CN102761359B - Combine method and device that base station receiver and user equipment transmitting power are set - Google Patents

Abstract

The present invention proposes a kind of newly combine method and device that base station receiver and user equipment transmitting power are set.According to the present invention, the system utility of MIMO communication system, the transmitting power of subscriber equipment and base station receiver three included in a unified Optimization Framework by mean square error (Mean Square Error, MSE) this physical quantity.Under this Optimization Framework based on MSE, with system utility optimization for criterion, by the repeated optimization of multi-user's power division and Receiver Design, system utility can be improved continuously; And obtain optimized system utility, and subscriber equipment power division during system utility optimization and base station receiver are arranged.

Description

Combine method and device that base station receiver and user equipment transmitting power are set

Technical field

The present invention relates to mobile communication technology, particularly relate to the Poewr control method in mobile communications network and base station.

Background technology

In 3GPP lte-a system, for frequency division multiplexing (Frequency DivisionDuplex, FDD) and time division multiplexing (Time Division Duplex, TDD) system, (Base Station, BS) can adopt 4 and 8 antennas respectively in each base station.For LTE system, this antenna configuration enhanced can improve upstream performance and the flexibility thereof of multi-user's multiple-input and multiple-output (Multi-User Multiple-Input Multiple-output, MU-MIMO) system conscientiously.In systems in practice for the ease of realizing MU-MIMO, receiving terminal generally tends to adopt linear or based on iterative interference cancellation (Successive Interference Cancellation, SIC) least mean-square error (Minimum Mean Square Error, MMSE) receiver, it is utilized to replace maximum likelihood (Maximal Likelihood, ML) receiver.In addition, power in MU-MIMO system controls (optimization) has its uniqueness feature as a kind of indispensable important means, it is by regulating the transmitting power of pairing user mutually on Spatial Dimension, obtain the highest total throughout or maximum speed weighted sum thus, balance presence of intercell interference (Inter-CellInterference, ICI) intensity simultaneously.From the global design of system, expect that the optimization aim that these power controls and the target that MU-MIMO scheduler is pursued keep consistent with each other.Therefore, the final utility of the raising MU-MIMO system needing suitable multi-user's power optimization strategy to act in agreement.

MMSE receiver is a kind of linear process structure of optimum, and its filter construction depends on the second-order statistics of transmitting power size, channel information and Noise and Interference.Just due to this complementary feature, in multi-user's power optimization problem and MU-MIMO system, the optimal design problem of MMSE receiver has natural coupled characteristic between the two.It is a complicated nonlinear optimal problem that this coupled characteristic determines above-mentioned multi-user's power joint optimizing process.At present, the best power prioritization scheme for MU-MIMO system is multi-user's iterative water-filling method.But multi-user's iterative waterfilling is the theoretical method that one is only only applicable to desirable MU-MIMO receiver (i.e. ML receiver).Compared to the MU-MIMO system of configuration MMSE receiver, the multi-user's power optimization problem in the MU-MIMO system of configuration ML receiver is a comparatively convex optimization problem of easy to handle.In actual applications, the complexity due to ML receiver is much higher than MMSE receiver, so general little employing ML receiver, therefore the range of application of multi-user's iterative water-filling method is severely limited.

Meanwhile, existing multi-user's power optimization method pursues merely capacity/throughput-maximized usually.In multi-user transmission scene, capacity/throughput is one and comparatively simply measures, and it fails to embody in general networking effectiveness target about other characteristic of User Priority.Therefore, in the MU-MIMO system of configuration MMSE receiver, pursuing the maximized multi-user's power optimization of network utility is a problem demanding prompt solution.

Summary of the invention

For solving above-mentioned shortcoming of the prior art, the present invention proposes a kind of newly combine method and device that base station receiver and user equipment transmitting power are set.According to the present invention, the system utility of MIMO communication system, the transmitting power of subscriber equipment and base station receiver three included in a unified Optimization Framework by mean square error (Mean Square Error, MSE) this physical quantity.Under this Optimization Framework based on MSE, with system utility optimization for criterion, by the repeated optimization of multi-user's power division and Receiver Design, system utility can be improved continuously; And obtain optimized system utility, and subscriber equipment power division during system utility optimization and base station receiver are arranged.

Particularly, according to an embodiment of the invention, provide a kind of and combine the method that base station receiver and user equipment transmitting power are set in a communications system, described communication system is multi-input multi-output system, described receiver is least mean-square error receiver, and described method comprises

Step 1: Initialize installation is carried out in base station, arranges channel parameter, initialization system effectiveness and system utility desired value, set a power initial value;

Step 2: according to channel parameter and power initial value, calculate the filtering matrix of a least mean-square error receiver; Set a power and variable, for the filtering matrix of least mean-square error receiver, calculate normalized mean squared error, and utilize described normalized mean squared error to represent system utility, with optimization system effectiveness for criterion, calculate described power and variable and system utility; And the power and variable calculated described in power initial value is set to;

Step 3: comparison system effectiveness and system utility desired value, if system utility converges to system utility desired value, performs step 4, if system utility does not converge to system utility desired value, returns step 2;

Step 4: power and variable when system utility being converged to system utility desired value is as user equipment transmitting power; And power and variable when converging to system utility desired value according to channel parameter and described system utility calculate a least mean-square error receiver filtering matrix and using the filtering matrix of the filtering matrix of described least mean-square error receiver as the least mean-square error receiver of base station receiver.

According to a specific embodiment of the present invention, described system utility is throughput of system, or speed weighted sum.

According to a specific embodiment of the present invention, described receiver is linear minimum mean-squared error receiver or the least mean-square error receiver based on iterative interference cancellation.

According to an embodiment of the invention, there is provided a kind of and combine the device that base station receiver and user equipment transmitting power are set in a communications system, described communication system is multi-input multi-output system, and described receiver is least mean-square error receiver, and described device comprises:

Initialization unit, for arranging channel parameter, initialization system effectiveness and system utility desired value, set a power initial value;

System utility highest optimizating unit, for according to channel parameter and power initial value, calculates the filtering matrix of a least mean-square error receiver; And set a power and variable, for filtering matrix, calculate normalized mean squared error, and utilize described normalized mean squared error to represent system utility, with optimization system effectiveness for criterion, calculate described power and variable and system utility; And the power and variable calculated described in power initial value is set to;

Comparing unit, for comparison system effectiveness and system utility desired value, if system utility converges to system utility desired value, the power initial value obtained by system utility highest optimizating unit outputs to output valve setting unit, if system utility does not converge to system utility desired value, then reporting system optimal utility unit proceeds system utility optimization;

Output valve setting unit, for obtain when comparing unit system utility converge to system utility desired value time, the power and variable value obtained by system utility highest optimizating unit is as user equipment transmitting power; And the filtering matrix that when system utility being converged to system utility desired value, filtering matrix computing unit obtains is as the filtering matrix of the least mean-square error receiver of base station receiver.

According to a specific embodiment of the present invention, described system utility is throughput of system, or is speed weighted sum.

According to a specific embodiment of the present invention, described receiver is linear minimum mean-squared error receiver or the least mean-square error receiver based on iterative interference cancellation.

According to an embodiment of the invention, a kind of base station is provided, comprise the basic operate in open loop state dot element of uplink transmission power and filter for receiver unit, further comprise the device that combining according to any one of claim 4-6 arranges base station receiver and user equipment transmitting power, the described device arranging base station receiver and user equipment transmitting power of combining exports user equipment transmitting power, to filter for receiver unit output filtering matrix to the basic operate in open loop state dot element of uplink transmission power.

Accompanying drawing explanation

By below in conjunction with the description of the drawings, and understand more comprehensively along with to of the present invention, other objects of the present invention and effect will become clearly and easy to understand, wherein:

Fig. 1 represents the up MU-MIMO transmission in lte-a system.

Fig. 2 represents the equivalent channel structure of the MU-MIMO system being configured with MMSE receiver.

Fig. 3 represent according to the embodiment of the present invention combine the flow chart that base station receiver and user equipment transmitting power are set.

Fig. 4 represents the structural representation of combining the device arranging base station receiver and user equipment transmitting power according to the embodiment of the present invention.

Fig. 5 represent according to the embodiment of the present invention comprise the architecture of base station schematic diagram of combining the device that base station receiver and user equipment transmitting power are set.

Fig. 6 a, 6b represent respectively according to the embodiment of the present invention turn to throughput schematic diagram in the optimizing process of target and power division schematic diagram so that throughput of system is maximum.

Fig. 7 a, 7b represent respectively and turn to throughput schematic diagram in the optimizing process of target and power division schematic diagram according to another embodiment of the present invention so that throughput of system is maximum.

In all above-mentioned accompanying drawings, identical label represents to have identical, similar or corresponding feature or function.

Embodiment

Embodiments of the present invention are specifically described below in conjunction with accompanying drawing.

Power iterative optimization method proposed by the invention, sets up contact by mean square error (MeanSquare Error, MSE) this physical quantity, by this system utility, transmitting power and Receiver Design three is included in a unified Optimization Framework.Under this Optimization Framework based on MSE, system utility can be considered a positve term function about MSE (posynominal function).This positve term function can pass through the repeated optimization of multi-user's power division and Receiver Design, minimizes with the process of iteration.In other words, by iteration optimization power division, system utility can be improved continuously.Thus, for the mimo system of configuration MMSE receiver, the power allocation scheme that meets required precise requirements finally can be obtained.Below, the Optimization Framework based on MSE will be described from mathematical form, and describe the iterative process of power optimization in detail, set forth basic thought of the present invention and algorithm thus.

Here the up MU-MIMO transmission in lte-a system is considered.As shown in Figure 1, H _krepresent one from a kth user terminal (User Equipment, UE) to M × 2MIMO channel matrix of BS.At each scheduling interval, BS selects D from K UE altogether, and allows it on same running time-frequency resource, send data.Scheduling metrics (system utility) maximized criterion is followed in the selection of this D UE, and its general type can be described as maximizing multi-user's speed weighted sum, i.e. problem 1:

$\underset{\{k_1,k_2,\·\·\·,k_D\}\⋐\{\mathrm{1,2},\·\·\·,K\}}{\max }\left\{\underset{k\∈\{k_1,k_2,\·\·\·,k_D\}}{\mathrm{\Σ}}{w}_k\underset{j\∈t_k}{\mathrm{\Σ}}{r}_{k,j}\left(p_{k,j}\right)\right\}$

$s.t.\underset{k\∈\{k_1,k_2,\·\·\·,k_D\}}{\mathrm{\Σ}}{a}_k{p}_k\≤1$

Here:

T _krepresent the sending mode selected by a kth UE.Specifically, the t when adopting double-deck sending mode _k={ 1,2}, and t during individual layer sending mode _k={ 1}.

P _krepresent the total transmitting power distributing to a kth UE; p _{k, j}represent the transmitting power distributing to a kth UE jth layer, it meets according to LTE-A specification, total transmitting power strictly etc. gives each transmitting antenna.

R _{k, j}(p _{k, j}) represent and transmit by a kth UE jth layer data rate obtained.

W _k(w _k> 0) represent and correspond to the weighted factor of a kth UE, it is used for weighing the priority of this user, and concrete size is determined by the MU-MIMO scheduler of system.For equitable proportion (Proportional Fair, PF) scheduler, this weighted factor equals the inverse of user's average transmission rate.

A _krepresent the normalization equivalence obstacle gain of a kth UE to neighbor bss.

BS end adopts MMSE receiver, detects d the active traffic simultaneously sent by D UE.This MMSE receiver can be described as the receiving matrix R of a d × M, here, represent the active traffic that D UE sends simultaneously number (| t _k| represent set t _kgesture).Therefore, up MU-MIMO channel can be described as the equivalent up channel that corresponds to d active traffic, as shown in Figure 2.

C _irepresent the equivalent channel vector of M × 1 corresponding to i-th data flow, which depict the corresponding group effect launching precoding and physical channel.

represent the transmitting power corresponding to i-th data flow.

X _it () represents the modulated symbol corresponding to i-th data flow.

represent that corresponding to multi-user's transmitting power is time MMSE receiver.When using linear MMSE receiver, it can be expressed as

Here C=[c ₁c ₂c _d]; represent the variance of additive noise; Subscript () ^hrepresent conjugate transpose.

Here the weighted factor corresponding to i-th data flow is introduced according to LTE-A specification, set { H _k, p _k, w _kbetween must have following one-to-one relationship.

Mapping rule:

When a kth UE sends i-th data flow on jth layer, so

And

$c_i=\left\{\begin{array}{cc}{H}_k\left[\begin{array}{c}1\\ 0\end{array}\right]& \mathrm{if}{t}_k=\left\{\mathrm{1,2}\right\},j=1\\ H_k\left[\begin{array}{c}0\\ 1\end{array}\right]& \mathrm{if}{t}_k=\left\{\mathrm{1,2}\right\},j=2\\ H_{k}s& \mathrm{if}{t}_k=\left\{1\right\}\end{array}\right.$

Here, indicate (Precoding Matrix Index, PMI) from following collection according to the pre-coding matrix of each UE, determine the concrete vector value of S

$s\∈\{\left[\begin{array}{c}\frac{1}{\sqrt{2}}\\ \frac{1}{\sqrt{2}}\end{array}\right],\left[\begin{array}{c}\frac{1}{\sqrt{2}}\\ -\frac{1}{\sqrt{2}}\end{array}\right],\left[\begin{array}{c}\frac{1}{\sqrt{2}}\\ i\frac{1}{\sqrt{2}}\end{array}\right],\left[\begin{array}{c}\frac{1}{\sqrt{2}}\\ -i\frac{1}{\sqrt{2}}\end{array}\right],\left[\begin{array}{c}1\\ 0\end{array}\right],\left[\begin{array}{c}0\\ 1\end{array}\right]\}$

The stochastic behaviour of usual hypothesis signal and noise meets Gauss feature, so by i-th obtainable maximum rate of data flow, just can represent with the normalization MMSE acquired by i-th data flow, namely

Here used and can obtain Signal to Interference plus Noise Ratio SINR (Signal to Interference and NoiseRatio) and MMSE famous relational expression between the two, namely

${\mathrm{MMSE}}_i=\frac{1}{1+{\mathrm{SINR}}_i}$

By utilize mapping rule and maximization speed weighted sum problem about D UE transmitting power can be expressed as:

Problem 2:

$\max \underset{k\∈\{k_1,k_2,\·\·\·,k_D\}}{\mathrm{\Σ}}{w}_k\underset{j\∈t_k}{\mathrm{\Σ}}{r}_{k,j}\left(p_{k,j}\right)$

$s.t.\underset{k\∈\{k_1,k_2,\·\·\·,k_D\}}{\mathrm{\Σ}}{a}_k{p}_k\≤1,$

And can be converted to the optimization problem of next equivalence, problem 3:

For fixing transmitting power and corresponding linear MMSE receiver can obtain

Here [ ] _{i, j}(i, j) individual element of representing matrix.Inherently, the optimization problem based on MMSE is not the optimization problem of a standard, still has very high complexity.

On the other hand, when fixed linear receiving filter, its power optimization can be summed up as a simple posynomial geometric programming (Geometric Programming, GP) problem.Particularly, when transmitting power matrix is with linear receiver be time, (here be not correspond to mMSE receiver), the normalization MSE that i-th data flow obtains is

Here [A] _i:i-th row vector of representing matrix A.Therefore, by following easy-to-handle standard GP problem, can directly obtain for set receiver optimal power allocation matrix

Problem 4:

For obtained mSE can be minimized further followed by optimization of receiver algorithms design, and obtain corresponding MMSE receiver obviously, above-mentioned two optimizing processs achieve

Similarly, for fixing obtain further by Solve problems 4 again obviously,

Use the mode of iteration constantly to repeat above-mentioned GP and receiver optimizing process, can obtain with next monotonic decreasing and the sequence of bounded

This Monotone Bounded sequence shows: as n → ∞, can converge on the minimum value an of this locality (or overall situation), namely this minimum value is the minimum value of problem 3, and obtains required power allocation scheme simultaneously.By this, for the solving of problem 1 of complexity, realize by iterative solution simple question 4 in an iterative manner.It should be noted that problem 4 is positve term GP problems of a low-dimensional, utilize the canonical algorithm of low complex degree to solve easily.

Based on above analysis, algorithm 1 summarises the basic calculating flow process of Solve problems 3.Algorithm 1 solves the multi-user's power optimization problem in the MU-MIMO system of configuration linear MMSE receiver.

According to above-mentioned Algorithm Analysis, provide below in conjunction with Fig. 3 and implement two specific embodiments of the present invention.

Embodiment 1: configuration linear MMSE receiver MU-MIMO system in combine the method that base station receiver and user equipment transmitting power are set

Step S301: carry out Initialize installation, input a _k(k ∈ { k ₁, k ₂..., k _d), and C, and initialization maximum iteration time n is set respectively _maxwith maximum acceptable error ε.Meanwhile, n=0 and system utility parameter U is made _pre=inf.

Step S302: optimization system effectiveness.Specifically comprise:

1: calculate receiving filter according to following formula

2: for receiver and transmitting power normalization MMSE is calculated according to following formula

3: computing system effectiveness and difference DELTA=U _pre-U _post;

4：U _pre＝U _post；

5: for receiver and transmitting power normalization MSE is calculated according to following formula

6: by solving the positve term GP problem of following standard, obtain

7：n＝n+1.

Step S303: judge whether system utility converges to system utility desired value, concrete, whether meet Δ < ε, if do not met, repeat step S302; If met, perform step S304; Also can maximum iteration time n be set _maxif meet n > n _max, exit iterative process, perform step S304;

Step S304: the power allocation scheme needed for output and filter

Embodiment 2: for the MU-MIMO system of configuration SIC-MMSE receiver, the method that similar combining arranges base station receiver and user equipment transmitting power can be derived.Do not lose generality ground, suppose that multiple data flow is with i=1 here, 2 ..., the sequential iteration of d detects, and omission error is propagated.

Step S301: carry out Initialize installation, input a _k(k ∈ { k ₁, k ₂..., k _d), and C, and initialization maximum iteration time n is set respectively _maxwith maximum acceptable error ε.Meanwhile, n=0 and system utility parameter U is made _pre=inf.

Step S302: optimization system effectiveness.Specifically comprise:

1: calculate SIC receiving filter according to following formula

Here

C _i＝[c _ic _i+1… c _d]

2: for receiver and transmitting power normalized MMSE is calculated according to following formula

3: computing system effectiveness and difference DELTA=U _pre-U _post;

4：U _pre＝U _post；

5: for SIC receiver and transmitting power according to following formula calculate normalization MSE (i=1,2 ..., d),

Here

6: by solving the positve term GP problem of following standard, obtain

7：n＝n+1.

Step S303: judge whether system utility converges to system utility desired value, concrete, whether meet Δ < ε, if do not met, repeat step S302; If met, perform step S304; Also can maximum iteration time n be set _maxif meet n > n _max, exit iterative process, perform step S304;

Step S304: the power allocation scheme needed for output and filter

Fig. 4 gives and combines according to embodiment of the present invention the device arranging base station receiver and user equipment transmitting power.In the present embodiment, combine the device 400 that base station receiver and user equipment transmitting power are set and comprise initialization unit 401, system utility highest optimizating unit 402, comparing unit 403, output valve setting unit 404.

Concrete, initialization unit 401 is configured to for arranging channel parameter, initialization system effectiveness and system utility desired value, sets a power initial value; Concrete, as input a _k(k ∈ { k ₁, k ₂..., k _d), and C, and initialization maximum iteration time n is set respectively _maxwith maximum acceptable error ε.Meanwhile, n=0 and system utility parameter U is made _pre=inf.

System utility highest optimizating unit 402 is configured to, for according to channel parameter and power initial value, calculate the filtering matrix of a least mean-square error receiver; And set a power and variable, for filtering matrix, calculate normalized mean squared error, and utilize described normalized mean squared error to represent system utility, with optimization system effectiveness for criterion, calculate described power and variable and system utility; And the power and variable calculated described in power initial value is set to; The function that system utility highest optimizating unit 402 completes is corresponding with step S302.

Comparing unit 403, be configured to for comparison system effectiveness and system utility desired value, if system utility converges to system utility desired value, the power initial value obtained by system utility highest optimizating unit outputs to output valve setting unit, if system utility does not converge to system utility desired value, then reporting system optimal utility unit proceeds system utility optimization; Judging whether system utility converges in the concrete enforcement of system utility desired value, can see and whether meet Δ < ε, if do not met, repeat step S302; If met, perform step S304; Also can maximum iteration time n be set _maxif meet n > n _max, exit iterative process, perform step S304.

Output valve setting unit 404, be configured to for obtain when comparing unit system utility converge to system utility desired value time, the power and variable value obtained by system utility highest optimizating unit is as user equipment transmitting power; And the filtering matrix that when system utility being converged to system utility desired value, filtering matrix computing unit obtains is as the filtering matrix of the least mean-square error receiver of base station receiver.

Fig. 5 provide according to the embodiment of the present invention comprise the architecture of base station schematic diagram of combining the device that base station receiver and user equipment transmitting power are set.In the present embodiment, base station 500 comprises the device 400 of combining and arranging base station receiver and user equipment transmitting power, the basic operate in open loop state dot element 502 of uplink transmission power, filter for receiver unit 503.Combine the device 400 that base station receiver and user equipment transmitting power are set and export user equipment transmitting power to the basic operate in open loop state dot element 502 of uplink transmission power, to filter for receiver unit 503 output filtering matrix.

Proposed by the invention combines the strategy arranging base station receiver and user equipment transmitting power, first time adopts attainable iterative manner, for the mimo system of configuration MMSE receiver, solve the Non-linear coupling problem in its power division (control).

Secondly, the present invention, from the angle of system, promotes network utility by multi-user's power optimization.Specifically, the power iteration optimization strategy proposed is by utilizing the low-complexity of positve term GP, and Joint iteration optimizes multi-user's power division and Receiver Design, thus realizes the maximization of speed weighted sum.Usually, speed weighted sum is the general type of all kinds of MIMO scheduler system utility (optimization aim).This just means that the present invention can directly apply to the MU-MIMO system of the different scheduler of various employing.

Again, the present invention's design by the transmission power level of adjustment mutual pairing user on Spatial Dimension, thus obtains the maximum rate weighted sum of maximum system throughput or multi-user, balances ICI intensity simultaneously.

By solution proposed by the invention, simply can realize multi-user's power division optimization problem, especially can improve the basic operate in open loop state point of uplink transmission power.This programme can with less iterative computation cost, remarkable elevator system performance.By following simulation example, can quantize the performance gain of this method and the cost of iterative computation are described.

Following emulation experiment have evaluated the performance characteristics of power iterative optimization method proposed by the invention in wireless cellular system and calculation cost.In assessed cellular system, base station configures 2 reception antennas, and adopts linear MMSE receiver.This means that 2 UE can be served at most in this base station simultaneously.In order to assess conveniently, suppose that each UE all adopts individual layer sending mode here, and the basic operate in open loop state point of identical uplink transmission power is set.Do not lose generality, suppose here and suppose that power optimization is keeping the constant constraints of total transmitting power to carry out, namely meanwhile, suppose systematic function evaluate and optimize index respectively with throughput and system utility consider.Here two typical channel scenario are considered.

Scene 1: suppose that the equivalent channel of 2 UE is independent identically distributed, an one concrete channel is embodied as

$c_1=\left[\begin{array}{c}0.0413736134896147+0.426387557408945i\\ -0.734169112696739-0.372808741723504i\end{array}\right]$

$c_2=\left[\begin{array}{c}-0.0308137300123200-0.236454583757186i\\ 0.232347012624477+2.02369088660305i\end{array}\right]$

Fig. 6 a describes the system throughput flow gain that power iteration optimization in scene 1 obtains after 12 iterative computation, throughput of system converges on maximum 6.405, and it is greater than initial value 6.305.In above-mentioned iterative process, the evolution process of corresponding power assignment value as shown in Figure 6 b.In Fig. 6 a, transverse axis represents iterations, and the longitudinal axis represents throughput of system.In figure 6b, the power of transverse axis representative of consumer equipment 1, the power of longitudinal axis representative of consumer equipment 2.

Scene 2: suppose that the average power that the equivalent channel of 2 UE exists 3dB due to path loss is poor, an one concrete channel is embodied as

$c_1=\left[\begin{array}{c}0.0413736134896147+0.426387557408945i\\ -0.734169112696739-0.372808741723504i\end{array}\right]$

$c_2=\left[\begin{array}{c}-0.0308137300123200-0.236454583757186i\\ 0.232347012624477+2.02369088660305i\end{array}\right].$

Fig. 7 a describes the system throughput flow gain that power iteration optimization in scene 2 obtains after 30 iterative computation, throughput of system converges on maximum 9.4, and it is greater than initial value 8.2.In above-mentioned iterative process, the evolution process of corresponding power assignment value as shown in Figure 7b.In figure 7 a, transverse axis represents iterations, and the longitudinal axis represents throughput of system.In fig .7b, the power of transverse axis representative of consumer equipment 1, the power of longitudinal axis representative of consumer equipment 2.

Above embodiment is all the MU-MIMO system for configuration MMSE receiver, should be noted that, for Single User MIMO system, is equivalent to the special case of multiuser MIMO, and therefore the present invention is equally applicable to the Single User MIMO system configuring MMSE receiver.

The present invention can realize with hardware, software, firmware and their combination.One skilled in the art would recognize that and also can embody the present invention in computer program set on the signal bearing medium for any suitable data treatment system.This signal bearing medium can be transmission medium or the recordable media for machine sensible information, comprises magnetizing mediums, light medium or other suitable media.The example of recordable media comprises: the disk in hard disk drive or floppy disk, the CD for CD-ROM drive, tape, and those skilled in the art's other media thinkable.One skilled in the art would recognize that any communication equipment with suitable programmed device all can perform the step as the inventive method embodied in program product.

Should be appreciated that from foregoing description, without departing from the spirit of the invention, can each execution mode of the present invention be modified and be changed.Description in this specification is only used for illustrative, and should not be considered to restrictive.Scope of the present invention is only by the restriction of claims.

Attached: the explanation of symbol is illustrated:

● M: the reception antenna number representing base station (BS).

● I: representation unit matrix.

● Re{*}: represent a real.

● [*] _i:: the i-th row vector representing the matrix in square brackets, i.e. a row vector forming according to original order of this matrix i-th row all elements.

● [*] _{i, 1:D}: represent the row vector that front D element of the i-th row vector of the matrix in square brackets forms according to original order.

Claims (7)

1. combine the method arranging base station receiver and user equipment transmitting power in a communications system, described communication system is multi-input multi-output system, and described receiver is least mean-square error receiver, and described method comprises,

Step 1: Initialize installation is carried out in base station, arranges channel parameter, initialization system effectiveness and system utility desired value, set a power initial value;

Step 2: according to channel parameter and power initial value, calculate the filtering matrix of a least mean-square error receiver; Set a power and variable, for the filtering matrix of least mean-square error receiver, calculate normalized mean squared error, and utilize described normalized mean squared error to represent system utility, with optimization system effectiveness for criterion, calculate described power and variable and system utility; And the power and variable calculated described in power initial value is set to;

Step 3: comparison system effectiveness and system utility desired value, if system utility converges to system utility desired value, performs step 4, if system utility does not converge to system utility desired value, returns step 2;

Step 4: power and variable when system utility being converged to system utility desired value is as user equipment transmitting power; And power and variable when converging to system utility desired value according to channel parameter and described system utility calculate a least mean-square error receiver filtering matrix and using the filtering matrix of the filtering matrix of described least mean-square error receiver as the least mean-square error receiver of base station receiver.

2. method according to claim 1, is characterized in that, described system utility is throughput of system, or speed weighted sum.

3. method according to claim 1, is characterized in that, described receiver is linear minimum mean-squared error receiver or the least mean-square error receiver based on iterative interference cancellation.

4. combine the device arranging base station receiver and user equipment transmitting power in a communications system, described communication system is multi-input multi-output system, and described receiver is least mean-square error receiver, and described device comprises:

Initialization unit, for arranging channel parameter, initialization system effectiveness and system utility desired value, set a power initial value;

System utility highest optimizating unit, for according to channel parameter and power initial value, calculates the filtering matrix of a least mean-square error receiver; And set a power and variable, for filtering matrix, calculate normalized mean squared error, and utilize described normalized mean squared error to represent system utility, with optimization system effectiveness for criterion, calculate described power and variable and system utility; And the power and variable calculated described in power initial value is set to;

Comparing unit, for comparison system effectiveness and system utility desired value, if system utility converges to system utility desired value, the power initial value obtained by system utility highest optimizating unit outputs to output valve setting unit, if system utility does not converge to system utility desired value, then reporting system optimal utility unit proceeds system utility optimization;

Output valve setting unit, for obtain when comparing unit system utility converge to system utility desired value time, the power and variable value obtained by system utility highest optimizating unit is as user equipment transmitting power; And the filtering matrix that when system utility being converged to system utility desired value, filtering matrix computing unit obtains is as the filtering matrix of the least mean-square error receiver of base station receiver.

5. device according to claim 4, is characterized in that, described system utility is throughput of system, or is speed weighted sum.

6. device according to claim 4, is characterized in that, described receiver is linear minimum mean-squared error receiver or the least mean-square error receiver based on iterative interference cancellation.

7. a base station, comprise the basic operate in open loop state dot element of uplink transmission power and filter for receiver unit, further comprise the device that combining according to any one of claim 4-6 arranges base station receiver and user equipment transmitting power, the described device arranging base station receiver and user equipment transmitting power of combining exports user equipment transmitting power, to filter for receiver unit output filtering matrix to the basic operate in open loop state dot element of uplink transmission power.