CN110049565A - A kind of 5G network power distribution method based on available capacity - Google Patents
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Abstract
The 5G network power distribution method based on available capacity that the invention discloses a kind of, the described method comprises the following steps: obtaining the power distribution mode of two user's asymptotic optimalities, maximizes available capacity by optimization power；Transmission network is derived into the scene to users multiple in single carrier channel；Using the characteristics of two subscriber signals transmit in single carrier channel, optimal precondition is set for multi-user transmission, then solve total maximum available capacity.The present invention can effectively overcome current these to be confined to the research of power distribution, without in view of the technical matters under specific QoS restraint condition.
Description
Technical Field
The invention relates to the field of 5G network power distribution, in particular to a 5G network power distribution method based on effective capacity.
Background
Today with the increasing progress of scientific technology, the implementation scene of communication technology has evolved from the initial voice telephone to the subsequent digital communication and then to multimedia communication, and the application scene has also evolved from the voice communication requiring single communication to a series of scenes with high requirements on communication delay and signal transmission quality, including video conferences, internet of things, internet of vehicles, satellite positioning, and the like. The 5G communication technology has come into play in such a large background. Because the requirement of people on the quality of Service (QoS) of communication is higher and higher, and because the characteristics of limited wireless communication resources and complex and changeable channel environment, how to reasonably and effectively allocate the limited resources is more and more important.
With the advent of the definition of 5G networks, a great deal of research on related contents is started, and the effective capacity region is still an important content because the 5G networks and the 4G networks adopt different standards, and there is no interference between signals in the 4G networks adopting orthogonal multiple access, and in the 5G NOMA networks, because non-orthogonal transmission is adopted, signals interfere with each other during transmission, so that it can be known that different results are generated under two different environments, and the effective capacity region needs to be researched again.
Much work has been done in the current state of the art on power allocation, including: a user grouping algorithm of a symmetric matrix is proposed to research a resource allocation mechanism in a non-orthogonal multiple access system; aiming at the problem of capacity-based optimization of downlink subcarrier and power allocation of a NOMA system, a user grouping and power allocation scheme is provided; and by researching the power allocation algorithm of the NOMA, a corresponding improvement strategy is provided.
However, these studies are currently limited to the study of power allocation algorithms, and do not consider the situation under specific QoS constraints.
Disclosure of Invention
The invention provides a 5G network power distribution method based on effective capacity, which can effectively overcome the current researches limited to power distribution without considering the technical problem under the condition of specific QoS constraint and is described in detail as follows:
a method for 5G network power allocation based on effective capacity, the method comprising the steps of:
acquiring a asymptotic optimal power distribution mode of two users, and maximizing effective capacity by optimizing power;
deducing a transmission network to a scene of a plurality of users on a single carrier channel; by utilizing the characteristics of signal transmission of two users in a single carrier channel, the optimal precondition is set for multi-user transmission, and then the total maximum effective capacity is solved.
The obtaining of the asymptotic optimal power distribution mode of the two users specifically includes:
using a NOMA network, P, with two subscribers1And P2Is the power of two clients, f is the frequency domain, H1And H2Is the channel gain of both user terminals,P1|h1|1and P2| h22Respectively representing the power of the transmission signals of the two users;
the signal transmission in the NOMA network is divided into uplink and downlink, wherein the uplink is that the mobile phone terminal sends signals to the base station, and the downlink is that the base station sends signals to the mobile phone terminal.
Further, the setting of optimal preconditions for multi-user transmission by using the characteristics of signal transmission of two users in a single carrier channel and solving the total maximum effective capacity specifically include:
determining a decoding sequence according to the gain of the user channel, and processing the interference generated by other signals as noise when the signal with the maximum gain is decoded;
subtracting the total signal after the signal decoding is finished, and preferentially decoding the signal with the second largest gain from the rest signals until only the signal with the smallest gain is left;
the minimum signal is only disturbed by noise in the channel, resulting in maximum effective capacity.
Wherein,
wherein,for an optimal power allocation scheme, HiWhere i is 1 and 2 denotes the carrier-to-noise ratio CNR, θkK is 1,2 represents the qos constraint index of two ues, βi＝θiT/ln2，λiIs a vector of dual variables related to power constraints, wiAnd S is duration time of interference and noise received by the ith user base station receiving end.
The technical scheme provided by the invention has the beneficial effects that:
1. through the intensive research on the wireless resource allocation problem under the QoS constraint, the invention obtains the optimal power allocation algorithm for two users on a single carrier channel, thereby maximizing the effective capacity by optimizing the power. On the basis, the method is deduced to the scenes of a plurality of users on a single carrier channel, and the maximum effective capacity under the scene of the plurality of users is solved. The problem that limited resources cannot be reasonably and effectively allocated due to the fact that wireless communication resources are limited and channel environments are complex and changeable is solved.
2. The invention uses the Monte Carlo method to carry out simulation experiment, compares with the power distribution algorithm based on the maximum throughput as the target, and the experimental result proves the correctness and the effectiveness of the method:
that is, when the weight ratio between three users is close to 1, the maximum effective capacity sum can be obtained, and the comparison experiment is performed with the power allocation algorithm based on the maximum throughput (ST) method as the evaluation standard, the influence of different QoS constraints on the effective capacity of multiple users is observed by the method of comparing the experiment results, and the effect difference between the power allocation algorithm (EC) based on the effective capacity and the power allocation algorithm (ST) based on the maximum throughput proposed in the present invention is that the power allocation algorithm (ST) based on the maximum total throughput does not consider the influence of the QoS constraints on the wireless network system, and the finally obtained maximum throughput data also tends to a constant value.
Drawings
Fig. 1 is a flow chart of a 5G network power allocation method based on effective capacity;
FIG. 2 is a schematic diagram of a power distribution model;
FIG. 3 is a graph illustrating the sum of the effective capacities of two users at different lambda values;
FIG. 4 is a graphical illustration of the maximum effective capacity of two users at different values of theta;
fig. 5 is a diagram illustrating the sum of the effective capacities of three users under different weight ratios.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
Example 1
In order to achieve the above object, an embodiment of the present invention provides a 5G network power allocation method based on effective capacity, and referring to fig. 1, the method includes the following steps:
101: acquiring a power distribution algorithm for gradually optimizing two users, and maximizing effective capacity by optimizing power;
102: deducing a transmission network to a scene of a plurality of users on a single carrier channel;
103: setting an optimal precondition for multi-user transmission by utilizing the characteristics of signal transmission of two users in a single carrier channel, and solving the total maximum effective capacity;
104: experiments prove the correctness and the effectiveness of the power distribution method provided by the invention.
In one embodiment, step 101 obtains an optimal power allocation algorithm for two users by converting an original problem into a mathematical problem, and the specific steps are as follows:
first, considering the situation of two users on a single carrier of an uplink network, the power allocation model (as shown in fig. 2) designed in the embodiment of the present invention considers that a NOMA network with two users, P, is used1And P2Is the power of the user terminals 1 and 2, f is the frequency domain, H1And H2Is the channel gain of user ends 1 and 2, P1| h11And P2| h22Representing the power of the signals transmitted by user 1 and user 2. In NOMA networksThe transmission of the number is divided into uplink and downlink, wherein the uplink is that the mobile phone terminal sends a signal to the base station, and the downlink is that the base station sends a signal to the mobile phone terminal.
When a sending end is considered, the embodiment of the invention considers that a single cell is adopted in two user simulation models to generate a base station, a serial interference deletion code is adopted at a receiving end to correctly solve an original signal, and when the decoding is finally successful, the decoding sequence does not influence the resultant rate, so that any decoding sequence can be set. Obtaining an optimal power distribution scheme after formula calculation: i.e. a larger constraint corresponds to a smaller effective capacity and a smaller constraint corresponds to a larger effective capacity.
In one embodiment, the reanalysis derivation of the transmission network in step 102 is derived to a scenario with multiple users on a single carrier channel, and the specific steps are as follows:
the method of overlapping transmission of a plurality of users in the same time frequency resource is still adopted at the transmitting end, and the receiving end adopts the serial interference elimination detection algorithm for receiving. The parameters of the two user models are adopted for each item of setting at the sending end, the difference is that two users are changed into a plurality of users, and then the relation between QoS constraint and effective capacity is continuously analyzed under the condition of the plurality of users.
In one embodiment, step 103 sets optimal preconditions for multi-user transmission by using known characteristics of two-user signal transmission in a single-carrier channel, and then solves for the total maximum effective capacity, which specifically comprises the following steps:
still adopt the mode of introducing the interference voluntarily, consider that the gain according to user's signal channel under the multiuser condition confirms the decoding order, namely must confirm the gain magnitude of each user first, regard interference that other signals produced as the noise processing when decoding the signal of the maximum gain first, subtract from total signal after the signal decoding is finished, decode the signal of the second maximum gain from the remaining signal preferentially again, similar to the previous step, until only remaining the signal of the minimum gain, it is not interfered by other signals, but only is interfered by the noise in the signal channel, thus receive the maximum effective capacity.
In one embodiment, step 104 is performed to prove the correctness and effectiveness of the power allocation method proposed by the embodiment of the present invention.
MATLAB tool software is used, a Monte Carlo method is used for carrying out simulation experiments, and the correctness and the effectiveness of the power distribution method provided by the embodiment of the invention are proved by comparing the simulation experiments with a power distribution algorithm which takes the maximum throughput as a target.
Example 2
The scheme of example 1 is further described below with reference to specific calculation formulas and examples, which are described in detail below:
201: converting the problem of solving the boundary point of the effective capacity area into a mathematical problem to solve, obtaining a power distribution algorithm for two users to be asymptotically optimal, and maximizing the effective capacity by optimizing the power;
taking two additive white gaussian noise channels as an example, the baseband received signal model is as shown in formula (1):
y＝x1+x2+w (1)
where w is interference and noise received by the base station receiving end, and follows a complex gaussian distribution w — CN (0, N0), N0 is an additive white gaussian noise power spectral density, y is a received signal at the base station receiving end, and xi (i is 1,2) is a signal of an end user i.
202: distributing the optimal power of a single-carrier user;
wherein, this step includes:
1) initializing w1, w2 being 1-w1, and parameters such as transmission power and QoS constraint, and repeating the following steps 2) -7);
2) simulating base station information to generate channel gain;
3) calculating a channel noise ratio and a channel power interference noise ratio according to the generated channel gain;
4) initializing lambdai 1，i＝1，2；
5) Calculating an optimal power allocation scheme P according to equation (2)i *I is 1, 2; l (λ) is a Lagrangian dual function.
6) Calculating a maximum effective capacity set E according to formula (3)c(P,θ)；
Ec(P,θ):＝[Ec(P1,θ1),Ec(P2,θ2)]T(3)
Wherein E isc(P1,θ1) Effective capacity of service procedures for user 1, Ec(P2,θ2) Effective capacity of service procedures for user 2, EcAnd (P, theta) is the maximum effective capacity set of the user 1 and the user 2 in the service process, P is the power distributed to the user, theta is a QoS constraint index, and T is transposition.
7) And stopping repeating the step 1) when w1 is equal to 1), otherwise, w1 is equal to w1+ △ w, and △ w is the offset of the received interference and noise.
The power distribution algorithm for obtaining the asymptotic optimal power distribution of the two users after calculation is shown as a formula (4):
wherein Hi(i ═ 1,2) to denote the carrier-to-noise ratio CNR, duration, θk(k-1, 2) represents the quality of service QOS constraint indices for user 1 and user 2, respectively, βi＝θiT/ln2，λiIs a vector of dual variables associated with the power constraint.
203: deriving a transmission network to a scenario of multiple users on a single carrier channel;
the sending end still adopts a plurality of users to carry out superposition transmission under the same time-frequency resource, and the receiving end adopts a serial interference elimination detection algorithm to carry out receiving.
204: in the multi-user wireless network system model, a single cell is still considered, a plurality of users are transmitted on a single carrier, and a baseband received signal model of the multi-user wireless network system model is shown in formula (5) by taking an additive white gaussian noise channel of the plurality of users as an example:
y＝x1+x2+…+xn+w (5)
wherein, similar to the two user models, w is the interference and noise received by the receiving end of the base station, and obeys the complex Gaussian distribution w-CN (0, N0), N0 is the power spectrum density of additive white Gaussian noise, y is the received signal of the base station, x isi(i ═ 1,2 … n) is the signal of end user i.
205: the method is characterized in that the known characteristics of signal transmission of two users in a single carrier channel are utilized, the optimal precondition is set for multi-user transmission, namely, parameters which are the same as those of two user models are adopted for each setting of a transmitting end, the difference is that the two users are converted into a plurality of users, and then the relation between QoS constraint and effective capacity is continuously analyzed under the condition of the plurality of users. Solving a total maximum effective capacity set according to a formula (6);
Ec(P,θ):＝[Ec(P1,θ1),Ec(P2,θ2)，…Ec(Pn,θn)]T(6)
wherein E isc(Pn,θn) The effective capacity of the service process for user n, the rest of the content is in accordance with the meaning in equation (3).
The embodiment of the invention still adopts a mode of actively introducing interference, considers that the decoding sequence is determined according to the gain of a user channel under the condition of multiple users, namely the gain of each user is determined firstly, the interference generated by other signals is treated as noise when the signal with the maximum gain is decoded firstly, the noise is subtracted from the total signal after the signal is decoded, and the signal with the second maximum gain is decoded from the rest signals preferentially, which is similar to the previous step until only the signal with the minimum gain is left, is not interfered by other signals, but is only interfered by the noise in the channel.
206: then, in the process of solving the multi-user optimal power, the derivation process in the two user models can be used, and the limiting conditions are changed from 1 to 2 to 1 to n, and the derivation processes are the same, so that the same optimal power distribution result can be obtained:
207: experiments prove the correctness and the effectiveness of the proposed power distribution method.
Example 3
In the embodiment of the invention, a Monte Carlo simulation method and MATLAB R2016a are used for simulation and result analysis, and the transmission power is set in the experiment so as to have little influence on the experiment, because the experiment aims at solving the optimal power, the experiment process can optimize the transmission power until the optimal power is reached. When the QoS constraint theta values of two users are both 0.0001, and the range of allowed values of lambda, namely lambda, is not less than 7, the effective capacity sum values of the two users are firstly increased and then reduced along with the lambda values.
Firstly, enabling two users to have the same QoS constraint theta value of 0.0001, recording and observing the values of the optimal power and the maximum effective capacity of the two users when changing the lambda value, and adopting a famous Monte Carlo statistical simulation method in a simulation experiment to ensure the effectiveness of the experiment, wherein the experimental result is the average value of 10000 experiments. In order to have a more intuitive effect, the QoS constraint theta values are all 0.0001 in the experimental process, the lambda values are respectively 7, 10, 15, 20 and 30, and the influence of the lambda value on the effective capacity is illustrated by observing the variation trend of the maximum effective capacity sum of two users.
The maximum sum of the effective capacity can be obtained when the weight ratio between three users is close to 1, which is the same as the model of two users. And finally, performing a simulation experiment by adopting a Monte Carlo method, setting the simulation times to be 1 ten thousand, simultaneously performing a comparison experiment with a power distribution algorithm based on a maximum throughput (ST) method as an evaluation standard, observing the influence of the two methods on the effective capacity of multiple users under different QoS constraints by a method for comparing the experiment results, and displaying the advantages of the invention by the difference of the effects of the two methods. It can also be seen that the method has significant advantages over the power allocation algorithm ST based on maximum overall throughput. The resulting maximum throughput data also tends to be constant. And 5G network power allocation based on effective capacity is met when the specific QoS requirement is met.
In fig. 3, when the value of lambda is 15, the system can always obtain the optimal effective capacity sum regardless of the variation of the value range of the weight vector. And according to the meaning of the effective capacity, which represents the transmission rate under the QoS constraint, the maximum effective capacity is obtained, that is, the maximum transmission rate supported by the system. On the other hand, it can be seen from the above experimental results that the maximum value can be obtained when the weight ratio of the two users is consistent, and this result is always valid under different parameters.
In fig. 4, the effective capacities of two users under different QoS constraint parameters are given, and it can be seen from fig. 4 that the value of the effective capacity obtained when the constraints of user 1 and user 2 are both 0.0001 is greater than that when the constraints are both 0.001 and 0.0005, and the value of the effective capacity when the constraint parameter is 0.0005 is greater than that when the constraint parameter is 0.001.
In fig. 5, it is evident that the maximum sum of effective capacities is obtained when the weight ratio between three users is close to 1, which is the same as the model for two users.
Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-described embodiments of the present invention are merely provided for description and do not represent the merits of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (4)
1. A5G network power distribution method based on effective capacity is characterized by comprising the following steps:
acquiring a asymptotic optimal power distribution mode of two users, and maximizing effective capacity by optimizing power;
deducing a transmission network to a scene of a plurality of users on a single carrier channel; by utilizing the characteristics of signal transmission of two users in a single carrier channel, the optimal precondition is set for multi-user transmission, and then the total maximum effective capacity is solved.
2. The 5G network power allocation method based on effective capacity according to claim 1, wherein the obtaining of the asymptotically optimal power allocation manner for the two users is specifically:
using a NOMA network, P, with two subscribers1And P2Is the power of two clients, f is the frequency domain, H1And H2Is the channel gain of two clients, P1| h11And P2| h22Respectively representing the power of the transmission signals of the two users;
the signal transmission in the NOMA network is divided into uplink and downlink, wherein the uplink is that the mobile phone terminal sends signals to the base station, and the downlink is that the base station sends signals to the mobile phone terminal.
3. The method according to claim 1, wherein the optimal precondition is set for multi-user transmission by using the characteristics of signal transmission of two users in a single carrier channel, and then the total maximum effective capacity is obtained by:
determining a decoding sequence according to the gain of the user channel, and processing the interference generated by other signals as noise when the signal with the maximum gain is decoded;
subtracting the total signal after the signal decoding is finished, and preferentially decoding the signal with the second largest gain from the rest signals until only the signal with the smallest gain is left;
the minimum signal is only disturbed by noise in the channel, resulting in maximum effective capacity.
4. The 5G network power allocation method based on effective capacity according to claim 2,
wherein, Pi *For an optimal power allocation scheme, HiRepresenting carrier noiseRatio CNR, thetakK is 1,2 represents the qos constraint index of two ues, βi＝θiT/ln2，λiIs a vector of dual variables related to power constraints, wiAnd S is duration time of interference and noise received by the ith user base station receiving end.
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