST_PATH_IMAGE068
;

步骤3.3：判断

Figure 387210DEST_PATH_IMAGE069
是否大于0，若是，则
Figure 125490DEST_PATH_IMAGE070
，否则，
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； Step 3.3: Judgment
Figure 387210DEST_PATH_IMAGE069
Is it greater than 0, if so, then
Figure 125490DEST_PATH_IMAGE070
,otherwise,
Figure 729559DEST_PATH_IMAGE071
;

步骤3.4：将

Figure 118952DEST_PATH_IMAGE063
替代
Figure 403303DEST_PATH_IMAGE051
带入到拉格朗日函数对
Figure 628879DEST_PATH_IMAGE051
的一阶偏导数中，得到解
Figure 391299DEST_PATH_IMAGE069
，跳到 步骤3.2； Step 3.4: Put
Figure 118952DEST_PATH_IMAGE063
replace
Figure 403303DEST_PATH_IMAGE051
into the Lagrange function pair
Figure 628879DEST_PATH_IMAGE051
In the first partial derivative of , the solution is obtained
Figure 391299DEST_PATH_IMAGE069
, skip to step 3.2;

步骤3.5：此时得到的

Figure 635198DEST_PATH_IMAGE063
为
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的解。Step 3.5: At this point get
Figure 635198DEST_PATH_IMAGE063
for
Figure 90450DEST_PATH_IMAGE051
solution.

本申请技术方案，考虑在认知无线供能网络中，配备反向散射单元的发射机采用反向散射模式中继主用户数据，然后传输自己的数据，配备能量捕获单元的发射机进行射频能量捕获，然后使用捕获到的能量进行数据传输。通过优化中继、能量捕获以及数据传输的时间使得次级用户的总吞吐量最大化，从而提升网络的频谱利用率和能量效率。在此处，考虑的前提是主用户在一个时隙内需要满足其目标吞吐量，主用户空闲时，次级用户才能接入授权频谱。然后，通过对总吞吐量问题的单调性分析，将问题进行转化，并证明其是一个凸优化问题，再对其拉格朗日函数求偏导，以及采用二分搜索算法求得优化变化得表达式，再将问题用最优解迭代算法求解。从而保证主用户在满足其目标吞吐量的前提下，实现次级用户总吞吐量的最大化。The technical solution of this application considers that in the cognitive wireless energy supply network, the transmitter equipped with the backscattering unit uses the backscattering mode to relay the primary user data, and then transmits its own data, and the transmitter equipped with the energy capture unit performs radio frequency energy capture, and then use the captured energy for data transmission. By optimizing the time of relay, energy capture and data transmission, the total throughput of secondary users is maximized, thereby improving the spectrum utilization and energy efficiency of the network. Here, the premise considered is that the primary user needs to meet its target throughput within a time slot, and the secondary user can access the licensed spectrum only when the primary user is idle. Then, through the monotonic analysis of the total throughput problem, the problem is transformed, and it is proved that it is a convex optimization problem, and then the partial derivative of its Lagrangian function is obtained, and the expression of the optimization change is obtained by using the binary search algorithm formula, and then solve the problem with the optimal solution iterative algorithm. In this way, it is ensured that the primary user can maximize the total throughput of the secondary user under the premise of satisfying its target throughput.

附图说明Description of drawings

图1为本申请认知无线供能网络在中级阶段示意图；Figure 1 is a schematic diagram of the cognitive wireless energy supply network of the present application at the intermediate stage;

图2为本申请认知无线供能网络在反向散射数据传输阶段示意图；Figure 2 is a schematic diagram of the cognitive wireless energy supply network of the present application in the backscatter data transmission stage;

图3为本申请认知无线供能网络在能量捕获数据传输阶段示意图；FIG. 3 is a schematic diagram of the cognitive wireless energy supply network in the energy capture data transmission stage of the present application;

图4为本申请实施例单个时隙划分示意图。FIG. 4 is a schematic diagram of division of a single time slot according to an embodiment of the present application.

具体实施方式Detailed ways

为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅用以解释本申请，并不用于限定本申请。In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

如图1至图3所示，基于反向散射中继传输的认知无线供能网络主用户包括一个主发射机、一个主接收机。次级用户又分为两种，一种次级用户包括N个配备能量捕获单元的次级发射机（称为能量捕获单元发射机）和一个次级接收机（能量捕获接收机），能量捕获接收机只负责接收能量捕获单元发射机的数据；另一种次级用户包括M个配备反向散射单元的次级发射机（称为反向散射单元发射机）和一个次级接收机（反向散射接收机），反向散射接收机只负责接收反向散射单元发射机的数据。As shown in Figures 1 to 3, the main user of the cognitive wireless power supply network based on backscatter relay transmission includes a main transmitter and a main receiver. Secondary users are divided into two types. One secondary user includes N secondary transmitters equipped with energy harvesting units (called energy harvesting unit transmitters) and a secondary receiver (energy harvesting receiver). Energy harvesting The receiver is only responsible for receiving data from the energy harvesting unit transmitter; another secondary user includes M secondary transmitters equipped with backscatter units (called backscatter unit transmitters) and a secondary receiver (reverse backscatter receiver), the backscatter receiver is only responsible for receiving the data from the backscatter unit transmitter.

在一个实施例中，基于反向散射中继传输的认知无线供能网络优化方法，包括：In one embodiment, the cognitive wireless power supply network optimization method based on backscatter relay transmission includes:

将所述认知无线供能网络的工作时隙分为中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段；Dividing the working time slots of the cognitive wireless energy supply network into a relay stage, a backscatter data transmission stage and an energy harvesting data transmission stage;

其中，在中继阶段主发射机发送数据给主接收机，配备反向散射单元的次级发射机采用反向散射模式中继主用户数据给主接收机，配备能量捕获单元的次级发射机进行能量捕获；Among them, in the relay stage, the main transmitter sends data to the main receiver, the secondary transmitter equipped with backscatter unit adopts the backscatter mode to relay the primary user data to the main receiver, and the secondary transmitter equipped with energy harvesting unit perform energy capture;

在反向散射数据传输阶段，主发射机发送数据给主接收机，配备反向散射单元的次级发射机采用反向散射模式发送数据给反向散射接收机，配备能量捕获单元的次级发射机进行能量捕获；In the backscatter data transmission phase, the primary transmitter sends data to the primary receiver, the secondary transmitter equipped with a backscatter unit sends data to the backscatter receiver in backscatter mode, and the secondary transmitter equipped with an energy harvesting unit machine for energy capture;

在能量捕获数据传输阶段，主发射机休眠，配备能量捕获单元的次级发射机利用捕获的能量传输数据给能量捕获接收机。In the energy harvesting data transmission stage, the primary transmitter is dormant, and the secondary transmitter equipped with an energy harvesting unit uses the captured energy to transmit data to the energy harvesting receiver.

具体的，如图1至图3所示，中继阶段：Specifically, as shown in Figures 1 to 3, the relay stage:

主发射机发送数据给主接收机，即频谱忙碌。M个配备反向散射单元的次级发射机采用反向散射模式中继主用户数据给主接收机。N个配备能量捕获单元的次级发射机进行能量捕获。The main transmitter sends data to the main receiver, ie the spectrum is busy. M secondary transmitters equipped with backscatter units relay primary user data to the primary receiver in backscatter mode. Energy harvesting is performed by N secondary transmitters equipped with energy harvesting units.

反向散射数据传输阶段，授权频谱处于忙碌，主发射机发送数据给主接收机。M个配备反向散射单元的次级发射机采用反向散射模式发送数据给反向散射接收机。N个只配备能量捕获单元的次级发射机进行能量捕获。In the phase of backscatter data transmission, the licensed spectrum is busy, and the main transmitter sends data to the main receiver. M secondary transmitters equipped with backscatter units transmit data to backscatter receivers in backscatter mode. N secondary transmitters equipped with only energy harvesting units perform energy harvesting.

由于配备反向散射单元的次级发射机中继主发射机的数据，因此主发射机可以提前满足其在一个时隙内的目标吞吐量。Since the secondary transmitter equipped with a backscatter unit relays the data from the primary transmitter, the primary transmitter can meet its target throughput in one slot ahead of time.

而在能量捕获数据传输阶段，授权频谱处于空闲，主发射机休眠。N个配备能量捕获单元的次级发射机利用捕获的能量传输数据给能量捕获接收机。In the phase of energy harvesting data transmission, the licensed spectrum is idle and the main transmitter is dormant. N secondary transmitters equipped with energy harvesting units utilize the captured energy to transmit data to an energy harvesting receiver.

本实施例中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时间 分别表示为：

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,
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和
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，如图4所示。由于中继阶段持续时间
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的增加会使得主用户更快地 满足目标吞吐量，授权频谱处于忙碌的时间减少，反向散射数据传输阶段
Figure 792696DEST_PATH_IMAGE002
减少，因此配备 能量捕获单元的次级发射机捕获能量的时间减少。
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,
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和
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之间存在折衷，需要进行优化 来得到时间分配的最优比例。 In this embodiment, the durations of the relay stage, the backscatter data transmission stage and the energy capture data transmission stage are respectively expressed as:
Figure 301858DEST_PATH_IMAGE001
,
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and
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,As shown in Figure 4. Due to the relay phase duration
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The increase of λ will allow the primary user to meet the target throughput faster, the licensed spectrum is busy for less time, and the backscatter data transmission phase
Figure 792696DEST_PATH_IMAGE002
Reduced, and therefore less time for secondary transmitters equipped with energy harvesting units to capture energy.
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,
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and
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There is a trade-off between and needs to be optimized to get the optimal ratio of time allocation.

在一个具体的实施例中，所述基于反向散射中继传输的认知无线供能网络优化方法，还包括：In a specific embodiment, the cognitive wireless power supply network optimization method based on backscatter relay transmission further includes:

步骤F1、将中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时 间分别表示为：

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,
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和
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，在满足主用户目标吞吐量的前提下，以实现次级用户的总吞吐量 最大化为目标构建优化模型
Figure 47331DEST_PATH_IMAGE004
： In step F1, the durations of the relay phase, the backscatter data transmission phase and the energy capture data transmission phase are respectively expressed as:
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,
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and
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, under the premise of satisfying the target throughput of the primary user, an optimization model is constructed with the goal of maximizing the total throughput of the secondary user
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:

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其中，

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表示在能量捕获数据传输阶段，第
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个配备能量捕获单元的次级发射机产 生的吞吐量，
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表示在反向散射数据传输阶段，第
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个配备反向散射单元的次级发射机产 生的吞吐量，M表示配备反向散射单元的次级发射机数量，N表示配备能量捕获单元的次级 发射机数量。 in,
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Indicates that in the energy harvesting data transmission stage, the first
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Throughput produced by secondary transmitters equipped with energy harvesting units,
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Indicates that in the backscatter data transmission stage, the first
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where M is the number of secondary transmitters equipped with backscatter elements, and N is the number of secondary transmitters equipped with energy harvesting elements.

本实施例中，在满足主用户目标吞吐量的前提下，通过联合优化中继阶段

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，反向 散射数据传输阶段
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和能量捕获数据传输阶段的持续时间
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，实现次级用户的总吞吐量最 大化。 In this embodiment, under the premise of meeting the target throughput of the primary user, the relay stage is jointly optimized
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, the backscatter data transmission stage
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and the duration of the energy harvesting data transfer phase
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, to maximize the total throughput of secondary users.

在反向散射数据传输阶段，M个配备反向散射单元的次级发射机采用反向散射模 式发送数据给反向散射接收机，包括：M个配备反向散射单元的次级发射机被分配到相同的 时长传输数据，即

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。 In the backscatter data transmission phase, M secondary transmitters equipped with backscatter units transmit data to the backscatter receiver in the backscatter mode, including: M secondary transmitters equipped with backscatter units are allocated to transmit data for the same duration, ie
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.

在能量捕获数据传输阶段，N个只配备能量捕获单元的次级发射机利用捕获的能 量传输数据给能量捕获接收机，包括：N个配备能量捕获单元的次级发射机以时分多址 （Time Division Multiple Access，TDMA）的方式传输数据。每个发射机被分配到的时间表 示为：

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。In the energy harvesting data transmission stage, N secondary transmitters equipped with energy harvesting units use the captured energy to transmit data to energy harvesting receivers, including: N secondary transmitters equipped with energy harvesting units in time division multiple access (Time Division Multiple Access, TDMA) to transmit data. The times to which each transmitter is assigned are expressed as:
Figure 120330DEST_PATH_IMAGE074
.

实现次级用户的总吞吐量最大化，被表述为以下数学优化模型：Maximizing the total throughput of secondary users is expressed as the following mathematical optimization model:

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Figure 236053DEST_PATH_IMAGE075

本实施例优化模型的约束条件：

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,
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。 待优化的变量：
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。 The constraints of the optimization model in this embodiment:
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,
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. Variables to optimize:
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.

上述优化模型中，各个参数说明如下：In the above optimization model, each parameter is described as follows:

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：中继阶段的持续时间，单位是秒；
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: The duration of the relay phase, in seconds;

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：反向散射数据传输的持续时间，单位是秒；
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: Duration of backscatter data transmission, in seconds;

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：能量捕获数据传输阶段的持续时间，单位是秒；
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: The duration of the energy harvesting data transmission phase, in seconds;

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：在能量捕获数据传输阶段，第
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个配备能量捕获单元的次级发射机被分配到的 时间，单位是秒；
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: In the energy harvesting data transmission phase, the first
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The time, in seconds, that a secondary transmitter equipped with an energy harvesting unit is assigned;

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：在能量捕获数据传输阶段，第
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个配备能量捕获单元的 次级发射机产生的吞吐量，单位是比特每秒；
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: In the energy harvesting data transmission phase, the first
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Throughput produced by secondary transmitters equipped with energy harvesting units, in bits per second;

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：在反向散射数据传输阶段，第
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个配备反向散射单 元的次级发射机产生的吞吐量，单位是比特每秒，
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反向散射系数，
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表示主发射机的发射 功率；
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: In the backscatter data transmission stage, the first
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Throughput produced by secondary transmitters equipped with backscatter elements in bits per second,
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backscatter coefficient,
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Indicates the transmit power of the main transmitter;

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：在中继阶段，主接收机处实现的吞吐 量，单位是比特每秒；
Figure 711212DEST_PATH_IMAGE018
: In the relay phase, the throughput achieved at the main receiver, in bits per second;

Figure 996700DEST_PATH_IMAGE019
： 在反向散射数据传输阶段，主接收机处实现的吞吐 量，单位是比特每秒；
Figure 996700DEST_PATH_IMAGE019
: The throughput achieved at the main receiver during the backscatter data transmission phase, in bits per second;

Figure 999291DEST_PATH_IMAGE020
：主用户在每个时隙内的目标吞吐量，单位是比特每秒；
Figure 999291DEST_PATH_IMAGE020
: The target throughput of the primary user in each time slot, in bits per second;

Figure 99840DEST_PATH_IMAGE021
：信道带宽，单位是赫兹；
Figure 99840DEST_PATH_IMAGE021
: Channel bandwidth, unit is Hz;

Figure 264105DEST_PATH_IMAGE022
：环境噪声功率，单位是瓦；
Figure 264105DEST_PATH_IMAGE022
: ambient noise power, in watts;

Figure 568048DEST_PATH_IMAGE023
：第
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个配备能量捕获单元的次级发射机在授权频谱忙碌时捕 获到的能量，单位是焦耳；
Figure 568048DEST_PATH_IMAGE023
: No.
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The energy captured by a secondary transmitter equipped with an energy harvesting unit when the licensed spectrum is busy, in joules;

Figure 34112DEST_PATH_IMAGE024
：能量捕获效率；
Figure 34112DEST_PATH_IMAGE024
: energy capture efficiency;

Figure 962754DEST_PATH_IMAGE025
：从第
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个配备能量捕获单元的次级发射机到能量捕获接收机的信道增益；
Figure 962754DEST_PATH_IMAGE025
: from the
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The channel gain from a secondary transmitter equipped with an energy harvesting unit to an energy harvesting receiver;

Figure 816495DEST_PATH_IMAGE026
：从第
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个配备反向散射单元的次级发射机到反向散射接收机的信道增益；
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: from the
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channel gain from a secondary transmitter equipped with a backscatter unit to a backscatter receiver;

Figure 148436DEST_PATH_IMAGE027
：从主发射机到第
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个配备反向散射单元的次级发射机的信道增益；
Figure 148436DEST_PATH_IMAGE027
: From the main transmitter to the second
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channel gain of a secondary transmitter equipped with backscatter elements;

Figure 856946DEST_PATH_IMAGE028
：从主发射机到第
Figure 209430DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机的信道增益；
Figure 856946DEST_PATH_IMAGE028
: From the main transmitter to the second
Figure 209430DEST_PATH_IMAGE009
The channel gain of a secondary transmitter equipped with an energy harvesting unit;

Figure 469422DEST_PATH_IMAGE029
：从第
Figure 704095DEST_PATH_IMAGE009
个配备反向散射单元的次级发射机到主接收机的信道增益；
Figure 469422DEST_PATH_IMAGE029
: from the
Figure 704095DEST_PATH_IMAGE009
channel gain from a secondary transmitter equipped with a backscatter unit to the primary receiver;

Figure 390291DEST_PATH_IMAGE030
：从主发射机到主接收机的信道增益。
Figure 390291DEST_PATH_IMAGE030
: channel gain from main transmitter to main receiver.

本实施例中，约束条件说明如下：In this embodiment, the constraints are described as follows:

Figure 410331DEST_PATH_IMAGE006
：本实施例将一个时隙的长度归一化为1秒，三个阶段的时间 之和不超过一个时隙的长度。对于其他长度的时隙，本申请提供的方法仍然适用，只需按照 时隙长度等比例得到三个阶段的时长即可；
Figure 410331DEST_PATH_IMAGE006
: In this embodiment, the length of one time slot is normalized to 1 second, and the sum of the times of the three stages does not exceed the length of one time slot. For time slots of other lengths, the method provided by this application is still applicable, and it is only necessary to obtain the duration of the three stages in proportion to the length of the time slot;

Figure 523780DEST_PATH_IMAGE078
：每个阶段的持续时间非负；
Figure 523780DEST_PATH_IMAGE078
: the duration of each stage is non-negative;

Figure 776907DEST_PATH_IMAGE079
：在每个时隙中，主用户的吞吐量至少要满足目标吞吐量。
Figure 776907DEST_PATH_IMAGE079
: In each time slot, the throughput of the primary user must at least meet the target throughput.

步骤F2、求解优化模型的最优解，得到中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时间。Step F2, solving the optimal solution of the optimization model to obtain the duration of the relay phase, the backscatter data transmission phase and the energy capture data transmission phase.

本实施例通过对

Figure 1215DEST_PATH_IMAGE004
问题分别求关于
Figure 374296DEST_PATH_IMAGE001
，
Figure 658647DEST_PATH_IMAGE002
和
Figure 133491DEST_PATH_IMAGE013
的一阶偏导和二阶偏导，并且列出其 海森（Hessian）矩阵，发现该海森矩阵为半负定，因此可以得到
Figure 161490DEST_PATH_IMAGE004
问题是一个凸优化问题。 In this embodiment, the
Figure 1215DEST_PATH_IMAGE004
ask questions about
Figure 374296DEST_PATH_IMAGE001
,
Figure 658647DEST_PATH_IMAGE002
and
Figure 133491DEST_PATH_IMAGE013
The first-order partial derivative and second-order partial derivative of , and list its Hessian matrix, it is found that the Hessian matrix is semi-negative definite, so we can get
Figure 161490DEST_PATH_IMAGE004
The problem is a convex optimization problem.

假设

Figure 890542DEST_PATH_IMAGE004
问题的最优解为
Figure 345795DEST_PATH_IMAGE080
时，约束满足
Figure 307934DEST_PATH_IMAGE081
。 suppose
Figure 890542DEST_PATH_IMAGE004
The optimal solution to the problem is
Figure 345795DEST_PATH_IMAGE080
When the constraint satisfies
Figure 307934DEST_PATH_IMAGE081
.

假设

Figure 874045DEST_PATH_IMAGE004
问题的可行解为
Figure 487298DEST_PATH_IMAGE082
，且
Figure 113451DEST_PATH_IMAGE083
。 suppose
Figure 874045DEST_PATH_IMAGE004
The feasible solution to the problem is
Figure 487298DEST_PATH_IMAGE082
,and
Figure 113451DEST_PATH_IMAGE083
.

由于

Figure 31729DEST_PATH_IMAGE004
问题关于
Figure 401530DEST_PATH_IMAGE002
的偏导数大于0，使得可行解求得的吞吐量大于最优解的吞吐 量，这与最优解相矛盾。 because
Figure 31729DEST_PATH_IMAGE004
question about
Figure 401530DEST_PATH_IMAGE002
The partial derivative of is greater than 0, so that the throughput obtained by the feasible solution is greater than that of the optimal solution, which contradicts the optimal solution.

因而，通过上述结论

Figure 370754DEST_PATH_IMAGE004
问题取得最优解时，约束满足
Figure 167809DEST_PATH_IMAGE084
。此时优 化变量
Figure 838962DEST_PATH_IMAGE001
转化为
Figure 746875DEST_PATH_IMAGE031
。 Therefore, through the above conclusion
Figure 370754DEST_PATH_IMAGE004
When the problem is optimally solved, the constraints satisfy
Figure 167809DEST_PATH_IMAGE084
. Optimize variables at this time
Figure 838962DEST_PATH_IMAGE001
Converted to
Figure 746875DEST_PATH_IMAGE031
.

基于上述证明，

Figure 69141DEST_PATH_IMAGE004
问题转化为
Figure 37097DEST_PATH_IMAGE032
问题，如下： Based on the above proof,
Figure 69141DEST_PATH_IMAGE004
The problem turns into
Figure 37097DEST_PATH_IMAGE032
Questions are as follows:

Figure 461125DEST_PATH_IMAGE085
Figure 461125DEST_PATH_IMAGE085

其中，约束条件为：Among them, the constraints are:

Figure 172729DEST_PATH_IMAGE086
Figure 172729DEST_PATH_IMAGE086

转化为待优化的变量为：

Figure 850966DEST_PATH_IMAGE002
，
Figure 989823DEST_PATH_IMAGE087
Transformed into variables to be optimized are:
Figure 850966DEST_PATH_IMAGE002
,
Figure 989823DEST_PATH_IMAGE087

由于

Figure 369989DEST_PATH_IMAGE004
问题为凸优化问题，因此
Figure 885284DEST_PATH_IMAGE032
问题也为凸优化问题。 because
Figure 369989DEST_PATH_IMAGE004
The problem is a convex optimization problem, so
Figure 885284DEST_PATH_IMAGE032
The problem is also a convex optimization problem.

求解时，列出

Figure 176283DEST_PATH_IMAGE032
问题的拉格朗日函数，如下： When solving, list
Figure 176283DEST_PATH_IMAGE032
The Lagrangian function of the problem is as follows:

Figure 486041DEST_PATH_IMAGE088
。
Figure 486041DEST_PATH_IMAGE088
.

下面对拉格朗日函数中的各个参数进行说明，如下：The parameters in the Lagrangian function are described below, as follows:

Figure 353503DEST_PATH_IMAGE035
；
Figure 353503DEST_PATH_IMAGE035
;

Figure 406910DEST_PATH_IMAGE036
；
Figure 406910DEST_PATH_IMAGE036
;

Figure 59739DEST_PATH_IMAGE037
；
Figure 59739DEST_PATH_IMAGE037
;

Figure 540399DEST_PATH_IMAGE038
：拉格朗日乘子。
Figure 540399DEST_PATH_IMAGE038
: Lagrangian multiplier.

通过对拉格朗日函数求关于

Figure 160736DEST_PATH_IMAGE002
的一阶偏导数，令该一阶偏导数为零，可得
Figure 752254DEST_PATH_IMAGE002
的表达 式，如下： By finding the Lagrangian function about
Figure 160736DEST_PATH_IMAGE002
The first-order partial derivative of , let the first-order partial derivative be zero, we can get
Figure 752254DEST_PATH_IMAGE002
The expression of is as follows:

Figure 23705DEST_PATH_IMAGE039
； (1)
Figure 23705DEST_PATH_IMAGE039
; (1)

其中

Figure 675266DEST_PATH_IMAGE040
表示若
Figure 517320DEST_PATH_IMAGE041
，则
Figure 912529DEST_PATH_IMAGE042
，否则，
Figure 539951DEST_PATH_IMAGE043
。 in
Figure 675266DEST_PATH_IMAGE040
express if
Figure 517320DEST_PATH_IMAGE041
,but
Figure 912529DEST_PATH_IMAGE042
,otherwise,
Figure 539951DEST_PATH_IMAGE043
.

通过对拉格朗日函数求关于

Figure 362413DEST_PATH_IMAGE013
一阶偏导数，令该一阶偏导数为零，可得
Figure 691763DEST_PATH_IMAGE013
的表达 式，如下： By finding the Lagrangian function about
Figure 362413DEST_PATH_IMAGE013
The first-order partial derivative, let the first-order partial derivative be zero, we can get
Figure 691763DEST_PATH_IMAGE013
The expression of is as follows:

Figure 890664DEST_PATH_IMAGE044
Figure 890664DEST_PATH_IMAGE044

其中

Figure 871127DEST_PATH_IMAGE045
，发现该一阶偏导数是单调递减的，并由于超越函数很难得到
Figure 864491DEST_PATH_IMAGE013
的闭式表达式，因此采用二分搜索算法来求解
Figure 681137DEST_PATH_IMAGE013
。 in
Figure 871127DEST_PATH_IMAGE045
, it is found that the first-order partial derivative is monotonically decreasing, and due to the transcendental function it is difficult to obtain
Figure 864491DEST_PATH_IMAGE013
The closed-form expression of , so the binary search algorithm is used to solve
Figure 681137DEST_PATH_IMAGE013
.

拉格朗日乘子更新的表达式，如下：The expression of Lagrange multiplier update is as follows:

Figure 683728DEST_PATH_IMAGE089
Figure 683728DEST_PATH_IMAGE089

Figure 20163DEST_PATH_IMAGE090
Figure 20163DEST_PATH_IMAGE090

其中

Figure 184428DEST_PATH_IMAGE091
表示迭代次数，
Figure 488370DEST_PATH_IMAGE092
，
Figure 29073DEST_PATH_IMAGE093
为更新步长。 in
Figure 184428DEST_PATH_IMAGE091
represents the number of iterations,
Figure 488370DEST_PATH_IMAGE092
,
Figure 29073DEST_PATH_IMAGE093
is the update step.

本实施例

Figure 718549DEST_PATH_IMAGE004
问题的解决思路如下：首先将
Figure 319295DEST_PATH_IMAGE094
转化为
Figure 844954DEST_PATH_IMAGE032
问题；其次，由于
Figure 189348DEST_PATH_IMAGE094
为凸优化问题，因此
Figure 234795DEST_PATH_IMAGE032
问题也为凸优化问题。为求解
Figure 6442DEST_PATH_IMAGE032
问题，提出最优解迭代算法来解决； 通过块坐标下降法和梯度下降法分别更新待优化变量和拉格朗日乘子，直到待优化变量和 拉格朗日乘子都收敛，从而解得
Figure 19397DEST_PATH_IMAGE002
，
Figure 901903DEST_PATH_IMAGE003
，即
Figure 571830DEST_PATH_IMAGE094
的全局最优解。 This example
Figure 718549DEST_PATH_IMAGE004
The solution to the problem is as follows: firstly, the
Figure 319295DEST_PATH_IMAGE094
Converted to
Figure 844954DEST_PATH_IMAGE032
problems; secondly, due to
Figure 189348DEST_PATH_IMAGE094
is a convex optimization problem, so
Figure 234795DEST_PATH_IMAGE032
The problem is also a convex optimization problem. to solve
Figure 6442DEST_PATH_IMAGE032
The optimal solution iterative algorithm is proposed to solve the problem; the variables to be optimized and the Lagrangian multipliers are updated respectively by the block coordinate descent method and the gradient descent method until the variables to be optimized and the Lagrange multipliers converge, so that the solution is obtained
Figure 19397DEST_PATH_IMAGE002
,
Figure 901903DEST_PATH_IMAGE003
,Right now
Figure 571830DEST_PATH_IMAGE094
global optimal solution.

本实施例对于求解

Figure 514379DEST_PATH_IMAGE032
问题采用最优解迭代算法，步骤如下： This example solves for
Figure 514379DEST_PATH_IMAGE032
The optimal solution iteration algorithm is used for the problem, and the steps are as follows:

步骤4.1：设置初始化

Figure 14630DEST_PATH_IMAGE002
，
Figure 700826DEST_PATH_IMAGE048
的值，并且都大于等于0，初始化迭代次数
Figure 720866DEST_PATH_IMAGE049
。 Step 4.1: Setup initialization
Figure 14630DEST_PATH_IMAGE002
,
Figure 700826DEST_PATH_IMAGE048
value, and are greater than or equal to 0, the number of initialization iterations
Figure 720866DEST_PATH_IMAGE049
.

步骤4.2：判断

Figure 834316DEST_PATH_IMAGE050
超过N，若否，则采用二分搜索算法更新
Figure 821863DEST_PATH_IMAGE051
，通过固定
Figure 46171DEST_PATH_IMAGE002
，
Figure 684832DEST_PATH_IMAGE052
的 值，
Figure 703603DEST_PATH_IMAGE053
，然后跳到步骤4.2。否则，跳到步骤4.3。 Step 4.2: Judgment
Figure 834316DEST_PATH_IMAGE050
Exceeds N, if not, use binary search algorithm to update
Figure 821863DEST_PATH_IMAGE051
, fixed by
Figure 46171DEST_PATH_IMAGE002
,
Figure 684832DEST_PATH_IMAGE052
the value of
Figure 703603DEST_PATH_IMAGE053
, then skip to step 4.2. Otherwise, skip to step 4.3.

步骤4.3：通过固定

Figure 178447DEST_PATH_IMAGE054
基于公式(1)更新
Figure 206446DEST_PATH_IMAGE002
的值。 Step 4.3: Fix by
Figure 178447DEST_PATH_IMAGE054
Update based on formula (1)
Figure 206446DEST_PATH_IMAGE002
value.

步骤4.4：通过固定

Figure 201078DEST_PATH_IMAGE002
，
Figure 656330DEST_PATH_IMAGE055
基于公式(3)更新
Figure 352891DEST_PATH_IMAGE056
。 Step 4.4: Fix by
Figure 201078DEST_PATH_IMAGE002
,
Figure 656330DEST_PATH_IMAGE055
Update based on formula (3)
Figure 352891DEST_PATH_IMAGE056
.

步骤4.5：通过固定

Figure 919001DEST_PATH_IMAGE002
，
Figure 532254DEST_PATH_IMAGE057
基于公式(4)更新
Figure 158407DEST_PATH_IMAGE058
。 Step 4.5: Fix by
Figure 919001DEST_PATH_IMAGE002
,
Figure 532254DEST_PATH_IMAGE057
Update based on formula (4)
Figure 158407DEST_PATH_IMAGE058
.

步骤4.6：判断所有的变量是否收敛，若是，则跳到步骤4.7；否则，跳到步骤4.2。Step 4.6: Judge whether all variables are converged, if yes, go to step 4.7; otherwise, go to step 4.2.

步骤4.7：输出最优解

Figure 342264DEST_PATH_IMAGE059
，最优解
Figure 712065DEST_PATH_IMAGE060
。 Step 4.7: Output the optimal solution
Figure 342264DEST_PATH_IMAGE059
,Optimal solution
Figure 712065DEST_PATH_IMAGE060
.

其中，对于求解

Figure 681290DEST_PATH_IMAGE051
采用的二分搜索算法，步骤如下： Among them, for solving
Figure 681290DEST_PATH_IMAGE051
The binary search algorithm used, the steps are as follows:

步骤3.1：输入一个上界值

Figure 478344DEST_PATH_IMAGE061
，设置下界值
Figure 149497DEST_PATH_IMAGE062
，将
Figure 57410DEST_PATH_IMAGE063
替代
Figure 379676DEST_PATH_IMAGE051
带入到拉格朗日函数 对
Figure 347632DEST_PATH_IMAGE051
的一阶偏导数中，得到解
Figure 506081DEST_PATH_IMAGE064
； Step 3.1: Enter an upper bound value
Figure 478344DEST_PATH_IMAGE061
, set the lower bound value
Figure 149497DEST_PATH_IMAGE062
,Will
Figure 57410DEST_PATH_IMAGE063
replace
Figure 379676DEST_PATH_IMAGE051
into the Lagrange function pair
Figure 347632DEST_PATH_IMAGE051
In the first partial derivative of , the solution is obtained
Figure 506081DEST_PATH_IMAGE064
;

步骤3.2：设置循环次数为

Figure 217685DEST_PATH_IMAGE065
，初始值为1，判断解
Figure 895922DEST_PATH_IMAGE066
是否小于
Figure 34779DEST_PATH_IMAGE067
，
Figure 680524DEST_PATH_IMAGE067
为一个很小的数， 若是，则跳到步骤3.5，否则跳到步骤3.3，
Figure 195819DEST_PATH_IMAGE068
； Step 3.2: Set the number of cycles to
Figure 217685DEST_PATH_IMAGE065
, the initial value is 1, and the judgment solution
Figure 895922DEST_PATH_IMAGE066
Is it less than
Figure 34779DEST_PATH_IMAGE067
,
Figure 680524DEST_PATH_IMAGE067
is a very small number, if so, go to step 3.5, otherwise go to step 3.3,
Figure 195819DEST_PATH_IMAGE068
;

步骤3.3：判断

Figure 244676DEST_PATH_IMAGE069
是否大于0，若是，则
Figure 554435DEST_PATH_IMAGE070
，否则，
Figure 687476DEST_PATH_IMAGE071
； Step 3.3: Judgment
Figure 244676DEST_PATH_IMAGE069
Is it greater than 0, if so, then
Figure 554435DEST_PATH_IMAGE070
,otherwise,
Figure 687476DEST_PATH_IMAGE071
;

步骤3.4：将

Figure 740883DEST_PATH_IMAGE063
替代
Figure 393712DEST_PATH_IMAGE051
带入到拉格朗日函数对
Figure 874372DEST_PATH_IMAGE051
的一阶偏导数中，得到解
Figure 494709DEST_PATH_IMAGE069
，跳到 步骤3.2； Step 3.4: Put
Figure 740883DEST_PATH_IMAGE063
replace
Figure 393712DEST_PATH_IMAGE051
into the Lagrange function pair
Figure 874372DEST_PATH_IMAGE051
In the first partial derivative of , the solution is obtained
Figure 494709DEST_PATH_IMAGE069
, skip to step 3.2;

步骤3.5：此时得到的

Figure 86227DEST_PATH_IMAGE063
为
Figure 92098DEST_PATH_IMAGE051
的解。 Step 3.5: At this point get
Figure 86227DEST_PATH_IMAGE063
for
Figure 92098DEST_PATH_IMAGE051
solution.

以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。The above-mentioned embodiments only represent several implementation modes of the present application, and the description thereof is relatively specific and detailed, but it should not be construed as limiting the scope of the patent for the invention. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the scope of protection of the patent application should be based on the appended claims.

Claims (4)

1.一种基于反向散射中继传输的认知无线供能网络优化方法，其特征在于，所述认知无线供能网络包括对应主用户的主发射机和主接收机，以及对应第一次级用户的配备能量捕获单元的次级发射机和能量捕获接收机，以及对应第二次级用户的配备反向散射单元的次级发射机和反向散射接收机，所述基于反向散射中继传输的认知无线供能网络优化方法，包括：1. A cognitive wireless energy supply network optimization method based on backscatter relay transmission, characterized in that the cognitive wireless energy supply network includes a main transmitter and a main receiver corresponding to the main user, and a corresponding first A secondary transmitter equipped with an energy harvesting unit and an energy harvesting receiver of a secondary user, and a secondary transmitter and a backscatter receiver equipped with a backscatter unit corresponding to a second secondary user, the backscatter-based A cognitive wireless power supply network optimization method for relay transmission, including: 将所述认知无线供能网络的工作时隙分为中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段；Dividing the working time slots of the cognitive wireless energy supply network into a relay stage, a backscatter data transmission stage and an energy harvesting data transmission stage; 其中，在中继阶段主发射机发送数据给主接收机，配备反向散射单元的次级发射机采用反向散射模式中继主用户数据给主接收机，配备能量捕获单元的次级发射机进行能量捕获；Among them, in the relay stage, the main transmitter sends data to the main receiver, the secondary transmitter equipped with backscatter unit adopts the backscatter mode to relay the primary user data to the main receiver, and the secondary transmitter equipped with energy harvesting unit perform energy capture; 在反向散射数据传输阶段，主发射机发送数据给主接收机，配备反向散射单元的次级发射机采用反向散射模式发送数据给反向散射接收机，配备能量捕获单元的次级发射机进行能量捕获；In the backscatter data transmission phase, the primary transmitter sends data to the primary receiver, the secondary transmitter equipped with a backscatter unit sends data to the backscatter receiver in backscatter mode, and the secondary transmitter equipped with an energy harvesting unit machine for energy capture; 在能量捕获数据传输阶段，主发射机休眠，配备能量捕获单元的次级发射机利用捕获的能量传输数据给能量捕获接收机。In the energy harvesting data transmission stage, the primary transmitter is dormant, and the secondary transmitter equipped with an energy harvesting unit uses the captured energy to transmit data to the energy harvesting receiver. 2.根据权利要求1的基于反向散射中继传输的认知无线供能网络优化方法，其特征在于，所述基于反向散射中继传输的认知无线供能网络优化方法，还包括：2. The cognitive wireless power supply network optimization method based on backscatter relay transmission according to claim 1, wherein the cognitive wireless power supply network optimization method based on backscatter relay transmission further comprises: 将中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时间分别表示为：
Figure 641761DEST_PATH_IMAGE001
,
Figure 421499DEST_PATH_IMAGE002
和
Figure 879025DEST_PATH_IMAGE003
，在满足主用户目标吞吐量的前提下，以实现次级用户的总吞吐量最大化为目标构建优化模型
Figure 693397DEST_PATH_IMAGE004
：Denote the durations of the relay phase, the backscatter data transmission phase, and the energy harvesting data transmission phase as:
Figure 641761DEST_PATH_IMAGE001
,
Figure 421499DEST_PATH_IMAGE002
and
Figure 879025DEST_PATH_IMAGE003
, under the premise of satisfying the target throughput of the primary user, an optimization model is constructed with the goal of maximizing the total throughput of the secondary user
Figure 693397DEST_PATH_IMAGE004
:
Figure 328909DEST_PATH_IMAGE005
；
Figure 328909DEST_PATH_IMAGE005
; 满足如下约束条件：
Figure 658259DEST_PATH_IMAGE006
；
Figure 168744DEST_PATH_IMAGE007
；Satisfy the following constraints:
Figure 658259DEST_PATH_IMAGE006
;
Figure 168744DEST_PATH_IMAGE007
; 其中，
Figure 837622DEST_PATH_IMAGE008
表示在能量捕获数据传输阶段，第
Figure 893303DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机产生的吞吐量，
Figure 647632DEST_PATH_IMAGE010
表示在反向散射数据传输阶段，第
Figure 384644DEST_PATH_IMAGE011
个配备反向散射单元的次级发射机产生的吞吐量，M表示配备反向散射单元的次级发射机数量，N表示配备能量捕获单元的次级发射机数量，
Figure 721079DEST_PATH_IMAGE012
；
Figure 150923DEST_PATH_IMAGE013
表示在能量捕获数据传输阶段，第
Figure 454866DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机被分配到的时间；in,
Figure 837622DEST_PATH_IMAGE008
Indicates that in the energy harvesting data transmission stage, the first
Figure 893303DEST_PATH_IMAGE009
Throughput produced by secondary transmitters equipped with energy harvesting units,
Figure 647632DEST_PATH_IMAGE010
Indicates that in the backscatter data transmission stage, the first
Figure 384644DEST_PATH_IMAGE011
Throughput produced by secondary transmitters equipped with backscatter elements, M is the number of secondary transmitters equipped with backscatter elements, N is the number of secondary transmitters equipped with energy harvesting elements,
Figure 721079DEST_PATH_IMAGE012
;
Figure 150923DEST_PATH_IMAGE013
Indicates that in the energy harvesting data transmission stage, the first
Figure 454866DEST_PATH_IMAGE009
The time at which secondary transmitters equipped with energy harvesting units are assigned;
Figure 729989DEST_PATH_IMAGE014
，表示在能量捕获数据传输阶段，第
Figure 685044DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机产生的吞吐量；
Figure 729989DEST_PATH_IMAGE014
, which means that in the stage of energy harvesting data transmission, the first
Figure 685044DEST_PATH_IMAGE009
Throughput produced by secondary transmitters equipped with energy harvesting units;
Figure 20211DEST_PATH_IMAGE015
，表示在反向散射数据传输阶段，第
Figure 811449DEST_PATH_IMAGE011
个配备反向散射单元的次级发射机产生的吞吐量，
Figure 890264DEST_PATH_IMAGE016
反向散射系数，
Figure 935711DEST_PATH_IMAGE017
表示主发射机的发射功率；
Figure 20211DEST_PATH_IMAGE015
, which means that in the backscatter data transmission stage, the first
Figure 811449DEST_PATH_IMAGE011
Throughput produced by secondary transmitters equipped with backscatter elements,
Figure 890264DEST_PATH_IMAGE016
backscatter coefficient,
Figure 935711DEST_PATH_IMAGE017
Indicates the transmit power of the main transmitter;
Figure 707358DEST_PATH_IMAGE018
，表示在中继阶段，主接收机处实现的吞吐量；
Figure 707358DEST_PATH_IMAGE018
, represents the throughput achieved at the master receiver during the relay phase;
Figure 985893DEST_PATH_IMAGE019
，表示在反向散射数据传输阶段，主接收机处实现的吞吐量；
Figure 985893DEST_PATH_IMAGE019
, represents the throughput achieved at the main receiver during the backscatter data transmission phase;
Figure 868398DEST_PATH_IMAGE020
表示主用户在每个时隙内的目标吞吐量；
Figure 868398DEST_PATH_IMAGE020
Indicates the target throughput of the primary user in each time slot;
Figure 532467DEST_PATH_IMAGE021
表示信道带宽；
Figure 532467DEST_PATH_IMAGE021
Indicates the channel bandwidth;
Figure 475015DEST_PATH_IMAGE022
表示环境噪声功率；
Figure 475015DEST_PATH_IMAGE022
Indicates the ambient noise power;
Figure 975266DEST_PATH_IMAGE023
，表示第
Figure 395883DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机在授权频谱忙碌时捕获到的能量，
Figure 681502DEST_PATH_IMAGE024
表示能量捕获效率；
Figure 975266DEST_PATH_IMAGE023
, indicating the first
Figure 395883DEST_PATH_IMAGE009
The energy captured by a secondary transmitter equipped with an energy harvesting unit when the licensed spectrum is busy,
Figure 681502DEST_PATH_IMAGE024
Indicates the energy capture efficiency;
Figure 794952DEST_PATH_IMAGE025
表示从第
Figure 516920DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机到能量捕获接收机的信道增益；
Figure 794952DEST_PATH_IMAGE025
means from the
Figure 516920DEST_PATH_IMAGE009
The channel gain from a secondary transmitter equipped with an energy harvesting unit to an energy harvesting receiver;
Figure 741228DEST_PATH_IMAGE026
表示从第
Figure 374029DEST_PATH_IMAGE009
个配备反向散射单元的次级发射机到反向散射接收机的信道增益；
Figure 741228DEST_PATH_IMAGE026
means from the
Figure 374029DEST_PATH_IMAGE009
channel gain from a secondary transmitter equipped with a backscatter unit to a backscatter receiver;
Figure 658380DEST_PATH_IMAGE027
表示从主发射机到第
Figure 133224DEST_PATH_IMAGE009
个配备反向散射单元的次级发射机的信道增益；
Figure 658380DEST_PATH_IMAGE027
Indicates from the main transmitter to the second
Figure 133224DEST_PATH_IMAGE009
channel gain of a secondary transmitter equipped with backscatter elements;
Figure 161223DEST_PATH_IMAGE028
表示从主发射机到第
Figure 890275DEST_PATH_IMAGE009
个配备能量捕获单元的次级发射机的信道增益；
Figure 161223DEST_PATH_IMAGE028
Indicates from the main transmitter to the second
Figure 890275DEST_PATH_IMAGE009
The channel gain of a secondary transmitter equipped with an energy harvesting unit;
Figure 79948DEST_PATH_IMAGE029
表示从第
Figure 307667DEST_PATH_IMAGE009
个配备反向散射单元的次级发射机到主接收机的信道增益；
Figure 79948DEST_PATH_IMAGE029
means from the
Figure 307667DEST_PATH_IMAGE009
channel gain from a secondary transmitter equipped with a backscatter unit to the primary receiver;
Figure 873778DEST_PATH_IMAGE030
表示从主发射机到主接收机的信道增益；
Figure 873778DEST_PATH_IMAGE030
Indicates the channel gain from the main transmitter to the main receiver; 求解优化模型的最优解，得到中继阶段、反向散射数据传输阶段和能量捕获数据传输阶段的持续时间。The optimal solution of the optimized model is solved for the duration of the relay phase, the backscatter data transmission phase, and the energy harvesting data transmission phase. 3.根据权利要求2的基于反向散射中继传输的认知无线供能网络优化方法，其特征在于，所述求解优化模型的最优解，包括：3. The cognitive wireless energy supply network optimization method based on backscatter relay transmission according to claim 2, wherein the optimal solution of the optimization model includes: 将优化变量
Figure 221451DEST_PATH_IMAGE001
转化为
Figure 909922DEST_PATH_IMAGE031
，带入到优化模型，得到优化模型
Figure 297041DEST_PATH_IMAGE032
：will optimize the variable
Figure 221451DEST_PATH_IMAGE001
Converted to
Figure 909922DEST_PATH_IMAGE031
, into the optimization model to obtain the optimization model
Figure 297041DEST_PATH_IMAGE032
:
Figure 479892DEST_PATH_IMAGE033
；
Figure 479892DEST_PATH_IMAGE033
; 列出
Figure 370487DEST_PATH_IMAGE032
的拉格朗日函数，如下：list
Figure 370487DEST_PATH_IMAGE032
The Lagrange function of is as follows:
Figure 964280DEST_PATH_IMAGE034
Figure 964280DEST_PATH_IMAGE034
 其中：in:
Figure 573115DEST_PATH_IMAGE035
；
Figure 573115DEST_PATH_IMAGE035
;
Figure 323771DEST_PATH_IMAGE036
；
Figure 323771DEST_PATH_IMAGE036
;
Figure 334453DEST_PATH_IMAGE037
；
Figure 334453DEST_PATH_IMAGE037
;
Figure 99146DEST_PATH_IMAGE038
，为拉格朗日乘子；
Figure 99146DEST_PATH_IMAGE038
, is the Lagrangian multiplier; 通过对拉格朗日函数求关于
Figure 8328DEST_PATH_IMAGE002
的一阶偏导数，令该一阶偏导数为零，得到
Figure 47828DEST_PATH_IMAGE002
的表达式，如下：By finding the Lagrangian function about
Figure 8328DEST_PATH_IMAGE002
The first-order partial derivative of , let the first-order partial derivative be zero, get
Figure 47828DEST_PATH_IMAGE002
The expression of is as follows:
Figure 913016DEST_PATH_IMAGE039
； （1）
Figure 913016DEST_PATH_IMAGE039
; (1) 其中
Figure 97878DEST_PATH_IMAGE040
表示若
Figure 681306DEST_PATH_IMAGE041
，则
Figure 258918DEST_PATH_IMAGE042
，否则，
Figure 244192DEST_PATH_IMAGE043
；in
Figure 97878DEST_PATH_IMAGE040
express if
Figure 681306DEST_PATH_IMAGE041
,but
Figure 258918DEST_PATH_IMAGE042
,otherwise,
Figure 244192DEST_PATH_IMAGE043
; 通过对拉格朗日函数求关于
Figure 101421DEST_PATH_IMAGE013
一阶偏导数，令该一阶偏导数为零，得
Figure 172145DEST_PATH_IMAGE013
的表达式，如下：By finding the Lagrangian function about
Figure 101421DEST_PATH_IMAGE013
The first-order partial derivative, let the first-order partial derivative be zero, get
Figure 172145DEST_PATH_IMAGE013
The expression of is as follows:
Figure 287868DEST_PATH_IMAGE044
Figure 287868DEST_PATH_IMAGE044
 其中
Figure 127648DEST_PATH_IMAGE045
；in
Figure 127648DEST_PATH_IMAGE045
; 拉格朗日乘子更新的表达式，如下：The expression of Lagrange multiplier update is as follows:
Figure 191331DEST_PATH_IMAGE046
； （3）
Figure 191331DEST_PATH_IMAGE046
; (3)
Figure 280510DEST_PATH_IMAGE047
； （4）
Figure 280510DEST_PATH_IMAGE047
;(4) 然后求解优化模型
Figure 137608DEST_PATH_IMAGE032
，包括：Then solve the optimization model
Figure 137608DEST_PATH_IMAGE032
,include: 步骤4.1：设置初始化
Figure 644943DEST_PATH_IMAGE002
，
Figure 296505DEST_PATH_IMAGE048
的值，并且都大于等于0，初始化迭代次数
Figure 404138DEST_PATH_IMAGE049
；Step 4.1: Setup initialization
Figure 644943DEST_PATH_IMAGE002
,
Figure 296505DEST_PATH_IMAGE048
value, and are greater than or equal to 0, the number of initialization iterations
Figure 404138DEST_PATH_IMAGE049
; 步骤4.2：判断
Figure 799347DEST_PATH_IMAGE050
超过N，若否，则采用二分搜索算法更新
Figure 659725DEST_PATH_IMAGE051
，通过固定
Figure 75662DEST_PATH_IMAGE002
，
Figure 342696DEST_PATH_IMAGE052
的值，
Figure 89066DEST_PATH_IMAGE053
，然后跳到步骤4.2；否则，跳到步骤4.3；Step 4.2: Judgment
Figure 799347DEST_PATH_IMAGE050
Exceeds N, if not, use binary search algorithm to update
Figure 659725DEST_PATH_IMAGE051
, fixed by
Figure 75662DEST_PATH_IMAGE002
,
Figure 342696DEST_PATH_IMAGE052
the value of
Figure 89066DEST_PATH_IMAGE053
, then skip to step 4.2; otherwise, skip to step 4.3; 步骤4.3：通过固定
Figure 492366DEST_PATH_IMAGE054
基于公式(1)更新
Figure 813625DEST_PATH_IMAGE002
的值；Step 4.3: Fix by
Figure 492366DEST_PATH_IMAGE054
Update based on formula (1)
Figure 813625DEST_PATH_IMAGE002
value; 步骤4.4：通过固定
Figure 879539DEST_PATH_IMAGE002
，
Figure 616551DEST_PATH_IMAGE055
基于公式(3)更新
Figure 202253DEST_PATH_IMAGE056
；Step 4.4: Fix by
Figure 879539DEST_PATH_IMAGE002
,
Figure 616551DEST_PATH_IMAGE055
Update based on formula (3)
Figure 202253DEST_PATH_IMAGE056
; 步骤4.5：通过固定
Figure 632098DEST_PATH_IMAGE002
，
Figure 421193DEST_PATH_IMAGE057
基于公式(4)更新
Figure 961896DEST_PATH_IMAGE058
；Step 4.5: Fix by
Figure 632098DEST_PATH_IMAGE002
,
Figure 421193DEST_PATH_IMAGE057
Update based on formula (4)
Figure 961896DEST_PATH_IMAGE058
; 步骤4.6：判断所有的变量是否收敛，若是，则跳到步骤4.7，否则，跳到步骤4.2；Step 4.6: Judging whether all variables are convergent, if so, skip to step 4.7, otherwise, skip to step 4.2; 步骤4.7：输出最优解
Figure 667684DEST_PATH_IMAGE059
，最优解
Figure 314435DEST_PATH_IMAGE060
。Step 4.7: Output the optimal solution
Figure 667684DEST_PATH_IMAGE059
,Optimal solution
Figure 314435DEST_PATH_IMAGE060
. 4.根据权利要求3的基于反向散射中继传输的认知无线供能网络优化方法，其特征在于，所述采用二分搜索算法更新
Figure 43356DEST_PATH_IMAGE051
，包括：4. The cognitive wireless energy supply network optimization method based on backscattering relay transmission according to claim 3, characterized in that, the binary search algorithm is used to update
Figure 43356DEST_PATH_IMAGE051
,include: 步骤3.1：输入一个上界值
Figure 184488DEST_PATH_IMAGE061
，设置下界值
Figure 682465DEST_PATH_IMAGE062
，将
Figure 1582DEST_PATH_IMAGE063
替代
Figure 217800DEST_PATH_IMAGE051
带入到拉格朗日函数对
Figure 162622DEST_PATH_IMAGE051
的一阶偏导数中，得到解
Figure 844269DEST_PATH_IMAGE064
；Step 3.1: Enter an upper bound value
Figure 184488DEST_PATH_IMAGE061
, set the lower bound value
Figure 682465DEST_PATH_IMAGE062
,Will
Figure 1582DEST_PATH_IMAGE063
replace
Figure 217800DEST_PATH_IMAGE051
into the Lagrange function pair
Figure 162622DEST_PATH_IMAGE051
In the first partial derivative of , the solution is obtained
Figure 844269DEST_PATH_IMAGE064
; 步骤3.2：设置循环次数为
Figure 786817DEST_PATH_IMAGE065
，初始值为1，判断解
Figure 224751DEST_PATH_IMAGE066
是否小于
Figure 707685DEST_PATH_IMAGE067
，
Figure 993304DEST_PATH_IMAGE067
为一个很小的数，若是，则跳到步骤3.5，否则跳到步骤3.3，
Figure 841174DEST_PATH_IMAGE068
；Step 3.2: Set the number of cycles to
Figure 786817DEST_PATH_IMAGE065
, the initial value is 1, and the judgment solution
Figure 224751DEST_PATH_IMAGE066
Is it less than
Figure 707685DEST_PATH_IMAGE067
,
Figure 993304DEST_PATH_IMAGE067
is a very small number, if so, go to step 3.5, otherwise go to step 3.3,
Figure 841174DEST_PATH_IMAGE068
; 步骤3.3：判断
Figure 828722DEST_PATH_IMAGE069
是否大于0，若是，则
Figure 426931DEST_PATH_IMAGE070
，否则，
Figure 567057DEST_PATH_IMAGE071
；Step 3.3: Judgment
Figure 828722DEST_PATH_IMAGE069
Is it greater than 0, if so, then
Figure 426931DEST_PATH_IMAGE070
,otherwise,
Figure 567057DEST_PATH_IMAGE071
; 步骤3.4：将
Figure 225309DEST_PATH_IMAGE063
替代
Figure 637836DEST_PATH_IMAGE051
带入到拉格朗日函数对
Figure 462572DEST_PATH_IMAGE051
的一阶偏导数中，得到解
Figure 644155DEST_PATH_IMAGE069
，跳到步骤3.2；Step 3.4: Put
Figure 225309DEST_PATH_IMAGE063
replace
Figure 637836DEST_PATH_IMAGE051
into the Lagrange function pair
Figure 462572DEST_PATH_IMAGE051
In the first partial derivative of , the solution is obtained
Figure 644155DEST_PATH_IMAGE069
, skip to step 3.2; 步骤3.5：此时得到的
Figure 912456DEST_PATH_IMAGE063
为
Figure 874596DEST_PATH_IMAGE051
的解。Step 3.5: At this point get
Figure 912456DEST_PATH_IMAGE063
for
Figure 874596DEST_PATH_IMAGE051
solution.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014172978A1 (en) * 2013-04-22 2014-10-30 东南大学 Ofdm wireless relay network system and resource distribution method therefor
CN109547039A (en) * 2019-01-16 2019-03-29 西安交通大学 A kind of intelligent environment backscatter communication method
KR102090620B1 (en) * 2018-11-27 2020-03-18 성균관대학교 산학협력단 System and method for backscatter-based cooperative communication in wireless-powered heterogeneous network
CN112087792A (en) * 2020-08-07 2020-12-15 浙江工业大学 Node-to-relay node communication method of backscattering-assisted wireless energy supply network
CN112564779A (en) * 2020-12-08 2021-03-26 南京爱而赢科技有限公司 Throughput optimization method based on transmission fairness for backscattering communication network
CN113473497A (en) * 2021-06-11 2021-10-01 河南垂天科技有限公司 Maximum sum rate optimization method in backscatter assisted cooperative NOMA system
CN113490223A (en) * 2021-08-13 2021-10-08 西北工业大学太仓长三角研究院 Wireless energy supply backscattering communication method and system based on IRS
CN114222318A (en) * 2021-12-08 2022-03-22 重庆邮电大学 A Robust Optimization Method for Cognitive Wireless Powered Backscatter Communication Networks

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014172978A1 (en) * 2013-04-22 2014-10-30 东南大学 Ofdm wireless relay network system and resource distribution method therefor
KR102090620B1 (en) * 2018-11-27 2020-03-18 성균관대학교 산학협력단 System and method for backscatter-based cooperative communication in wireless-powered heterogeneous network
CN109547039A (en) * 2019-01-16 2019-03-29 西安交通大学 A kind of intelligent environment backscatter communication method
CN112087792A (en) * 2020-08-07 2020-12-15 浙江工业大学 Node-to-relay node communication method of backscattering-assisted wireless energy supply network
CN112564779A (en) * 2020-12-08 2021-03-26 南京爱而赢科技有限公司 Throughput optimization method based on transmission fairness for backscattering communication network
CN113473497A (en) * 2021-06-11 2021-10-01 河南垂天科技有限公司 Maximum sum rate optimization method in backscatter assisted cooperative NOMA system
CN113490223A (en) * 2021-08-13 2021-10-08 西北工业大学太仓长三角研究院 Wireless energy supply backscattering communication method and system based on IRS
CN114222318A (en) * 2021-12-08 2022-03-22 重庆邮电大学 A Robust Optimization Method for Cognitive Wireless Powered Backscatter Communication Networks

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
毛科技，吴晏媛，黄亮: "后向散射辅助无线供能网络中的节点间高吞吐量通信方案", 传感技术学报, vol. 33, no. 12, 15 December 2020 (2020-12-15), pages 1 - 8 *

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