CN102170412B - Interruption relaxation alignment method based on multi-point multi-user coordination downlink - Google Patents
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Abstract
The invention discloses an interruption relaxation alignment method based on multi-point multi-user coordination downlink. The method specially comprises the following steps: (1) completing channel estimation at a sending end by using a corresponding channel estimation technique according to that different performances and transmission modes are required by communication systems to obtain channel matrix parameters; (2) establishing an optimized equation consisting of constraint conditions and a target function, wherein the constraint conditions are formed after relaxed interruption and alignment are carried out on constraint conditions by a relaxation factor lambda; (3) solving the optimized equation; (4) respectively performing premultiplication on a sending signal by various receiving ends with a solved wave beam formation matrix so as to complete pretreatment; and (5) carrying out conjugated transposition premultiplication of the received signal by various receiving ends with a solved interruption elimination matrix so as to complete post-treatment. The method has the advantages that a wave beam formation matrix set and an interruption elimination matrix set which are used for inhibiting multi-user interruption can be rapidly solved, and the pre-treatment and post-treatment are respectively carried out by the sending end and receiving ends so as to inhibit the multi-user interruption.
Description
Technical Field
The invention belongs to the technical field of communication, and further relates to the technical field of multipoint and multi-user cooperative downlink communication.
Background
In a downlink of the multi-point multi-user cooperative communication system, a plurality of transmission points simultaneously transmit information to a plurality of users in a cooperative mode. Any user will receive signals from other transmission points while receiving a desired signal, possibly resulting in multi-user interference. In order to eliminate interference, interference alignment technology is mainly adopted at present to make the desired received signal and the interference signal clearly separable, so as to achieve the purpose of eliminating multi-user interference.
Krishna Gomadam provides a method for realizing Interference Alignment by combining beam forming during multi-point and multi-user cooperative downlink transmission in the article "adaptive the Capacity of Wireless networks and Distributed Interference Alignment" (Global telecom conference, 2008.IEEE GLOBECOM 2008.IEEE, pp.1-6, Nov.302008-Dec.42008). The method comprises the following implementation steps: firstly, a joint processing center of a transmitting end comprehensively considers channel information of all links, and calculates an optimal beam forming matrix and an optimal interference elimination matrix for each transmitting end and each receiving end based on an optimization target of maximizing channel capacity (namely, maximizing the sum of equivalent independent channel numbers obtained by all users); secondly, the transmitting end preprocesses the signal before transmitting the signal (namely, the beamforming matrix is multiplied by the transmitting signal in a left-hand mode); third, the receiving end performs post-processing on the received signal (i.e., the received signal is multiplied by the conjugate transpose of the interference cancellation matrix). Although the method achieves the purpose of eliminating multi-user interference through the combined processing of the sending end and the receiving end, the method still has the defects that: when the number of the sending ends and the number of the receiving ends are both more than or equal to 3, the solution of the combined beamforming is an NP-hard (Nondeterministic Polynomial time hard) problem, and it is difficult to solve a beamforming matrix set and an interference cancellation matrix set which are required by a system for eliminating multi-user interference in Polynomial time, so that the sending end and the receiving end have no way to perform next combined beamforming in engineering, and the interference alignment cannot be realized to eliminate the multi-user interference. Although the beam forming matrix set and the interference elimination matrix set can be obtained by adopting an iterative solution method, the multi-user interference is amplified in the operation process, and the effect in actual operation is poor.
Disclosure of Invention
The present invention aims to overcome the above deficiencies of the prior art, and provides a joint beamforming method based on "interference relaxation alignment", which can quickly find an effective solution of joint beamforming, and implement interference relaxation alignment to suppress multi-user interference generated by multi-point multi-user cooperative downlink communication.
The method comprises the following specific steps:
(1) channel matrix parameters are obtained. According to the different performance requirements and the different transmission modes of the communication system, the sending end adopts the corresponding channel estimation technology to complete channel estimation, and channel matrix parameters are obtained.
(2) And establishing an optimization equation.
2a) A constraint is determined. And determining a corresponding relaxation factor lambda according to the maximum tolerable residual multi-user interference generated by different performance requirements of each system. And (4) relaxing the interference alignment constraint condition by using a relaxation factor lambda, wherein the relaxation is not more than the maximum tolerable residual multi-user interference, and obtaining the constraint condition of interference relaxation alignment.
2b) An objective function is selected. And according to an optimization criterion for maximizing the channel capacity, selecting the maximum sum of the equivalent independent channel numbers obtained by all the receiving ends as an objective function of an optimization equation.
2c) Establishing an optimization equation consisting of constraint conditions and an objective function:
an objective function: <math>
<mrow>
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<mi>d</mi>
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constraint conditions are as follows: <math>
<mfenced open='{' close=''>
<mtable>
<mtr>
<mtd>
<msubsup>
<mi>U</mi>
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<mi>H</mi>
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<mi>H</mi>
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<mo>≤</mo>
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wherein d iskFor the number of equivalent independent channels obtained for receiver k,
Ukfor the interference cancellation matrix at the kth receiver,
[·]His the conjugate transpose of the matrix and,
Hkjfor the channel matrix parameters from the jth transmitting end to the kth receiving end,
Vjfor the beamforming matrix of the jth transmit end,
is the power of additive white gaussian noise,
i is an identity matrix and is a matrix of the identity,
rank () is the rank of the matrix,
Hkkfor the channel matrix parameters from the kth transmitting end to the kth receiving end,
Vkis the beamforming matrix of the kth transmitting end.
(3) And solving an optimization equation to obtain a beam forming matrix set and an interference elimination matrix set for inhibiting multi-user interference, and respectively sending the beam forming matrix set and the interference elimination matrix set to the corresponding sending end and the receiving end.
(4) And each transmitting end respectively uses the corresponding beam forming matrix in the obtained beam forming matrix set to be multiplied by the transmitting signal to finish the preprocessing of the transmitting signal.
(5) And each receiving terminal multiplies the received signal by the conjugate transpose of the corresponding interference elimination matrix in the obtained interference elimination matrix set to finish the post-processing of the received signal.
Compared with the prior art, the invention has the following advantages:
first, the present invention solves the problem of the prior art that NP-difficult problem cannot be solved by introducing a relaxation factor, and can rapidly solve a beamforming matrix set and an interference cancellation matrix set required for suppressing multi-user interference.
Secondly, the invention is not only suitable for the situation that the number of the sending ends and the number of the receiving ends are both more than or equal to 3, but also can be applied to quickly solve the beam forming matrix set and the interference elimination matrix set which are required for inhibiting the multi-user interference when the number of the sending ends and the number of the receiving ends are not both more than or equal to 3.
Thirdly, the invention can respectively carry out preprocessing and post-processing at the sending end and the receiving end based on the solved beam forming matrix set and the interference elimination matrix set, thereby realizing the interference relaxation alignment of distinguishing the interference and the expected received signal and inhibiting the mutual interference among multiple users.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a diagram of coordinated downlink transmission of multiple points and multiple users.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
For the multi-point multi-user cooperative downlink transmission scenario shown in fig. 2, the process of suppressing multi-user interference in the present invention is shown in fig. 1, and the implementation steps are as follows:
step 1, obtaining channel matrix parameters. According to the different performance requirements and the different transmission modes of the communication system, the sending end adopts the corresponding channel estimation technology to complete channel estimation, and channel matrix parameters are obtained.
Channel estimation techniques can be divided into two categories: blind estimation and reference signal based estimation. Different channel estimation technologies obtain different spectrum utilization performances, and when a communication system needs higher spectrum utilization performance, blind estimation can be adopted, and the blind estimation completely utilizes the inherent information of transmission data to realize channel estimation. Obviously, blind estimation saves bandwidth and improves the spectrum utilization rate of the system, but the algorithm has larger computation amount and poorer flexibility, thereby bringing great processing time delay. Conversely, when better delay performance is required for the communication system, reference signal based channel estimation may be employed. The channel estimation based on the reference signal determines the parameter to be estimated according to a certain estimation criterion, or gradually tracks and adjusts the estimation value of the parameter to be estimated according to certain criteria. It is characterized by the need of reference signal, i.e. pilot or training sequence. Estimation based on training sequences and pilot sequences is collectively referred to as a reference signal based estimation algorithm. The channel estimation algorithm based on the training sequence is suitable for a system of a burst transmission mode. The known training sequence is sent, initial channel estimation is carried out at a receiving end, and when useful information data is sent, a judgment updating is carried out by utilizing the initial channel estimation result, so that the real-time channel estimation is completed. The channel estimation based on pilot symbols is suitable for systems with continuous transmission mode. By inserting known pilot frequency symbols into the transmitted useful data, a channel estimation result of a pilot frequency position can be obtained; and then, the channel estimation result of the useful data position is obtained by interpolation by utilizing the channel estimation result of the pilot frequency position, and the channel estimation is finished. The channel estimation technique of the embodiment of the invention adopts a pilot-based Minimum Mean Square Error (MMSE) channel estimation technique which has lower frequency spectrum utilization rate but better time delay performance.
The MMSE channel estimation method based on the pilot frequency is to insert the pilot frequency at a proper position of a sending end, a receiving end recovers the channel information at the pilot frequency position by using the pilot frequency, and then all the channel information is obtained by means of interpolation, filtering, conversion and the like. In practice, there are two ways to insert pilots: comb pilots and block pilots. Different pilot patterns are selected for channel estimation depending on the channel conditions. The comb-shaped pilot frequency distributes the pilot frequency at intervals in the frequency domain, and the channel estimation carried out by the comb-shaped pilot frequency is continuous in the time domain; the block pilots are periodically distributed in the time domain, and the channel estimation with the block pilots is continuous in the frequency domain. The performance of both pilot patterns is exactly the same under invariant channel conditions when Additive White Gaussian Noise (AWGN) is used, but comb pilots are preferred over block pilots in fast varying channels. In the embodiment of the invention, the comb-shaped pilot frequency with better performance is selected for channel estimation.
After receiving the symbol containing comb-shaped pilot frequency information, the receiving end recovers the pilot frequency time channel information from the pilot frequency position according to the MMSE criterion.
The time domain MMSE estimation result of the channel obtained by the MMSE channel estimation formula is:
wherein,for the result of the time-domain MMSE estimation,
RhYis a cross-correlation matrix of h and Y, h is a channel impulse response,
[·]-1in the form of an inverse matrix of the input signal,
RYYis an autocorrelation matrix of Y and is,
y is a frequency domain receiving signal obtained by the receiving end after N-point Discrete Fourier Transform (DFT),
n is the length of the discrete fourier transform interval.
Based on the above time domain estimation results, willThe frequency domain MMSE estimation result of the channel can be obtained by multiplying the frequency domain MMSE estimation result by the N-point DFT transformation matrix F:
wherein,
and 2, establishing an optimization equation.
2a) The constraint is determined according to the maximum tolerable residual multi-user interference generated by different performance requirements of each system.
After the sending signal is preprocessed by the sending end and transmitted by the channel, the signal reaching the kth receiving end is as follows:
yk＝HkkVksk+∑HkjVjsj+zk
wherein, ykFor the signal received by the kth receiving end,
Hkkfor the channel matrix parameters from the kth transmitting end to the kth receiving end,
Vkfor the beamforming matrix of the kth transmitting end,
skfor the transmission signal of the kth transmitting end,
Hkjfor the channel matrix parameters from the jth transmitting end to the kth receiving end,
Vjfor the beamforming matrix of the jth transmit end,
sjfor the transmission signal of the jth transmitting end,
zkis additive white Gaussian noise and follows normal distribution Is the noise power. Signal y received at the receiving endkAfter post-processing, the finally demodulated signals are:
wherein,for the signal demodulated by the kth receiving end,
Ukfor the interference cancellation matrix at the kth receiver,
[·]Hrepresenting the conjugate transpose of the matrix.
Second item of (1)HkjVjResidual multi-user interference after interference alignment. Constraint strip for ideal interference alignmentThe parts are as follows:
it can be seen that the ideal interference alignment constraint condition obtained by theoretical derivation requires that residual multi-user interference after interference alignment is completely zero, and in practice, due to the existence of background noise, ideal interference alignment is completely unnecessary, and the engineering implementation of the algorithm is too complex. The maximum tolerable residual multi-user interference generated by each system with different performance requirements is different, the performance refers to the magnitude of the residual multi-user interference, and the corresponding relaxation factor lambda is determined to meet the following requirements according to the maximum tolerable residual multi-user interference generated by different systems:
wherein,to maximize the tolerable residual multi-user interference,
and I is an identity matrix.
And performing relaxation on the ideal interference alignment constraint condition by using the determined relaxation factor lambda, wherein the relaxation is not more than the maximum tolerable residual multi-user interference, so that the residual multi-user interference meets the following constraint condition:
if the system requires the residual multiuser interference to be less than or equal to half the noise power, λ is 2. The constraint conditions satisfied by the residual multi-user interference are:
2b) an optimization objective function is selected. The larger the number of equivalent independent channels that can be obtained by the receiving end is, the larger the channel capacity is obtained by the receiving end. In order to maximize the sum of the channel capacities of all the receiving ends after the interference relaxation alignment, an optimization equation objective function is selected to maximize the sum of the equivalent independent channel numbers obtained by all the receiving ends according to an optimization criterion of maximizing the channel capacity, wherein the expression of the optimization objective function at the moment is as follows:
wherein d iskFor the number of equivalent independent channels obtained for receiver k,
rank () is the rank of the matrix.
2c) And establishing an optimization equation. Establishing an optimization equation consisting of the constraints set in step 2a) and the objective function selected in step 2b) as follows:
an objective function: <math>
<mrow>
<mi>max</mi>
<munder>
<mi>Σ</mi>
<mrow>
<mi>k</mi>
<mo>∈</mo>
<mi>K</mi>
</mrow>
</munder>
<msub>
<mi>d</mi>
<mi>k</mi>
</msub>
</mrow>
</math>
constraint conditions are as follows: <math>
<mfenced open='{' close=''>
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<mtd>
<msubsup>
<mi>U</mi>
<mi>k</mi>
<mi>H</mi>
</msubsup>
<msub>
<mi>H</mi>
<mi>kj</mi>
</msub>
<msub>
<mi>V</mi>
<mi>j</mi>
</msub>
<mo>≤</mo>
<msubsup>
<mi>σ</mi>
<mi>k</mi>
<mn>2</mn>
</msubsup>
<mi>I</mi>
<mo>/</mo>
<mi>λ</mi>
<mo>,</mo>
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</math>
the optimization equation is to find a beam forming matrix set and an interference elimination matrix set which enable the sum of channel capacities to be maximum under the constraint condition that the residual multi-user interference after the interference relaxation alignment is less than or equal to the maximum tolerable residual multi-user interference of the system.
And 3, solving an optimization equation to obtain an effective solution of the combined beam forming. Solving the optimization equation established in the step 2 through a joint processing center of the transmitting end to obtain a beam forming matrix set Vm(m ═ 1, 2.. L) and an interference cancellation matrix set UnAnd (n ═ 1, 2.. K), and respectively sending to the corresponding sending end and receiving end, wherein the beamforming matrix set is used for preprocessing of each sending end in step 4, and the interference cancellation matrix set is used for post-processing of each receiving end in step 5.
And 4, preprocessing the sending end. Each transmitting end respectively uses the beam forming matrix set V obtained in the step 3mAnd (m is 1, 2.. L), the corresponding beam forming matrix is multiplied by the transmission signal to complete the preprocessing step.
At the transmitting end 1, a beamforming matrix V is used1Left-hand multiplication of the transmission signal s1To obtain V1s1Then, it is transmitted;
at the transmitting end 2, the beamforming matrix V is used2Left-hand multiplication of the transmission signal s2To obtain V2s2Then, it is transmitted; at the transmitting end L, using a beamforming matrix VLLeft-hand multiplication of the transmission signal sLTo obtain VLsLAnd then transmits it.
And 5, post-processing at the receiving end. Using the interference elimination matrix set U obtained in step 3 respectively for each receiving endnAnd (n is 1, 2.. K), and performing post-processing by performing conjugate transpose and left multiplication on the received signal by using the corresponding interference cancellation matrix.
At the receiving end 1, using the interference cancellation matrix U1Conjugate transpose ofBy left-multiplying the received signal y1To obtain the final demodulated signalAt the receiving end 2, using interferenceEliminating matrix U2Conjugate transpose ofBy left-multiplying the received signal y2To obtain the final demodulated signalAt the receiving end K, using the interference cancellation matrix UKConjugate transpose ofBy left-multiplying the received signal yKTo obtain the final demodulated signal
Claims (5)
1. A method for aligning interference relaxation based on multi-point and multi-user cooperation downlink comprises the following steps:
(1) obtaining channel matrix parameters: according to the difference of the communication system on performance requirements and transmission modes, a sending end adopts a corresponding channel estimation technology to complete channel estimation to obtain channel matrix parameters;
(2) establishing an optimization equation
2a) Determining constraint conditions, and determining a corresponding relaxation factor lambda according to the maximum tolerable residual multi-user interference generated by different performance requirements of each system, wherein the relaxation factor lambda is the ratio of the residual multi-user interference to noise power; carrying out relaxation on the interference alignment constraint condition by using a relaxation factor lambda, wherein the relaxation is not more than the maximum tolerable residual multi-user interference, and obtaining the constraint condition of interference relaxation alignment;
the corresponding relaxation factor λ should satisfy the following formula:
wherein,to maximize the tolerable residual multi-user interference,
Ukfor the interference cancellation matrix at the kth receiver,
[·]Hrepresents the conjugate transpose of the matrix and,
Hkjfor the channel matrix parameters from the jth transmitting end to the kth receiving end,
Vjfor the beamforming matrix of the jth transmit end,
is the power of additive white gaussian noise,
i is an identity matrix;
2b) selecting an objective function: according to an optimization criterion for maximizing the channel capacity, selecting the maximum sum of equivalent independent channel numbers obtained by all receiving ends as a target function of an optimization equation;
2c) establishing an optimization equation consisting of constraint conditions and an objective function:
an objective function: <math>
<mrow>
<mi>max</mi>
<munder>
<mi>Σ</mi>
<mrow>
<mi>k</mi>
<mo>∈</mo>
<mi>K</mi>
</mrow>
</munder>
<msub>
<mi>d</mi>
<mi>k</mi>
</msub>
</mrow>
</math>
constraint conditions are as follows: <math>
<mfenced open='{' close=''>
<mtable>
<mtr>
<mtd>
<msubsup>
<mi>U</mi>
<mi>k</mi>
<mi>H</mi>
</msubsup>
<msub>
<mi>H</mi>
<mi>kj</mi>
</msub>
<msub>
<mi>V</mi>
<mi>j</mi>
</msub>
<mo>≤</mo>
<msubsup>
<mi>σ</mi>
<mi>k</mi>
<mn>2</mn>
</msubsup>
<mi>I</mi>
<mo>/</mo>
<mi>λ</mi>
</mtd>
<mtd>
<mo>∀</mo>
<mi>k</mi>
<mo>≠</mo>
<mi>j</mi>
</mtd>
</mtr>
<mtr>
<mtd>
<mi>rank</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>U</mi>
<mi>k</mi>
<mi>H</mi>
</msubsup>
<msub>
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<mi>kk</mi>
</msub>
<msub>
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</msub>
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</msub>
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<mo>≤</mo>
<mi>k</mi>
<mo>≤</mo>
<mi>K</mi>
</mtd>
</mtr>
</mtable>
</mfenced>
</math>
wherein d iskFor the number of equivalent independent channels obtained for receiver k,
Ukfor the interference cancellation matrix at the kth receiver,
[·]His the conjugate transpose of the matrix and,
Hkjfor the channel matrix parameters from the jth transmitting end to the kth receiving end,
Vjfor the beamforming matrix of the jth transmit end,
is the power of additive white gaussian noise,
i is an identity matrix and is a matrix of the identity,
rank () is the rank of the matrix,
Hkkfor the channel matrix parameters from the kth transmitting end to the kth receiving end,
Vkfor the beamforming matrix of the kth transmitting end,
k is the number of receiving ends, and the value range of K is a positive integer;
(3) solving an optimization equation to obtain a beam forming matrix set Vm(m =1, 2.. L) and an interference cancellation matrix set Un(n =1, 2.. K), where m denotes the number of transmitting ends, L denotes the number of transmitting ends, n denotes the number of receiving ends, and K denotes the number of receiving ends;
(4) each transmitting end is according to VmCorresponding to the mth sending end, respectively using the corresponding beamforming matrix in the obtained beamforming matrix set to be pre-multiplied by the sending signal to finish the preprocessing of the sending signal;
(5) each receiving end is according to UnCorresponding to the nth receiving end, respectively using the corresponding interference elimination matrix in the obtained interference elimination matrix setU n The received signal is multiplied by the left side by the conjugate transpose of (c), and the post-processing of the received signal is completed.
2. The method according to claim 1, wherein the performance of the communication system in step (1) includes spectrum utilization performance and delay performance.
3. The method according to claim 1, wherein the transmission modes of the communication system in step (1) include a burst transmission mode and a continuous transmission mode.
4. The method according to claim 1, wherein the corresponding channel estimation technique in step (1) employs blind estimation and reference signal-based estimation.
5. The method according to claim 1, wherein the performance in step (2) refers to the magnitude of the residual multiuser interference.
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| EP1816758A2 (en) * | 2006-02-03 | 2007-08-08 | Samsung Electronics Co.,Ltd. | Apparatus and method for determining beamforming vector in a codebook-based beamforming system |
| CN101227219A (en) * | 2008-01-31 | 2008-07-23 | 上海交通大学 | Signal processing method of multi-user multi-aerial communication system transmit-receive combination |
| CN101902306A (en) * | 2009-05-26 | 2010-12-01 | 中兴通讯股份有限公司 | Method and device for multi-antenna space-time processing received data and block interference cancellation |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1816758A2 (en) * | 2006-02-03 | 2007-08-08 | Samsung Electronics Co.,Ltd. | Apparatus and method for determining beamforming vector in a codebook-based beamforming system |
| CN101227219A (en) * | 2008-01-31 | 2008-07-23 | 上海交通大学 | Signal processing method of multi-user multi-aerial communication system transmit-receive combination |
| CN101902306A (en) * | 2009-05-26 | 2010-12-01 | 中兴通讯股份有限公司 | Method and device for multi-antenna space-time processing received data and block interference cancellation |
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