CN104617997A - Method for optimizing base station side antenna port position of multi-cell distributed MIMO system - Google Patents
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Abstract
The invention discloses a method for optimizing the base station side antenna port position of a multi-cell distributed MIMO system. The method comprises the steps of (1) setting the basic conditions of the multi-cell distributed MIMO system and constructing a multi-cell distributed MIMO system compound channel model, thereby obtaining the cell structure of the system and a system signal model, (2) performing mathematical analysis on the outage probability in the multi-cell distributed MIMO system to obtain the system outage probability and the system mean outage probability both related to the cell radius and the antenna position, and (3) calculating the minimum value of the system mean outage probability by use of an iterative search algorithm, and obtaining system antenna position corresponding to the minimum value of the system mean outage probability as the optimal position of the antenna port of the multi-cell distributed MIMO system. According to the method, the outage probability performance of the multi-cell distributed MIMO system is improved and the optimal coverage of the port antenna is realized, and consequently, energy saving and environmental protection of the distributed antenna system are realized and the cost expenditure of network layout is reduced.
Description
Technical Field
The invention relates to a method for optimizing the position of a base station side antenna port of a multi-cell distributed MIMO system based on the optimization target of the system interrupt probability, which is used for realizing upper network planning and position optimization design of the base station side antenna port of the distributed MIMO system in a multi-cell environment and belongs to the field of modern wireless communication.
Background
With the recent proposal and strong advocated introduction of low-energy green mobile communication technology, distributed MIMO systems are gradually drawing wide attention of domestic and foreign scholars. The distributed MIMO system can greatly reduce the transmitting power of the system, improve the communication stability, improve the system capacity and the like due to the fact that the average access distance between the mobile station and the access antenna port in the cell is shortened; these prominent numerous advantages make it one of the hot candidates for fifth generation mobile communication systems compared to conventional centralized MIMO systems.
In a distributed MIMO system, a frequency reuse technology is generally adopted by a plurality of adjacent cells to improve the spectrum efficiency of the system, and obviously, the co-channel interference among the cells is very serious due to the network spectrum planning, so that the multi-cell environment needs to be considered in the process of optimizing the antenna position, and the influence of the co-channel interference is introduced.
Currently, research on antenna position optimization of a distributed MIMO system has been extended from a linear single cell to a planar single cell, and further to a complex environment where interference of neighboring cells is considered by multiple cells. For the problem of optimal antenna port position distribution in a multi-cell distributed MIMO system, in the existing research, the optimal position of an antenna port is designed mainly based on the average capacity of the system so as to improve the system performance; however, the interruption probability has very important practical value and research significance as another important index reflecting the user session access performance, but due to the complexity of the theoretical research of the interruption probability, the current research mainly focuses on the theoretical analysis aspect of the interruption probability.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for optimizing the position of an antenna port at the base station side of a multi-cell distributed MIMO system, which can realize the optimal coverage of the port antenna by theoretically optimizing the antenna arrangement position in a multi-cell environment, and is beneficial to realizing the energy conservation and environmental protection of the distributed antenna system and reducing the cost of network arrangement.
In order to achieve the purpose, the invention is realized by the following technical scheme:
the invention discloses a method for optimizing the position of an antenna port at the base station side of a multi-cell distributed MIMO system, which comprises the following steps:
(1) setting basic conditions of the multi-cell distributed MIMO system, establishing (by using a known mathematical approximation means) a multi-cell distributed MIMO system composite channel model, obtaining a cell structure of the multi-cell distributed MIMO system (a honeycomb structure formed by a plurality of cells is taken as a research object), and obtaining an analysis model of a system receiving signals under the influence of composite fading;
(2) performing mathematical analysis on the interruption probability in the multi-cell distributed MIMO system to obtain the system interruption probability and the system average interruption probability related to the cell radius and the antenna position;
(3) and calculating the minimum value of the average interruption probability of the system according to an iterative search algorithm, wherein the system antenna position corresponding to the minimum value of the average interruption probability of the system is the optimal position of the antenna port of the multi-cell distributed MIMO system.
In step (1), the basic condition setting method of the multi-cell distributed MIMO system is as follows:
and 7 distributed antenna ports are arranged in the cell with the radius of R, one distributed antenna port is fixed at the center of the cell No. 0, and the other 6 distributed antenna ports are uniformly distributed on the circumference with the distance of R from the center of the cell No. 0.
In step (1), the antenna of the mobile user in cell 0 receives the signal from the jth distributed antenna port in the cell, which may be represented as:
wherein, the first item is a signal to be detected, the second item is a same frequency interference signal of an adjacent cell, z represents additive complex Gaussian noise received by an antenna of a mobile station, and xiRepresenting the energy normalized signal, x, from cell i0Representing the energy normalized signal from cell 0, antenna sideThe communication power of the port is E. gi,jRepresenting antenna ports APi,jSmall scale fading, S, with the mobile station antennai,jRepresenting antenna ports APi,jThe large scale fading between the mobile station and the antenna is processed approximately after logarithm to obtain the average value of mui,jStandard deviation of σi,j。Si,jObeying a lognormal distribution, with its probability density function obeying <math>
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</math> Wherein,andmean and standard deviation of the logarithm, ξ 10/ln10, respectively, standard deviation in the macrocellThe value range is 5-12 dB, in a micro rangeThe cellular area is 4-13 dB, and the receiving signal-to-noise ratio gamma is expected to obtain
μi,jThe following expression is given:
μi,j＝10lg(d0/di,j)βdi,j＞d0
wherein d is0For reference distance, β is the path loss exponent, di,jRepresenting antenna ports APi,jThe distance from the mobile station antenna, in polar coordinates, can be expressed as:
in the above equation, the polar coordinate position of the mobile station is expressed as (ρ, θ), and the antenna port AP is expressed asi,jIs noted as (ρ)i,j,θi,j)。
In the step (2), the method for performing mathematical analysis on the outage probability in the multi-cell distributed MIMO system is as follows:
firstly, the output signal-to-interference-and-noise ratio of the multi-cell distributed MIMO system is analyzed: when 6 peripheral distributed transmitting antennas in the 0 cell are uniformly distributed on a circle with r as the radius, and interference and noise of adjacent cells are modeled as Gaussian noise according to the central limit theorem, the cumulative distribution function of the signal-to-interference-and-noise ratio gamma is obtained as follows:
where erfc is a complementary error function, where γ isjRepresents that the mobile station in the research cell receives the signal-to-interference-and-noise ratio with j of the antenna port of the cell, gamma is the signal-to-interference-and-noise ratio finally output by the multi-cell distributed MIMO, and muj(r, ρ, θ) and σjRespectively representing 10lg gamma when the peripheral 6 distributed transmitting antennas are distributed on a circle with r as a radius in the research celljAnd both in dB, by approximating muj(r, ρ, θ) is an expression for r and the mobile station position (ρ, θ), μj(r, ρ, θ) may be represented by μi,jWhere i is calculated as 0, for convenience of description, the subscript 0 is omitted and μ isj(r, ρ, θ); mean value mu when antenna port position changes in a particular multi-cell environmentj(r, ρ, θ) will change accordingly, while the standard deviation σjThen no change occurs, X represents the distribution function of the signal to interference plus noise ratio gamma;
then, the cumulative distribution function of the mobile station receiving signal-to-interference-and-noise ratio gamma in the multi-cell distributed MIMO system can be represented by the formula, the interruption probability of the multi-cell distributed MIMO system can be further obtained, and the interruption probability is that when the signal-to-interference-and-noise ratio gamma is lower than a certain determined signal-to-interference-and-noise ratio threshold value gammathThe probability of interruption of the multi-cell distributed MIMO system is expressed as:
in the step (2), the method for calculating the average outage probability of the multi-cell distributed MIMO system is as follows:
and (3) recording the distribution function of the mobile stations in the cell as f (rho, theta), so that the average outage probability of the multi-cell distributed MIMO system is as follows:
where (ρ, θ) represents the coordinates of the mobile station in the cell in polar coordinates, R is the cell radius, and E is the radius of the cell when the 6 distributed transmission antennas at the periphery in cell No. 0 are uniformly distributed on a circle with R as the radiusρ,θ[°]Representing a mathematically expected operation on the variables p and theta.
In the step (3), the method for calculating the minimum value of the average outage probability of the system according to the iterative search algorithm to obtain the optimal position of the antenna port of the multi-cell distributed MIMO system comprises the following steps:
a, initializing multi-cell parameters, including determining the radius of a cell and a composite fading channel model, wherein the composite fading channel model respectively comprises a large-scale fading model containing path loss and shadow fading and a small-scale fading model containing Nakagami distribution; let 0 number intra-cell antenna port AP0,j(j 1,2,3.. said., 6) are uniformly distributed on a circumference with a radius r; at a set iterationUnder the condition that the step length is s, obtaining that the set of the corresponding antenna distribution circumferences is omega-R when different R is taken in the cell 0 with the radius of R1,r2,r3,.....,rN}，rm(m 1,2,3.. times.n) indicates that when the peripheral 6 distributed transmitting antennas are uniformly distributed at rmIs on the circumference of a radius;
b setting average interruption probability initial value of cellSetting an initial value m of the iteration number to be 1;
c, when the iteration times m are less than N, N is a set maximum iteration time threshold value and accords with the loop condition, executing the following loop body all the time;
the content of the D cycle body is as follows: according to μi,j＝10lg(d0/di,j)βAndcalculating the radius r in the cell 0mOn the circumference of (a), the path loss μ of the jth (j ═ 1, 2.. said.6) distributed transmitting antennaj(r,ρ,θ)，μj(r, ρ, θ) may be represented by μi,jCalculating to obtain the value of i by taking 0; secondly, according to the average interruption probability formulaCalculating the pointAnd further performing operations in a computer simulation programThe interrupt probability of the system is corrected, then incremental operation m is carried out on the iteration number pointer to be m +1, then the step C is returned, when the maximum value of the iteration number is reached, the calculation of the average interrupt probability of the system is stopped, and the average interrupt probability of the corresponding position is obtained;
e doesDetermining the optimal antenna position: comparisonTaking the minimum average interrupt probability valueThe antenna position of r corresponding to the minimum average outage probability value is the optimal position of the antenna port of the multi-cell distributed MIMO system.
The antenna port position optimization method based on the multi-cell distributed MIMO system interrupt probability is suitable for various modulation systems; the antenna port position optimization method based on the system interruption probability as the analysis object adopts the iterative search algorithm to solve the optimal antenna position according to the system average interruption probability function derived by theory as the criterion and the optimization target, improves the interruption probability performance of the multi-cell distributed MIMO system, realizes the optimal coverage of the port antenna, and is beneficial to realizing the energy conservation and environmental protection of the distributed antenna system and reducing the cost overhead of network distribution.
Drawings
FIG. 1 is a schematic diagram of a circular single-cell distributed MIMO system;
FIG. 2 is a schematic diagram of a distributed MIMO system in a multi-cell environment;
fig. 3 is a schematic diagram illustrating an analysis of the radius of the optimal antenna location distribution in the central cell 0;
fig. 4 is a flowchart of the method for optimizing the position of the antenna port at the base station side of the multi-cell distributed MIMO system according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
A specific embodiment of the present invention comprises the steps of: establishing a composite channel model of a multi-cell distributed MIMO system; calculating the average interruption probability of the system under the multi-cell environment; setting a maximum threshold of iteration times by using an iteration search algorithm and taking the average interruption probability as an optimization target, obtaining the average interruption probability corresponding to each antenna position of the system when the maximum iteration times is reached, and terminating the calculation; further, for different antenna positions of the system, corresponding system average interruption probabilities are obtained, and finally, the interruption probability values are compared and analyzed, and the system antenna position corresponding to the minimum value of the system average interruption probability is taken, so that the system antenna position is the optimal position of the multi-cell distributed MIMO system antenna. The invention can realize the optimal coverage of the base station side antenna by theoretically optimizing the antenna position of the multi-cell distributed MIMO system, and is beneficial to realizing the energy conservation and environmental protection of the distributed antenna system and reducing the cost overhead of network deployment.
Referring to fig. 1, a schematic diagram of a single circular cell distributed MIMO system is shown. In a cellular circular cell with a side length of R, a plurality of transmitting antennas are distributed at different geographical positions in the cell, and the specific distribution is as follows: taking a cell 0 at the center as an example, 7 distributed antenna ports are arranged in a cell with the side length of R; one antenna port is fixed at the center of the No. 0 cell, and the other 6 distributed transmitting antennas are uniformly distributed on the circumference of which the distance from the center of the cell is r. Adjacent cells 1-6 are honeycomb-shaped and surround cell number 0, and have the same number of cell antenna ports and similar arrangement of circumference plus center point antennas, except that the distance between adjacent antenna ports inside the adjacent cells is temporarily set to be a fixed value in the process of analyzing the outage probability and is related to the radius of the cells. The central base station and the peripheral 6 distributed antennas of each cell are set to transmit signals according to requirements; the mobile station MS is provided with only one receiving antenna and the location within the cell is subject to a uniform distribution.
Considering a regular multi-cell distributed MIMO system with a cellular structure, the system structure diagram is shown in fig. 2 of the specification, and 7 cells are present, so that0 to 6 are numbered and there are 7 distributed antenna ports in each cell. By AP0,0Polar coordinates are established for the origin, and the mobile station MS coordinates (p, θ) are located in the central cell, cell 0, as shown in fig. 2.
Referring to fig. 4, the method for optimizing the position of the antenna port at the base station side of the multi-cell distributed MIMO system according to the present invention is as follows:
(1) setting basic conditions of the multi-cell distributed MIMO system, establishing a composite channel model of the multi-cell distributed MIMO system by means of mathematical approximation, obtaining a cell structure of the multi-cell distributed MIMO system, taking a honeycomb structure formed by seven cells as a research object, and obtaining an analysis model of a received signal of the system under the influence of composite fading;
(2) performing mathematical analysis on the interruption probability in the multi-cell distributed MIMO system to obtain the system interruption probability and the system average interruption probability related to the cell radius and the antenna position;
(3) and calculating the minimum value of the average interruption probability of the system according to an iterative search algorithm, wherein the system antenna position corresponding to the minimum value of the average interruption probability of the system is the optimal position of the antenna port of the multi-cell distributed MIMO system.
Performing composite channel modeling in a multi-cell interference environment, where an antenna of a mobile user in cell 0 receives a signal from a jth antenna port in the cell, may be represented as:
wherein, the first item is a signal to be detected, the second item is a same frequency interference signal of an adjacent cell, z represents additive complex Gaussian noise received by an antenna of a mobile station, and xiRepresenting the energy normalized signal, x, from cell i0Representing the energy normalized signal from cell 0, the communication power at the antenna port is E. gi,jRepresenting antenna ports APi,jSmall scale fading, S, with the mobile station antennai,jRepresenting antenna ports APi,jThe large scale fading between the mobile station and the antenna is processed approximately after logarithm to obtain the average value of mui,jStandard deviation of σi,j。Si,jObeying a lognormal distribution, with its probability density function obeying <math>
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</math> Wherein,andmean and standard deviation of the logarithm, ξ 10/ln10, respectively, standard deviation in the macrocellThe value range is 5-12 dB, the value range is 4-13 dB in a microcell, the receiving noise ratio gamma is expected, and the receiving noise ratio gamma can be obtained
μi,j＝10lg(d0/di,j)βdi,j＞d0
Wherein d is0For reference distance, β is the path loss exponent, di,jRepresenting antenna ports APi,jThe distance from the mobile station, in polar coordinates, can be expressed as:
in the above equation, the polar coordinate position of the mobile station is expressed as (ρ, θ), and the antenna port AP is expressed asi,jIs noted as (ρ)i,j,θi,j). Since the antennas in the cell 0 except the central port are uniformly distributed on the circumference with the radius r, it is obvious that the coordinates of the antenna ports in the cell will change correspondingly when the values of r are different.
When the cell 0 is taken as a research object, and the system average interrupt probability expression in the cell 0 is derived under the condition that the signals transmitted by the adjacent cells 1-6 are regarded as background Gaussian noise, as described in the following formula, the mu in the average interrupt probability expression0，j(r, ρ, θ) will be related to the radius of the circumference r, μ, where the antenna port is locatedj(r, ρ, θ) may be represented by μi,jWhere i is calculated as 0, for convenience of description, the subscript 0 is omitted and μ isj(r, ρ, θ). Mean value mu when antenna port position changes in a particular multi-cell environmentj(r, ρ, θ) will change accordingly, while the standard deviation σjNo change occurs.
Performing mathematical analysis on the outage probability in the multi-cell distributed MIMO system, firstly analyzing the output signal-to-interference-and-noise ratio of the multi-cell system, and calculating and deducing, wherein when 6 distributed transmitting antennas in the cell 0 are uniformly distributed on a circle with r as a radius and according to a central limit theorem, the interference and noise of adjacent cells can be regarded as Gaussian noise, an accumulated distribution function of the signal-to-interference-and-noise ratio gamma is obtained as follows:
then, the multi-cell distributed MIM can be characterized by the above formulaThe cumulative distribution function of the signal-to-interference-and-noise ratio gamma of the mobile station receiving signals in the O system can further obtain the interruption probability of the multi-cell distributed MIMO system, wherein the interruption probability is that when the signal-to-interference-and-noise ratio gamma is lower than a certain determined signal-to-interference-and-noise ratio threshold value gammathThe probability of (c). The interruption probability expression of the multi-cell distributed MIMO system is as follows:
the system average outage probability, i.e. the influence of the integrated mobile station cell coordinates, is then calculated in a multi-cell environment. Therefore, if the distribution function of the mobile stations in the cell is denoted as f (ρ, θ), the average outage probability of the multi-cell distributed MIMO system is denoted as:
according to the iterative search method, a set of circumferences corresponding to different R in a cell with a radius R is set to be [ omega ] { R ]1,r2,r3,.....,rNAnd set the iterative search step size tos, wherein rm(m 1,2,3.. times.n) indicates when the peripheral 6 distributed transmitting antennas are uniformly distributed at rmIs a circle of a radius, as shown in the description and attached to fig. 3. The threshold of the iteration times is N, and the flow of calculating the average interrupt probability of the system by using the iterative algorithm is as follows:
and when the maximum value of the iteration times is reached, terminating the calculation of the average interruption probability of the system, obtaining the average interruption probability of the corresponding position, carrying out comparative analysis, selecting the minimum average interruption probability value, and obtaining the minimum average interruption probability value, wherein the position of r corresponding to the minimum average interruption probability value is the optimal distribution position of the multi-cell distributed MIMO system antenna.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. The method for optimizing the position of the antenna port at the base station side of the multi-cell distributed MIMO system is characterized by comprising the following steps:
(1) setting basic conditions of the multi-cell distributed MIMO system, establishing a composite channel model of the multi-cell distributed MIMO system, obtaining a cell structure of the multi-cell distributed MIMO system, and obtaining an analysis model of a system receiving signals under the influence of composite fading;
(2) performing mathematical analysis on the interruption probability in the multi-cell distributed MIMO system to obtain the system interruption probability and the system average interruption probability related to the cell radius and the antenna position;
(3) and calculating the minimum value of the average interruption probability of the system according to an iterative search algorithm, wherein the system antenna position corresponding to the minimum value of the average interruption probability of the system is the optimal position of the antenna port of the multi-cell distributed MIMO system.
2. The method of claim 1, wherein the base station side antenna port position of the multi-cell distributed MIMO system is optimized,
in step (1), the basic condition setting method of the multi-cell distributed MIMO system is as follows:
and 7 distributed antenna ports are arranged in the cell with the radius of R, one distributed antenna port is fixed at the center of the cell No. 0, and the other 6 distributed antenna ports are uniformly distributed on the circumference with the distance of R from the center of the cell No. 0.
3. The method for optimizing the position of antenna ports on the base station side in the multi-cell distributed MIMO system according to claim 2,
in step (1), the antenna of the mobile user in cell 0 receives the signal from the jth distributed antenna port in the cell, which may be represented as:
wherein, the first item is a signal to be detected, the second item is a same frequency interference signal of an adjacent cell, z represents additive complex Gaussian noise received by an antenna of a mobile station, and xiRepresenting the energy normalized signal, x, from cell i0Representing the energy normalized signal from cell 0, E is the communication power at the antenna port, gi,jRepresenting antenna ports APi,jSmall scale fading, S, with the mobile station antennai,jRepresenting antenna ports APi,jThe large scale fading between the mobile station and the antenna is processed approximately after logarithm to obtain the average value of mui,jStandard deviation of σi,j；Si,jObeying a lognormal distribution, with its probability density function obeying <math>
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<mo>^</mo>
</mover>
<mi>x</mi>
</mrow>
</mfrac>
<mi>exp</mi>
<mo>[</mo>
<mo>-</mo>
<mfrac>
<msup>
<mrow>
<mo>(</mo>
<mn>10</mn>
<mi>lgx</mi>
<mo>-</mo>
<mover>
<mi>μ</mi>
<mo>^</mo>
</mover>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mrow>
<mn>2</mn>
<msup>
<mover>
<mi>σ</mi>
<mo>^</mo>
</mover>
<mn>2</mn>
</msup>
</mrow>
</mfrac>
<mo>]</mo>
<mo>,</mo>
<mi>x</mi>
<mo>≥</mo>
<mn>0</mn>
<mo>,</mo>
</mrow>
</math> Wherein,andmean and standard deviation of the logarithm, ξ ═ 10/ln10, respectively;
μi,jthe following expression is given:
μi,j＝10lg(d0/di,j)βdi,j＞d0
wherein d is0For reference distance, β is the path loss exponent, di,jRepresenting antenna ports APi,jThe distance from the mobile station antenna, in polar coordinates, can be expressed as:
in the above equation, the polar coordinate position of the mobile station is expressed as (ρ, θ), and the antenna port AP is expressed asi,jIs noted as (ρ)i,j,θi,j)。
4. The method of claim 3, wherein the base station side antenna port position of the multi-cell distributed MIMO system is optimized,
in the step (2), the method for performing mathematical analysis on the outage probability in the multi-cell distributed MIMO system is as follows:
firstly, the output signal-to-interference-and-noise ratio of the multi-cell distributed MIMO system is analyzed: when 6 peripheral distributed transmitting antennas in the 0 cell are uniformly distributed on a circle with r as the radius, and interference and noise of adjacent cells are modeled as Gaussian noise according to the central limit theorem, the cumulative distribution function of the signal-to-interference-and-noise ratio gamma is obtained as follows:
where erfc is a complementary error function, where γ isjRepresents that the mobile station in the research cell receives the signal-to-interference-and-noise ratio with j of the antenna port of the cell, gamma is the signal-to-interference-and-noise ratio finally output by the multi-cell distributed MIMO, and muj(r, ρ, θ) and σjRespectively representing 10lg gamma when the peripheral 6 distributed transmitting antennas are distributed on a circle with r as a radius in the research celljAnd both in dB, by approximating muj(r, ρ, θ) is an expression for r and the mobile station position (ρ, θ), μj(r, ρ, θ) may be represented by μi,jWhere i is calculated as 0, for convenience of description, the subscript 0 is omitted and μ isj(r, ρ, θ); mean value mu when antenna port position changes in a particular multi-cell environmentj(r, ρ, θ) will change accordingly, while the standard deviation σjThen no change occurs, X represents the distribution function of the signal to interference plus noise ratio gamma;
then, the cumulative distribution function of the mobile station receiving signal-to-interference-and-noise ratio gamma in the multi-cell distributed MIMO system can be represented by the formula, the interruption probability of the multi-cell distributed MIMO system can be further obtained, and the interruption probability is that when the signal-to-interference-and-noise ratio gamma is lower than a certain determined signal-to-interference-and-noise ratio threshold value gammathThe probability of interruption of the multi-cell distributed MIMO system is expressed as:
5. the method for optimizing the position of antenna ports at the base station side in the multi-cell distributed MIMO system according to claim 4,
in the step (2), the method for calculating the average outage probability of the multi-cell distributed MIMO system is as follows:
and (3) recording the distribution function of the mobile stations in the cell as f (rho, theta), so that the average outage probability of the multi-cell distributed MIMO system is as follows:
where (ρ, θ) represents the coordinates of the mobile station in the cell in polar coordinates, R is the cell radius, and E is the radius of the cell when the 6 distributed transmission antennas at the periphery in cell No. 0 are uniformly distributed on a circle with R as the radiusρ,θ[о]Representing a mathematically expected operation on the variables p and theta.
6. The method of claim 5, wherein the antenna port position optimization method at the base station side of the multi-cell distributed MIMO system,
in the step (3), the method for calculating the minimum value of the average outage probability of the system according to the iterative search algorithm to obtain the optimal position of the antenna port of the multi-cell distributed MIMO system comprises the following steps:
a, initializing multi-cell parameters, including determining the radius of a cell and a composite fading channel model, wherein the composite fading channel model respectively comprises a large-scale fading model containing path loss and shadow fading and a small-scale fading model containing Nakagami distribution; let 0 number intra-cell antenna port AP0,j(j 1,2,3.. said., 6) are uniformly distributed on a circumference with a radius r; under the condition that the iteration step length is set to be s, the set of the corresponding antenna distribution circumferences is obtained when different R are taken in a cell 0 with the radius of R, wherein the set of the corresponding antenna distribution circumferences is omega ═ R1,r2,r3,.....,rN}，rm(m 1,2,3.. times.n) indicates that when the peripheral 6 distributed transmitting antennas are uniformly distributed at rmIs on the circumference of a radius;
b setting average interruption probability initial value of cellSetting an initial value m of the iteration number to be 1;
c, when the iteration times m are less than N, N is a set maximum iteration time threshold value and accords with the loop condition, executing the following loop body all the time;
the content of the D cycle body is as follows: according to μi,j＝10lg(d0/di,j)βAnd <math>
<mrow>
<msub>
<mi>d</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>=</mo>
<msqrt>
<msup>
<mi>ρ</mi>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>ρ</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>-</mo>
<msub>
<mrow>
<mn>2</mn>
<mi>ρρ</mi>
</mrow>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mi>cos</mi>
<mrow>
<mo>(</mo>
<mi>θ</mi>
<mo>-</mo>
<msub>
<mi>ρ</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
</msqrt>
</mrow>
</math> calculating the radius r in the cell 0mOn the circumference of (a), the path loss μ of the jth (j ═ 1, 2.. said.6) distributed transmitting antennaj(r,ρ,θ)，μj(r, ρ, θ) may be represented by μi,jCalculating to obtain the value of i by taking 0; secondly, according to the average interruption probability formulaCalculating the pointAnd further performing operations in a computer simulation programThe interrupt probability of the system is corrected, then incremental operation m is carried out on the iteration number pointer to be m +1, then the step C is returned, when the maximum value of the iteration number is reached, the calculation of the average interrupt probability of the system is stopped, and the average interrupt probability of the corresponding position is obtained;
e, determining the optimal antenna position: comparisonTaking the minimum average interrupt probability valueThe antenna position of r corresponding to the minimum average outage probability value is the optimal position of the antenna port of the multi-cell distributed MIMO system.
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