CN-116095692-B - Power distribution method of energy acquisition cognitive wireless network based on non-cooperative game

Abstract

The invention provides a power distribution method of an energy acquisition cognitive wireless network based on non-cooperative game, which comprises the following steps of S1, a step of setting a determined minimum signal-to-noise ratio threshold in the data transmission process of a (1-tau) T time period of a time slot T, wherein a primary user transmitter PT transmits data to a primary user receiver PR through an antenna, each secondary user receiver SU is provided with an omnidirectional antenna for energy acquisition to acquire energy in PU radio frequency signals, and a step of S2, a step of transmitting data to a secondary user receiver PR is carried out in the data transmission process of the (1-tau) T time period of the time slot T The method comprises the steps of S3, carrying out power distribution on SU i (i=1, 2.) in a (1-tau) T time period of a time slot T in a non-cooperative game mode, S4, solving utility functions of SU i (i=1, 2.) in a (1-tau) T time period of the time slot T, and finally achieving Nash equilibrium, maximizing throughput of a secondary user and benefits of the primary user and the secondary user.

Inventors

• WANG JUN
• LIU SHENG
• LIN RUIQUAN
• WANG RUILIANG
• BAO JIAWANG
• Qiu hangding

Assignees

• 福州大学

Dates

Publication Date

20260505

Application Date

20221029

Claims (1)

1. 1. The power distribution method of the energy acquisition cognitive wireless network based on the non-cooperative game is used for a radio network and is characterized by comprising the following steps of; Step S1, in one time slot A kind of electronic device During a time period, the primary user transmitter PT transmits data via the antenna to the primary user receivers PR, each secondary user receiver The omnidirectional antenna for energy collection is equipped to collect the energy in the PU radio frequency signal so as to relieve the energy consumption in the data transmission stage, and the obtained energy is ; Step S2, in one time slot A kind of electronic device Setting a certain minimum signal-to-noise ratio threshold value in the data transmission process of the time period And interference power threshold of PU ; Step S3, in one time slot A kind of electronic device In the course of the time period, , Performing power distribution in a non-cooperative game mode, and defining a utility function by taking the transmitting power as a cost function; Step S4, in one time slot A kind of electronic device Solving for the time period Finally, nash equilibrium is achieved, and an optimal power allocation strategy is obtained under the condition of Nash equilibrium solution, so that throughput of the secondary user and benefits of the primary user and the secondary user are maximized; the radio network is an underley cognitive radio, and step S1 specifically comprises the steps of, in a time slot A kind of electronic device During a time period, the PT transmits data to the PR via the directional antenna, each An omni-directional antenna for energy collection is arranged to collect the energy in the PU radio frequency signal to relieve the energy consumption in the data transmission stage, and the obtained energy is : , wherein, The energy harvesting efficiency is represented by the energy harvesting efficiency, In order for the energy to be harvested for gain, Representing the transmit power of the PT, in which a pair of primary users and two secondary users are set; The radio network is an underley cognitive radio, and no reflection exists or the reflection is negligible in the data transmission process in the step S2, and the method comprises the following steps of; Step S21 in one time slot A kind of electronic device During a time period when Is greater than a certain determined minimum snr threshold When the data is considered to be successfully transmitted, namely: , Then The signal-to-noise ratio at the receiving end is defined as: Formula one; Wherein, the Representing the power of the gaussian white noise, Representation of Is used for the transmission power of the (c), Representation of Link gain with the secondary user access point SBS, Is defined as , Is a constant, is determined by fading, Representation of Distance to SBS, fading factor Is a constant; Make the upper middle In the second formula, the first formula is, Representation of Interference received; step S22, in one time slot A kind of electronic device In the course of the time period, On the premise of ensuring the communication quality of the PU, sharing the spectrum resource of the PU, and setting an interference power threshold value by the PU , At less than the PU interference power threshold On the premise of carrying out data transmission, if no reflection exists in the data transmission process, the interference constraint condition of the system is expressed as follows: A formula III; Wherein, the Representation of The link gain to the PU can be derived from equation three: A formula IV; from the above equation, if Is set to the transmission power of (a) Exceeding the maximum transmit power Then it will affect the normal communication of the PU, then the The transmission power must be reduced or the spectrum of the section must be exited to ensure the communication quality of the PU; the radio network is an underley cognitive radio, and step S3 specifically comprises the steps of, in a time slot A kind of electronic device In the course of the time period, Performing power distribution in a non-cooperative game mode, and defining a utility function by taking the transmitting power as a cost function, wherein the method comprises the following steps of; step S31 in one time slot A kind of electronic device In the time period, the power distribution problem based on the energy acquisition cognitive radio network is regarded as a repeated non-cooperative game process, a utility function model of power distribution is provided for the non-cooperative game model, and in the utility function model, Representing a non-cooperative game of chance, The number of secondary users is indicated, Representation of Policy space of (a) , Is that Is used for the transmission of the data, Representing the benefits of the game, wherein Representation divide by Therefore, the non-cooperative game power distribution model of the energy acquisition cognitive radio network can be defined as A fifth formula; step S32, in one time slot A kind of electronic device In the course of the time period, Selecting an optimal strategy to obtain Nash equilibrium, i.e Due to The higher the transmit power, the more interference will be to other nodes and more energy will be consumed by itself, so the utility function is defined as a cost function with transmit power, namely: a formula six; Wherein, the Is of the size of The number of information bits contained in the bit data packet, For the transmission rate of the data, Is an efficiency function defined as The formula seven is given by the formula, Wherein the method comprises the steps of As a bit error rate, the bit error rate depends on the channel state and the interference from other network links; the representation is based on a transmit power cost function, Representing the price adjustment factor, the presence of the cost function causing Selecting factor constraints subject to global optimum transmit power; The radio network is an underley cognitive radio, and step S4 is specifically performed in a time slot A kind of electronic device Solving for the time period Finally, nash equilibrium is achieved, and an optimal power allocation strategy is obtained under the condition of Nash equilibrium solution, so that throughput and income of the Nash equilibrium solution are maximized, and the method comprises the following steps: Step S41 from Policy space for transmit power of (a) Find an optimal transmit power In order to obtain the optimal transmitting power, the model must be verified to have a unique Nash equilibrium point; The verification method comprises determining the transmitting power of utility function expression according to the definition of the super-mode game model First derivative of (i.e.) Formula eight; Re-pairing The first order partial derivative is obtained and the first order partial derivative is obtained, Formula nine; Wherein: Formula ten; Formula eleven; When (when) In the time-course of which the first and second contact surfaces, Thus can be deduced Formula twelve; According to Topkis, according to the principle of the fixed point, all the supermode games have unique Nash equilibrium points, so that the Nash equilibrium points of the model exist and have uniqueness to be demonstrated; step S42, nash equilibrium solution for solving the model Determining the transmitting power of the utility function expression Is obtained by first derivative of (a) Formula thirteen; according to the maximum theory, let its partial derivative expression equal to 0, obtain: Formula fourteen; solving the above method can be achieved: Fifteen equations; Adopting Newton iteration method to obtain The iterative formula of the transmitting power is: A formula sixteen; Step S43, substituting each power iteration value into the following formula to obtain corresponding throughput until iteration is stopped, and obtaining the maximum throughput at the moment; Seventeenth formula; Wherein, the Representing the bandwidth of the channel; Step S44, substituting each power iteration value into the following formula to obtain corresponding benefits until iteration is stopped, and obtaining the maximum benefits at the moment; The formula eighteen.

Description

Power distribution method of energy acquisition cognitive wireless network based on non-cooperative game Technical Field The invention relates to the technical field of cognitive radio, in particular to a power distribution method of an energy acquisition cognitive wireless network based on non-cooperative game. Background With the development of technology, wireless communication devices have increased dramatically, and various wireless communication devices have largely accessed into wireless networks, resulting in shortage of wireless spectrum resources. Cognitive radio is a technology that can fully utilize idle spectrum resources. The intelligent communication system can sense the external communication environment and perform self-regulation according to the change of the environment, so that the intelligent communication function is realized, and the problem of shortage of electromagnetic spectrum resources can be relieved to a certain extent. Therefore, the cognitive radio technology also becomes a hot research direction of new generation wireless communication. A cognitive radio network is a wireless communication network that can intelligently learn and perceive surrounding network environment information and change some parameters (such as power, modulation techniques, rate, etc.) during surrounding environment interactions. The cognitive radio network can sense holes in the electromagnetic spectrum and effectively utilize the specific idle spectrum, so that the situation of shortage of electromagnetic spectrum resources can be effectively relieved. The secondary user is controlled to access to a specific idle frequency spectrum by the primary user under the condition of guaranteeing the communication quality, so that the frequency spectrum resource utilization rate of the primary user and the system capacity of the whole cognitive radio network are higher. In addition, in the cognitive radio network, a certain problem exists in energy supply, and secondary users in the traditional cognitive radio network often adopt a storage battery power supply mode to supply power, and the secondary users need to be charged or replaced regularly. This places a certain limit on the performance of the cognitive radio network. Therefore, to solve this problem, how to apply the energy harvesting technology to the cognitive radio network is also a necessary consideration. The energy collection is a technology for supporting continuous power supply of energy-limited equipment, and can collect energy from natural environment to supply power for the equipment under the condition of no supervision. The energy collection technology can collect energy from natural resources such as sunlight, wind, geothermal, tide and the like and radio frequency resources, however, natural resource collection is often carried out through some special power equipment, and the collection of the radio frequency resources can be realized by simply utilizing the antenna of the communication equipment for multiplexing, so that the application is facilitated. Here, we will mainly consider radio frequency energy collection, where the radio frequency energy collection technology allows the secondary user to collect energy from the radio frequency signal of the primary user and use the energy for data transmission, which can solve the problem that the secondary user breaks information due to insufficient energy in the data transmission process, and can reduce energy consumption in the cognitive radio network to a certain extent. Therefore, the energy collection technology is introduced into the cognitive radio network, so that not only can the spectrum resources be fully utilized, but also the problem of energy supply can be partially solved. In the cognitive radio network, due to the competition relationship among the secondary users, each secondary user can increase its own transmitting power as much as possible in order to maximize its benefit in the process of electromagnetic spectrum resource allocation. However, the transmit power of each secondary user is interfering with other adjacent secondary users, and blindly increasing the transmit power of each other may result in greater interference in the network, but may not necessarily result in a higher signal-to-noise ratio. Therefore, the reasonable power distribution mechanism can reduce interference generated by secondary users, improve the throughput of the system, save electricity to prolong the service life of the terminal and improve the network performance. The game theory is an effective mathematical analysis tool, and can effectively solve the problem of competition of power distribution among secondary users. Disclosure of Invention The invention provides a power distribution method of an energy acquisition cognitive radio network based on a non-cooperative game, which improves the throughput and the income of secondary users under the condition that all constraint conditions are