CN112788765B

CN112788765B - Power optimization method of user equipment energy efficiency, communication method and device

Info

Publication number: CN112788765B
Application number: CN202011630720.8A
Authority: CN
Inventors: 陈宇; 李羽佳
Original assignee: Beijing University of Posts and Telecommunications
Current assignee: Beijing University of Posts and Telecommunications
Priority date: 2020-12-30
Filing date: 2020-12-30
Publication date: 2022-09-09
Anticipated expiration: 2040-12-30
Also published as: CN112788765A

Abstract

The invention provides a power optimization method, a communication method and a device for energy efficiency of user equipment, wherein the power optimization method comprises the following steps: user devices of multiple cells whose spectra overlap form a set of players; according to the data volume and the bit error rate function of the data packet to be sent generated by the user equipment in the player set, the successful sending probability of the data packet of the user equipment is obtained; obtaining the effective capacity efficiency of the user equipment according to the effective capacity, the transmission power, the circuit module energy consumption and the successful data packet transmission probability of the cell to which each user equipment belongs; taking the transmitting power of the user equipment as a player strategy and taking an effective capacity efficiency function as a utility function; and adjusting the transmitting power of the user equipment, calculating a signal-to-interference-and-noise ratio, and calculating an effective capacity efficiency value according to the effective capacity efficiency function and the signal-to-interference-and-noise ratio value to obtain a transmitting power value at the Nash equilibrium value. By the scheme, the energy-efficient power distribution can be optimized under the condition of ensuring the service quality of the user conveniently.

Description

Power optimization method of user equipment energy efficiency, communication method and device

Technical Field

The invention relates to the technical field of wireless communication, in particular to a power optimization method, a communication method and a device for energy efficiency of user equipment.

Background

The ultra-dense networking improves the reuse degree of network space resources, realizes the improvement of network capacity, gradually deploys a large number of micro base stations, pico base stations, home base stations and other small micro base stations on the basis of a heterogeneous network, and greatly increases access points. Access point densification, however, has raised significant problems while improving coverage, throughput, spectral efficiency, etc.

The increasing density of base station deployment has shortened the distance between base stations. When a 5G network is actually deployed, because an OFDM (Orthogonal Frequency Division Multiplexing) technology is used, a same-Frequency Multiplexing mechanism is adopted among densely deployed base stations to save scarce spectrum resources, which inevitably causes a serious inter-cell interference problem and greatly affects the overall performance of the network.

Due to the emergence of diverse emerging services of the internet, mobile users have more stringent and differentiated requirements for quality of service (QoS). Therefore, guaranteeing QoS requirements of services presents a great challenge to technologies such as resource allocation, analysis and deployment of ultra-dense networks.

In the ultra-dense network, the energy consumption of user equipment is greatly increased, the electricity consumption time is seriously shortened, and the problems of resource waste and environmental pollution are caused. The energy efficiency related problem has attracted extensive industry attention, and the international telecommunication union IMT-2020 push group has proposed the target of improving the energy efficiency of a system in a 5G wireless mobile network by 100 times.

Therefore, the research on the power control scheme for realizing the energy efficiency optimization on the premise of guaranteeing the QoS requirement has important significance for the efficient utilization of system resources.

Disclosure of Invention

In view of this, the present invention provides a power optimization method, a communication method, and an apparatus for energy efficiency of a ue, so as to optimize power allocation for energy efficiency while ensuring user service quality.

In order to achieve the purpose, the invention is realized by adopting the following scheme:

according to an aspect of an embodiment of the present invention, a power optimization method for energy efficiency of a user equipment is provided, including:

respectively selecting user equipment from a plurality of cells with overlapped communication frequency spectrums in a set wireless communication network, and taking each selected user equipment as a player to form a player set;

according to the data volume of the data packet to be sent generated by each user equipment in the player set and the function of the bit error rate of the set wireless communication network on the uplink communication signal-to-interference-and-noise ratio, obtaining a function of the successful sending probability of the data packet of the corresponding user equipment on the uplink communication signal-to-interference-and-noise ratio;

obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio and contains the transmission power parameter, according to the effective capacity of the cell to which each user equipment belongs in the player set, the transmission power parameter of the corresponding user equipment, the energy consumption of a circuit module of the corresponding user equipment and a function of the successful transmission probability of the data packet of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio;

taking the transmission power parameter of the user equipment in the player set as a player strategy of a corresponding player, taking an effective capacity efficiency function of the user equipment in the player set as a utility function of the corresponding player, and constructing a non-cooperative game model according to the player, the player strategy and the utility function;

adjusting the value of the transmission power parameter of the user equipment in the player set, and calculating the value of the signal-to-interference-and-noise ratio of uplink communication co-channel interference caused by receiving the transmission power of the user equipment belonging to the rest cells in the player set when the base station of the cell to which the corresponding user equipment belongs receives the signaling sent by the corresponding user equipment according to the adjusted value of the transmission power parameter, and calculating the effective capacity efficiency value of the corresponding user equipment under the adjusted value of the transmission power parameter according to the effective capacity efficiency function of the corresponding user equipment and the value of the signal to interference plus noise ratio of the corresponding user equipment under the adjusted value of the transmission power parameter, and carrying out iterative computation on the non-cooperative game model to obtain the transmitting power value of each user equipment in the player set at the Nash equilibrium value, and taking the transmitting power value as the transmitting power of the corresponding user equipment after the energy efficiency is optimized.

In some embodiments, selecting user equipments from a plurality of cells in which overlapping communication spectrums in a wireless communication network are set, and regarding each selected user equipment as a player, forming a player set, includes:

one user equipment is selected from each of a plurality of cells in which the communication frequency spectrums in the wireless communication network are set to overlap, and each selected user equipment is taken as a player to form a player set.

In some embodiments, obtaining a function of successful transmission probability of the data packet of the corresponding user equipment with respect to the uplink communication signal-to-interference-and-noise ratio according to the data amount of the data packet to be transmitted generated by each user equipment in the player set and the function of the bit error rate of the set wireless communication network with respect to the uplink communication signal-to-interference-and-noise ratio includes:

determining a function of a bit error rate relative to an uplink communication signal-to-interference-and-noise ratio according to a modulation and demodulation mode used by the communication technology standard of the set wireless communication network;

and obtaining a function of the successful transmission probability of the data packet of the corresponding user equipment on the uplink communication signal-to-interference-and-noise ratio according to the average data volume of the data packet to be transmitted generated by each user equipment in the player set and the function of the bit error rate of the set wireless communication network on the uplink communication signal-to-interference-and-noise ratio.

In some embodiments, obtaining an effective capacity efficiency function of the corresponding ue with respect to the uplink communication signal to interference plus noise ratio and including the transmit power parameter according to a function of an effective capacity of a cell to which each ue in the player set belongs, the transmit power parameter of the corresponding ue, an energy consumption of a circuit module of the corresponding ue, and a successful packet transmission probability of the corresponding ue with respect to the uplink communication signal to interference plus noise ratio includes:

calculating to obtain the effective capacity of the cell to which the corresponding user equipment belongs according to the moment mother function of each user equipment in the player set, the time slot length of the corresponding user equipment and the service quality index of the corresponding user equipment;

obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to the user sending data volume and contains the transmission power parameter, according to the effective capacity of the cell to which each user equipment belongs in the player set, the transmission power parameter of the corresponding user equipment and the energy consumption of a circuit module of the corresponding user equipment;

and obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio and contains the transmission power parameter, according to a distribution function of the uplink communication signal-to-interference-and-noise ratio of the user transmission data volume and an effective capacity efficiency function of the user equipment, which is related to the user transmission data volume and contains the transmission power parameter, in the player set.

In some embodiments, the value of the transmission power parameter of the user equipment in the player set is adjusted, the base station of the cell to which the corresponding user equipment belongs calculates the value of the signal-to-interference-and-noise ratio of uplink communication subjected to co-frequency interference due to the reception of the transmission power of the user equipment belonging to the remaining cells in the player set when receiving a signaling sent by the corresponding user equipment with the adjusted value of the transmission power parameter, and the effective capacity efficiency value of the corresponding user equipment under the adjusted value of the transmission power parameter is calculated according to the effective capacity efficiency function of the corresponding user equipment and the value of the signal-to-interference-and-noise ratio of the corresponding user equipment under the adjusted value of the transmission power parameter, so as to perform iterative calculation on the non-cooperative game model, obtain the transmission power value of each user equipment in the player set at the nash equilibrium value as the transmission power of the corresponding user equipment after energy efficiency optimization, the method comprises the following steps:

setting the transmission power parameter of each user equipment in the player set not to exceed the initial value of the maximum transmission power, then starting from the initial transmission power value, adjusting the value of the transmission power parameter of one user equipment in the player set according to the set transmission power step length, calculating the value of the signal-to-interference and noise ratio of uplink communication subjected to uplink communication due to the reception of the transmission power of the user equipment belonging to the rest cells in the player set when the base station of the cell to which the corresponding user equipment belongs receives the signaling sent by the corresponding user equipment according to the value of the adjusted transmission power parameter, calculating the effective capacity efficiency value of the corresponding user equipment under the value of the adjusted transmission power parameter according to the effective capacity efficiency function of the corresponding user equipment and the value of the signal-to-interference and noise ratio of the corresponding user equipment under the value of the adjusted transmission power parameter, and comparing the effective capacity efficiency value of the corresponding user equipment under the value of the adjusted transmission power parameter with the transmission power efficiency value before adjustment The difference value of the effective capacity efficiency values under the values of the rate parameters is used for carrying out iterative calculation on the non-cooperative game model until the difference value of the effective capacity efficiency value under the adjusted transmission power parameter value of each user equipment in the player set and the effective capacity efficiency value under the adjusted transmission power parameter value is smaller than a set threshold value, and the maximum effective capacity efficiency value of each user equipment is obtained; and obtaining the transmitting power value of the corresponding user equipment at the Nash equilibrium value according to the transmitting power corresponding to the maximum effective capacity efficiency value of each user equipment in the player set, and using the transmitting power value as the transmitting power of the corresponding user equipment after the energy efficiency optimization.

In some embodiments, when the modulation and demodulation scheme used in the setting of the communication technology standard of the wireless communication network is the modulation and demodulation scheme of an M-QAM modulation system used in the LTE communication technology standard, the function of the bit error rate of the setting of the wireless communication network with respect to the uplink communication signal-to-interference-plus-noise ratio is represented as:

wherein BER (. gamma.) is _i ) Representing bit error rate, gamma _i Representing the signal-interference-noise ratio of uplink communication, Q (-) represents a Q function, and M represents the system of quadrature amplitude modulation;

the successful data packet transmission probability of the user equipment is expressed as a function of the uplink communication signal-to-interference-and-noise ratio as follows:

f(γ _i )＝(1-BER(γ _i )) ^L ，

wherein, f (gamma) _i ) Indicating the successful transmission probability of the data packet of the user equipment, and L indicating the average data quantity of the data packet to be transmitted generated by the user equipment.

In some embodiments, the intalox of each user device in the set of players is represented as:

wherein the content of the first and second substances,

representing the moment mother function, u _i Denotes the quality of service index, S, of the ith user equipment _i Represents the data service volume in the time slot of the ith user equipment, E [ ·]Express expectationAn operator;

the effective capacity of the cell to which the user equipment belongs is expressed as:

wherein the content of the first and second substances,

representing the effective capacity, p, of a cell comprising N user equipments ₁ ,...,p _N Representing a transmission power parameter, T, of N user equipments in a cell _s Indicating the time slot length;

the effective capacity efficiency function of the user equipment with respect to the amount of data sent by the user and including the transmit power parameter is expressed as:

wherein eta (p) ₁ ,...,p _N ,u _i ) Representing the effective capacity efficiency, p, of the ith user equipment _i Representing the transmission power parameter, P, of the ith user equipment _c Circuit module energy consumption of the user equipment;

in the case that the data amount sent by the user conforms to a random variable of the independent synchronization distribution, the distribution function of the data amount sent by the user with respect to the uplink communication signal-to-interference-and-noise ratio is expressed as follows:

where B denotes the channel bandwidth, p denotes the probability, γ _i Representing the signal-to-interference-and-noise ratio of uplink communication;

the effective capacity efficiency function of the user equipment with respect to the uplink communication signal-to-interference-and-noise ratio and including the transmission power parameter is expressed as:

wherein R is _i Representing the data transmission rate.

According to an aspect of an embodiment of the present invention, there is provided a communication method including: the ue sends a signaling to the base station of the cell to which the ue belongs, with the transmission power after the energy efficiency optimization determined by using the power optimization method for the energy efficiency of the ue according to any of the embodiments.

According to an aspect of the embodiments of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method according to any of the above embodiments when executing the program.

According to an aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a computer program, which when executed by a processor, performs the steps of any of the above-described embodiments of the method.

According to the power optimization method for the energy efficiency of the user equipment, the communication method, the electronic equipment and the computer readable storage medium, the energy efficiency optimization of the uplink wireless communication can be realized under the condition of ensuring the service quality by obtaining the effective capacity efficiency and constructing the non-cooperative game model to optimize the transmitting power based on the effective capacity efficiency. The optimization method of the non-cooperative game model is not complex, so that the signaling overhead is low, the calculation complexity is low, and the power optimization of a large-scale network can be adapted. Compared with the existing power control scheme, the method can well improve the energy efficiency under the condition of ensuring the QoS requirement.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:

fig. 1 is a flowchart illustrating a power optimization method for energy efficiency of a ue according to an embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a modeling system based on a super-dense network scenario according to an embodiment of the present invention;

FIG. 3 is a diagram of a queuing model in accordance with an embodiment of the invention;

FIG. 4 is a graph of the trend of effective capacity efficiency as a function of signal to interference and noise ratio for an embodiment of the present invention;

fig. 5 is a schematic flow chart of an effective capacity efficiency optimized power control algorithm based on game theory according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.

The increasing density of base station deployment has shortened the distance between base stations. When a 5G network is actually deployed, due to the fact that an OFDM technology is used, a same-frequency multiplexing mechanism is adopted among base stations which are densely deployed so as to save scarce spectrum resources, serious inter-cell interference problems are inevitably caused, and overall performance of the network is greatly influenced; aiming at the emerging services of various internet, mobile users have stricter and differentiated requirements on quality of service (QoS); in the ultra-dense network, the energy consumption of user equipment is greatly increased, the electricity consumption time is seriously shortened, and the problems of resource waste and environmental pollution are caused. Therefore, the research on the power control scheme for realizing the energy efficiency optimization on the premise of guaranteeing the QoS requirement has important significance for the efficient utilization of system resources. The existing power control technology, such as the convex optimization method, needs complete channel state information, does not consider increasingly dense access points and ultra-large scale communication, has huge calculation amount, is a huge challenge for the energy consumption, signaling overhead and calculation capacity of user equipment and a base station server, and can bring serious time delay.

In view of the foregoing problems, embodiments of the present invention provide a power optimization method for energy efficiency of a user equipment, so as to optimize power allocation of energy efficiency while guaranteeing user service quality.

Fig. 1 is a flowchart illustrating a power optimization method for energy efficiency of a ue according to an embodiment of the present invention. As shown in fig. 1, the power optimization method for energy efficiency of the ue of this embodiment may include the following steps S110 to S150.

Specific embodiments of steps S110 to S150 will be described in detail below.

Step S110: the method comprises the steps of respectively selecting user equipment from a plurality of cells with overlapped communication frequency spectrums in a set wireless communication network, and taking each selected user equipment as a player to form a player set.

In step S110, the wireless communication network may be set to be an ultra-dense network. A wireless communication network may include a plurality of cells, each of which may include a plurality of user equipments and a base station. The uplink frequency spectrums of the user equipment in the same cell can be orthogonal, and the frequency spectrums of the user equipment between different cells are overlapped, so that the same frequency interference can exist.

For multiple cells with overlapping frequency spectrums, i.e., co-channel interference, one or more user devices can be selected from each cell, and the user devices selected from the cells can be placed in a set, which can be used as a set of players in a non-cooperative gaming model.

In some embodiments, for ease of analysis, a user equipment may be selected from each of a plurality of co-channel interfering cells.

The step S110 of selecting user equipments from a plurality of cells with overlapping uplink communication frequency spectrums in a wireless communication network, and forming a player set by using each selected user equipment as a player may specifically include the steps of: s111, selecting a user equipment from each of a plurality of cells in which the uplink communication frequency spectrums of the wireless communication network are overlapped, and forming a player set by using each of the selected user equipments as a player.

In this embodiment, each user device plays games with the user devices of other cells on behalf of the cell to which it belongs.

Step S120: and obtaining a function of the successful transmission probability of the data packet of the corresponding user equipment on the uplink communication signal-to-interference-and-noise ratio according to the data volume of the data packet to be transmitted generated by each user equipment in the player set and the function of the bit error rate of the set wireless communication network on the uplink communication signal-to-interference-and-noise ratio.

In step S120, the data amount of the data packet to be sent of the user equipment may be obtained by using the statistical result of the data packet sent by the user equipment. Or, the data volume of the data packet to be sent of the user equipment may be obtained by using the data volume statistical results of the data packets sent by the plurality of user equipments in the cell.

The bit error rate expression may be determined according to a modulation and demodulation scheme of a modulation system used in a communication technology standard of the wireless communication network.

For example, the communication technology standard of the wireless communication network may be an LTE (long term evolution) communication technology standard, and the LTE uses an M-QAM modulation system, in which case, a bit error rate expression of M-QAM modulation may be obtained.

In a specific implementation, when the modulation and demodulation scheme used for setting the communication technology standard of the wireless communication network may be a modulation and demodulation scheme of an M-QAM modulation system used in an LTE (long term evolution) communication technology standard, a function of the bit error rate of the set wireless communication network with respect to the uplink communication signal-to-interference-and-noise ratio may be represented as:

wherein BER (gamma) _i ) Representing bit error rate, gamma _i Represents the uplink communication signal-to-interference-and-noise ratio, Q (-) represents a Q function, and M represents the binary system of the quadrature amplitude modulation.

The data packet can be considered to be successfully transmitted assuming that all bits in the data packet transmitted by the user equipment are correctly transmitted. If not, the data packet may be retransmitted. The probability of successful transmission of a data packet by the user equipment, i.e. the probability of successful transmission of a data packet, can be calculated based on this assumption.

Illustratively, the step S120 of obtaining a function of a successful transmission probability of the data packet of the corresponding user equipment with respect to the uplink communication signal-to-interference-and-noise ratio according to the data size of the data packet to be transmitted generated by each user equipment in the player set and the function of the bit error rate of the set wireless communication network with respect to the uplink communication signal-to-interference-and-noise ratio may specifically include the steps of: s121, determining a function of a bit error rate relative to an uplink communication signal-to-interference-and-noise ratio according to a modulation and demodulation mode used by the communication technology standard of the set wireless communication network; and S122, obtaining a function of the successful transmission probability of the data packet of the corresponding user equipment on the uplink communication signal-to-interference-and-noise ratio according to the average data volume of the data packet to be transmitted generated by each user equipment in the player set and the function of the bit error rate of the set wireless communication network on the uplink communication signal-to-interference-and-noise ratio.

Further, for example, the function of the successful transmission probability of the data packet of the user equipment with respect to the uplink communication signal-to-interference-and-noise ratio can be expressed as:

f(γ _i )＝(1-BER(γ _i )) ^L ，

wherein, f (gamma) _i ) Indicating the probability of successful transmission of a data packet by the user equipment, L indicating the average amount of data generated by the user equipment for a data packet to be transmitted, γ _i Representing the uplink communication signal to interference and noise ratio.

Step S130: and obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio and contains the transmission power parameter, according to the effective capacity of the cell to which each user equipment in the player set belongs, the transmission power parameter of the corresponding user equipment, the energy consumption of a circuit module of the corresponding user equipment and a function of the successful transmission probability of the data packet of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio.

In step S130, the effective capacity of the cell to which the user equipment belongs may be obtained based on a conventional effective capacity model. Effective capacity efficiency of user equipmentFunction η (p) ₁ ,...,p _N ,u _i ) According to the effective capacity of the cell to which the user equipment belongs

Transmission power parameter p for user equipment _i Energy consumption P of circuit module of corresponding user equipment _c And the probability of successful transmission of data packet of corresponding user equipment relates to the signal-to-interference-and-noise ratio gamma of uplink communication _i And (4) calculating.

For example, the effective capacity of the cell to which the user equipment belongs can be expressed as:

wherein the content of the first and second substances,

representing the effective capacity, p, of a cell comprising N user equipments ₁ ,...,p _N Representing a transmission power parameter, T, of N user equipments in a cell _s Indicates the slot length, u _i Indicating a quality of service index of the ith user equipment,

representing the moment mother function, S _i Indicating the data service volume in the time slot of the ith user equipment. The value of N may be several, or may be obtained according to all user equipments actually included in the cell to which the user equipment belongs in the player set.

The intalox of each user device in the set of players may be expressed as:

wherein the content of the first and second substances,

representing the moment mother function, u _i Indicating the quality of service index, S, of the ith user equipment _i Represents the data service volume in the time slot of the ith user equipment, E [ ·]Representing the desired operator.

The effective capacity efficiency function of the user equipment may be expressed as:

in particular, the effective capacity function can be converted into a function related to the signal to interference plus noise ratio.

Illustratively, the step S130 of obtaining an effective capacity efficiency function of the corresponding ue with respect to the uplink communication signal-to-interference-and-noise ratio and including the transmission power parameter according to a function of the effective capacity of the cell to which each ue in the player set belongs, the transmission power parameter of the corresponding ue, the power consumption of the circuit module of the corresponding ue, and the successful transmission probability of the data packet of the corresponding ue with respect to the uplink communication signal-to-interference-and-noise ratio includes: s131, calculating to obtain the effective capacity of the cell to which the corresponding user equipment belongs according to the moment mother function of each user equipment in the player set, the time slot length of the corresponding user equipment and the service quality index of the corresponding user equipment; s132, obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to user sending data volume and contains the transmission power parameter, according to the effective capacity of the cell to which each user equipment belongs in the player set, the sending power parameter of the corresponding user equipment and the energy consumption of a circuit module of the corresponding user equipment; s133, according to the distribution function of the uplink communication signal-to-interference-and-noise ratio of the user sending data volume and the effective capacity efficiency function of the user equipment in the player set, which is related to the user sending data volume and contains the transmission power parameter, the effective capacity efficiency function of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio and contains the transmission power parameter, is obtained.

For example, the effective capacity efficiency function of the user equipment with respect to the amount of data transmitted by the user and including the transmit power parameter can be expressed as:

wherein η (p) ₁ ,...,p _N ,u _i ) Representing the effective capacity efficiency, p, of the ith user equipment _i Representing the transmission power parameter, P, of the ith user equipment _c Circuit module energy consumption of user equipment, u _i Indicating the quality of service index, S, of the ith user equipment _i Indicating the amount of data service in the time slot, T, of the ith user equipment _s Indicating the slot length.

The distribution function of the data volume sent by the user can be obtained based on the condition that the data volume sent by the user accords with certain distribution.

For example, in the case that the amount of data transmitted by the user conforms to a random variable of the independent synchronization distribution, the distribution function of the amount of data transmitted by the user with respect to the uplink communication signal-to-interference-and-noise ratio can be expressed as:

where B denotes the channel bandwidth, p denotes the probability, γ _i Representing the signal-to-interference-and-noise ratio, T, of the uplink communication _s Denotes the slot length, f (gamma) _i ) Indicating the probability of successful transmission of a data packet by the user equipment. 1-f (gamma) _i ) May represent the probability of a failed transmission of a data packet.

The effective capacity efficiency function of the user equipment with respect to the uplink communication signal-to-interference-and-noise ratio and including the transmission power parameter can be expressed as:

wherein R is _i Representing the data transmission rate.

Step S140: and taking the transmission power parameter of the user equipment in the player set as a player strategy of the corresponding player, taking the effective capacity efficiency function of the user equipment in the player set as a utility function of the corresponding player, and constructing a non-cooperative game model according to the player, the player strategy and the utility function.

In step S140, the user equipments in different cells with same frequency interference want to increase the transmission power due to the interference, but increasing the transmission power will increase the interference to other cells, so the user equipments in different cells play games, and the game strategy is to want to increase the transmission power of their own user equipments. In this case, the effective capacity efficiency is taken as the utility function, so that the utility function tends to be the maximum in the process of the user equipment gaming in different cells, namely, the effective capacity efficiency is the maximum. Therefore, the effective capacity efficiency of the whole network can be improved as much as possible under the condition of ensuring the transmitting power, the service quality and the like of each user equipment, thereby reducing the energy consumption of the user equipment.

Step S150: adjusting the value of the transmission power parameter of the user equipment in the player set, and calculating the value of the signal-to-interference-and-noise ratio of uplink communication co-channel interference caused by receiving the transmission power of the user equipment belonging to the rest cells in the player set when the base station of the cell to which the corresponding user equipment belongs receives the signaling sent by the corresponding user equipment according to the adjusted value of the transmission power parameter, and calculating the effective capacity efficiency value of the corresponding user equipment under the adjusted value of the transmission power parameter according to the effective capacity efficiency function of the corresponding user equipment and the value of the signal to interference plus noise ratio of the corresponding user equipment under the adjusted value of the transmission power parameter, and carrying out iterative computation on the non-cooperative game model to obtain the transmitting power value of each user equipment in the player set at the Nash equilibrium value, and taking the transmitting power value as the transmitting power of the corresponding user equipment after the energy efficiency is optimized.

In this step S150, a value of the transmission power that does not exceed the maximum value of the transmission power may be set for each user device in the player set. In each iteration calculation process, the transmission power can be adjusted for one user equipment, the value of each effective capacity efficiency under the transmission power values can be obtained, the transmission power of the user equipment corresponding to the maximum effective capacity efficiency value can be found, and the transmission power can be used as the optimal transmission power of the user equipment. By analogy, the optimal transmitting power corresponding to each user equipment can be obtained. At nash equalization, the effective capacity efficiency of the user equipment of each cell reaches a maximum with the transmit power of the user equipment of the other cells unchanged.

Exemplarily, the step S150 may specifically include the steps of: s151, setting the transmission power parameter of each user equipment in the player set not to exceed the initial value of the maximum transmission power, then starting from the initial transmission power value, adjusting the value of the transmission power parameter of one user equipment in the player set according to the set transmission power step length, calculating the value of the SINR of the uplink communication subjected to the same frequency interference due to the reception of the transmission power of the user equipment belonging to the rest cells in the player set when the base station of the cell to which the corresponding user equipment belongs receives the signaling sent by the corresponding user equipment according to the value of the transmission power parameter after adjustment, calculating the effective capacity efficiency value of the corresponding user equipment under the value of the transmission power parameter after adjustment according to the effective capacity efficiency function of the corresponding user equipment and the SINR value of the corresponding user equipment under the value of the transmission power parameter after adjustment, and comparing the effective capacity efficiency value of the corresponding user equipment under the value of the transmission power parameter after adjustment with the effective capacity efficiency value before adjustment Performing iterative computation on the non-cooperative game model until the difference between the effective capacity efficiency value of each user equipment in the player set under the adjusted value of the transmission power parameter and the effective capacity efficiency value of each user equipment in the player set under the adjusted value of the transmission power parameter is smaller than a set threshold value, and obtaining the maximum effective capacity efficiency value of each user equipment; and obtaining the transmitting power value of the corresponding user equipment at the Nash equilibrium value according to the transmitting power corresponding to the maximum effective capacity efficiency value of each user equipment in the player set, and using the transmitting power value as the transmitting power of the corresponding user equipment after the energy efficiency optimization.

Wherein the initial value of the setting for the transmit power parameter of each user device in the set of players may be a value of reasonable transmit power that does not exceed a maximum transmit power. The starting transmit power value may be incremented by some offset, starting from a smaller transmit power value, e.g., starting from 0. In other embodiments, the power level may be decremented with some offset from the maximum transmit power level.

Based on the same inventive concept as the power optimization method for energy efficiency of the user equipment shown in fig. 1, the embodiment of the invention also provides a communication method. The communication method of the embodiments includes: the ue sends a signaling to the base station of the cell to which the ue belongs, with the transmission power after the energy efficiency optimization determined by using the power optimization method for the energy efficiency of the ue according to any of the embodiments.

In addition, an embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the power optimization method for energy efficiency of a user equipment according to any embodiment or the steps of the communication method according to any embodiment when executing the program.

In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the power optimization method for energy efficiency of the user equipment according to any of the above embodiments or the steps of the communication method according to any of the above embodiments.

The above method is described below with reference to a specific example, however, it should be noted that the specific example is only for better describing the present application and is not to be construed as limiting the present application.

In a specific embodiment, an energy efficiency optimization power control method based on effective capacity efficiency is provided to solve the problem that inter-cell interference affects energy efficiency. The specific technical scheme can be divided into three parts, namely system modeling, effective capacity efficiency derivation and power control algorithm design.

System modeling

The communications industry has experienced a new growth through densification of network infrastructure driven by the explosive growth of data traffic and new demands for quality of service by mobile users. As densities and Access Points (APs) increase, networks benefit from spatial reuse of near-end transmission and system resources, introducing a new paradigm known as Ultra Dense Networks (UDNs). Therefore, the system modeling process is described by taking the modeling based on the ultra-dense network scene as an example.

Fig. 2 is a schematic structural diagram of a super-dense network scenario modeling system in an embodiment of the present invention, and as shown in fig. 2, it is assumed that a wireless communication network has N cells SC1 and SC2 …, each cell includes a small base station SCB and several user equipments UE, for example, cell SC1 includes a small base station SCB and user equipments UE1 and UE2 ….

Fig. 3 is a diagram of a queuing model according to an embodiment of the present invention, and referring to fig. 3, in the queuing model at the transmitting end of the ue, for uplink communication, a data packet to be transmitted generated by the ue is stored in a buffer queue, which is assumed to be infinite and first-in-first-out (FIFO).

It is assumed that rayleigh block fading exists in a wireless channel, and simultaneously, due to the frequency division multiplexing technology, channel states of user equipments UE in a cell SC are mutually independent and co-channel interference does not exist, and co-channel interference can be generated in uplink communication by multiplexing channels between cells SC. Assumption set M _i Is the set of cells SC that are subject to co-channel interference from the ith cell SCi. Let the transmission power of the ith user equipment UEi be p _i The distance between the ith user equipment UEi and the ith base station SCBi in its cell is d _ii Then the actual signal power received by the ith cell site SCBi in the cell is p _ii Considering the path loss and channel gain, p _ii The expression can be expressed as:

p _ii ＝p _i (d _ii ) ^-a |H _ii | ² (1)

wherein α is the road loss index, H _ii Is the Rayleigh fading coefficient, | H _i,i | ² Representing the channel gain, are independent and equally distributed random variables in different time slots and follow an exponential distribution with a mean value of 1. In addition, | H _i,n | ² Channel gain may also be indicated, where subscripts i and n may indicate the base stations of different cells.

Therefore, based on the above assumptions, the signal-to-interference-plus-noise ratio (SINR) of the uplink of the ith cell SCi follows the same distribution γ _i And γ _i Is a function of the actual signal power and the interference power of other base stations and can be expressed as:

wherein, the flow rate of the water is controlled by the control unit. T is _s Is the slot length. S _ii Indicating the data service volume in the ith time slot of the ith user equipment. Sigma ² Is an additive white Gaussian noise power, which can be expressed as

σ ² ＝N ₀ B (3)

N ₀ Is the additive white gaussian noise power spectral density and B is the channel bandwidth.

According to shannon' S theorem, the data service volume S (or denoted S) of each time slot of the ith user equipment UEi _ii ) Can be expressed as:

S＝BT _s log ₂ (1+γ) (4)

wherein γ can be expressed as an uplink communication signal-to-interference-and-noise ratio.

It is assumed that the length of data generated by each time slot of the user equipment UE follows an exponential distribution with a mean value L. Probability density function f of UE data arrival amount a _An (a) Can be as follows:

(II) effective capacity efficiency derivation

In order to reduce the influence of inter-cell interference on the energy efficiency of the service quality sensitive service as much as possible, the embodiment innovates based on the traditional effective capacity theory, considers the energy efficiency, deduces the effective capacity efficiency according with the system structure, and provides a basis for designing the efficient power control algorithm in the next step. The effective capacity efficiency derivation process is divided into two parts, wherein the first part introduces a traditional effective capacity model, and the second part derives an effective capacity efficiency theory.

1. Introduction of effective Capacity

In the effective capacity theory, a QoS index u is defined to characterize certain QoS requirements. The effective capacity is a cross-layer capacity model, and the physical meaning of the effective capacity is the maximum average data arrival rate under a certain QoS requirement. The effective capacity of the ith cell SCi according to the effective capacity definition

The expression may be:

wherein u is _i For the QoS index (quality of service index) of the ith user equipment UEi,

u _i a larger value of (c) indicates better QoS performance,

is S _i The expression may be:

wherein, E [ ·]To the desired operator, S _i Serving the amount of data in the time slot.

2. Effective capacity efficiency formula derivation

In order to reduce the energy consumption of user equipment and realize high energy efficiency while ensuring the QoS performance of the service, the effective capacity theory is further deduced. Firstly, the probability of successfully sending a data packet by User Equipment (UE) is analyzed, and then an effective capacity efficiency formula is deduced on the basis.

(1) Probability of successful transmission of data packet

Assuming that the average data amount in a data packet to be transmitted generated by User Equipment (UE) is L (bits), when all bits in the packet are correctly transmitted, the data packet is considered to be successfully transmitted, otherwise, the data packet can be retransmitted. Based on the above analysis, the probability f (γ) that each packet is successfully transmitted can be found as:

f(γ)＝(1-BER(γ)) ^L (8)

wherein BER (γ) is a bit error rate, for example, in an ultra-dense network, LTE technology is used for communication, LTE uses an M-QAM modulation system for modulation and demodulation, and a bit error rate BER expression of M-QAM modulation may be:

for example, assuming a 16-QAM modulation method is adopted, the bit error rate BER (γ) expression of 16-QAM modulation may be:

where Q (-) is a Q function and γ represents the signal to interference plus noise ratio.

(2) Effective capacity efficiency formula

The effective capacity efficiency concept is provided to improve the performance index in the aspect of energy efficiency on the basis of the effective capacity concept. Based on the above analysis, on the basis of the original effective capacity, consideration is added to the transmission power and the power consumption of the user equipment circuit module, and the effective capacity efficiency can be expressed as:

wherein, P _c Is the user equipment circuit module power consumption. Substituting equations (6) and (7) into equation (11) yields:

further, due to interference and other factors, the transmitted data may be lost, received incorrectly, and so on, and then needs to be retransmitted. Therefore, for any time slot, the data amount S transmitted by the user is an independent and equally distributed random variable, and follows the following distribution:

further, the air conditioner is characterized in that,

wherein R is _i Representing the data transmission rate.

(3) Substituting equation (14) into equation (12) yields the effective capacity efficiency equation:

(III) Power control Algorithm

According to the analysis, uplink frequency spectrums of users in the cells SC are orthogonal, the frequency spectrums of the cells SC are overlapped, and the uplink communication has the same frequency interference. For each UE of different cells SC, to ensure its quality of service (QoS), the transmit power is increased as much as possible, but the larger the transmit power is, the more serious the co-channel interference to other cells SC is, so as to reduce the signal-to-interference-and-noise ratio of SC users in other cells within the interference range, and further reduce the effective capacity efficiency of SC users in other cells within the interference range, and the functional relationship between the effective capacity efficiency and the signal-to-interference-and-noise ratio is shown in fig. 4.

Therefore, the non-cooperative game relationship is formed among the cells with the same frequency interference, and obviously, the problem can be solved by using a game theory method. The following first constructs a non-cooperative game model according to the above system structure, and then describes specific algorithm steps.

1. Non-cooperative gaming model

The non-cooperative game is composed of three parts, namely a player, a strategy of the player and a utility function. The method is applied to the system model, the user equipment UE from different cell SC forms a player set, and for convenience of analysis, only one user equipment UE is considered to participate in the game in each cell SC; the strategy of the player is the transmission power of the user equipment UE; and the utility function is the effective capacity efficiency of the user equipment UE. The process of the game is that the user equipment UE adjusts the transmit power by each round until the transmit power converges, i.e. nash equilibrium is reached. At Nash equilibrium, the utility function for each player reaches a maximum with other player strategies unchanged. Therefore, the user equipment UE with mutual interference among the cells can realize the gradual optimization of the effective capacity efficiency through the game, and the optimal scheme of the effective energy efficiency of the user equipment UE can be obtained by achieving the Nash equilibrium. The non-cooperative game model constructed by the invention is as follows:

G＝[N,{p _i },{u _i (p _i |P _-i )}]

wherein: n ═ {1, 2.., N } denotes the set of UEs participating in the game, { p } _i }＝{p _i ∈[0,p _max ]And e.n represents a set of transmit powers of the UE,

representing the utility function of the UE. And calculating the effective energy efficiency of each cell by multiple iterations, wherein the user takes the optimal Response (RB) as the transmission power in each iteration, and the iteration is stopped until the transmission power converges to a fixed value. And when the transmitting power of all the cell users participating in the game is converged, obtaining the Nash equilibrium of the game. On the premise that the transmitting power of other cell users is not changed, the utility function of the user at the Nash equilibrium position reaches the maximum value, so the power value distribution at the Nash equilibrium position is the global optimal scheme of the effective energy efficiency of the cell users.

2. As shown in fig. 5, the algorithm steps are as follows:

(1) setting initial transmitting power for UE in SC set N participating in game

Transmission power p of all users _i Must not be greater than the maximum transmission power p _max ；

(2) And (3) iteratively calculating the effective capacity efficiency of each cell:

a. each UE sends signaling containing the transmitting power to all SCBs participating in the game, so that each SCB acquires the transmitting power of all the UE participating in the game

b. All SCBs utilize the signal to interference and noise ratio formula (2) to calculate the signal to interference and noise ratio of the UE in the SC under different transmitting powers

Wherein the transmitting power is gradually increased from 0 to the maximum transmitting power p in a certain step _max ；

c. And then using the SINR under different transmitting power obtained in the step b to calculate the effective capacity efficiency by using a formula (15)

d. Selecting the transmitting power corresponding to the maximum value (namely the optimal corresponding value in the iteration of the current round) from the effective capacity efficiencies obtained in the step c as output

e. Calculate the output of this round

With the last round of output

The difference e between the two.

When the difference e is small enough, the convergence is realized, and the iteration is stopped; otherwise, repeating the step (2).

(3) The UE transmitting power set of each cell obtained after the step (2) is finished

That is, nash equalization, the UE can obtain the maximum effective capacity efficiency by transmitting data with the transmission power at the nash equalization value, and realize global optimization.

Specifically, for example, assuming that there are 3 cells each having one base station SCB, there are 3 base stations SCB, each SCB taking into account one user equipment UE, an initial transmission power is first set for each UE

Each UE sends signaling containing transmission power to the first base station SCB1, the second base station SCB2 and the third SCB3 respectively, so that each SCB obtains the transmission power

And calculating the next round of transmitting power of the UE aiming at the transmitting power of other UEs, wherein the specific calculation process can be as follows:

taking SCB1 as an example, let p ₁ Respectively taking 0, p,2p,3p, … …, wherein p is step size, p ₁ ∈[0,p _max ]The effective capacity efficiency is obtained by using the formula (15) as follows

… … where p corresponds to the maximum value of effective capacity efficiency ₁ The output of the circular output is used as the circular output of the current round,

meanwhile, the SCB2 and the SCB3 calculate the cycle output of the current round,

next, calculate

If e is greater than epsilon (convergence accuracy of algorithm), repeating the above loop, and the specific process can be:

each UE sends signaling containing transmission power to SCB1, SCB2, SCB3 respectively, so thatGet each SCB to obtain the transmission power

then calculate

If e is greater than ε (which may be a sufficiently small threshold), the above cycle may be repeated.

With this cycle, e is less than epsilon after the nth cycle,

then nash equalization. The UE may obtain maximum effective capacity efficiency by transmitting data at the nash equalization value with transmit power, thereby achieving global optimization.

In the embodiment, an ultra-dense network scenario is taken as an example, conditions such as co-frequency interference among all cells (SC) and maximum transmission power constraint of Users (UE) in the cells are comprehensively considered, an energy efficiency analysis model and a power control algorithm mechanism based on effective capacity efficiency are designed, and the problem of energy efficiency optimization in various communication scenarios is solved. Compared with the prior art, the method has the advantages that the energy efficiency optimization of the uplink wireless communication is realized under the condition of ensuring the service quality, and the algorithm steps are not complicated, so that the signaling cost is low and the calculation complexity is low. Compared with the existing power control scheme, the method can well improve the energy efficiency under the condition of ensuring the QoS requirement.

In summary, according to the power optimization method for the energy efficiency of the user equipment, the communication method, the electronic device and the computer-readable storage medium in the embodiments of the present invention, the energy efficiency optimization of the uplink wireless communication can be achieved while ensuring the quality of service by obtaining the effective capacity efficiency and constructing the non-cooperative game model based on the effective capacity efficiency to optimize the transmission power. Because the optimization method of the non-cooperative game model is not complex, the signaling overhead is low, the calculation complexity is low, and the power optimization of a large-scale network can be adapted. Compared with the existing power control scheme, the method can well improve the energy efficiency under the condition of ensuring the QoS requirement.

In the description herein, reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," "an example," "a particular example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the various embodiments is provided to illustrate the practice of the invention, and the sequence of steps is not limited thereto and can be adjusted as desired.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. A power optimization method for energy efficiency of User Equipment (UE) is characterized by comprising the following steps:

obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio and contains the transmission power parameter, according to the effective capacity of the cell to which each user equipment in the player set belongs, the transmission power parameter of the corresponding user equipment, the energy consumption of a circuit module of the corresponding user equipment and a function of the successful transmission probability of the data packet of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio;

2. The method as claimed in claim 1, wherein the step of selecting the ue from a plurality of cells with overlapping communication spectrums in the wireless communication network, and forming the set of players with each selected ue as a player comprises:

3. The method of claim 1, wherein the obtaining a function of successful transmission probability of the data packet of the corresponding ue with respect to the uplink communication signal-to-interference-and-noise ratio according to the data size of the data packet to be transmitted generated by each ue in the set of players and the function of the bit error rate of the set wireless communication network with respect to the uplink communication signal-to-interference-and-noise ratio comprises:

4. The method of claim 1, wherein the obtaining an effective capacity efficiency function of the corresponding ue with respect to an uplink communication signal-to-interference-and-noise ratio and including a transmit power parameter according to a function of an effective capacity of a cell to which each ue in the player set belongs, a transmit power parameter of the corresponding ue, an energy consumption of a circuit module of the corresponding ue, and a successful packet transmission probability of the corresponding ue with respect to the uplink communication signal-to-interference-and-noise ratio comprises:

and obtaining an effective capacity efficiency function of the corresponding user equipment, which is related to the uplink communication signal-to-interference-and-noise ratio and contains the transmission power parameter, according to a distribution function of the uplink communication signal-to-interference-and-noise ratio of the user transmission data volume and an effective capacity efficiency function of the user equipment, which is related to the user transmission data volume and contains the transmission power parameter, of the player set.

5. The power optimization method for energy efficiency of user equipment according to claim 1, wherein the value of the transmission power parameter of the user equipment in the player set is adjusted, and the base station of the cell to which the corresponding user equipment belongs calculates the value of the SINR subject to uplink communication co-channel interference due to receiving the transmission power of the user equipment belonging to the remaining cells in the player set when receiving the signaling sent by the corresponding user equipment with the adjusted value of the transmission power parameter, and calculates the value of the effective capacity efficiency of the corresponding user equipment under the adjusted value of the transmission power parameter according to the function of the effective capacity efficiency of the corresponding user equipment and the value of the SINR of the corresponding user equipment under the adjusted value of the transmission power parameter, so as to perform iterative calculation on the non-cooperative game model to obtain the transmission power value of each user equipment in the player set at the Nash equilibrium value, the energy efficiency optimized transmission power of the corresponding user equipment comprises the following steps:

setting the transmission power parameter of each user equipment in the player set not to exceed the initial value of the maximum transmission power, then starting from the initial transmission power value, adjusting the value of the transmission power parameter of one user equipment in the player set according to the set transmission power step length, calculating the value of the SINR (signal to interference plus noise ratio) of uplink communication subjected to the same frequency interference due to the reception of the transmission power of the user equipment belonging to the rest cellular cells in the player set when the base station of the cellular cell to which the corresponding user equipment belongs receives the signaling sent by the corresponding user equipment according to the value of the transmission power parameter after adjustment, calculating the effective capacity efficiency value of the corresponding user equipment under the value of the transmission power parameter after adjustment according to the effective capacity efficiency function of the corresponding user equipment and the value of the SINR of the corresponding user equipment under the value of the transmission power parameter after adjustment, and comparing the effective capacity efficiency value of the corresponding user equipment under the value of the transmission power parameter after adjustment with the transmission power efficiency value before adjustment The difference value of the effective capacity efficiency values under the values of the rate parameters is used for carrying out iterative calculation on the non-cooperative game model until the difference value of the effective capacity efficiency value under the adjusted transmission power parameter value of each user equipment in the player set and the effective capacity efficiency value under the adjusted transmission power parameter value is smaller than a set threshold value, and the maximum effective capacity efficiency value of each user equipment is obtained; and obtaining the transmitting power value of the corresponding user equipment at the Nash equilibrium value according to the transmitting power corresponding to the maximum effective capacity efficiency value of each user equipment in the player set, and taking the transmitting power value as the transmitting power of the corresponding user equipment after the energy efficiency is optimized.

6. The user equipment energy efficiency power optimization method according to claim 3,

when the modulation and demodulation scheme used by the communication technology standard of the wireless communication network is the modulation and demodulation scheme of the M-QAM modulation system used by the LTE communication technology standard, the function of the bit error rate of the wireless communication network with respect to the uplink communication signal-to-interference-and-noise ratio is represented as:

wherein BER (gamma) _i ) Representing bit error rate, gamma _i Representing the signal-interference-noise ratio of uplink communication, Q (-) represents a Q function, and M represents the system of quadrature amplitude modulation;

f(γ _i )＝(1-BER(γ _i )) ^L ，

wherein, f (gamma) _i ) Indicating the successful transmission probability of the data packet of the user equipment, and L indicating the average data volume of the data packet to be transmitted generated by the user equipment.

7. The user equipment energy efficiency power optimization method according to claim 4,

the intalox of each user device in the set of players is represented as:

Λ _Si (-u _i )＝logE[exp(-u _i S _i ]，

wherein, Λ _Si (-u _i ) Representing the moment mother function, u _i Indicating the quality of service index, S, of the ith user equipment _i Represents the data service volume in the time slot of the ith user equipment, E [ ·]Representing a desired operator;

wherein the content of the first and second substances,

wherein eta (p) ₁ ,...,p _N ,u _i ) Representing the effective capacity efficiency, p, of the ith user equipment _i Representing the transmission power parameter, P, of the ith user equipment _c Represents the circuit module energy consumption of the user equipment;

in the case that the data amount sent by the user conforms to a random variable of the independent synchronization distribution, the distribution function of the data amount sent by the user with respect to the uplink communication signal-to-interference-and-noise ratio is expressed as:

wherein R is _i Indicating the data transmission rate, f (gamma) _i ) Indicating the probability of successful transmission of a data packet by the user equipment.

8. A method of communication, comprising: the UE sends signaling to the base station of the cell to which the UE belongs at the energy-efficient optimized transmission power determined by the energy-efficient power optimization method according to any one of claims 1 to 7.

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 8 when executing the program.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.