CN101198132B

CN101198132B - Dynamic channel allocating method

Info

Publication number: CN101198132B
Application number: CN2006101618666A
Authority: CN
Inventors: 江海
Original assignee: ZTE Corp
Current assignee: ZTE Corp
Priority date: 2006-12-05
Filing date: 2006-12-05
Publication date: 2010-08-04
Anticipated expiration: 2026-12-05
Also published as: CN101198132A

Abstract

The invention provides a dynamic channel allocation method, comprising the following steps that: step S202. the upstream channel impulse response matrix of a user and the upstream channel impulse response matrix of the inference noise are obtained according to the estimation of the channel; step S204. the spatial related matrix of the upstream signal and the inference noise are calculated; step S206. the target user measures and reports the downstream inference noise power of each downstream time slot; step S208. the upstream inference of each upstream time slot of the target user and the downstream inference of each downstream time slot are calculated; step S210. the upstream time slot and the downstream time slot with the smallest inference are taken as the optimal allocation time slots of the target user. Therefore, the inference between the users in the cell and the users in the adjacent cell is avoided to the utmost extent.

Description

Dynamic channel allocation method

Technical Field

The invention relates to the field of communication, in particular to a dynamic channel allocation method which is used for avoiding interference between users of a local cell and users of adjacent cells in space in a time division-synchronous code division multiple access (TD-SCDMA) system.

Background

TD-SCDMA systems use joint detection and smart antennas to combat inter-user interference. Joint detection enables simultaneous detection of multiple user signals, thus eliminating interference between users. Generally, due to the limitation of the computation complexity in implementation, the joint detection algorithm is mainly used to eliminate the interference between multiple users in the same cell.

The intelligent antenna can isolate users from space, and plays a role in restraining interference in a cell and between cells. Specifically, the smart antenna can suppress interference between users having different angles of arrival (DOA) by beamforming, and contribute to both intra-cell and inter-cell user interference. However, for the interference between users in the same direction, the interference suppression effect of the smart antenna is greatly reduced.

The performance of the intelligent antenna for inhibiting the interference between users in space plays a good or bad role, and the performance of the TD-SCDMA network is directly influenced. Therefore, Dynamic Channel Allocation (DCA) is adopted to ensure that the smart antenna performs the function of suppressing interference in space to the maximum extent. The DCA is to perform optimal configuration on channel resources through a channel quality criterion and a traffic parameter in the user access and service process, so as to achieve the purposes of avoiding interference and efficiently utilizing wireless resources. The DCA is used for allocating and adjusting the resource allocation of the users, so that the interference of the users from the inside of the cell and the between the cells is minimized under the action of the intelligent antenna, and the system performance is improved.

Patent [ CN1710979A ] introduces that DCA algorithm is used in TD-SCDMA system to allocate multiple users with the same direction angle in the cell to different time slots, so as to fully utilize the space interference suppression function of smart antenna and improve the system performance. However, this patent has a disadvantage in that the direction of interfering users of the neighboring cells is not considered when allocating resources. In the TD-SCDMA system, the interference between the users in the local cell can be eliminated by joint detection, and the interference of the users in the neighboring cell has a larger impact on the performance.

Disclosure of Invention

In order to simultaneously consider the mutual interference between users in a cell and users in the cell and allocate the time slot frequency point resource with the minimum interference to the users, the invention provides a dynamic channel allocation method, which achieves the aim, thereby avoiding the interference to the maximum extent and further improving the system performance.

The invention provides a dynamic channel allocation method, which is used for avoiding the interference between users of a local cell and a neighboring cell and comprises the following steps: step S202, respectively estimating uplink channel impulse response of each user of each time slot according to channel estimation, then arranging the uplink channel impulse response into an uplink channel impulse response matrix, and arranging noise interference on each antenna into an uplink interference noise matrix; step S204, calculating an uplink signal space correlation matrix of each user according to the uplink channel impact response matrix, and calculating a space correlation matrix of uplink interference noise according to the uplink interference noise matrix; step S206, the target user measures and reports the downlink interference noise power received in each downlink time slot; step S208, calculating the uplink interference suffered by the target user in each uplink time slot and the downlink interference suffered by the target user in each downlink time slot; and step S210, selecting the time slot with the minimum interference from all the uplink time slots as the uplink time slot allocated to the target user, and selecting the time slot with the minimum interference from all the downlink time slots as the downlink time slot allocated to the target user.

According to the invention, step S208 is implemented by: and calculating the uplink interference size of the target user in each uplink time slot according to the uplink signal space correlation matrix, the uplink interference noise matrix and the interference suppression factor of the uplink joint detection technology, and calculating the downlink interference size of the target user in each downlink time slot according to the uplink signal space correlation matrix, the downlink interference noise power and the interference suppression factor of the downlink joint detection technology.

The antenna according to the invention is a smart antenna; and the smart antenna is an array antenna.

According to the invention, an objective function J for measuring the uplink interference degree of a target user in a time slot_upCan be expressed as:

<math><mrow><msub><mi>J</mi><mi>up</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>up</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mo>+</mo><msub><mi>β</mi><mi>up</mi></msub><msub><mi>R</mi><mi>N</mi></msub><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow><mo>,</mo></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀Representing the uplink channel impulse response matrix, R, of the target user_kRepresenting the spatial correlation matrix, R, of the uplink signal_NUplink spatial correlation matrix, alpha, representing interference noise_upIndicating interference between users in the local cell after joint detection techniqueResidual size, beta_upRepresenting the weights of neighbor cell interference and noise.

In addition, α according to the present invention_upIs a number, alpha, ranging between (0, 1)_upThe smaller the interference, the less interference remaining between users in the cell.

Beta according to the invention_upIs a number with a value range between (0, 1) and represents the weight of the interference and the noise of the adjacent cells when the beta value is beta_upWhen 1 is taken, the influence of 100% neighbor cell interference and noise is considered in resource allocation, and when β is_upWhen 0 is taken, the influence of any adjacent cell interference and noise is not considered in the resource allocation.

According to the invention, an objective function J for measuring the downlink interference degree of a target user in a time slot_downCan be expressed as:

<math><mrow><msub><mi>J</mi><mi>down</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>down</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mi></mi><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow><msub><mrow><mo>+</mo><mi>β</mi></mrow><mi>down</mi></msub><msubsup><mi>P</mi><mi>N</mi><mi>down</mi></msubsup><mo>,</mo></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀Representing the uplink channel impulse response matrix, R, of the target user_kRepresenting the spatial correlation matrix, R, of the uplink signal_NUplink spatial correlation matrix, alpha, representing interference noise_downRepresents the residual size, beta, of the interference between users in the cell after the joint detection technique is adopted_downWeights representing neighbor cell interference and noise。

wherein, P_k(θ) is the signal space intensity distribution, P, of each user per time slot_N(theta) is the signal spatial intensity distribution of the interference noise signal, alpha_upRepresents the residual size, beta, of the interference between users in the cell after the joint detection technique is adopted_upRepresenting the weights of neighbor cell interference and noise.

Signal spatial intensity distribution P according to the invention_k(θ) is expressed as:

where a (θ) is a direction vector corresponding to the direction angle θ.

In addition, the signal spatial intensity distribution P of the interference noise signal according to the invention_N(θ) is expressed as:

according to the present invention, for a linear array smart antenna, a (θ) can be expressed as:

where d is the array element spacing and λ is the carrier wavelength.

Therefore, the dynamic channel allocation method can allocate the time slot frequency point resource with the minimum interference to the user while considering the mutual interference between the users in the cell and the users in the cell, thereby avoiding the interference to the maximum extent and further improving the system performance.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

drawings

Fig. 1 is a schematic diagram of a linear array smart antenna according to an embodiment of the present invention;

FIG. 2 is a flow chart of a dynamic channel allocation method according to the present invention; and

fig. 3 is a block diagram of a dynamic channel allocation apparatus according to the present invention.

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.

Detailed Description

Fig. 1 is a schematic diagram of a linear array smart antenna according to an embodiment of the present invention. Fig. 2 is a flow chart of a dynamic channel allocation method according to the present invention.

As shown in fig. 1, the array element spacing between each array element of the 8-array element linear array intelligent antenna is d, and θ represents a direction angle. The specific steps of the dynamic channel allocation method shown in fig. 2 will be described in detail below with reference to fig. 1, and with reference to fig. 2, the specific steps of the dynamic channel allocation method are as follows.

Step S202, according to the channel estimation, the uplink channel impulse response of each user of each time slot is respectively estimated, then the uplink channel impulse response is arranged into an uplink channel impulse response matrix, and the noise interference on each antenna is arranged into an uplink interference noise matrix.

That is, according to the embodiment of the present invention, the base station first receives a signal of the training sequence portion:

wherein Kn is 1, 2, and Kn represents an antenna serial number of a base station; mRepresenting a training sequence matrix with dimensions 128 x 128, n_m ^knRepresenting various interferences and noises, the dimension is 128 x 1, h^knRepresenting the channel impulse responses of all users on the receive antenna kn, the dimension is 128 x 1.

Thus, a channel impulse response estimate is derived

Comprises the following steps:

then toThe channel impact response of the user in the local cell can be obtained by processingAnd channel impulse response to neighbor cell interference and noise

Channel impulse response application for different usersExpressed as follows:

wherein,

the channel impulse response of antenna kn of the kth user is represented with dimension W × 1, W is the channel estimation window length. The channel impulse response matrix H for all antennas of user k_kExpressed as:

wherein, (x)^TRepresenting the transpose of matrix x.

Thus, the channel impulse response matrix HN for all antennas interfering with noise can be expressed as:

and step S204, calculating an uplink signal space correlation matrix of each user according to the uplink channel impact response matrix, and calculating a space correlation matrix of uplink interference noise according to the uplink interference noise matrix.

That is, according to equation (4), the signal space correlation matrix Rk for user k is represented as:

R_k＝H_k·(H_k)^H (6)

wherein, (x)^HRepresenting the conjugate transpose of matrix x.

According to the formula (5), the uplink space correlation matrix R of the interference noise is formed_NExpressed as:

R_N＝H_N·(H_N)^H (7)

step S206, the target user measures and reports the downlink interference noise power (ISCP) P suffered by each downlink time slot_N ^down。

Step S208, calculating the uplink interference suffered by the target user in each uplink time slot and the downlink interference suffered by the target user in each downlink time slot. The specific implementation of step S208 is as follows:

(a) target function J for measuring uplink interference degree of target user in one time slot_upExpressed as:

<math><mrow><msub><mi>J</mi><mi>up</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>up</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mo>+</mo><msub><mi>β</mi><mi>up</mi></msub><msub><mi>R</mi><mi>N</mi></msub><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow><mo>-</mo><mo>-</mo><mo>-</mo><mrow><mo>(</mo><mn>8</mn><mo>)</mo></mrow></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀A channel impulse response matrix representing the target user. Alpha is alpha_upIs a number with a value range between (0, 1) and represents the residual interference between users in the cell after the joint detection technology is adopted, and alpha is_upThe smaller the interference is, the less the interference between users in the cell is left; at the same time, beta_upIs also a number with the value range between (0, 1) and represents the weight of the interference and the noise of the adjacent cells when the beta value is beta_upWhen 1 is taken, the influence of 100% neighbor cell interference and noise is considered in resource allocation, and when β is_upWhen 0 is taken, the influence of any adjacent cell interference and noise is not considered in the resource allocation.

Wherein, the physical meaning of the formula (8) is to calculate the sum of the interference power of each path of all users and interference noise in the time slot to the target user.

(b) Will measure the targetObjective function J of downlink interference degree of user in one time slot_downExpressed as:

<math><mrow><msub><mi>J</mi><mi>down</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>down</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mi></mi><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow><msub><mrow><mo>+</mo><mi>β</mi></mrow><mi>down</mi></msub><msubsup><mi>P</mi><mi>N</mi><mi>down</mi></msubsup><mo>-</mo><mo>-</mo><mo>-</mo><mrow><mo>(</mo><mn>9</mn><mo>)</mo></mrow></mrow></math>

considering the difference in demodulation performance between the base station and the user equipment, α_upAnd alpha_downAnd β_upAnd beta_downCan be varied.

Alternatively, the uplink interference experienced by the target user in one timeslot can be calculated in another manner, as follows:

taking a linear array intelligent antenna as an example, firstly, the signal space intensity distribution P of each user of each time slot is calculated_k(θ)：

Where a (θ) is a direction vector corresponding to the direction angle θ, and for the linear array smart antenna, a (θ) can be expressed as

Where d is the array element spacing as shown in fig. 1 and λ is the carrier wavelength.

Secondly, the signal spatial intensity distribution P of the interference noise signal_N(θ) is as follows:

then, an objective function J for measuring the uplink interference level received by the target user in a timeslot_upCan be expressed as:

target function J for measuring downlink interference degree of target user in time slot_downCan be expressed as:

step S210, selecting the time slot with the minimum interference from all uplink time slots as the uplink time slot allocated to the target user, and selecting the time slot with the minimum interference from all downlink time slots as the downlink time slot allocated to the target user.

Thus, the entire dynamic channel allocation of the present invention is completed.

Fig. 3 is a block diagram of a dynamic channel allocation apparatus 300 according to the present invention. As shown in fig. 3, the dynamic channel allocation apparatus 300 includes: a matrix arrangement module 302, configured to estimate uplink channel impulse responses of each user of each time slot according to channel estimation, arrange the uplink channel impulse responses into an uplink channel impulse response matrix, and arrange noise interference on each antenna into an uplink interference noise matrix; a matrix calculation module 304, configured to calculate an uplink signal spatial correlation matrix of each user according to the uplink channel impulse response matrix, and calculate a spatial correlation matrix of uplink interference noise according to the uplink interference noise matrix; a power measurement module 306, configured to measure and report downlink interference noise power received in each downlink timeslot; an interference calculation module 308, configured to calculate uplink interference received by the target user in each uplink time slot and downlink interference received by the target user in each downlink time slot; and a time slot selection module 310, configured to select a time slot with the minimum interference from all uplink time slots as the uplink time slot allocated to the target user, and select a time slot with the minimum interference from all downlink time slots as the downlink time slot allocated to the target user.

The interference calculation module 308 calculates the uplink interference and the downlink interference by the following method: calculating the uplink interference size searched by the target user in each uplink time slot according to the uplink signal space correlation matrix, the uplink interference noise matrix and the interference suppression factor of the uplink joint detection technology; and calculating the downlink interference size of the target user in each downlink time slot according to the uplink signal space correlation matrix, the downlink interference noise power and the interference suppression factor of the downlink joint detection technology.

According to the invention, the antenna is a smart antenna and the smart antenna is an array antenna.

In the interference calculation module 308, the objective function Jup for measuring the uplink interference level received by the target user in a timeslot may be represented as:

<math><mrow><msub><mi>J</mi><mi>up</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>up</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mo>+</mo><msub><mi>β</mi><mi>up</mi></msub><msub><mi>R</mi><mi>N</mi></msub><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀Representing the uplink channel impulse response matrix, R, of the target user_kRepresenting the spatial correlation matrix, R, of the uplink signal_NUplink spatial correlation matrix, alpha, representing interference noise_upRepresents the residual size, beta, of the interference between users in the cell after the joint detection technique is adopted_upRepresenting the weights of neighbor cell interference and noise.

Wherein alpha is_upIs a number, alpha, ranging between (0, 1)_upThe smaller the interference, the less interference remaining between users in the cell. Beta is a_upIs a number with a value range between (0, 1) and represents the weight of the interference and the noise of the adjacent cells when the beta value is beta_upWhen 1 is taken, the influence of 100% neighbor cell interference and noise is considered in resource allocation, and when β is_upWhen 0 is taken, the influence of any adjacent cell interference and noise is not considered in the resource allocation.

In addition, in the interference calculation module 308, the objective function J is used for measuring the downlink interference degree received by the target user in one timeslot_downCan be expressed as:

<math><mrow><msub><mi>J</mi><mi>down</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>down</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mi></mi><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow><msub><mrow><mo>+</mo><mi>β</mi></mrow><mi>down</mi></msub><msubsup><mi>P</mi><mi>N</mi><mi>down</mi></msubsup></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀Representing target usersOf the uplink channel impulse response matrix, R_kRepresenting the spatial correlation matrix, R, of the uplink signal_NUplink spatial correlation matrix, alpha, representing interference noise_downRepresents the residual size, beta, of the interference between users in the cell after the joint detection technique is adopted_downRepresenting the weights of neighbor cell interference and noise.

According to the invention, a is determined by the difference in demodulation performance between the base station and the user equipment_upAnd alpha_downAnd β_upAnd beta_downCan be varied.

In the interference calculation module 308, an objective function J for measuring the uplink interference level received by a target user in a timeslot_upCan be expressed as:

wherein, P_k(θ) is the signal space intensity distribution, P, of each user per time slot_N(theta) is the signal spatial intensity distribution of the interference noise signal, alpha_upRepresents the residual size, beta, of the interference between users in the cell after the joint detection technique is adopted_upRepresents a neighborhoodCell interference and noise weight.

In addition, the signal spatial intensity distribution P_k(θ) is expressed as:

where a (θ) is a direction vector corresponding to the direction angle θ.

Also, the signal spatial intensity distribution P of the interference noise signal_N(θ) is expressed as:

where d is the array element spacing and λ is the carrier wavelength.

It can be seen that, the dynamic channel allocation method and apparatus of the present invention select the time slot resource with the minimum interference to the target user to allocate to the target user by calculating the interference 1 of the target user in each uplink and downlink time slot, and selecting the time slot resource with the minimum interference to the target user, thereby achieving the purpose of minimum mutual interference and maximum capacity in the system.

The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A dynamic channel allocation method is used for avoiding interference between users of a local cell and a neighbor cell, and is characterized by comprising the following steps:

step S202, respectively estimating uplink channel impulse response of each user of each time slot according to channel estimation, then arranging the uplink channel impulse response into an uplink channel impulse response matrix, and arranging noise interference on each antenna into an uplink interference noise matrix;

step S204, calculating an uplink signal space correlation matrix of each user according to the uplink channel impact response matrix, and calculating a space correlation matrix of uplink interference noise according to the uplink interference noise matrix;

step S206, the target user measures and reports the downlink interference noise power received in each downlink time slot;

step S208, calculating the uplink interference suffered by the target user in each uplink time slot and the downlink interference suffered by the target user in each downlink time slot; and

2. The dynamic channel allocation method according to claim 1, wherein said step S208 is implemented by: and calculating the uplink interference size of the target user in each uplink time slot according to the uplink signal space correlation matrix, the uplink interference noise matrix and the interference suppression factor of the uplink joint detection technology, and calculating the downlink interference size of the target user in each downlink time slot according to the uplink signal space correlation matrix, the downlink interference noise power and the interference suppression factor of the downlink joint detection technology.

3. The dynamic channel allocation method according to claim 1, wherein said antennas are smart antennas.

4. The dynamic channel allocation method according to claim 3, wherein the smart antennas are array antennas.

5. The dynamic channel allocation method according to any one of claims 1 to 4, wherein an objective function J for measuring the uplink interference level received by the target user in a time slot_upCan be expressed as:

<math><mrow><msub><mi>J</mi><mi>up</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>up</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mo>+</mo><msub><mi>β</mi><mi>up</mi></msub><msub><mi>R</mi><mi>N</mi></msub><mo>)</mo></mrow><mo>·</mo><mi>H</mi><mo>)</mo></mrow><mo>,</mo></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀An uplink channel impulse response matrix, R, representing the target user_kRepresenting said spatial correlation matrix, R, of said uplink signals_NAn uplink spatial correlation matrix, α, representing the interference noise_upRepresenting the residual size, beta, of the interference between users of the cell after the joint detection technique is adopted_upRepresenting the weights of the neighbor cell interference and the noise.

6. The dynamic channel allocation method according to claim 5, wherein,

a is said_upIs a number, alpha, ranging between (0, 1)_upThe smaller the interference is, the less the interference between users in the cell is left; and

beta is the same as_upIs a number with a value range between (0, 1) and represents the weight of the interference and the noise of the adjacent cell when the beta value is_upWhen 1 is taken, the influence of the interference and the noise of the adjacent cell of 100 percent is considered when the resource is allocated, and when the beta value is beta_upAnd when 0 is taken, the influence of the interference and the noise of any adjacent cell is not considered in the resource allocation.

7. Dynamic channel according to any of claims 1 to 4The allocation method is characterized in that an objective function J for measuring the downlink interference degree of the target user in a time slot_downCan be expressed as:

<math><mrow><msub><mi>J</mi><mi>down</mi></msub><mo>=</mo><mi>trace</mi><mrow><mo>(</mo><msubsup><mi>H</mi><mn>0</mn><mi>H</mi></msubsup><mo>·</mo><mrow><mo>(</mo><msub><mi>α</mi><mi>down</mi></msub><munderover><mi>Σ</mi><mrow><mi>k</mi><mo>=</mo><mn>1</mn></mrow><mi>K</mi></munderover><msub><mi>R</mi><mi>k</mi></msub><mo>)</mo></mrow><mo>·</mo><msub><mi>H</mi><mn>0</mn></msub><mo>)</mo></mrow><mo>+</mo><msub><mi>β</mi><mi>down</mi></msub><msubsup><mi>P</mi><mi>N</mi><mi>down</mi></msubsup><mo>,</mo></mrow></math>

wherein trace (x) represents the sum of diagonal elements of matrix x, H₀An uplink channel impulse response matrix, R, representing the target user_kRepresenting said spatial correlation matrix, R, of said uplink signals_NAn uplink spatial correlation matrix, α, representing the interference noise_downRepresents the residual interference, beta, between the users of the cell after the joint detection technique is adopted_downWeights representing the neighbor cell interference and the noise.

8. The dynamic channel allocation method according to any one of claims 1 to 4, wherein an objective function J for measuring the uplink interference level received by the target user in a time slot_upCan be expressed as:

wherein, P_k(θ) is the signal space intensity distribution, P, of each user per time slot_N(theta) is the signal spatial intensity distribution of the interference noise signal, alpha_upRepresents the residual interference, beta, between the users of the cell after the joint detection technique is adopted_upWeights representing the neighbor cell interference and the noise.

9. The dynamic channel allocation method according to claim 8, wherein,

the signal spatial intensity distribution P_k(θ) is expressed as:

P_k(θ)＝a^H(θ)·R_k·a(θ)，

k is 1, 2.. K, where a (θ) is a direction vector corresponding to the direction angle θ;

signal spatial intensity distribution P of the interference noise signal_N(θ) is expressed as: p_N(θ)＝a^H(θ)·R_N·a(θ)，

And

a (θ) can be expressed as:

wherein d is between array elementsDistance, λ, is the carrier wavelength.