CN104540209B - A kind of method for lifting interference alignment network transmission speed - Google Patents

A kind of method for lifting interference alignment network transmission speed Download PDF

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CN104540209B
CN104540209B CN201410720471.XA CN201410720471A CN104540209B CN 104540209 B CN104540209 B CN 104540209B CN 201410720471 A CN201410720471 A CN 201410720471A CN 104540209 B CN104540209 B CN 104540209B
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CN104540209A (en
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赵楠
练笔站
殷洪玺
郝洋
王欣
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Dalian University of Technology
State Grid Corp of China SGCC
Information and Telecommunication Branch of State Grid Henan Electric Power Co Ltd
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Dalian University of Technology
State Grid Corp of China SGCC
Information and Telecommunication Branch of State Grid Henan Electric Power Co Ltd
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Abstract

The present invention relates to a kind of method for lifting interference alignment network transmission speed, the pre-coding matrix and decoding matrix for disturbing alignment network are calculated first, and the total transmission power for the network that secondly alignd interference optimizes distribution K user;Distribution is finally optimized again its data flow the transmission power of each user after distribution.This method can effectively solve the power distribution problems in interference alignment network between multiple data stream under actual environment with relatively low computation complexity, lift the speed of information transfer, actual communication networks are more suitable for, solve realistic problem present in interference alignment techniques practical application.

Description

A kind of method for lifting interference alignment network transmission speed
Technical field
The present invention relates to a kind of method for lifting interference alignment network transmission speed, belong to radio communication interference management neck Domain.
Background technology
Radio communication develops rapidly, and daily life various aspects have been goed deep into related application.In order to further improve nothing The transmission rate of line communication network, will use heterogeneous network in next generation wireless communication system, all kinds and scale it is small Area coexists.Then, it is inevitably present and disturbs between various users of all cells, has a strong impact on communication quality and transmission speed Rate.Therefore interference management is the key problem in next generation wireless communication field.
In order to eliminate the interference in radio communication between user and improve the speed of transmission, people once investigated many sides Method improves the quality of communication.These methods can reduce the influence of inter-user interference to varying degrees, however, pressing down in interference It is not ideal enough in effect processed and the utilization rate of frequency spectrum resource.Recently, the appearance of alignment techniques is disturbed, this can be efficiently solved One problem.Interference alignment can effectively remove the interference between multi-user, make full use of frequency spectrum resource, improve systematic function.Interference The main thought of alignment techniques is to carry out precoding in transmitting terminal, interference is limited in a certain subspace of receiving terminal, and then Desired signal is disturbed and recovers by decoding to remove.
But the existing research work lifting of concern interference alignment network throughput in ideal conditions mostly, very Some specific questions of real network, such as asymmetrical network, each user's location distribution, user and data flow are considered less Between power distribution the problems such as.When considering real network model, each user is due to location distribution and transient channel shape The difference of state, it is necessary to consider the problem of power distribution etc. is more practical.When each user transmits multiple data flows, interference alignment Power distribution problems in network between each data flow will become extremely complex, if not reasonably to each data flow it Between carry out power distribution, this will seriously affect the speed and communication quality of information transfer, cause transmission rate to substantially reduce.
The content of the invention
It is an object of the invention to provide a kind of method for lifting interference alignment network transmission speed, to solve without reasonable Ground to carry out power distribution between each data flow and caused by the speed of information transfer substantially reduce the problem of.
To achieve the above object, the solution of the present invention includes a kind of method for lifting interference alignment network transmission speed, first First calculate the pre-coding matrix and decoding matrix of interference alignment network;This method is further comprising the steps of:
1) distribution, is optimized K user total transmission power of interference alignment network;
2) distribution, is optimized again data flow the transmission power of each user after distribution.
The optimization formula that distribution is optimized described in step 1) is:
Wherein, P[k]It is the transmission power of k-th of user, PsumIt is the total transmission power of K user, d[k]It is k-th of user Send the number of data flow, σ2It is interchannel noise,It is between k-th of user transmitting terminal and receiving terminal Efficient channel.
The optimization formula for being optimized distribution in step 2) again is:
Wherein, siIt is the distribution power in k-th of user, i-th of data flow, x+It is defined as It is matrix D[k]Diagonal entry, D[k]It is pairCarry out singular value decomposition to obtain, i.e.,And μ Meet
The present invention passes through on the basis of distribution is optimized between user in total transmission power and to each after distribution Optimized distribution between the data flow of user again, the transmission power of all data flows of each user is obtained optimization point Match somebody with somebody, transmission rate is optimized using this method.
This method can effectively solve to disturb more data in alignment network under actual environment with relatively low computation complexity Power distribution problems between stream, the speed of information transfer is lifted, be more suitable for actual communication networks, it is real to solve interference alignment techniques Realistic problem present in the application of border.
Brief description of the drawings
Fig. 1 is simple structure block diagram of the present invention;
Fig. 2 is the total throughout of network with the tendency chart of the change of transmitting signal to noise ratio.
Embodiment
The present invention will be further described in detail below in conjunction with the accompanying drawings.
It is a kind of lifted interference alignment network transmission speed method, first calculate interference alignment network pre-coding matrix and Decoding matrix;This method is further comprising the steps of:1), total transmission power of interference alignment network is carried out K user Optimization distribution;2) distribution, is optimized again data flow the transmission power of each user after distribution.
Based on above technical scheme, with reference to accompanying drawing, provide with next embodiment.
The present invention provides a kind of method for lifting interference alignment network transmission speed, and power point is carried out by all users Match somebody with somebody, then carrying out power distribution each user's multiple data stream, the transmission power of all data flows is optimized, effectively Improve the transmission rate of interference alignment network.
As shown in figure 1, this method calculates interference alignment network and encoder matrix and decoding matrix first, then to total hair Penetrate power and distribution is optimized between K user, finally the transmission power of each user is carried out again each data flow excellent Change distribution.
Due to having there is many methods to calculate for calculating the solution of interference alignment pre-coding matrix and decoding matrix in Fig. 1, Therefore mainly the transmission power distribution user and the transmission power reallocation between data flow are described here.
After obtaining interference alignment pre-coding matrix and decoding matrix, optimization mesh is up to the total throughout of whole network Mark, do not consider the power distribution between each data flow of each user first, the general power of each user transmitting is optimized.Cause This, it is assumed that the interference in network is completely eliminated, shown in optimization aim such as formula (1).
In formula (1), P[k]It is the transmission power of k-th of user, PsumIt is the limitation of the total transmission power of each user, d[k]It is the number that k-th user sends data flow, σ2It is interchannel noise,It is k-th of user's transmitting Efficient channel between end and receiving terminal.
The power point between each data flow is not considered due to the power distribution optimization between the user based on formula (1) Match somebody with somebody, therefore problem solving is simple, many optimized algorithms can be used and solved.Here low complex degree better performances can be used Interior point method formula (1) is solved.
After power distribution solves each user, it is assumed that the transmission power that k-th of user is assigned to is It can incite somebody to actionIn the d of k-th of user[k]Reallocated between individual data flow further to optimize.It is effective due to k-th user ChannelIt is a d[k]×d[k]Matrix, therefore ideal disturb alignment network in, can be by kth Individual user regards transmitting terminal d as[k]Root antenna, receiving terminal d[k]Channel between root antenna, transmitting and receiving terminal isD[k] ×d[k]MIMO single user communication systems.Because each channel with known whole network per family is believed in aliging network in interference Breath, therefore to the d in k-th of user[k]Also can regards d as to power distribution between individual data flow[k]×d[k]Mimo system in To transmitting terminal d[k]Transmission power on root equivalent aerial is allocated.Here using water flood to k-th in interference alignment network User d[k]Transmission power between individual data flow is allocated.
The optimal transmission power matrix of each data flow can be expressed as diagonal matrix S[k], Wherein each element siIt is the power of the distribution in i-th of data flow, according to water flood, as shown in formula (2).
Wherein D[k]It is to channelCarry out singular value decomposition to obtain, be speciallyx+It is defined as Max (x, 0),It is matrix D[k]Diagonal entry, and μ meet
After distribution, the transmission rate of k-th of user solves according to formula (3),
Wherein, matrix
By the solution of above-mentioned several calculation formula, the power reallocation between the data flow of each user is finally drawn, with Relatively low complexity completes the power distribution of multiple data stream in interference alignment network.The transmitting work(of each data flow of each user Rate is optimized, and then lifts the speed of information transfer, and this method is more suitable for actual communication networks, solves interference alignment skill Realistic problem present in art practical application.
Embodiment
In one interference alignment cordless communication network comprising K=3 user, the transmitting terminal and receiving terminal point of each user With 4 antennas are equipped with, limited according to the feasibility condition of interference alignment, each household allows the number of the data flow of transmission to be 2.Using Distributed iterative algorithm solves the precoding of each user and decoding matrix;For the power distribution between each user, using interior Point method solves;For the power distribution between each data, solved using the water flood shown in formula (2) and formula (3).According to The present invention transmission power of each each data flow of user in network of being alignd to interference carries out optimum allocation, the total throughout of network with Launch the variation tendency of signal to noise ratio as shown in Figure 2 and Table 1.In Fig. 2, transverse axis is transmitting signal to noise ratio, and the longitudinal axis is aggregate network throughput, Curve 1 represents the total throughout of the network after user and data flow distribution, and the network after curve 2 distributes between user is always handled up Amount, curve 3 distribute for data flow between after network total throughout, curve 4 for inactivity distribute after network total throughout.
Table 1
It was found from from Fig. 2 and table 1, the present invention can realize each user and data under relatively low computation complexity Optimal power allocation between stream, improve the rate of information throughput of interference alignment network.
Specific embodiment is presented above, but the present invention is not limited to described embodiment.The base of the present invention This thinking is above-mentioned basic scheme, for those of ordinary skill in the art, according to the teachings of the present invention, designs various changes The model of shape, formula, parameter simultaneously need not spend creative work.It is right without departing from the principles and spirit of the present invention The change, modification, replacement and modification that embodiment is carried out are still fallen within protection scope of the present invention.

Claims (1)

1. a kind of method for lifting interference alignment network transmission speed, the pre-coding matrix for calculating interference alignment network first is conciliate Code matrix;Characterized in that, methods described is further comprising the steps of:
1) distribution, is optimized K user total transmission power of interference alignment network;
2) distribution, is optimized again data flow the transmission power of each user after distribution;
The optimization formula that distribution is optimized described in the step 1) is:
<mrow> <mtable> <mtr> <mtd> <munder> <mi>max</mi> <mrow> <msup> <mi>P</mi> <mrow> <mo>&amp;lsqb;</mo> <mn>1</mn> <mo>&amp;rsqb;</mo> </mrow> </msup> <mo>,</mo> <msup> <mi>P</mi> <mrow> <mo>&amp;lsqb;</mo> <mn>2</mn> <mo>&amp;rsqb;</mo> </mrow> </msup> <mo>,</mo> <mn>...</mn> <mo>,</mo> <msup> <mi>P</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>K</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> </mrow> </munder> </mtd> <mtd> <mrow> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msub> <mi>log</mi> <mn>2</mn> </msub> <mo>|</mo> <msub> <mi>I</mi> <msup> <mi>d</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> </msub> <mo>+</mo> <mfrac> <msup> <mi>P</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> <mrow> <msup> <mi>d</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> <msup> <mi>&amp;sigma;</mi> <mn>2</mn> </msup> </mrow> </mfrac> <msup> <mover> <mi>H</mi> <mo>&amp;OverBar;</mo> </mover> <mrow> <mo>&amp;lsqb;</mo> <mrow> <mi>k</mi> <mi>k</mi> </mrow> <mo>&amp;rsqb;</mo> </mrow> </msup> <msup> <mover> <mi>H</mi> <mo>&amp;OverBar;</mo> </mover> <mrow> <mrow> <mo>&amp;lsqb;</mo> <mrow> <mi>k</mi> <mi>k</mi> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mo>*</mo> </mrow> </msup> <mo>|</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> </mrow> </mtd> <mtd> <mrow> <msup> <mi>P</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> <mo>&amp;GreaterEqual;</mo> <mn>0</mn> <mo>,</mo> <mo>&amp;ForAll;</mo> <mi>k</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>K</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow></mrow> </mtd> <mtd> <mrow> <munderover> <mi>&amp;Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msup> <mi>P</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> <mo>=</mo> <msup> <mi>P</mi> <mrow> <mi>s</mi> <mi>u</mi> <mi>m</mi> </mrow> </msup> </mrow> </mtd> </mtr> </mtable> <mo>,</mo> </mrow>
Wherein, P[k]It is the transmission power of k-th of user, PsumIt is the total transmission power of K user, d[k]It is that k-th of user sends The number of data flow, σ2It is interchannel noise,It is having between k-th of user transmitting terminal and receiving terminal Imitate channel;
The optimization formula for being optimized distribution described in the step 2) again is:
<mrow> <msub> <mi>s</mi> <mi>i</mi> </msub> <mo>=</mo> <msup> <mrow> <mo>(</mo> <mi>&amp;mu;</mi> <mo>-</mo> <mfrac> <msup> <mi>&amp;sigma;</mi> <mn>2</mn> </msup> <mrow> <msubsup> <mi>P</mi> <mrow> <mi>o</mi> <mi>p</mi> <mi>t</mi> </mrow> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msubsup> <msup> <mrow> <mo>(</mo> <msubsup> <mi>&amp;delta;</mi> <mi>i</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </mfrac> <mo>)</mo> </mrow> <mo>+</mo> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mo>...</mo> <mo>,</mo> <msup> <mi>d</mi> <mrow> <mo>&amp;lsqb;</mo> <mi>k</mi> <mo>&amp;rsqb;</mo> </mrow> </msup> <mo>,</mo> </mrow>
Wherein, siIt is the distribution power in k-th of user, i-th of data flow, x+Max (x, 0) is defined as,It is square Battle array D[k]Diagonal entry, D[k]It is pairCarry out singular value decomposition to obtain, i.e.,And μ meets
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CN108683442B (en) * 2018-05-16 2020-12-11 大连理工大学 Energy efficiency optimization method of unmanned aerial vehicle communication system based on interference alignment

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CN103166685A (en) * 2013-02-04 2013-06-19 重庆邮电大学 Interference aligning method based on combined power distribution in LTE

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