CN116981037A - Wireless energy-carrying communication method and system - Google Patents
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Abstract
The embodiment of the application provides a wireless energy-carrying communication method and system, and belongs to the technical field of wireless communication. The method comprises the following steps: acquiring a preset power distribution function; wherein the power allocation function is a function obtained from a pre-constructed reference communication system comprising a reference base station, a reference information receiver and a reference energy receiver; determining a first number of target energy receivers in the target communication system and determining a second number of target information receivers in the target communication system; performing power calculation on the power distribution function according to the first quantity, the second quantity and preset constraint conditions to obtain target power; and performing power distribution on the target energy receiver and the target information receiver according to the target power. The embodiment of the application can realize wireless energy-carrying communication in a mixed scene of near field communication and far field communication.
Description
Technical Field
The present application relates to the field of wireless communications technologies, and in particular, to a wireless energy-carrying communication method and system.
Background
Wireless power-carrying communication (Simultaneous Wireless Information and Power Transfer, swit) is a technology capable of transmitting both signals and power simultaneously, i.e., capable of powering a wireless device while interacting with the wireless device. In the related art, the research of the wireless energy-carrying communication method mainly considers near field communication or far field communication, but in practical application, the mixed condition of near field communication and far field communication is more easy to occur, namely, a near field terminal and a far field terminal are simultaneously present in a wireless communication network. Therefore, if a wireless energy-carrying communication method is provided to adapt to the mixed situation of near field communication and far field communication, the technical problem to be solved is urgent.
Disclosure of Invention
The embodiment of the application mainly aims to provide a wireless energy-carrying communication method and system, which aim to realize wireless energy-carrying communication in a mixed scene of near field communication and far field communication.
To achieve the above object, a first aspect of an embodiment of the present application provides a wireless energy-carrying communication method, including:
acquiring a preset power distribution function; the power distribution function is obtained according to a pre-constructed reference communication system, the reference communication system comprises a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is in a first preset distance range, the distance between the reference information receiver and the reference base station is in a second preset distance range, and the maximum value of the first preset distance range is smaller than the minimum value of the second preset distance range;
determining a first number of target energy receivers in a target communication system and determining a second number of target information receivers in the target communication system;
performing power calculation on the power distribution function according to the first quantity, the second quantity and preset constraint conditions to obtain target power;
And carrying out power distribution on the target energy receiver and the target information receiver according to the target power.
In some embodiments, the method of constructing the power allocation function from the reference communication system comprises:
determining a first distance of the reference base station from the reference energy receiver;
obtaining a near-field channel model according to the first distance and a first space angle between the reference base station and the reference energy receiver;
determining a second distance between the reference base station and the reference information receiver;
obtaining a far-field channel model according to the second distance and a second space angle between the reference base station and the reference information receiver;
constructing a receiving signal model of the reference information receiver according to the far-field channel model;
constructing a collection power model of the reference energy receiver according to the near-field channel model;
and acquiring a reference correlation matrix of the reference information receiver and the reference energy receiver, and constructing the power distribution function according to the reference correlation matrix, the received signal model and the collected power model.
In some embodiments, the calculating the power of the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
If the first number is equal to zero and the second number is not equal to zero, performing conversion processing on the power distribution function to obtain a first distribution function;
performing power calculation on the first distribution function according to the preset constraint condition to obtain the target power; wherein the preset constraint condition comprises And y ID 0.gtoreq.m represents said second quantity, +.>Coefficient vector, y representing the target information receiver m ID A power allocation vector representing said target information receiver,/->A target correlation matrix representing said target information receiver and said target energy receiver,/->And (3) representing the noise of the target information receiver m, and R represents the achievable rate of the target information receiver.
In some embodiments, the calculating the power of the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
if the first number is not equal to zero, the second number is equal to zero, and the power distribution function is subjected to transformation processing to obtain a second distribution function;
performing power calculation on the second distribution function according to the preset constraint condition to obtain the target power; wherein the preset constraint condition comprises And y EH 0 or more, K represents the first number, M represents the second number, y EH A power allocation vector, P, representing the target energy receiver 0 Representing the maximum transmission signal power of a target base station in the target communication system.
In some embodiments, the calculating the power of the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
if the first number is not equal to zero and the second number is equal to 1, performing transformation processing on the power distribution function to obtain a third distribution function;
according to the preset constraint condition pairThe third distribution function performs power calculation to obtain the target power; wherein the preset constraint condition comprises c ID Coefficient vector representing the target information receiver, +.>Power allocation vector representing target energy receiver and target information receiver, +.>A target correlation matrix representing said target information receiver and said target energy receiver,/->Representing the noise of the target information receiver, P 0 Representing the maximum transmission signal power of a target base station in the target communication system.
In some embodiments, the calculating the power of the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
If the first number is not equal to zero and the second number is not equal to zero, acquiring a preset variable;
performing power calculation on a power distribution function according to the preset variable and the preset constraint condition to obtain target power; wherein the preset constraint condition comprises y is greater than or equal to 0, M represents the second quantity, S m And I m All represent preset variables, R represents the target information receiverIs (are) achievable rate,/->And a coefficient vector representing the target information receiver m, and y represents power allocation vectors of the target energy receiver and the target information receiver.
To achieve the above object, a second aspect of an embodiment of the present application proposes a wireless energy-carrying communication system, the system comprising:
the power distribution function acquisition module is used for acquiring a preset power distribution function; the power distribution function is obtained according to a pre-constructed reference communication system, the reference communication system comprises a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is in a first preset distance range, the distance between the reference information receiver and the reference base station is in a second preset distance range, and the maximum value of the first preset distance range is smaller than the minimum value of the second preset distance range;
A number determination module configured to determine a first number of target energy receivers in a target communication system and determine a second number of target information receivers in the target communication system;
the power calculation module is used for carrying out power calculation on the power distribution function according to the first quantity, the second quantity and preset constraint conditions to obtain target power;
and the power distribution module is used for distributing power to the target energy receiver and the target information receiver according to the target power.
To achieve the above object, a third aspect of the embodiments of the present application proposes an electronic device, including a memory storing a computer program and a processor implementing the method according to the first aspect when the processor executes the computer program.
To achieve the above object, a fourth aspect of the embodiments of the present application proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of the first aspect.
The wireless energy-carrying communication method and system provided by the application construct a power distribution function through a pre-constructed reference communication system, and solve the power distribution function according to the first number of target energy receivers and the second number of target information receivers in a target communication system to obtain target power. Because the reference communication system comprises the reference energy receiver arranged in the first preset distance range and the reference information receiver arranged in the second preset distance range, the constructed power distribution function can adapt to the target communication system comprising the target energy receiver and the target information receiver, and wireless energy carrying communication under the mixed far-near field condition is realized.
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Fig. 1 is a flowchart of a wireless energy-carrying communication method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a reference communication system provided by an embodiment of the present application;
FIG. 3 is a flow chart of constructing a power allocation function provided by an embodiment of the present application;
fig. 4 is a flowchart of step S103 in fig. 1;
fig. 5 is a flowchart of another embodiment of step S103 in fig. 1;
FIG. 6 is a flowchart of another embodiment of step S103 in FIG. 1;
FIG. 7 is a flowchart of another embodiment of step S103 in FIG. 1;
fig. 8 is a schematic structural diagram of a wireless energy-carrying communication system according to an embodiment of the present application;
fig. 9 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
It should be noted that although functional block diagrams are depicted as block diagrams, and logical sequences are shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the block diagrams in the system. The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the application only and is not intended to be limiting of the application.
First, referring to table 1 below, several nouns involved in the present application are parsed:
TABLE 1
Sixth generation (6G) wireless networks are expected to support the ever-increasing demands for ultra-high data rates, ultra-high reliability, ultra-low latency, ultra-low power consumption, etc. However, existing fifth generation (5G) technologies may not fully meet these requirements, and thus new technologies need to be developed for 6G. For example, 6G communications are expected to migrate to higher frequency bands, such as millimeter wave (mmWave) and terahertz (THz), to take advantage of the vast available bandwidth. In addition, by dramatically increasing the number of antennas to another order of magnitude, the high band severe path loss can be largely compensated for by ultra-high spectral efficiency and spatial resolution achieved by ultra-large scale arrays/surfaces (XL-array/surfaces).
With a significant increase in carrier frequency and number of antennas, the well-known rayleigh range will expand to tens of meters or even hundreds of meters. This will lead to a fundamental paradigm shift in electromagnetic field properties, turning from conventional far field communication to new near field communication. In particular, unlike far field communications, where the electromagnetic field may be approximated as a plane wave, radio propagation in near field communications should be accurately modeled with a spherical wave. This unique channel characteristic enables a new function of beam focusing that is capable of focusing beam energy at a specific location (region) rather than a specific direction as in conventional far field communications. Near field channel estimation/beam training is necessary to obtain the beam focusing gain of the XL-array, however, this is more challenging than far field communication. For example, near field beam training requires two-dimensional beam searching over the angular and distance domains, which is very different from far field situations where only one-dimensional angular domain beam searching is required. Thus, applying DFT-based far-field codebooks to near-field beam training will result in reduced training accuracy and rate performance. This phenomenon can be explained by a near-field energy spread effect in which the energy of a far-field beam in a specific direction is spread to a plurality of angles of the near field, and thus it is difficult to determine the angle of a real terminal based on the maximum received signal power. To solve this problem, a new polar-domain codebook is proposed in the related art, in which each beam codeword points to a specific location having a target angle and distance. One direct beam training method using this codebook is to perform a two-dimensional exhaustive search of all possible beam codewords. However, this approach results in extremely high beam training overhead and thus leaves less time for data transmission. In order to reduce the training overhead, an efficient two-phase beam training method is proposed in the related art, which first estimates the terminal space angle and then determines the terminal distance. This approach relies on the key fact that when using far field DFT beams for beam training, the true terminal spatial angle is approximately in the middle of the main angular region where the received signal power is high enough. The required training overhead can be further reduced by designing layered near-field beam training and performing beam training using a deep learning method.
Near field or far field communication is mainly considered in the related art, but in practical application, near field and far field hybrid communication is more likely to occur, that is, near field and far field terminals exist in the network at the same time. For example, assume that the antenna diameter of one Base Station (BS) is 0.5 meters (m), and the operating frequency is 30GHz. The well-known rayleigh distance in this case is about 50m. This means that in a representative communication scenario, the terminal may be located in the near field or far field region of the base station, resulting in more complex interference problems. More specifically, due to energy spreading effects, near-field terminals may be subject to strong interference with far-field terminal angles of DFT-based far-field beams when the spatial angle of the near-field terminal is nearby. On the other hand, energy leakage of DFT-based far-field beams can also be used to effectively charge near-field users, thus emerging new applications of hybrid near-far field wireless energy transfer (swift), where Energy Harvesting (EH) is located in the near field and Information Decoding (ID) receivers are located in the far field.
The related art focuses on the design of conventional far-field and near-field SWIPT systems, while the related art faces performance loss problems due to system mismatch for the phenomenon of mixed far-field. Moreover, there is currently no efficient design for mixed-field SWIPT systems.
In addition, the system design of hybrid far-near field SWIPTs also faces several new challenges. For example, by utilizing near field beam focusing characteristics, the beamforming of the near field EH receiver should be carefully designed to maximize EH efficiency while minimizing interference with the far field ID receiver. Second, energy spreading effects should be considered in designing beamforming for far field ID receivers, which can opportunistically charge near field EH receivers when they are located at similar angles. In addition, the power allocation of the BS should be carefully designed to balance the effects of the new near-far tradeoff with beam focusing and energy spread in the mixed-field swit.
Based on the above, the embodiment of the application provides a wireless energy-carrying communication method and a system, which aim to realize wireless energy-carrying communication under the mixed far-near field condition.
The following describes a wireless energy-carrying communication method provided by the embodiment of the application.
Referring to fig. 1, an embodiment of the present application provides a wireless energy-carrying communication method, which includes, but is not limited to, steps S101 to S104.
Step S101, obtaining a preset power distribution function; the power distribution function is obtained according to a pre-constructed reference communication system, the reference communication system comprises a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is in a first preset distance range, the distance between the reference information receiver and the reference base station is in a second preset distance range, and the maximum value of the first preset distance range is smaller than the minimum value of the second preset distance range;
Step S102, determining a first number of target energy receivers in the target communication system and determining a second number of target information receivers in the target communication system;
step S103, performing power calculation on the power distribution function according to the first quantity, the second quantity and preset constraint conditions to obtain target power;
step S104, the power distribution is carried out on the target energy receiver and the target information receiver according to the target power.
In the steps S101 to S104 shown in the embodiment of the present application, a power allocation function is constructed by a pre-constructed reference communication system, and the power allocation function is solved according to a first number of target energy receivers and a second number of target information receivers in a target communication system, so as to obtain target power. Because the reference communication system comprises the reference energy receiver arranged in the first preset distance range and the reference information receiver arranged in the second preset distance range, the constructed power distribution function can adapt to the target communication system comprising the target energy receiver and the target information receiver, and wireless energy carrying communication under the mixed far-near field condition is realized.
In step S101 of some embodiments, referring to fig. 2, the power allocation function is a function constructed according to the reference communication system as shown in fig. 2, and the power allocation function is used to describe the power allocated by each receiver. In a reference communication system, including a reference base station, a reference information receiver (i.e., an ID receiver), a reference energy receiver (i.e., an ID receiver) EH receiver). And taking the region with the distance from the reference base station in the first preset distance range as a near field region, and taking the region with the distance from the reference base station in the second preset distance range as a far field region. The reference energy receiver is in the near field region and the reference information receiver is in the far field region. The second predetermined distance range being greater than the so-called rayleigh distance, defined asWhere D represents the antenna array aperture and λ represents the carrier wavelength. It will be appreciated that the reference base station is in the form of a very large scale array, e.g. comprising N antennas. The reference information receiver and the reference energy receiver are both single antenna receivers. The reference communication system may include a plurality of reference information receivers and a plurality of reference energy receivers, such as a reference energy receiver comprising K single wires and M reference energy receivers,the reference base station performs power distribution on K+M reference energy receivers and reference information receivers by using a mixed beam forming method, wherein the number of radio frequency circuits of the reference base station satisfies N RF ≥K+M。
Referring to fig. 3, a method of constructing a power allocation function according to a reference communication system includes, but is not limited to, including steps S301 to S307.
Step S301, determining a first distance between a reference base station and a reference energy receiver;
Step S302, obtaining a near-field channel model according to a first distance and a first space angle between a reference base station and a reference energy receiver;
step S303, determining a second distance between the reference base station and the reference information receiver;
step S304, obtaining a far-field channel model according to the second distance and the second space angle between the reference base station and the reference information receiver;
step S305, a receiving signal model of a reference information receiver is built according to the far-field channel model;
step S306, constructing a collection power model of the reference energy receiver according to the near-field channel model;
step S307, a reference correlation matrix of the reference information receiver and the reference energy receiver is obtained, and a power distribution function is constructed according to the reference correlation matrix, the received signal model and the collected power model.
In steps S301-S302 of some embodiments, for a reference energy receiver k in the near field region, its channel from the XL-array BS may be modeled as:
wherein a LoS path and L exist between the reference base station and the reference energy receiver k k And NLoS paths. In the embodiment of the present application, considering that the swift channels in the high frequency band (e.g., mmWave and THz) are susceptible to blocking, the LoS channel components of the reference energy receiver and the reference information receiver will be mainly considered, and the NLoS component is ignored due to the low power. Therefore, the channel from the reference base station to the reference energy receiver k can be approximated as
The near field channel model modeling process is as follows. First, based on a near-field spherical wavefront propagation model, the nth antenna of the reference base station (i.e., (0, δ) n d) Distance from the reference energy receiver k)As shown in the following formula (1).
Wherein,,representing the distance (i.e. the first distance) between the reference base station center and the reference energy receiver k,represents the spatial angle (i.e., the first spatial angle) at the reference base station, phi k Representing the physical AoD from the reference base station center to the reference energy receiver k.
Then, utilize second order Taylor expansionThe LoS channel between the nth antenna of the reference base station and the reference energy receiver k can be modeled as +.>Wherein,,is the complex-valued channel gain in reference to the energy receiver k antenna direction. It will be appreciated that when the distance r between the reference base station and the reference energy receiver k is k When smaller than Rayleigh distance, develop +.>Is sufficiently accurate.
It is assumed that the reference energy receiver k is located in the Frenell Zone (Fresnel Zone) of the radiation, i.e. Under the above assumption, +.>Wherein->Is the shared complex-valued channel gain for different antennas.
Based on the above, the LoS-dominated near-field channel (i.e., near-field channel model) from the reference base station to the reference energy receiver k can be modeled simply as shown in equation (2) below.
Wherein b (θ) k ,r k ) Representing a normalized near field channel steering vector, can be calculated from equation (3) below.
In steps S303 to S304 of some embodiments, for each reference information receiver (e.g., reference information receiver m) located in the far field region of the reference base station, the channel from the reference base station may be characterized based on a planar wavefront propagation model as shown in the following equation (4).
Wherein a LoS path and L exist between the reference base station and the reference information receiver m m And NLoS paths. By ignoring negligible NLoS components in the high frequency band, the channels of the reference base station and the reference information receiver m (i.e., far-field channel model) can be approximated by corresponding LoS components, modeled as shown in the following equation (5).
Wherein,,complex-valued channel gain, r, representing reference information receiver m m Representing the distance (i.e., the second distance) between the center of the reference base station and the reference information receiver m. a (theta) m ) Representing normalized far-field channel steering vector, a (θ m ) Calculated by the following formula (6).
Wherein the method comprises the steps ofRepresenting the spatial angle of the reference base station (i.e., the second spatial angle), where φ m Representing the physical AoD from the reference base station center to the reference information receiver m.
In step S305 of some embodiments, let Indicating power of +.>The transmission energy of the reference energy receiver k is carried by a signal,/or->Indicating power of +.>Is a transmission information bearing signal of the reference information receiver m. By applying the hybrid beamforming, the signal vector transmitted by the reference base station is shown in the following equation (7).
Wherein,,F D representing a (K+M) x (K+M) digital precoder +.>Representing an N x (K+M) analog precoder +.>Analog beamforming vector representing reference energy receiver k +.>Representing the analog beamforming vector of the reference information receiver m.
In an embodiment of the application, in order to obtain efficient results and reduce the hardware cost of XL-array, the performance gain achieved by analog beamforming alone is evaluated by a pure analog beamforming design, thus setting the digital precoder as a unitary matrix. In addition, to further improve performance, an analog precoder F may be provided A Is based on weighted least mean square error or zero-forcing figures.
Order theRepresenting a beam scheduling indication set, wherein +.>Binary schedule variable representing each reference energy receiver k +.>A binary schedule variable representing the reference information receiver m. Specifically, if the reference energy receiver k is scheduled by the reference base station, +. >Otherwise-> Is defined in a similar way to->And will not be described in detail.
The received signal model is modeled as follows:
wherein,,represents the AWGN received at the reference signal receiver m, with an average value of zero and a power of +.>On this basis, the signal-to-interference-plus-noise ratio (SINR) received at the reference signal receiver m may be calculated according to the following equation:
wherein,,
the corresponding achievable rate in units of per second per hertz is calculated by:
in step S306 of some embodiments, for wireless power transfer, each reference energy receiver may collect wireless energy from the energy and information signals based on the broadcast characteristics of the wireless channel. Thus, by ignoring negligible noise power at the reference energy receiver, and assuming a linear energy harvesting model, the power harvested at the reference energy receiver k (i.e., harvested power model) is shown as follows:
wherein,,representing energy harvesting efficiency.
In step S307 of some embodiments, it is assumed that the reference base station has the optimal CSI for all reference energy receivers and all reference information receivers, i.e. has a near field channel control vector a, a far field channel control vector b, and a channel gain And->The CSI may be obtained by estimation of far-field signals and near-field channels, and a beam training method, and the embodiments of the present application will not be described in detail.
Further, for ease of implementation, it is assumed that if a reference energy receiver (or reference information receiver) is scheduled, the reference base station directs a beam towards the reference energy receiver (or reference information receiver) to maximize the reference energy receiver (or reference information receiver) received power based on, for example, codebook-based beamforming, i.e.Under the above assumption, the achievable rate of each reference information receiver m can be rewritten as:
the collected energy of each reference energy receiver k is:
the aim of the embodiment of the application is to jointly optimize the beam scheduling of XL-array BSAnd power allocationTo maximize the weighted energy sum of the acquisitions. In this process, the total rate constraint R of all reference information receivers and the total reference base station transmit power P 0 Constraint.
Let alpha k 0 represents the predefined power weight of each reference energy receiver k, when a reference energy receiver k corresponds to alpha k When the value is larger, it indicates that the reference base station has a higher energy transmission preference for the reference energy receiver than for other energy receivers. The weighted sum energy transmitted to all reference energy receivers is denoted by Q and can be expressed as:
Based on the above, the power allocation function shown in (P1) can be as follows.
(P1):
It is understood that the content after s.t. represents constraints.
The power allocation function (P1) is a mixed integer optimization problem based on binary beam scheduling and continuous power allocation. Furthermore, beam scheduling and power allocation optimization are strongly coupled in objective functions and constraints, which makes it more difficult for the power allocation function (P1) to get an optimal solution. In order to solve the above-mentioned problems, an embodiment of the present application proposes an efficient algorithm to be able to obtain an optimal solution (i.e., target power) of the power allocation function (P1) in the target communication system. The effective algorithm is described below.
The efficient algorithm, which in fact restates the power distribution function (P1) in a more compact form, includes a total of two important steps of eliminating the binary optimization variables and determining the reference energy receiver and reference signal receiver correlations. These two important steps are separately described below.
First, the elimination of the binary optimization variable will be described.
To solve this problem, embodiments of the present application eliminate the binary optimization variables by introducing continuous variables as shown below:
Based on this, it is possible to obtain:
it should be noted that the number of the substrates,and->There is a one-to-one correspondence between them. For example, when-> When->Because, the following equivalent formula can be obtained:
the method comprises the steps of,
based on the above, the power allocation function (P1) can be equivalently represented as (P2) below:
(P2)：
next, a description will be given of determining the correlation of the reference energy receiver and the reference signal receiver.
Defining any two near field steering vectors b H (θ p ,r p ) And b (theta) q ,r q ) The correlation between them is:
η(θ p ,θ q ,r p ,r q )＝|b H (θ p ,r p )b(θ q ,r q )|
based on the above definition, by calling the Fresnel function, an approximate expression of the above near field steering vector correlation can be obtained:
wherein,,
finally, based on the above-mentioned operation of binary variable elimination and correlation determination, it is possible to obtain:
to further simplify the power allocation function, the following reference correlation matrix is defined:
wherein the method comprises the steps ofThe correlation between channel steering vectors of the reference energy receiver p and the reference information receiver q is represented by the following formula:
in order to obtain a more compact form, the power distribution function (P2) is transformed. Specifically, the form of the reference correlation matrix Λ is further changed by setting some diagonal elements to zero, resulting in a new correlation matrix:
order theRepresenting a vector containing all the power allocation optimization variables. The power distribution function (P2) can be equivalently rewritten as a power distribution function (P3) on this basis:
(P3):
y≥0
Wherein c EH Andcalculated according to the following formula:
in step S102 of some embodiments, the reference communication system is a hypothetical model system, and in order to be able to match the power allocation function with the actual communication system (i.e. the target communication system), it is also necessary to determine the actual situation of the communication system, i.e. to determine the actual situation in which the first number of target energy receivers (i.e. EH receivers) and the second number of target information receivers (i.e. ID receivers) are included in the actual situation communication system.
In step S103 of some embodiments, the power distribution function is solved according to the first number, the second number and the preset constraint condition, to obtain the target power.
Referring to fig. 4, in some embodiments, step S103 includes, but is not limited to including, step S401 through step S402.
Step S401, if the first number is equal to zero and the second number is not equal to zero, performing transformation processing on the power distribution function to obtain a first distribution function;
step S402, performing power calculation on the first distribution function according to a preset constraint condition to obtain target power; wherein the preset constraint condition comprises And y ID More than or equal to 0, M represents a second quantity, +.>Coefficient vector, y representing target information receiver m ID Power allocation vector representing the target information receiver, < >>Target correlation matrix representing target information receiver and target energy receiver, < >>And representing the noise of the target information receiver m, and R represents the achievable rate of the target information receiver.
In steps S401 to S402 of some embodiments, when the first number is equal to zero and the second number is not equal to zero, it is indicated that only the target information receiver is included in the target communication system. At this time, the power allocation function (P3) may be optimized as the following first allocation function (P4):
(P4):find y ID
y ID ≥0
wherein y is ID A power allocation vector representing the target information receiver, from the representation of the first allocation function (P4), the first allocation function (P4) is a feasibility check problem. Thus, the feasibility check problem can be equivalently translated into the following:
if R is * And R, the first allocation function (P4) is viable. Where R represents a constraint of an achievable rate of the target information receiver, R * Representing the achievable rate of the function (P5), i.e. R * Is the maximum of the following function (P5):
(P5):
y ID ≥0
it follows that the first allocation function (P4) is possible when the constraints of the first allocation function (P4) are all met. If the total power budget is not fully utilized, the sum rate can be increased by allocating more power to the target information receiver, so the power sum constraint equation holds. Second, if the maximum value of the function (P5) is greater than R, the total rate constraint (i.e., the objective function of the function (P5)) holds. That is, it may be determined from the function (P5) whether the first allocation function (P4) is viable, In the case where the first allocation function (P4) is viable, the optimal solution y of the first allocation function (P4) ID I.e. representing the target power.
It will be appreciated that the function (P5) is a non-convex optimization problem due to the inclusion of complex ratio terms in the objective function of the function (P5). To address this problem, a split-plan approach may be called to convert the objective function into a more tractable form. Specifically, the function (P5) is an concave-convex part planning problem, and the concave-convex objective function can be converted into a series of concave sub-problems which are easy to solve through secondary transformation, so that a solution of the function (P5) is obtained.
Referring to fig. 5, in other embodiments, step S103 includes, but is not limited to including, step S501 through step S502.
Step S501, if the first number is not equal to zero and the second number is equal to zero, performing transformation processing on the power distribution function to obtain a second distribution function;
step S502, performing power calculation on the second distribution function according to a preset constraint condition to obtain target power; wherein the preset constraint condition comprisesAnd y EH 0, K represents a first number, M represents a second number, y EH Power allocation vector, P, representing a target energy receiver 0 Representing the maximum transmission signal power of the target base station in the target communication system.
In steps S501 to S502 of some embodiments, when the first number is not equal to zero and the second number is equal to zero, it is indicated that only the target energy receiver is included in the target communication system. At this time, y may be expressed asIn this case, the goal is to maximize the weighted sum power of the near field region target energy receiver given the transmit power constraints. Thus, the power allocation function (P3) may be optimized as a second allocation function (P6) as follows:
(P6):
y EH ≥0
it can be seen that the second distribution function (P6) is a problem of linear programming. To obtain the optimal solution of the second allocation function (P6), embodiments of the present application define an energy harvesting priority function and obtain the optimal beam scheduling and power allocation. It will be appreciated that the optimal solution y according to the second distribution function (P6) EH I.e. representing the target power.
Specifically, it willDefining an energy harvesting priority for each target energy receiver k, wherein the highest energy harvesting priority is expressed as:
it will be appreciated that the defined energy harvesting priority corresponds to the target function coefficient of each target energy receiver k in the second distribution function (P6), the energy harvesting priority essentially representing the energy harvesting capability of the target energy receiver k in the near field region WPT system. In a near field region WPT system, each target energy receiver may collect not only energy from an energy beam directed at itself, but also leaked energy from other target energy receivers.
In the optimal solution of the second allocation function (P6), all transmit power should be allocated to the target energy receiver with the highest energy harvesting priority. That is, the optimal power allocation is as follows:
since the second distribution function (P6) is a linear programming problem, its optimal solution can be obtained by the Karush-Kuhn-Tucker (KKT) condition.
As can be seen from steps S401 to S402 and steps S501 to S502, the above two special cases with the target information receiver or the target energy receiver show different principles of beam scheduling and power allocation in the near field region (or far field region). In particular, the power allocation of the target information receiver in the far field region follows a water-filling structure, while the target energy receiver in the near field region allocates all power to the receiver with the highest energy harvesting priority. However, for a new hybrid field SWIPT system having both a target energy receiver and a target information receiver, it is not known how to reasonably allocate the target base station transmit power.
To address the above, referring to fig. 6, in some embodiments, step S103 includes, but is not limited to including, step S601 to step S602 in other embodiments.
Step S601, if the first number is not equal to zero and the second number is equal to 1, performing transformation processing on the power distribution function to obtain a third distribution function;
step S602, performing power calculation on the third distribution function according to a preset constraint condition to obtain target power; wherein the preset constraint condition comprises c ID Coefficient vector representing the target information receiver, +.>Power allocation vector representing target energy receiver and target information receiver, +.>Target correlation matrix representing target information receiver and target energy receiver, < >>Representing noise of target information receiver, P 0 Representing the maximum transmission signal power of the target base station in the target communication system. />
In steps S601 to S602 of some embodiments, when the first number is not equal to zero and the second number is equal to 1, it is indicated that a plurality of target energy receivers and one target information receiver are included in the target communication system. At this time, the power allocation function (P3) may be optimized as the following third allocation function (P7):
wherein,,
the third distribution function (P7) is a linear programming problem, and the optimal solution of the third distribution function (P7)I.e. the target power. Optimal solution of third distribution function (P7)>The following are provided:
If ρ+.K+1, then
If ρ=k+1, then
Optimal solution of third distribution function (P7)It can also be determined by KKT conditions.
From the above-mentioned optimal solution, the optimal power allocation is determined by a defined energy harvesting priority function. In particular, if the target energy receiver with the highest energy acquisition priority is taken as the best target energy receiver (i.e., ρ+.k+1), the optimal power allocation scheme is to allocate a portion of the power to the target information receiver to meet the rate and constraints, while the remaining power should be allocated to the best target energy receiver. Further, if the target information receiver has the highest energy priority (i.e., ρ=k+1), all power should be allocated to the target information receiver.
Referring to fig. 7, in other embodiments, step S103 includes, but is not limited to including, step S701 through step S702.
Step S701, if the first number is not equal to zero and the second number is not equal to zero, obtaining a preset variable;
step S702, performing power calculation on the power distribution function according to a preset variable and a preset constraint condition to obtain target power; wherein the preset constraint condition comprises y is greater than or equal to 0, M represents a second quantity, S m And I m All represent preset variables, R represents the achievable rate of the target information receiver, < > >Coefficient vector representing target information receiver m, y representing targetPower allocation vector of the energy receiver and the target information receiver.
In step S701 of some embodiments, if the first number is not equal to zero and the second number is also not equal to zero, it indicates that the target communication system includes a plurality of target energy receivers and a plurality of target information receivers. At this time, { S by introducing a relaxation variable (i.e., a preset variable) m Sum { I } m Determines the target power. Wherein the relaxation variable satisfies the following formula:
on this basis, the power distribution function (P3) can be changed to the following form (P8):
(P8):
y≥0
it will be appreciated that when x is assumed>0，y>0, can obtainIs a convex function with respect to x, y. Complex constraints in the function (P8) can thus be handled based on the SCA method.
It should be noted that when another x>0，y>0, can obtainIs a convex function with respect to x, y. Complex constraints in the function (P8) can thus be handled based on the SCA method.
Specifically, by applying a first order Taylor expansion,the lower bound of (2) may be defined as:
wherein,,representing any feasible point. Therefore, the function (P8) approximates the following function (P9):
(P9):
y≥0
the function (P9) is a convex optimization problem that can be solved by a standard solver, such as CVX. It should be noted that the target power obtained from the function (P9) requires an iterative process until the fractional increase of the target function is below the threshold value ζ, ζ >0. It is understood that the suboptimal solution y of the function (P9) is the target power.
In step S104 of some embodiments, the beam scheduling and the target power are combined, and the power allocation is performed on the target energy receiver and the target information receiver, so as to implement efficient swits of the far-near field hybrid channel. It will be appreciated that beam scheduling is not performed when the target power corresponding to the target energy receiver (or target information receiver) is equal to zero. And when the target power corresponding to the target energy receiver (or the target information receiver) is not equal to zero, performing beam scheduling.
The wireless energy-carrying communication method provided by the embodiment of the application has the beneficial effects that:
(1) Aiming at the condition that only far-field region SWIPT and near-field region SWIPT are concerned in the related technology, the embodiment of the application provides a SWIPT system for mixing far-near channels. In addition, because the related technology cannot be directly applied to the SWIPT system of the mixed far and near channels, the embodiment of the application also provides a power distribution method according to the SWIPT system of the mixed far and near channels, and realizes high-efficiency SWIPT by jointly optimizing beam scheduling and power distribution.
(2) Aiming at the SWIPT system of the mixed far and near channels, the embodiment of the application provides four power distribution methods under different scenes. Compared with the power distribution method in the related art
(3) For a scenario in which the target communication system comprises a plurality of target energy receivers and a plurality of target information receivers, an efficient function (P9) is obtained by invoking the SCA technique, whereby a more general beam scheduling and power allocation method is obtained and a lower complexity is achieved.
The following describes a wireless energy-carrying communication system provided in an embodiment of the present application.
Referring to fig. 8, an embodiment of the present application further provides a wireless energy-carrying communication system, which may implement the above wireless energy-carrying communication method, where the system includes:
a power allocation function obtaining module 801, configured to obtain a preset power allocation function; the power distribution function is obtained according to a pre-constructed reference communication system, the reference communication system comprises a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is in a first preset distance range, the distance between the reference information receiver and the reference base station is in a second preset distance range, and the maximum value of the first preset distance range is smaller than the minimum value of the second preset distance range;
a number determination module 802 for determining a first number of target energy receivers in the target communication system and determining a second number of target information receivers in the target communication system;
The power calculation module 803 is configured to perform power calculation on the power distribution function according to the first number, the second number, and a preset constraint condition, so as to obtain a target power;
the power allocation module 804 is configured to allocate power to the target energy receiver and the target information receiver according to the target power.
The specific implementation of the wireless energy-carrying communication system is basically the same as the specific embodiment of the wireless energy-carrying communication method, and will not be described herein.
The embodiment of the application also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the wireless energy-carrying communication method when executing the computer program. The electronic equipment can be any intelligent terminal including a tablet personal computer, a vehicle-mounted computer and the like.
Referring to fig. 9, fig. 9 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:
the processor 901 may be implemented by a general purpose CPU (central processing unit), a microprocessor, an application specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), or one or more integrated circuits, etc. for executing related programs to implement the technical solution provided by the embodiments of the present application;
The memory 902 may be implemented in the form of read-only memory (ReadOnlyMemory, ROM), static storage, dynamic storage, or random access memory (RandomAccessMemory, RAM). The memory 902 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, relevant program codes are stored in the memory 902, and the processor 901 invokes a wireless energy-carrying communication method for executing the embodiments of the present disclosure;
an input/output interface 903 for inputting and outputting information;
the communication interface 904 is configured to implement communication interaction between the device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);
a bus 905 that transfers information between the various components of the device (e.g., the processor 901, the memory 902, the input/output interface 903, and the communication interface 904);
wherein the processor 901, the memory 902, the input/output interface 903 and the communication interface 904 are communicatively coupled to each other within the device via a bus 905.
The embodiment of the application also provides a computer readable storage medium, which stores a computer program, and the computer program realizes the wireless energy carrying communication method when being executed by a processor.
The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiments described in the embodiments of the present application are for more clearly describing the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application, and those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.
It will be appreciated by persons skilled in the art that the embodiments of the application are not limited by the illustrations, and that more or fewer steps than those shown may be included, or certain steps may be combined, or different steps may be included.
The system embodiments described above are merely illustrative, in that the units illustrated as separate components may or may not be physically separate, i.e., may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Those of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof.
The terms "first," "second," "third," "fourth," and the like in the description of the application and in the above figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "and/or" for describing the association relationship of the association object, the representation may have three relationships, for example, "a and/or B" may represent: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided by the present application, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the above elements is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interface, system or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a storage medium, including multiple instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing a program.
The preferred embodiments of the present application have been described above with reference to the accompanying drawings, and are not thereby limiting the scope of the claims of the embodiments of the present application. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the embodiments of the present application shall fall within the scope of the claims of the embodiments of the present application.
Claims (9)
1. A method of wireless energy-carrying communication, the method comprising:
acquiring a preset power distribution function; the power distribution function is obtained according to a pre-constructed reference communication system, the reference communication system comprises a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is in a first preset distance range, the distance between the reference information receiver and the reference base station is in a second preset distance range, and the maximum value of the first preset distance range is smaller than the minimum value of the second preset distance range;
determining a first number of target energy receivers in a target communication system and determining a second number of target information receivers in the target communication system;
performing power calculation on the power distribution function according to the first quantity, the second quantity and preset constraint conditions to obtain target power;
And carrying out power distribution on the target energy receiver and the target information receiver according to the target power.
2. The method of claim 1, wherein constructing the power allocation function from the reference communication system comprises:
determining a first distance of the reference base station from the reference energy receiver;
obtaining a near-field channel model according to the first distance and a first space angle between the reference base station and the reference energy receiver;
determining a second distance between the reference base station and the reference information receiver;
obtaining a far-field channel model according to the second distance and a second space angle between the reference base station and the reference information receiver;
constructing a receiving signal model of the reference information receiver according to the far-field channel model;
constructing a collection power model of the reference energy receiver according to the near-field channel model;
and acquiring a reference correlation matrix of the reference information receiver and the reference energy receiver, and constructing the power distribution function according to the reference correlation matrix, the received signal model and the collected power model.
3. The method according to claim 2, wherein the performing power calculation on the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
If the first number is equal to zero and the second number is not equal to zero, performing conversion processing on the power distribution function to obtain a first distribution function;
performing power calculation on the first distribution function according to the preset constraint condition to obtain the target power; wherein the preset constraint condition comprises Andm represents said second quantity,/->Coefficient vector, y representing the target information receiver m ID A power allocation vector representing said target information receiver,/->A target correlation matrix representing said target information receiver and said target energy receiver,/->And (3) representing the noise of the target information receiver m, and R represents the achievable rate of the target information receiver.
4. The method according to claim 2, wherein the performing power calculation on the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
if the first number is not equal to zero, the second number is equal to zero, and the power distribution function is subjected to transformation processing to obtain a second distribution function;
performing power calculation on the second distribution function according to the preset constraint condition to obtain the target power; wherein the preset constraint condition comprises And->K represents the first number, M represents the second number, y EH A power allocation vector, P, representing the target energy receiver 0 Representing the maximum transmission signal power of a target base station in the target communication system.
5. The method according to claim 2, wherein the performing power calculation on the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
if the first number is not equal to zero and the second number is equal to 1, performing transformation processing on the power distribution function to obtain a third distribution function;
performing power calculation on the third distribution function according to the preset constraint condition to obtain the target power; wherein the preset constraint condition comprises c ID Coefficient vector representing the target information receiver, +.>Power allocation vector representing target energy receiver and target information receiver, +.>A target correlation matrix representing said target information receiver and said target energy receiver,/->Representing the noise of the target information receiver, P 0 Representing the maximum transmission signal power of a target base station in the target communication system.
6. The method according to claim 2, wherein the performing power calculation on the power allocation function according to the first number, the second number, and a preset constraint condition to obtain a target power includes:
if the first number is not equal to zero and the second number is not equal to zero, acquiring a preset variable;
performing power calculation on a power distribution function according to the preset variable and the preset constraint condition to obtain target power; wherein the preset constraint condition comprises M represents the second number, S m And I m All represent preset variables, R represents the achievable rate of the target information receiver, +.>And a coefficient vector representing the target information receiver m, and y represents power allocation vectors of the target energy receiver and the target information receiver.
7. A wireless energy-carrying communication system, the system comprising:
the power distribution function acquisition module is used for acquiring a preset power distribution function; the power distribution function is obtained according to a pre-constructed reference communication system, the reference communication system comprises a reference base station, a reference information receiver and a reference energy receiver, the distance between the reference energy receiver and the reference base station is in a first preset distance range, the distance between the reference information receiver and the reference base station is in a second preset distance range, and the maximum value of the first preset distance range is smaller than the minimum value of the second preset distance range;
A number determination module configured to determine a first number of target energy receivers in a target communication system and determine a second number of target information receivers in the target communication system;
the power calculation module is used for carrying out power calculation on the power distribution function according to the first quantity, the second quantity and preset constraint conditions to obtain target power;
and the power distribution module is used for distributing power to the target energy receiver and the target information receiver according to the target power.
8. An electronic device comprising a memory storing a computer program and a processor implementing the method of any of claims 1 to 6 when the computer program is executed by the processor.
9. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method of any one of claims 1 to 6.
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