CN109120320A - Precoding technique based on time reversal in extensive MIMO network - Google Patents

Abstract

The invention relates to anti-interference technical means of massive MIMO network, in particular to the fusion and improvement of time inversion technology and precoding technology in massive MIMO network to achieve the purpose of interference suppression. The technology optimizes channels on the basis of time inversion technology, Using the space-time focusing of time inversion technology to achieve energy focusing; improving on the basis of zero-forcing precoding technology, through zero-forcing precoding in multipath environment to reduce inter-user interference and co-channel interference in massive MIMO systems, in order to achieve For the purpose of interference suppression, the receiver antenna can obtain the channel state information of the multipath channel at the base station antenna through channel detection, perform up-sampling at the base station antenna to reduce the symbol transmission rate, and reduce the number of users under multipath channel conditions through zero-forcing precoding. Therefore, the time-reversal-based precoding anti-jamming technology can reduce the average bit error rate, significantly improve the signal-to-interference-to-noise ratio, and the achievable rate of massive MIMO systems.

Description

Precoding Technology Based on Time Reversal in Massive MIMO Networks

technical field

The invention relates to the field of interference suppression in a MIMO network, in particular to a precoding technology based on time inversion in a massive MIMO network.

Background technique

With the continuous advancement of wireless technology, people's requirements for information transmission rate and data accuracy are also increasing. At the same time, the rapid increase in the number of mobile terminals has led to a shortage of originally limited frequency resources. The input multiple output system can no longer meet the above requirements. In order to meet this requirement, massive MIMO technology is proposed. Massive MIMO technology refers to the communication method that hundreds of antennas are installed on the base station side to serve many user terminals at the same time and frequency. , Compared with the traditional MIMO technology, it has higher spectrum utilization and energy efficiency. In the future cell network, massive MIMO can achieve high energy efficiency, and with the continuous increase of the number of base station antennas, some irrelevant Noise and fast fading gradually disappear, and only slow fading and inter-user interference affect users. It is precisely because of the large number of antennas in the massive MIMO system and the large number of serving users that there are inter-user interference and pilot pollution problems. Research shows that with the increase of the number of antennas, the interference caused by pilot pollution becomes a constraint for multi-cell. Important reasons for multi-user Massive MIMO systems.

The precoding technology in the current research is divided into two types: linear and non-linear. The method of linearly processing signals on the base station side is called linear precoding, which mainly includes: zero-forcing linear precoding, minimum mean square error linear precoding, matched filter precoding, etc. Non-linear precoding is to add design to the transmitted signal A good precoding vector is used to achieve the precoding method to suppress inter-user interference, which mainly includes: dirty paper coding, THP, etc. In general, the performance of nonlinear precoding is better than linear precoding. Although the current precoding technology can be certain To a certain extent, the inter-user interference and co-channel interference are reduced, but the precoding matrix leads to high complexity. Future and current research is also in reducing the complexity.

Time inversion technology is to perform a reverse order operation on the received signal in the time domain. It reverses the signal in the order in which it arrives at the receiving end. This technology can realize the focusing of the signal in time and space, the so-called time. Time focusing of inversion means that the maximum energy of each time-reversed signal transmitted through multipath in a complex medium will reach the target receiving point at the same time to achieve energy focusing in time, while spatial focusing means that there is no In the case of prior knowledge about the target receiving point, the time-reversed signal will be adaptively focused to the location of the target receiving point to achieve spatial energy accumulation. This spatiotemporal focusing characteristic of time inversion technology can effectively compensate for non-uniformity Signal multipath delay attenuation caused by complex environment or medium, so it has great potential in applications such as communication and detection. Due to space-time focusing, time inversion technology can be easily applied to ultra-wideband wireless communication systems. With the cooperation of the antenna, not only a very high array gain can be obtained, the signal-to-noise ratio can be improved, the interference between users can be suppressed, the design of the receiver can be simplified, and effective confidential communication can be realized.

In the rich multipath scattering environment, the time inversion regards the multipath channel as a distributed antenna. This high-resolution space-time focusing characteristic is reflected by the convolution time inversion channel impulse response, so the time inversion can effectively eliminate the code However, time inversion technology cannot fundamentally eliminate co-channel interference and inter-user interference. According to existing research, IUI is the main system performance limiting factor in multi-user time inversion systems. In this case, the time-reversal precoding technology of massive MIMO is proposed to eliminate the inter-user interference and co-channel interference in MIMO. The precoding technology in massive MIMO means that on the downlink, the base station will In the process of signal processing, the purpose of suppressing inter-user interference is achieved through linear precoding or non-linear precoding.

SUMMARY OF THE INVENTION

In order to solve the above technical problems, the present invention proposes a zero-forcing precoding method based on time inversion technology for the existing precoding technology. The precoding technology based on time inversion can better suppress interference and improve system capacity.

The precoding technology based on time inversion in the massive MIMO network of the present invention includes:

101. Determine the system model of the massive MIMO network and the channel sounding signal of the terminal antenna;

102. The base station antenna performs channel modeling on the multipath channel through the channel sounding signal and performs time inversion to determine the time inversion signal at the base station antenna;

103. Derive a corresponding single-user channel interference matrix through a channel modeling matrix;

104. Perform channel singular value decomposition on the interference matrix, and design the MIMO channel precoding matrix of the user terminal at the base station antenna end by using the zero-forcing precoding technology;

105. Through the channel precoding matrix, the load signal and the time-reversed signal of the terminal user can obtain the corresponding load signal at the user terminal, so that the performance of the scheme in reducing the interference between users and improving the signal-to-interference ratio can be determined by comparison. .

The invention has successively gone through channel detection, multipath channel modeling, interference channel analysis, channel precoding matrix design and time inversion precoding signal transmission derivation. The high antenna array gain improves the signal-to-interference-noise ratio, suppresses inter-user interference, and realizes effective secure communication. The multi-user MIMO channel is precoded. Since the base station antenna can accurately obtain the channel state information of each user, the base station antenna adopts the method of feedback interference cancellation, which can achieve interference suppression between users, significantly improve the signal-to-interference noise ratio, and reduce the bit error rate. , to improve system performance.

Description of drawings

Fig. 1 Multipath channel model diagram of massive MIMO network system;

Fig. 2 is the time-reversed precoding matrix derivation schematic diagram of the time-reversed precoding matrix based on the time-reversed precoding technology in the massive MIMO network of the present invention;

3 is a time-reversed transmission model in step 102 of the precoding technique based on time-reversal in a massive MIMO network of the present invention;

FIG. 4 is a simulation simulation of the precoding technology based on time inversion under the conditions of the number M of base station antennas and the number N of single-antenna users at the receiving end.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific simulation examples in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

Time inversion technology is to perform a reverse sequence operation on the received signal in the time domain. It reverses the signal in the order in which it arrives at the receiving end. In the frequency domain, it is equivalent to phase conjugation. This technology can achieve The focus of the signal in time and space, the so-called time-reversed time-focusing means that the maximum energy of each time-reversed signal after multipath transmission in a complex medium will arrive at the target receiving point at the same time, so as to realize the temporal focus. Energy focusing, while spatial focusing means that, without any prior knowledge about the target receiving point, the time-reversed signal will adaptively focus on the location of the target receiving point to achieve spatial energy gathering and time inversion. This spatiotemporal focusing feature of the technology can effectively compensate for the multipath delay and attenuation of signals caused by non-uniform and complex environments or media, so it has great potential in applications such as communication and detection.

The time inversion technology can be divided into three processes, as shown in Figure 3: First, suppose there is a signal source somewhere in space, which transmits a pulse signal outward, passes through a transmission channel with multipath effect, and is recorded by an array of wireless transceivers And save it, secondly, perform time inversion processing on these received signals, and finally, transmit these time-reversed signals from the positions of each transceiver to the same channel as in the first step, then they are The original signal source will be focused, and the characteristics of the pulsed signal source will be approximately restored.

The time-space focusing characteristics of time inversion technology determine that only in a very small spatial range and a very narrow time range, the signal reaches the strongest, and beyond its spatial focus range and time focus range, the signal is extremely weak, so the time This spatio-temporal focusing characteristic of the inversion technology has good security and confidentiality transmission characteristics, the spatial focusing characteristics of time inversion and the different channels contained in these time-reversed signals make the interception position of these time-reversed signals (signal). The maximum point in space) is different. Using the time-space focusing of time inversion technology, research and exploration are carried out from the aspects of physical layer key scheme, artificial interference noise, and anti-eavesdropping based on energy focusing. Based on the model, a safe and effective information transmission mechanism is established, and time inversion can effectively eliminate inter-symbol interference (ISI) and inter-user interference (IUI). Because of its unique characteristics, it can effectively capture the energy of multipath propagation signals, so the system signal-to-noise ratio can be effectively improved.

Aiming at the problem of inter-user interference caused by the increase of the number of base station antennas and the number of user terminals in massive multiple-input multiple-output networks, a precoding anti-interference technology based on time inversion in massive MIMO networks is proposed. The channel optimization is carried out on the basis of the inversion technology, and the space-time focusing of the time inversion technology is used to achieve energy focusing. At the same time, the zero-forcing precoding technology is used to reduce the inter-user interference and co-channel interference in the massive MIMO system. The simulation results verify the time inversion precoding. Anti-jamming technology can reduce the average bit error rate, and significantly improve the signal-to-interference-noise ratio and the achievable rate of massive MIMO systems.

According to Fig. 1, the implementation of each step of the present invention is introduced, including:

101. Determine the system model of the massive MIMO network and the channel sounding signal of the terminal antenna;

102. The base station antenna performs channel modeling on the multipath channel through the channel sounding signal and performs time inversion to determine the time inversion signal at the base station antenna;

103. Derive a corresponding single-user channel interference matrix through a channel modeling matrix;

104. Perform channel singular value decomposition on the interference matrix, and design the MIMO channel precoding matrix of the user terminal at the base station antenna end by using the zero-forcing precoding technology;

105. Through the channel precoding matrix, the load signal and the time-reversed signal of the terminal user can obtain the corresponding load signal at the user terminal, so that the performance of the scheme in reducing the interference between users and improving the signal-to-interference ratio can be determined by comparison. .

Embodiments of each step of the present invention will be introduced below.

In the step 101, determine the system model of the massive MIMO network and the channel sounding signal of the terminal antenna; that is, according to the digital baseband downlink wireless transmission system, the transmission system is set as a massive MIMO time division duplex channel, and its multipath channels are relatively independent And it obeys multipath Rayleigh fading. The system model is shown in Figure 1. The base station has M transmit antennas and N single-antenna user terminals. The base station transmit antenna sends an independent data stream to the user. Define X(j) as sending The signal to user j, whose j∈[1,2,...,N], ^t∈Z is the continuous time coefficient, defines the additive white Gaussian noise of n(t) with mean 0 and variance σ2.

In step 102, the base station antenna performs channel modeling on the multipath channel through the channel detection signal and performs time inversion to determine the time inversion signal at the base station antenna; after the time inversion passes through the detection phase and the retransmission phase, the receiver receives The time-reversed signal with load information is represented as: Among them, a is the downlink transmit power, assuming that these transmitted signals have unit average power, H(t) is the downlink channel matrix, and H ^T (-t) is the time-reversed signal of the probe signal at the receiving end antenna. The channel matrix (which is the reverse order operation of the detection signal in the time domain, which is equivalent to the phase conjugation in the frequency domain), p(-t) is the reverse order operation of the detection signal. Under the conditions, the load signal can achieve perfect information transmission in the MIMO system through time inversion technology. In a massive MIMO system, the base station antenna needs to communicate with multiple UEs simultaneously. Specifically, as shown in Fig. 1, the up-sampling representation of the load signal is to be sent to the j-th user terminal information (which is represented as X(j)), firstly, up-sampling is performed by the sampling factor D to reduce the inter-symbol The interference is then pre-coded through the channel matrix. In fact, in order to suppress the ISI caused by the multipath channel, the introduction of the sampling factor D also reduces the symbol transmission rate.

After the signal form is upsampled, its representation is: For a single-antenna user terminal, it is assumed that the signal is transmitted from the base station antenna to the user terminal through L multipath channels, so the time-reversed transmission of the received system signal without the precoding matrix is expressed as:

The above formula includes four parts: the user's desired signal part, the inter-user interference and inter-symbol interference received by user j from other users, and the additive white Gaussian noise with a mean value of 0 and a variance of σ ² in the channel.

Described step 103, deriving the corresponding single user channel interference matrix through the channel modeling matrix;

Due to the fact that the channel state information has multipath delay and Doppler frequency shift, etc., time inversion is not fully applicable to the actual massive MIMO scenario, and the channel state information has Rayleigh fading, large-scale fading and shadowing With fading factors such as fading, the inter-user interference also increases under ideal conditions. Therefore, in massive MIMO systems, inter-user interference becomes the main factor restricting performance. In order to suppress the IUI in the channel, the corresponding single User channel interference matrix, which defines the interference channel of user j: The precoding matrix Mj is designed by the block diagonalization method so that the precoding matrix is in the null space of the interference channel of user _j , so the high capacity potential of the single-antenna user channel can be realized by transmitting multiple data subchannels in parallel.

In step 104, channel singular value decomposition is performed on the interference matrix, and a MIMO channel precoding matrix of the user terminal is designed at the base station antenna end by using the zero-forcing precoding technology;

The zero-forcing precoding of the downlink in the MIMO system in the multipath environment is used to derive the precoding matrix for the user interference channel. The precoding technology based on time inversion can also use the block diagonalization method. The singular value decomposition of , and its singular value matrix is defined as: in, is the orthonormal basis of the null space of the interference matrix, let represent rank, and as The rightmost orthogonal basis of , so it can be used to derive the user precoding matrix M _j , in order to make the information transmission of user j in the interference channel in the null space, needs to be satisfied Therefore, the load signal generally needs to avoid convolutional spatial multiplexing of highly correlated channel matrices. For time-reversed channels, all rows of H _j are the same as In this way, a higher degree of freedom can be obtained when constructing the precoding matrix. Assuming that the relatively independent channel conditions satisfy each user terminal, define H' _S as the channel matrix relative to the null space of the interference channel after the channel singular value decomposition :

Using a solution based on singular value decomposition and zero-forcing precoding, the total achievable rate of the system is reaches the maximum in the null space of , and the singular value decomposition expression for H′ _S is:

select As the precoding matrix of user j, the equivalent transmission channel of user j is After the load signal is transmitted through the multipath channel, the signal received by the user terminal can be expressed as:

It can be seen that there are parallel sub-channels between user j and the base station antenna, which eliminates inter-user interference. Therefore, for the precoding technology based on time inversion of the present invention, the precoding matrix according to the singular value decomposition of the equivalent transmission channel is selected as : Among them, the Λ matrix is a diagonal matrix with eigenvalues of diagonal elements.

The load signal X _j at the antenna end of the base station is sampled by a discrete signal model after the time-reversal cavity and precoding matrix. The system signal transmission formula of user j at the receiving end is:

Finally, the inter-user interference can approach zero after time inversion and zero-forcing precoding matrix, and the inter-symbol interference can also be suppressed to a certain extent after time inversion and sampling. The additive white Gaussian noise has been enhanced to a certain extent, so in the case of high signal-to-noise ratio, the time-reversal precoding technique can obtain a higher signal-to-interference-to-noise ratio.

In step 105, the load signal and the time-reversed signal of the terminal user can obtain the corresponding load signal at the user terminal through the channel precoding matrix, so that it can be determined by comparison that the scheme can reduce the interference between users and improve the signal-to-interference ratio. aspect performance.

The power of the desired signal that can be received at the receiving end should be a without considering the channel attenuation. For the inter-symbol interference signal power of user j, its value is related to the sampling factor D and the number of multipath channels L, so the ISI The power greatly depends on the transmission environment. Similarly, as the transmission antenna M increases, the inter-user interference at the receiving end j will also increase, so it can be deduced that:

The power of the desired signal received by the receiver is:

The intersymbol interference power is:

The inter-user interference power is:

The signal-to-interference-to-noise ratio at the receiver is:

The performance of the research system is evaluated by calculating the average user bit error rate. According to the formula derivation method of the bit error rate of the maximum likelihood ratio precoding method, the performance of the load signal transmitted by each user of the massive MIMO system via the multipath channel depends on the The precoding scheme used, in addition, due to the diagonal zero-forcing precoding function, the information-carrying signal is statistically dependent on the multipath channel and the implementation of upsampling at the user end, which affects the user power, intersymbol interference power, and upsampling at the receiving end. Inter-user interference power, therefore, ρ is defined as the transmit signal-to-noise ratio, that is, the ratio between the total transmit power P _ε and the additive white Gaussian noise power σ ² :

For calculating the average bit error rate of QPSK modulation, the theoretical performance of the proposed massive MIMO system is evaluated by transmitting the signal-to-noise ratio function. As a modulation method, the signal-to-noise ratio for the receiving end user is defined as:

SNR=xρ

where x is the probability density function of the expected signal P _sig (k) after the load signal at the receiving end passes through the precoding matrix, so the bit error rate at the user end is expressed as:

For the time-reversal precoding technology, the transmission signal-to-noise ratio of the block zero-forcing precoding is defined, and the inter-symbol interference is ignored. After the precoding technology proposed in this paper suppresses the inter-user interference, the expression of ρ _ZF is:

in, is the independent and identically distributed standard deviation of The Gaussian variable set of , which satisfies the shape parameter of _NR and the scale parameter of 2σ ² =1 gamma distribution. According to the probability density function of the gamma distribution, its probability density function is defined as:

Therefore, the bit error rate of massive MIMO system is expressed as:

The above is a detailed elaboration of the anti-interference method based on time-reversal precoding in the present invention, which aims to minimize inter-user interference in massive MIMO networks and ensure efficient and accurate transmission of load signals in multipath channels. The following The performance of the time-reversal precoding anti-jamming method in massive MIMO networks will be simulated and visualized, combined with specific scenarios to help readers understand, and the anti-jamming performance of the time-reversal precoding anti-jamming method will be compared. illustrate.

In the simulation example, we consider Rayleigh fading in MIMO communication network, the multipath channel in the system model obeys the Rayleigh fading of CN(0,0.5), shadow fading and free path loss mainly consider the gain and fading under ideal multipath environment , the simulation running platform is matlab7.1 under windows. In the simulated network system, the channel bandwidth is W=500MHz, the upsampling factor of the load signal is set to D=15, the number of frames per second in the simulation is set to 10 ² frames, the number of bits per frame is 10 ³ , and the multipath channel is set to It is determined as 1000 spatial correlation channels to realize, and it is analyzed and compared through the number M of base station antennas and the number N of single-antenna users at the receiving end.

The simulation sets the system performance analysis of time-reversal precoding technology and traditional time-reversal technology in massive MIMO scenarios when the number of base station antennas is the same and compared with the number of users. The number of base station antennas is M=64, and the number of users is N. Under the same upsampling factor D, when the number of base stations remains unchanged, as the number of single-antenna users at the receiving end increases. increase, the power of the information component at the user end decreases, and the inter-user interference increases. Therefore, as the number of users increases, the inter-user interference increases, and the inter-symbol interference also increases accordingly, and the bit error rate of each user is also higher. In the massive MIMO scenario, the time-reversal precoding technology has a signal-to-noise ratio of -10dB under the same conditions, and when N=10, the simulation results are consistent with the theoretical analysis value of 0.084, which is smaller than 0.113 and 0.113 of the common precoding technology. The time inversion technology is 0.093, with the continuous increase of SNR, the bit error rate of ordinary precoding technology gradually becomes stable at 5dB, and finally its minimum bit error rate can reach 0.87*10 ^-4 . Under the same conditions, the precoding technology based on time inversion The bit error rate of the coding technology can reach 10 ^-8 , which is much lower than that of the time inversion technology and the common precoding technology. When the number of users on a single antenna is set to be the same, the average bit error rate of the users is compared when the number of base station antennas is different. In terms of inversion technology, the number of base station antennas increases, and the useful signal power also increases, but the correlation of base station load signals also increases. For inter-user interference, the number of users does not change, and the interference will increase with the increase of the number of base station antennas. When the number of base station antennas M is set to 64 and 128 respectively, the average bit error rate of users also increases with the increase of the number of antennas. Specifically, the number of base station antennas is N=10, and the number of single-antenna user terminals is When the SNR is -10dB, the simulation result and the theoretical analysis value are roughly the same, which is 0.136, which is smaller than 0.574 of the common precoding technology and 0.326 of the time inversion technology. When it is 0-5dB, it gradually becomes stable, and finally the bit error rate of the time-reversal-based precoding technology can reach a minimum of 0.724*10 ^-5 . Therefore, under the same conditions, the bit error rate performance of the time-reversal-based precoding technology is far Less than time inversion technology and common precoding technology.

In addition, under the condition of the same number of base station antennas, the influence of different single-antenna users at the receiving end on the achievable rate is compared. For the wireless multipath transmission environment, the research shows that the more base station transmission antennas, the higher the achievable rate of the system, and the single-antenna users at the receiving end. The more the number, the higher the reachable rate of the system. For the research on the influence of the number of base station antennas on the reachable rate, in the simulation stage of the present invention, when the number of single-antenna user terminals N is 10, the number of base station antennas is 32 and 64. Rate comparison, it can be seen from Figure 4 that the precoding technology based on time inversion has a signal-to-noise ratio of -30dB, and when M=64, its achievable rate is 31.5bps/Hz, which is greater than the time inversion technology. 26.3bps/Hz Compared with 27.7bps/Hz of common precoding technology, with the continuous increase of SNR, the achievable rate of the three anti-interference technologies will remain stable, and the achievable rate of time-reversal precoding technology will reach 49.8bps/Hz, which is much higher. Based on the time inversion anti-jamming technology of 40.4bps/Hz and the common precoding technology of 35.1bps/Hz, comparing the influence of single-antenna users at different receivers on the achievable rate under the same number of base station antennas, for the wireless multipath transmission environment, research It shows that the more base station transmission antennas, the higher the achievable rate of the system, the more the number of single-antenna users at the receiving end, and the higher the achievable rate of the system. , which can provide higher multiplexing gain.

The embodiments or examples of the present invention describe in detail the objectives, technical solutions and advantages of the present invention. It should be understood that the above-mentioned embodiments or examples are only preferred embodiments of the present invention, and are not intended to be used for To limit the present invention, any modification, equivalent replacement, improvement, etc. made to the present invention within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (9)

1. The precoding technology based on time reversal in the large-scale MIMO network is characterized in that: the method comprises the following steps:

101. determining a system model of a large-scale MIMO network and a channel detection signal of a terminal antenna;

102. the base station antenna carries out channel modeling and time reversal on a multipath channel through a channel detection signal, and determines a time reversal signal of the base station antenna end;

103. deducing a corresponding single user channel interference matrix through a channel modeling matrix;

104. performing channel singular value decomposition on the interference matrix, and designing an MIMO channel precoding matrix of the user terminal at the antenna end of the base station through a zero-forcing precoding technology;

105. the load signal and the time reversal signal of the terminal user can obtain the corresponding load signal at the user terminal through the channel pre-coding matrix, so that the performance of the scheme in the aspects of reducing the interference between users and improving the signal-to-interference ratio can be judged through comparison.

2. The precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein: after the time reversal passes through the detection stage and the re-emission stage, a receiving end receives a time reversal signal with load information, and the representation form is as follows:because time reversal has space-time focusing property, under ideal channel condition, the load signal can realize perfect information transmission in MIMO system by time reversal technique.

3. The precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein: in a massive MIMO system, a base station antenna needs to communicate with multiple user terminals simultaneously, specifically, for an up-sampling representation of a load signal, information (denoted as x (j)) to a jth user terminal is sent, and is first up-sampled by a sampling factor D to reduce inter-symbol interference, and then precoded through a channel matrix.

4. The precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein the representation form of the signal after up-sampling is:for a single-antenna subscriber terminal, it is assumed that the signal is transmitted from the base station antenna to the subscriber terminal via L multipath channels and is thus receivedThe time-reversal transmission of the system signal without the pre-coding matrix is represented as:

the above formula contains 4 moieties: the user desired signal portion, the user j received the inter-user interference, the inter-symbol interference and the mean value of the channel from other users are 0, and the variance is sigma²White additive gaussian noise.

5. The method of claim 3, wherein the interference matrix of the corresponding single user channel is derived by a channel modeling matrix, and the interference channel of the user j is defined as follows:design precoding matrix M by block diagonalization method_jThe precoding matrix is in the null space of the interfering channel of user j, so the high capacity potential of a single antenna user channel can be achieved by transmitting multiple data subchannels in parallel.

6. The precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein the precoding matrix derivation is performed on the user interference channel by the zero-forcing precoding in downlink in MIMO system under multipath environment, and the precoding technique based on time reversal can also be performed by using block diagonalization methodThe singular value matrix is defined as:wherein,for orthogonal basis of null space of interference matrix, orderRepresentsIs of a rank ofAsSo it can be used to derive the user precoding matrix M_j。

7. The precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein the information transmission of user j is in interference channelIn the null space of (a) or (b),need to satisfyIn general, it is therefore desirable to avoid convolving spatially-multiplexed highly correlated channel matrices, H for time-reversed channels_jAll rows of (2) are connected toIs linearly independent, so that a higher degree of freedom can be obtained in constructing the precoding matrix, and H 'is defined assuming that relatively independent channel conditions satisfy each user terminal'_SThe channel matrix of the null space relative to the interference channel after the singular value decomposition of the channel is as follows:

8. the precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein the solution based on singular value decomposition and zero-forcing precoding is used to make the total achievable rate of the system atIs maximized in the null space of (1), let H'_SThe singular value decomposition expression used is:

selectingAs the precoding matrix for user j. So that the equivalent transmission channel for user j isAfter the load signal is transmitted through the multipath channel, the signal received by the user terminal can be represented as:

therefore, parallel sub-channels exist between the user j and the base station antenna, and interference among users is eliminated. Therefore, in the precoding technology based on time reversal in the large-scale MIMO network, through singular value decomposition, the precoding matrix is selected as follows:wherein, the Λ matrix is a diagonal matrix with eigenvalues as diagonal elements.

9. The precoding technique based on time reversal in massive MIMO network as claimed in claim 1, wherein the base station antenna end loads signal X_jTime-lapse inversion chamberAfter the precoding matrix is matched, sampling is carried out by a discrete signal model, and a system signal transmission formula of a receiving end user j is as follows:

finally, the inter-user interference can approach to zero after time reversal and zero forcing precoding matrix, the inter-symbol interference is also inhibited to a certain extent after time reversal and sampling, but due to the existence of the precoding matrix, additive white Gaussian noise in a channel is enhanced to a certain extent, so that under the condition of high signal-to-noise ratio, the time reversal precoding technology can obtain higher signal-to-interference-plus-noise ratio.