CN106231665A - Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network - Google Patents

Abstract

The invention discloses a kind of several can resource allocation methods based on the switching of RRH dynamic mode in integrated network, comprise the following steps: S1, determine network model and host-host protocol；S2, calculate energy signal and data signal that each user receives, calculate data throughout and the energy harvesting amount of each user；S3, definition evaluation function, determine optimization aim；S4, the beam designing of data and the energy transmission determined according to channel information between RRH and the user of optimum；S5, the data transmission user in a time slot, RRH model selection, RRH power are allocated into places Optimization Solution；S6, selecting system the corresponding data transmission selection of user, the distribution of RRH power and the RRH model selection of the maximum time slot of evaluation function sum as the optimal choice of system, and calculate RRH according to the method for step S4 the optimal beam of user designed.The present invention is by the optimized distribution to power Yu RRH resource, hence it is evident that handling capacity and energy that the system that improves is overall gather in performance.

Description

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network

Technical field

The invention belongs to number energy integrated communication networking technology area, be specifically related under a kind of C-RAN scene move based on RRH Morphotype formula switches and meets time slot and the power resource allocation scheme of different user collection data and energy total demand.

Background technology

Number energy integrated network (Data and Energy Integrated Communication Networks, DEINs) being a kind of communication network coming from data and energy cooperative transmission technology and evolve, it exists with the difference of legacy network The data communication between user and base station not merely can be carried out, it is also possible to meet the energy requirement of different user, such as in it Communication equipment is carried out wireless charging.Its basic protocol stack includes: physical layer, link layer, Internet and application layer.Wherein thing Reason layer is mainly responsible for energy and the coding of data message and decoding, additionally includes design and the full duplex technology of beam shaping Introducing, the utilization simultaneously disturbed with eliminate also can emerge from physical layer.Link layer is mainly responsible for the reasonable of the communication resource Distribution, including to different time-gap, the optimized distribution of the resource such as frequency and space, be otherwise responsible for data rate control and The management of energy.Internet is mainly responsible for the routing Design in number energy integrated network, comes by designing multiple routing algorithm Meet the assorted demand of the network user, such as low time delay or low forwarding energy expenditure.Application layer is more partial to concrete network Overall planning, including to wireless sensor network, the network architecture of cognitive radio networks and conventional cellular network etc. sets Meter.

The application under following multi-user scene of the number energy integrated network will be all the fashion, because this technology is not merely The demand data making different user is met, it is also possible to carry out certain radio energy-transmitting to user, ensures that its energy supply needs Ask.But, while considering multi-user, the impact of systematic function is would have to be studied by distance factor.Distance Transmission The energy that base station user farther out receives is no doubt little compared with near user than other distance base stations, therefore which results in different use Unjustness between family.Traditional data information network introduces relaying technique for distance factor, thus greatly adds The handling capacity of system.But for number energy integrated network, can be reduced compared to a jumping by two energy jumping to destination node Many, therefore relaying is not a good selection.And another beam shaping new technique, it may be considered that the user farther out that adjusts the distance is excellent First look after beamforming design, but be also very little for passing the improvement that can bring.Along with the development of 5G technology, multiple spot is assisted Applying wider, its medium cloud wireless access network (Cloud Radio Access Network, C-RAN) would is that not Carry out a crucial network technology.In C-RAN, system has multiple remote radio-frequency heads (Remote Radio Head, RRH) point Cloth is in whole scene, and each user can select several RRH to access.Compared to traditional center base station networking side Formula, distributed RRH can effectively increase network coverage rate, preferably looks after the edge customer in network, improves system whole The handling capacity of body, and also improve the overall level of resources utilization.Therefore, we can consider this technology is applied to several energy Integrated network, by the way of setting up distributed RRH, preferably resolves the distance unjustness of user.

Current wireless number the research majority of simultaneous interpretation technology can lay particular emphasis on data signal and energy signal in same signal Segmentation, and the two is made certain balance.But, the radio transmission efficiency under these modes may not be satisfied with.According to grinding Studying carefully display, wireless energy transfer can be higher in higher frequency range efficiency, and the transmission of data message is then contrary, therefore, in order to Improving data and the respective efficiency of transmission of energy, we can consider to separate data with energy signal, unlike signal list Solely transmission, in high frequency band, data signal transmission, at lower band, this creates the terminal two kinds of RRH not in energy signal transmission With transmission mode data transmission pattern and energy transmission mode, RRH can dynamically regulate the switching of both of which and promote The performance of system.Meanwhile, we can also optimize time slot and the power resource allocation of system further, accomplishes united optimum Change.

Only one of which center base station in traditional Cellular Networks, which results in signal relatively other honeybees that edge customer receives Nest internal user can faint a lot.It addition, user is while meeting data communication, the most also can produce certain energy needs Asking, this just requires that system can carry out data capacity coordinating transmissions by controlling the selection of communication pattern to user.And for not Same user, also can be different to the demand of data and energy, and the user such as having is partial to get online without being tethered to a cable, and some users are the most inclined To in charging to the mobile phone of oneself, this generates a series of resource allocation problem.

Further, since we introduce data transmits two kinds of mechanism with energy, user will certainly be caused data and energy Different needs of problems.In a communication scenes, some user lays particular emphasis on the data rate of communication, and some user is then more Adding and lay particular emphasis on the harvesting of energy so that equipment charge, therefore this is accomplished by the different demands between these different users are carried out one Fixed coordination.

Summary of the invention

It is an object of the invention to overcome the unjustness that in legacy cellular net, user distance factor causes, different user The problem that data are different from energy requirement, and the high complexity of optimal algorithm is realisation with difficulty, it is provided that a kind of by power The optimized distribution of resource, hence it is evident that the number of handling capacity that the system that improves is overall and energy harvesting performance can base in integrated networks Suboptimization resource allocation methods in the switching of RRH dynamic mode.

It is an object of the invention to be achieved through the following technical solutions: number can be based on RRH dynamic analog in integrated networks The resource allocation methods of formula switching, comprises the following steps:

S1, determine network model and host-host protocol；Communication between user and RRH is divided by time slot, each time slot Messaging parameter (such as channel information) all may be different；

S2, calculate energy signal and data signal that each user receives, and calculate the data throughout of each user With energy harvesting amount；

S3, definition evaluation function, and determine optimization aim according to evaluation function；

S4, the beam designing of data and the energy transmission determined according to channel information between RRH and the user of optimum；

S5, the data transmission user in a time slot, RRH model selection, RRH power are allocated into places Optimization Solution, Including following sub-step:

S51, initialize data transmission user in this time slot select, the distribution of RRH power and RRH mode selection scheme；

Data the transmission selection of user, the RRH merit that S52, the sub-optimal algorithm of employing Dynamic iterations are optimum in obtaining this time slot Rate distribution and RRH mode selection scheme, and calculate the evaluation function sum of system in this time slot；

S6, the data transmission user in each time slot, RRH model selection, the distribution of RRH power carry out suboptimization successively and ask Solve, the data transmission selection of user that the maximum time slot of the evaluation function sum of selecting system is corresponding, the distribution of RRH power and RRH model selection is as the optimal choice of system, and calculates the RRH optimal beam design to user according to the method for step S4, The global optimization of completion system.

Further, step S1 includes following sub-step:

In S11, note model scene, user's number is K, and each user has an antenna；A total of N number of RRH in scene, Each RRH is fitted with M root antenna；Each RRH has two kinds of mode of operations, i.e. energy transmission mode and data-transmission mode, Both of which can switch the most accordingly；If the maximum transmission power of RRH is P_max, all RRH are due to center The management of reason device, therefore overall transmission power also has a restriction, is defined asThe noise power of note interchannel is σ²；

Communication between S12, user and RRH is divided by time slot, for each time slot, in order to avoid conflict is dry Disturbing, only allow a user to carry out data transmission, other users then carry out energy transmission, due to energy signal and data signal Frequency band different, therefore will not mutually produce interference；The data transmission user that Systematic selection is optimum, chooses each RRH corresponding simultaneously Number can transmission modes, define one user and selects vectorial l, in this time slot, if user i carries out data transmission, make l_i= 1, if it carries out energy transmission, then make l_i=0；Define a RRH model selection vector r, for the t RRH, if its Select data-transmission mode, make r_t=1, otherwise make r_t=0.

Further, step S2 concrete methods of realizing is: in each time slot, between the t RRH to i-th user Channel table is shown as h_t,i, whereinThe unit beam designing of t RRH isPower is assigned as p_t；User receives To energy signal be expressed as with data signal:

The data signal that i-th user receives is expressed as:

$y_i^D=l_i\underset{t=1}{\overset{N}{\Σ}}{r}_t\sqrt{p_t}{h}_{t,i}^H{\mathrm{\ω}}_t{x}_0+z$

Wherein,Represent h_t,iConjugate transpose, z is white Gaussian noise, x₀Stochastic signal for unit power；

The energy signal that i-th user receives is expressed as:

$y_i^E=(1-l_i)\underset{t=1}{\overset{N}{\Σ}}(1-r_t)\sqrt{p_t}{h}_{t,i}^H{\mathrm{\ω}}_t{x}_0+z$

In this time slot, according to Shannon's theorems, the data throughout of i-th user is:

$R_i=l_i\mathrm{\τ}\log (1+\frac{\underset{t=1}{\overset{N}{\Σ}}{r}_t{p}_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}}{{\mathrm{\σ}}^2})$

In this time slot, according to Shannon's theorems, the energy harvesting amount summation of i-th user is:

$E_i=(1-l_i)\mathrm{\τ}\underset{t=1}{\overset{N}{\Σ}}(1-r_t)p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}$

For ω_tConjugate transpose.

Further, step S3 concrete methods of realizing is: define an association evaluation function:

η_i=α_iR_i+β_iE_i

Wherein, α_iAnd β_iIt is respectively each data factor corresponding for user i and energy factors, if certain user i is more desirable to Carry out data communication, then α_iMore than β_iIf certain user i is more desirable to carry out energy harvesting to be come equipment charge, then β_iGreatly In α_i；

In order to increase the satisfaction sum of all users of whole system, need the evaluation function sum to user used by system Maximize, i.e. obtain following optimization problem:

$\underset{l,p,r,\mathrm{\ω}}{\max }\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\η}}_i$

The restrictive condition that needs meet is:

C1:

C2:

C3:

C4:

C5:

The variable optimized is that the data transmission selection of user, the selection of RRH both of which, RRH transmit merit in each time slot Rate distribution and the design of RRH transmission beam；Wherein, limiting C1 and representing wave beam is a unit power vector；Limit C2 and represent each The transmit power of RRH must not exceed this threshold value；Limit C3 and represent that the transmission general power of all RRH of synchronization must not exceed this Threshold value；Restriction C4 represents each time slot at most can only have a user to carry out data transmission, and other users can only carry out energy Transmission；Limit C5 to represent RRH and at a time can only choose one of which pattern and carry out signal transmission.

Further, step S4 includes following sub-step:

S41, determine that the optimal beam of user is designed by RRH under data-transmission mode: assume that i-th user carries out data biography Defeated, the t RRH is carried out beam designing, owing to only one of which data transmit user, therefore utilizes the water-filling of beam designing, The beam designing obtaining optimum is:

${\mathrm{\ω}}_t=\frac{h_{t,i}}{\left|\right|h_{t,i}\left|\right|};$

The optimal beam of user is designed by S42, the RRH determined under energy transmission mode: the beam designing of t RRH sets For ω_t, defining the set of an energy harvesting user, represent with Φ, the signal of this RRH transmission receives at all energy user ends To totalizing wattmeter be shown as:

$p^{rcv}=p_t\underset{i\∈\mathrm{\Φ}}{\Σ}{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}=p_t{\mathrm{\ω}}_t^H{h}_t^{\′}{\mathrm{\ω}}_t$

Wherein,

Now, optimization problem is for makingMaximize, by quadratic form method, above-mentioned optimization problem solved, The optimal beam of user is designed by the RRH obtained under energy transmission mode.

Further, the specific implementation of step S51 is: owing to the complexity of optimal algorithm is of a relatively high and is difficult to Realize, therefore intend by the suboptimization algorithm of a kind of Joint iteration, optimization problem described in step S3 being solved；The most random Determining that a user transmits user as data, other users then carry out energy transmission, the then choosing of a kind of RRH of stochastic generation pattern Select scheme, and meet the 5th constraint in optimization aim, finally random further according in optimization aim second and the 3rd constraint Generate a kind of power allocation scheme, as the initialization of iterative algorithm.

Further, step S52 includes following sub-step:

S521, data transmission user's selection scheme of fixing last grey iterative generation and RRH power allocation scheme, for the first time Fix during iteration and initialize the data transmission user's selection scheme and RRH power allocation scheme generated, solve the RRH pattern of optimum Selection scheme: the power transmitted due to each RRH is it is known that root event obtains the RRH mode scheme of optimum according to power distribution；Due to The energy signal of user or data signal are all the direct superpositions to multiple RRH signals, and for single data signal or Energy signal, the transmission of different RRH is independent, therefore by considering that the model selection of each RRH determines the RRH that the overall situation is overall Mode selection scheme；Method particularly includes: for the t RRH, calculate its income selecting data-transmission mode and select energy The income of transmission mode, is carried out contrast and selects preferable pattern to be transmitted；Beam designing according to step S41 and S2 step Suddenly the handling capacity obtained and energy, obtain the t RRH and be expressed as the data throughout of i-th user with energy harvesting amount:

$R_{t,i}={\mathrm{\τl}}_{i}log(1+\frac{p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}}{{\mathrm{\σ}}^2})$

$E_{t,i}=\mathrm{\τ}(1-l_i)p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}$

Income under both of which is expressed as:

${\mathrm{\η}}_t^D=\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\α}}_i{R}_{t,i}$

${\mathrm{\η}}_t^E=\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\β}}_i{E}_{t,i}$

Contrast, ifThen the t RRH selects data-transmission mode, the most then select energy transmission mould Formula；

S522, data transmission user's selection scheme of fixing S521 step output and RRH mode selection scheme, determine optimum RRH power allocation scheme: the data throughout of user i is respectively as follows: by the t RRH with the contribution of energy harvesting amount

$R_{t,i}=r_t{\mathrm{\τl}}_{i}log(1+\frac{p_t{\mathrm{\ξ}}_{t,i}}{{\mathrm{\σ}}^2})$

E_t,i=(1-r_t)τ(1-l_i)p_tξ_t,i

Wherein,

The evaluation function sum of all users of system is:

$\mathrm{\η}=\underset{t=1}{\overset{N}{\Σ}}\underset{i=1}{\overset{K}{\Σ}}({\mathrm{\α}}_i{R}_{t,i}+{\mathrm{\β}}_i{E}_{t,i})$

And then it is as follows to obtain optimization aim:

By optimization aim is solved, try to achieve the evaluation function sum of optimum, draw the RRH power allocation scheme of optimum；

S523, the RRH power allocation scheme of fixing S522 step output and RRH mode selection scheme, determine the data of optimum Transmission user's selection scheme: contrast each user as system evaluation functions sum corresponding during data transmission user, then Choose user corresponding during evaluation function sum maximum and transmit user's selection scheme selected as optimal data, return step S521；

S524, according to the order of S521 → S522 → S523 → S521 → S522 → S523 → S521 to S521, S522 and S523 is circulated iterative computation, if the difference of the evaluation function sum of twice adjacent iteration is less than the convergence threshold set, Then think iteration convergence, stop iteration, obtain final data transmission user's selection scheme, RRH power allocation scheme and RRH mould The joint optimization result that formula selects.

The invention has the beneficial effects as follows:

1, the unjustness that during the present invention solves legacy cellular net, user distance factor causes, and the number of different user According to the problem different from energy requirement；In view of the frequency band differences of energy signal Yu data signal, use the switching of RRH dynamic mode The scheme chosen with optimal power allocation and user, and introduce an evaluation function data and the energy requirement of user are carried out Normalizing optimization coordinates different user flexibly to energy and the demand of data, by the optimized distribution to power resource, hence it is evident that Handling capacity and energy that the system that improves is overall gather in performance；Different pieces of information according to different user and energy requirement carry out mesh Mark property optimization, high degree improve user based on data and the satisfaction of energy；

2, by introducing the evaluation function of an associating data throughout and energy harvesting amount, we can accomplish cleverer The demand data of the coordinates user lived and energy requirement, therefore can better meet user, promotes the performance of communication system.

Accompanying drawing explanation

Fig. 1 is the resource allocation methods flow chart of the present invention；

Fig. 2 is that the number of the present invention can integrated network illustraton of model.

Detailed description of the invention

Noun implication:

DEIN: number can integrated network.Difference with traditional communication net be its not merely can carry out network node it Between data message mutual, it is also possible to carry out corresponding between energy transmit mutually.

Beam shaping: under multi-input multi-output system, transmitters and receivers are all disposed with many antennas.Can pass through Regulating the transmitting power of every antenna, transmitter, phase and polarization mode etc. make signal concentration launch towards receiving terminal direction, because of This reduces the power loss in other useless directions.The vector being at one end made up of all antennas transmission signal is wave beam Shape vector.

C-RAN: cloud wireless access network.By the way of distributed connection, data Layer is separated with key-course, Yong Huke To realize the mutual of information by connection RRH, multiple RRH then realize resource-sharing by control pond, a center and dynamically adjust Degree, improves resource utilization and flexibility ratio.

Far end radio frequency head in RRH:C-RAN.The distribution of multiple RRH distributings accesses for user in the cell, alleviates limit The bottleneck problem of edge user, expands the network coverage.

Water-filling: when carrying out the distribution of beam shaping every antenna power, the antenna overabsorption power good to channel, letter The antenna of road difference distributes power less, thus maximizes transfer rate.

Radio transmission efficiency: receiving terminal receives the ratio of power and transmitting terminal transmit power, according to the difference of transferring content Radio energy-transmitting efficiency and wireless biography number efficiency can be divided into again.

Further illustrate technical scheme below in conjunction with the accompanying drawings.

As it is shown in figure 1, resource allocation methods based on the switching of RRH dynamic mode in a kind of several energy integrated network, including Following steps:

S1, determine network model and host-host protocol；The present invention number can integrated network models as in figure 2 it is shown, user with Communication between RRH is divided by time slot, and the messaging parameter (such as channel information) of each time slot may be different；This step Specifically include following sub-step:

In S11, note model scene, user's number is K, and each user has an antenna；A total of N number of RRH in scene, Each RRH is fitted with M root antenna；Each RRH has two kinds of mode of operations, i.e. energy transmission mode and data-transmission mode, Both of which can switch the most accordingly；If the maximum transmission power of RRH is P_max, all RRH are due to center The management of reason device, therefore overall transmission power also has a restriction, is defined asThe noise power of note interchannel is σ²；

Communication between S12, user and RRH is divided by time slot, for each time slot, in order to avoid conflict is dry Disturbing, only allow a user to carry out data transmission, other users then carry out energy transmission, due to energy signal and data signal Frequency band different, therefore will not mutually produce interference；The data transmission user that Systematic selection is optimum, chooses each RRH corresponding simultaneously Number can transmission modes, define one user and selects vectorial l, in this time slot, if user i carries out data transmission, make l_i= 1, if it carries out energy transmission, then make l_i=0；Define a RRH model selection vector r, for the t RRH, if its Select data-transmission mode, make r_t=1, otherwise make r_t=0.

S2, calculate energy signal and data signal that each user receives, and calculate the data throughout of each user With energy harvesting amount；Concrete methods of realizing is: in each time slot, and the t RRH is shown as to the channel table between i-th user h_t,i, whereinThe unit beam designing of t RRH isPower is assigned as p_t；The energy letter that user receives Number it is expressed as with data signal:

The data signal that i-th user receives is expressed as:

$y_i^D=l_i\underset{t=1}{\overset{N}{\Σ}}{r}_t\sqrt{p_t}{h}_{t,i}^H{\mathrm{\ω}}_t{x}_0+z$

Wherein,Represent h_t,iConjugate transpose, z is white Gaussian noise, x₀Stochastic signal for unit power；

The energy signal that i-th user receives is expressed as:

$y_i^E=(1-l_i)\underset{t=1}{\overset{N}{\Σ}}(1-r_t)\sqrt{p_t}{h}_{t,i}^H{\mathrm{\ω}}_t{x}_0+z$

In this time slot, according to Shannon's theorems, the data throughout of i-th user is:

$R=l_i\mathrm{\τ}log(1+\frac{\underset{t=1}{\overset{N}{\Σ}}{r}_t{p}_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}}{{\mathrm{\σ}}^2})$

In this time slot, according to Shannon's theorems, the energy harvesting amount summation of i-th user is:

$E_i=(1-l_i)\mathrm{\τ}\underset{t=1}{\overset{N}{\Σ}}(1-r_t)p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}$

For ω_tConjugate transpose.

S3, definition evaluation function, and determine optimization aim according to evaluation function；Concrete methods of realizing is: define a connection Conjunction evaluation function:

η_i=α_iR_i+β_iE_i

Wherein, α_iAnd β_iIt is respectively each data factor corresponding for user i and energy factors, if certain user i is more desirable to Carry out data communication, then α_iMore than β_iIf certain user i is more desirable to carry out energy harvesting to be come equipment charge, then β_iGreatly In α_i；

In order to increase the satisfaction sum of all users of whole system, need the evaluation function sum to user used by system Maximize, i.e. obtain following optimization problem:

$\underset{l,p,r,\mathrm{\ω}}{\max }\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\η}}_i$

The restrictive condition that needs meet is:

C1:

C2:

C3:

C4:

C5:

The variable optimized is that the data transmission selection of user, the selection of RRH both of which, RRH transmit merit in each time slot Rate distribution and the design of RRH transmission beam；Wherein, limiting C1 and representing wave beam is a unit power vector；Limit C2 and represent each The transmit power of RRH must not exceed this threshold value；Limit C3 and represent that the transmission general power of all RRH of synchronization must not exceed this Threshold value；Restriction C4 represents each time slot at most can only have a user to carry out data transmission, and other users can only carry out energy Transmission；Limit C5 to represent RRH and at a time can only choose one of which pattern and carry out signal transmission.

S4, the beam designing of data and the energy transmission determined according to channel information between RRH and the user of optimum；Specifically Including following sub-step:

S41, determine that the optimal beam of user is designed by RRH under data-transmission mode: assume that i-th user carries out data biography Defeated, the t RRH is carried out beam designing, owing to only one of which data transmit user, therefore utilizes the water-filling of beam designing, The beam designing obtaining optimum is:

${\mathrm{\ω}}_t=\frac{h_{t,i}}{\left|\right|h_{t,i}\left|\right|};$

The optimal beam of user is designed by S42, the RRH determined under energy transmission mode: the beam designing of t RRH sets For ω_t, defining the set of an energy harvesting user, represent with Φ, the signal of this RRH transmission receives at all energy user ends To totalizing wattmeter be shown as:

$p^{rcv}=p_t\underset{i\∈\mathrm{\Φ}}{\Σ}{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}=p_t{\mathrm{\ω}}_t^H{h}_t^{\′}{\mathrm{\ω}}_t$

Wherein,

Now, optimization problem is for makingMaximize, by quadratic form method, above-mentioned optimization problem solved, The optimal beam of user is designed by the RRH obtained under energy transmission mode.

S5, the data transmission user in a time slot, RRH model selection, RRH power are allocated into places Optimization Solution, Including following sub-step:

S51, initialize data transmission user in this time slot select, the distribution of RRH power and RRH mode selection scheme；Its Specific implementation is: owing to the complexity of optimal algorithm is of a relatively high and is difficult to, therefore intends by a kind of Joint iteration Suboptimization algorithm optimization problem described in step S3 is solved；Determine that a user uses as data transmission the most at random Family, other users then carry out energy transmission, the then selection scheme of a kind of RRH of stochastic generation pattern, and meet optimization aim In the 5th constraint, finally further according in optimization aim second and the 3rd constraint stochastic generation one power allocation scheme, make Initialization for iterative algorithm.

Data the transmission selection of user, the RRH merit that S52, the sub-optimal algorithm of employing Dynamic iterations are optimum in obtaining this time slot Rate distribution and RRH mode selection scheme, and calculate the evaluation function sum of system in this time slot；Specifically include following sub-step Rapid:

S521, data transmission user's selection scheme of fixing last grey iterative generation and RRH power allocation scheme, for the first time Fix during iteration and initialize the data transmission user's selection scheme and RRH power allocation scheme generated, solve the RRH pattern of optimum Selection scheme: the power transmitted due to each RRH is it is known that root event obtains the RRH mode scheme of optimum according to power distribution；Due to The energy signal of user or data signal are all the direct superpositions to multiple RRH signals, and for single data signal or Energy signal, the transmission of different RRH is independent, therefore by considering that the model selection of each RRH determines the RRH that the overall situation is overall Mode selection scheme；Method particularly includes: for the t RRH, calculate its income selecting data-transmission mode and select energy The income of transmission mode, is carried out contrast and selects preferable pattern to be transmitted；Beam designing according to step S41 and S2 step Suddenly the handling capacity obtained and energy, obtain the t RRH and be expressed as the data throughout of i-th user with energy harvesting amount:

$R_{t,i}={\mathrm{\τl}}_{i}log(1+\frac{p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}}{{\mathrm{\σ}}^2})$

$E_{t,i}=\mathrm{\τ}(1-l_i)p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}$

Income under both of which is expressed as:

${\mathrm{\η}}_t^D=\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\α}}_i{R}_{t,i}$

${\mathrm{\η}}_t^E=\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\β}}_i{E}_{t,i}$

Contrast, ifThen the t RRH selects data-transmission mode, the most then select energy transmission mould Formula；

S522, data transmission user's selection scheme of fixing S521 step output and RRH mode selection scheme, determine optimum RRH power allocation scheme: the data throughout of user i is respectively as follows: by the t RRH with the contribution of energy harvesting amount

$R_{t,i}=r_t{\mathrm{\τl}}_{i}log(1+\frac{p_t{\mathrm{\ξ}}_{t,i}}{{\mathrm{\σ}}^2})$

E_t,i=(1-r_t)τ(1-l_i)p_tξ_t,i

Wherein,

The evaluation function sum of all users of system is:

$\mathrm{\η}=\underset{t=1}{\overset{N}{\Σ}}\underset{i=1}{\overset{K}{\Σ}}({\mathrm{\α}}_i{R}_{t,i}+{\mathrm{\β}}_i{E}_{t,i})$

And then it is as follows to obtain optimization aim:

By optimization aim is solved, try to achieve the evaluation function sum of optimum, draw the RRH power allocation scheme of optimum；

S523, the RRH power allocation scheme of fixing S522 step output and RRH mode selection scheme, determine the data of optimum Transmission user's selection scheme: contrast each user as system evaluation functions sum corresponding during data transmission user, then Choose user corresponding during evaluation function sum maximum and transmit user's selection scheme selected as optimal data, return step S521；

S524, according to the order of S521 → S522 → S523 → S521 → S522 → S523 → S521 to S521, S522 and S523 is circulated iterative computation, if the difference of the evaluation function sum of twice adjacent iteration is less than the convergence threshold set, Then think iteration convergence, stop iteration, obtain final data transmission user's selection scheme, RRH power allocation scheme and RRH mould The joint optimization result that formula selects.

S6, the data transmission user in each time slot, RRH model selection, the distribution of RRH power carry out suboptimization successively and ask Solve, the data transmission selection of user that the maximum time slot of the evaluation function sum of selecting system is corresponding, the distribution of RRH power and RRH model selection is as the optimal choice of system, and calculates the RRH optimal beam design to user according to the method for step S4, The global optimization of completion system.

Those of ordinary skill in the art it will be appreciated that embodiment described here be to aid in reader understanding this Bright principle, it should be understood that protection scope of the present invention is not limited to such special statement and embodiment.This area It is each that those of ordinary skill can make various other without departing from essence of the present invention according to these technology disclosed by the invention enlightenment Planting concrete deformation and combination, these deform and combine the most within the scope of the present invention.

Claims (7)

1. resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network, it is characterised in that include following step Rapid:

S1, determine network model and host-host protocol；Communication between user and RRH is divided by time slot；

S2, calculate energy signal and data signal that each user receives, and calculate data throughout and the energy of each user Amount harvesting amount；

S3, definition evaluation function, and determine optimization aim according to evaluation function；

S4, the beam designing of data and the energy transmission determined according to channel information between RRH and the user of optimum；

S5, the data transmission user in a time slot, RRH model selection, RRH power are allocated into places Optimization Solution, including Following sub-step:

S51, initialize data transmission user in this time slot select, the distribution of RRH power and RRH mode selection scheme；

S52, use the sub-optimal algorithm of Dynamic iterations to obtain the data transmission selection of user optimum in this time slot, RRH power divides It is equipped with and RRH mode selection scheme, and calculates the evaluation function sum of system in this time slot；

S6, the data transmission user in each time slot, RRH model selection, the distribution of RRH power carry out suboptimization successively and solve, The data that the time slot of the evaluation function sum maximum of selecting system is corresponding transmit the selection of user, the distribution of RRH power and RRH mould Formula is selected as the optimal choice of system, and calculates RRH according to the method for step S4 and design the optimal beam of user, complete be The global optimization of system.

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network the most according to claim 1, its Being characterised by, described step S1 includes following sub-step:

In S11, note model scene, user's number is K, and each user has an antenna；In scene, a total of N number of RRH, each RRH is fitted with M root antenna；Each RRH has two kinds of mode of operations, i.e. energy transmission mode and data-transmission mode, two kinds Pattern can switch the most accordingly；If the maximum transmission power of RRH is P_max, all RRH are due to center processor Management, therefore overall transmission power has a restriction, is defined asThe noise power of note interchannel is σ²；

Communication between S12, user and RRH is divided by time slot, for each time slot, in order to avoid conflict interference, only Allowing a user to carry out data transmission, other users then carry out energy transmission, due to the frequency of energy signal Yu data signal Band is different, therefore will not mutually produce interference；The data transmission user that Systematic selection is optimum, chooses each RRH simultaneously and counts accordingly Energy transmission mode, defines a user and selects vector l, in this time slot, if user i carries out data transmission, make l_i=1, as Really it carries out energy transmission, then make l_i=0；Define a RRH model selection vector r, for the t RRH, if it selects Data-transmission mode, makes r_t=1, otherwise make r_t=0.

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network the most according to claim 2, its Being characterised by, described step S2 concrete methods of realizing is: in each time slot, the channel between the t RRH to i-th user It is expressed as h_t,i, whereinThe unit beam designing of t RRH isPower is assigned as p_t；User receives Energy signal is expressed as with data signal:

The data signal that i-th user receives is expressed as:

$y_i^D=l_i\underset{t=1}{\overset{N}{\Σ}}{r}_t\sqrt{p_t}{h}_{t,i}^H{\mathrm{\ω}}_t{x}_0+z$

Wherein,Represent h_t,iConjugate transpose, z is white Gaussian noise, x₀Stochastic signal for unit power；

The energy signal that i-th user receives is expressed as:

$y_i^E=(1-l_i)\underset{t=1}{\overset{N}{\Σ}}(1-r_t)\sqrt{p_t}{h}_{t,i}^H{\mathrm{\ω}}_t{x}_0+z$

In this time slot, according to Shannon's theorems, the data throughout of i-th user is:

$R_i=l_i\mathrm{\τ}log(1+\frac{\underset{t=1}{\overset{N}{\Σ}}{r}_t{p}_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}}{{\mathrm{\σ}}^2})$

In this time slot, according to Shannon's theorems, the energy harvesting amount summation of i-th user is:

$E_i=(1-l_i)\mathrm{\τ}\underset{t=1}{\overset{N}{\Σ}}(1-r_t)p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}$

For ω_tConjugate transpose.

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network the most according to claim 3, its Being characterised by, described step S3 concrete methods of realizing is: define an association evaluation function:

η_i=α_iR_i+β_iE_i

Wherein, α_iAnd β_iIt is respectively each data factor corresponding for user i and energy factors, if certain user i is more desirable to carry out Data communication, then α_iMore than β_iIf certain user i is more desirable to carry out energy harvesting to be come equipment charge, then β_iIt is more than α_i；

In order to increase the satisfaction sum of all users of whole system, need the evaluation function sum of user used by system is carried out Maximize, i.e. obtain following optimization problem:

$\underset{l,p,r,\mathrm{\ω}}{max}\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\η}}_i$

The restrictive condition that needs meet is:

$\begin{array}{cc}C1:& \left|\right|{\mathrm{\ω}}_t\left|\right|=1,\∀1\≤t\≤N\end{array}$

$\begin{array}{cc}C2:& p_t\≤P_{\max },\∀1\≤t\≤N\end{array}$

$\begin{array}{cc}C3:& \underset{t=1}{\overset{N}{\Σ}}{p}_t\≤P_{max}^{CP}\end{array}$

$\begin{array}{cc}C4:& \underset{i=1}{\overset{K}{\Σ}}{l}_i=1\end{array}$

$\begin{array}{cc}C5:& r_t=1or0,\∀1\≤t\≤N\end{array}$

The variable optimized is that the data transmission selection of user, the selection of RRH both of which, RRH through-put power are divided in each time slot It is equipped with and the design of RRH transmission beam；Wherein, limiting C1 and representing wave beam is a unit power vector；Limit C2 and represent each RRH's Transmit power must not exceed this threshold value；Limit C3 and represent that the transmission general power of all RRH of synchronization must not exceed this thresholding Value；Restriction C4 represents each time slot at most can only have a user to carry out data transmission, and other users can only carry out energy transmission； Limit C5 to represent RRH and at a time can only choose one of which pattern and carry out signal transmission.

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network the most according to claim 4, its Being characterised by, described step S4 includes following sub-step:

S41, determine that the optimal beam of user is designed by RRH under data-transmission mode: assume that i-th user carries out data transmission, The t RRH is carried out beam designing, owing to only one of which data transmit user, therefore utilizes the water-filling of beam designing, obtain Optimum beam designing is:

${\mathrm{\ω}}_t=\frac{h_{t,i}}{\left|\right|h_{t,i}\left|\right|};$

The optimal beam of user is designed by S42, the RRH determined under energy transmission mode: the beam designing of t RRH is set to ω_t, Define the set of energy harvesting user, represent with Φ, the signal of this RRH transmission all energy user termination receive total Power meter is shown as:

$p^{rcv}=p_t\underset{i\∈\mathrm{\Φ}}{\Σ}{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}=p_t{\mathrm{\ω}}_t^H{h}_t^{\′}{\mathrm{\ω}}_t$

Wherein,

Now, optimization problem is for makingMaximize, by quadratic form method, above-mentioned optimization problem is solved, obtain The optimal beam of user is designed by the RRH under energy transmission mode.

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network the most according to claim 5, its Being characterised by, the specific implementation of described step S51 is: intend being come step S3 by the suboptimization algorithm of a kind of Joint iteration Described optimization problem solves；Determining that a user transmits user as data the most at random, other users then carry out energy biography Defeated, the then selection scheme of a kind of RRH of stochastic generation pattern, and meet the 5th constraint in optimization aim, finally further according to In optimization aim second and the 3rd constraint stochastic generation one power allocation scheme, as the initialization of iterative algorithm.

Resource allocation methods based on the switching of RRH dynamic mode in number energy integrated network the most according to claim 6, its Being characterised by, described step S52 includes following sub-step:

S521, data transmission user's selection scheme of fixing last grey iterative generation and RRH power allocation scheme, iteration for the first time Time fix and initialize the data transmission user's selection scheme and RRH power allocation scheme generated, solve the RRH model selection of optimum Scheme: the power transmitted due to each RRH is it is known that root event obtains the RRH mode scheme of optimum according to power distribution；Due to user Energy signal or data signal be all the direct superposition to multiple RRH signals, and for single data signal or energy Signal, the transmission of different RRH is independent, therefore by considering that the model selection of each RRH determines the RRH pattern that the overall situation is overall Selection scheme；Method particularly includes: for the t RRH, calculate its income selecting data-transmission mode and select energy transmission The income of pattern, is carried out contrast and selects preferable pattern to be transmitted；Beam designing and S2 step according to step S41 are asked The handling capacity gone out and energy, obtain the t RRH and be expressed as the data throughout of i-th user with energy harvesting amount:

$R_{t,i}={\mathrm{\τl}}_{i}log(1+\frac{p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}}{{\mathrm{\σ}}^2})$

$E_{t,i}=\mathrm{\τ}(1-l_i)p_t{h}_{t,i}^H{\mathrm{\ω}}_t{\mathrm{\ω}}_t^H{h}_{t,i}$

Income under both of which is expressed as:

${\mathrm{\η}}_t^D=\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\α}}_i{R}_{t,i}$

${\mathrm{\η}}_t^E=\underset{i=1}{\overset{K}{\Σ}}{\mathrm{\β}}_i{E}_{t,i}$

Contrast, ifThen the t RRH selects data-transmission mode, the most then select energy transmission mode；

S522, data transmission user's selection scheme of fixing S521 step output and RRH mode selection scheme, determine the RRH of optimum Power allocation scheme: the data throughout of user i is respectively as follows: by the t RRH with the contribution of energy harvesting amount

$R_{t,i}=r_t{\mathrm{\τl}}_{i}log(1+\frac{p_t{\mathrm{\ξ}}_{t,i}}{{\mathrm{\σ}}^2})$

E_t,i=(1-r_t)τ(1-l_i)p_tξ_t,i

Wherein,

The evaluation function sum of all users of system is:

$\mathrm{\η}=\underset{t=1}{\overset{N}{\Σ}}\underset{i=1}{\overset{K}{\Σ}}({\mathrm{\α}}_i{R}_{t,i}+{\mathrm{\β}}_i{E}_{t,i})$

And then it is as follows to obtain optimization aim:

$\underset{p_t}{max}\mathrm{\η}$

By optimization aim is solved, try to achieve the evaluation function sum of optimum, draw the RRH power allocation scheme of optimum；

S523, the RRH power allocation scheme of fixing S522 step output and RRH mode selection scheme, determine the data transmission of optimum User's selection scheme: contrast each user as system evaluation functions sum corresponding during data transmission user, then choose User corresponding during evaluation function sum maximum transmits user's selection scheme selected as optimal data, returns step S521；

S524, S521, S522 and S523 are circulated iterative computation, if the difference of the evaluation function sum of twice adjacent iteration The convergence threshold that value sets less than one, then it is assumed that iteration convergence, stops iteration, obtains final data transmission user's selecting party Case, RRH power allocation scheme and the joint optimization result of RRH model selection.