CN101232356A - Precoding method, system and device in MIMO system - Google Patents

Abstract

The invention discloses a precoding method, system and device in a MIMO system. The method, system and device involved in the present invention can be applied in the case of orthogonal space-time coding. The method of the present invention adopts a non-unitary matrix for precoding, and the non-unitary matrix is constructed from the optimal precoding vector obtained by judgment. The system of the present invention includes a transmitter and a receiver, wherein the transmitter includes a codebook list, a precoding matrix construction unit and a precoding unit; the receiver includes a channel estimation unit, a codebook list and a decision unit. Through simulation and analysis, it can be known that, compared with the prior art, the scheme of the present invention can lower the bit error rate and reduce the decoding complexity under the same signal-to-noise ratio.

Description

Precoding method, system and device in MIMO system

technical field

The present invention relates to wireless communication technology, in particular to a precoding technology in MIMO system.

Background technique

Research on information theory proves that the communication system using multiple antennas can obtain higher channel capacity. Under the assumption that the channel is independent Rayleigh fading and the receiver knows the channel state information, the multiple-input multiple-output of multiple antennas is used at both the transmitting end and the receiving end. (Multiple Input Multiple Output, MIMO) The theoretical channel capacity of the system increases approximately linearly with the smaller value of the number of transmitting antennas and the number of receiving antennas. The way the MIMO system increases capacity is called space division multiplexing. The MIMO-OFDM system that combines the MIMO system with Orthogonal Frequency Division Multiplexing (OFDM) technology can effectively combat the multipath fading of the wireless channel, and is recognized as the most competitive technology in the fourth-generation mobile communication .

MIMO can use multiple independent channel gains to combat wireless channel fading, which is called diversity, including space diversity, time diversity and frequency diversity. Among them, Vertical Bell Laboratory Layer Space-Time Codes (V-BLAST) structure and Orthogonal Space-Time Block Codes (OSTBC) combine space division multiplexing and time diversity, Both of these encoding methods belong to space-time encoding schemes.

Usually, the transmitter of a MIMO system does not know the channel state information. However, if the transmitter can know the channel state information, we can process the transmitted signal at the transmitter to reduce interference and improve the average received SNR (Signal to Noise Ratio). Ratio, SNR), thereby reducing the average symbol error rate, we call this processing at the transmitter as precoding. The channel state information required by the transmitter can be instantaneous channel estimation, or first-order or second-order statistical information of channel estimation, which depends on the time fading characteristics of the channel. For example, for fast fading systems, we generally use channel estimation Statistical characteristics are used to reflect channel information; and for slow fading systems, we generally use instantaneous channel estimation.

In a symmetrical time division duplex (Time Division Duplex, TDD) system, the channel information of the uplink and downlink channels can be shared with each other. In this case, there is no need to make any changes to the system structure, and both the base station and the mobile station can use precoding . However, for an asymmetric time division duplex system or a frequency division duplex (Frequency Division Duplex, FDD) system, the situation is completely different. Taking the downlink precoding of such systems as an example, due to the asymmetry of the uplink and downlink channels, the receiving end It is necessary to pass the channel information to the transmitter through a feedback channel so that it can know the downlink channel. We call this MIMO system using the feedback mechanism a closed-loop MIMO (Closed-loop MIMO, CL-MIMO) system. Correspondingly, there is no feedback The current MIMO system is an open-loop MIMO (Open MIMO, OP-MIMO) system. The closed-loop MIMO system can optimize the system performance through feedback and make better use of the advantages of MIMO, so it has become one of the hotspots of MIMO research recently.

However, the channel information increases with the product of the number of transmit antennas, the number of receive antennas, and the number of users. For MIMO channel capacity, which increases linearly with the number of transmit antennas or the number of receive antennas, it is difficult to feed back complete channel information (ideal feedback) in practical systems. realized in. The limited feedback precoding scheme can solve the above problems. A closed-loop MIMO system using limited feedback precoding stores a set of precoding matrices, called codebooks, at both ends of the transceiver in advance. At the receiving end, the system selects the optimal precoding matrix from the codebook according to channel estimation and a certain decision criterion, and feeds back its index to the sending end, and the sending end obtains the precoding matrix according to the index. Taking a codebook containing N precoding matrices as an example, the limited feedback precoding scheme only needs to feed back log ₂ N bits to obtain the precoding matrix, which greatly reduces the amount of feedback information. It can be said that limited feedback precoding is the quantization of the ideal precoding matrix space.

At present, most of the precoding research literature and IEEE802.16e protocol standard draft adopt the above precoding scheme. The IEEE802.16e physical layer combines it with three space-time coding schemes, namely beamforming (BF), vertical A combination of layered space-time coding and orthogonal space-time block codes.

The structure and working process of a MIMO-OFDM system with limited feedback precoding are shown in Fig. 1 .

At the sending end, the data to be sent is first modulated to generate modulated symbols, and then the modulated symbols are subjected to space-time mapping (that is, space-time coding), and the signal obtained by space-time mapping is precoded, and finally undergoes inverse fast Fourier transform. , D\A conversion, up-mixing, and finally transmit the signal through the antenna. Wherein, in the precoding stage, the sending end receives the feedback information sent by the receiving end through the feedback channel, and the information informs the sending end which precoding matrix should be selected for precoding. After receiving the information, the sending end selects the precoding matrix in the codebook set, and uses the matrix to precode the signal obtained by space-time mapping.

At the receiving end, after the antenna receives the signal, on the one hand, the signal is down-mixed, A\D transformed, and fast Fourier transformed. The transformed signal is used as one of the input signals of the decoder. Estimation and optimal decision criteria, select the optimal precoding matrix from the codebook, feed back its serial number to the transmitter through the feedback channel, and at the same time, send the last optimal precoding matrix and channel estimation to the decoder for decoding . The specific decision process is as follows: the receiving end device performs channel estimation according to the received signal, uses the channel condition information obtained by channel estimation, and combines each precoding matrix in the codebook set to make an optimal decision, and passes the decision result through the feedback channel sent to the sender.

The key of limited feedback precoding is the codebook and the optimal decision criterion, both of which will directly affect the bit error rate performance of the system. Assuming that the optimal precoding matrix obtained through judgment is F, the draft IEEE802.16e protocol believes that according to the precoding theory, precoding does not increase the total transmission power, that is, satisfies

$\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}^{{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}}{\mathrm{<span\; class="notranslate">\; max</span>}}\frac{{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; Fs</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Among them, s represents a set of transmitted signal vectors, S represents the modulation symbol set, and ‖·‖ ₂ represents the vector 2 norm. Because the unitary matrix has the property of not changing the vector norm, a unitary matrix (when the number of transmitting antennas is equal to the number of data streams) or a quasi-unitary matrix (when the number of transmitting antennas is greater than the number of streams) is often used as the precoding matrix in precoding.

The IEEE802.16e protocol draft also adopts unitary matrix precoding. Therefore, the precoding matrix F specified in the draft protocol is a unitary matrix (when the number of transmitting antennas is equal to the number of data streams) or a pseudo-unitary matrix (when the number of transmitting antennas is greater than the number of streams).

In addition, the codebooks are classified according to different numbers of transmit antennas, different numbers of data streams, and different configurations of feedback bits. The IEEE802.16e protocol draft also proposes a codebook classification method, which defines The number of streams and the number of different feedback bits configure the codebook. The available codebooks given in the draft are shown in Table 1. "-" indicates that the codebook is not specified in the protocol.

Table 1 IEEE802.16e protocol codebook

Therefore, when the receiving end receives the signal, it selects one of the codebooks shown in Table 1 to make an optimal decision according to the number of transmitting antennas, data streams, and feedback bits.

Taking Alamouti orthogonal space-time block coding with 2 transmissions and 1 reception as an example, if the number of feedback bits is 3 bits, the optimal precoding matrix F is selected from the (2, 2, 3) codebook set in Table 1; if The number of feedback bits is 6 bits, then F is selected from the (2, 2, 6) codebook set in Table 1.

The purpose of the optimal decision is to minimize the bit error rate or maximize the capacity. Specifically, depending on the decoding algorithm, the specific expression of the optimal decision criterion for minimizing the bit error rate is

$\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&Phi;</span>}}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; max</span>}}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; HF</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, Ф represents the codebook set, and ‖·‖ _F represents the Frobenius norm of the matrix. If the judgment result shows that F is the optimal precoding matrix, then the serial number i of the optimal precoding matrix in the codebook is fed back to the sending end.

Contents of the invention

In the background technology part, the orthogonal space-time block coding in the above example is a kind of orthogonal space-time coding, and the orthogonal characteristic of the orthogonal space-time coding has the characteristic of not changing the channel distribution characteristics. At the same time, the unitary matrix also has the characteristic of not changing the channel distribution characteristics. In fact, if it is desired not to change the channel distribution characteristics during encoding, it is only necessary to perform encoding without changing the channel distribution characteristics once, and it is not necessary to perform such encoding more than twice. Therefore, if we have adopted orthogonal space-time coding in MIMO-OFDM system, non-unitary matrix can be used in precoding.

At the same time, in wireless transmission, it is always desired to achieve better bit error rate performance under the same SNR, that is, to obtain as large a SNR gain as possible. The purpose of the specific embodiment of the present invention is to provide a method, system and device for precoding using a non-unitary matrix in the aforementioned system, so as to obtain a better bit error rate under the condition that the channel distribution characteristics are not changed performance.

A specific embodiment of the present invention provides a precoding method in a MIMO system, the method adopts orthogonal space-time coding, and adopts more than two data stream numbers, and includes:

Select the optimal precoding vector in the beamforming codebook;

Constructing a precoding matrix by using the optimal precoding vector;

Precoding is performed using the precoding matrix.

The specific embodiment of the present invention further provides a MIMO system using limited feedback precoding, and the system includes a transmitter and a receiver. The system employs orthogonal space-time coding and employs more than two data stream numbers; and,

The receiver includes:

a channel estimation unit, configured to perform channel estimation, and provide the channel estimation result to the decision unit;

A codebook list storage unit, configured to provide a precoding matrix or a precoding vector to the decision unit;

a decision unit, configured to select an optimal precoding vector from the beamforming codebook of the codebook list storage unit according to the channel estimation result provided by the channel estimation unit and the set decision criterion, and store the optimal precoding vector The information of the coding vector is fed back to the transmitter;

The transmitter includes:

A codebook list storage unit, configured to provide a precoding matrix or a precoding vector to a precoding matrix construction unit;

A precoding matrix construction unit, configured to select a corresponding precoding vector in the codebook list storage unit of the transmitter according to the optimal precoding vector information fed back by the receiver decision unit, to construct a precoding matrix;

The precoding unit is configured to perform precoding according to the precoding matrix constructed by the precoding matrix construction unit.

A specific embodiment of the present invention provides a receiver used in a MIMO system, and the receiver includes:

a channel estimation unit, configured to perform channel estimation, and provide the channel estimation result to the decision unit;

A codebook list storage unit, configured to provide a precoding matrix or a precoding vector to the decision unit;

a decision unit, configured to select an optimal precoding vector from the beamforming codebook of the codebook list storage unit according to the channel estimation result provided by the channel estimation unit and the set decision criterion, and store the optimal precoding vector The information of the coding vector is fed back to the transmitter;

The specific embodiment of the present invention provides a transmitter used in a MIMO system, wherein the transmitter includes:

A codebook list storage unit, configured to provide a precoding matrix or a precoding vector to a precoding matrix construction unit;

A precoding matrix construction unit, configured to select a corresponding precoding vector in the codebook list storage unit of the transmitter according to the optimal precoding vector information fed back by the receiver decision unit, to construct a precoding matrix;

The precoding unit is configured to perform precoding according to the precoding matrix constructed by the precoding matrix construction unit.

The specific embodiments of the present invention provide a method, system, transmitter and receiver for constructing a precoding matrix by using a beamforming codebook. The precoding matrix constructed by the beamforming codebook is a non-unitary matrix. Therefore, by using the method, system, transmitter and receiver provided in the specific embodiments of the present invention, precoding using a non-unitary matrix can be realized. After precoding with the method described in the embodiment of the present invention, better bit error rate performance can be obtained than that of the unitary matrix precoding scheme, and it can be known through analysis that its decoding complexity is lower.

Description of drawings

FIG. 1 is a schematic diagram of a limited feedback precoding MIMO-OFDM system in the prior art;

Figure 2 is a comparison diagram of the relationship between the signal-to-noise ratio and the bit error rate under the type I ideal feedback and the type II ideal feedback in a low-speed mobile environment with a maximum Doppler frequency shift of 40;

Fig. 3 is under the low-speed mobile environment that the maximum Doppler frequency shift is 40, the (2, 1, 3) limited feedback provided by the embodiment of the present invention respectively, and the (2, 2, 3) used in the prior art ) simulation under the limited feedback situation, the obtained signal-to-noise ratio and bit error rate relationship comparison diagram;

Fig. 4 is under the low-speed mobile environment that the maximum Doppler frequency shift is 40, the (2, 1, 6) limited feedback provided by the embodiment of the present invention respectively, and the (2, 2, 6) used in the prior art ) simulation under the limited feedback situation, the obtained signal-to-noise ratio and bit error rate relationship comparison diagram;

Fig. 5 shows the (2, 1, 3) limited feedback provided by the specific embodiment of the present invention respectively when the moving speed is 3km/h under the independent 12-path TU channel, which is different from the (2, 2, 3) used in the prior art. 3) Carry out the simulation under the condition of limited feedback, and obtain the comparison diagram of the relationship between the signal-to-noise ratio and the bit error rate;

Fig. 6 shows the (2, 1, 6) limited feedback provided by the specific embodiment of the present invention respectively when the moving speed is 3km/h under the independent 12-path TU channel, which is different from the (2, 2, 6) used in the prior art. 6) Carry out the simulation under the condition of limited feedback, and obtain the comparison diagram of the relationship between the signal-to-noise ratio and the bit error rate;

FIG. 7 is a schematic diagram of a MIMO system and device using limited feedback precoding according to Embodiment 3 of the present invention.

Detailed ways

In order to make the technical solution of the present invention clearer, the specific implementation manners of the present invention are given below.

Specific implementation mode one:

The first specific embodiment describes how to use a non-unitary matrix for precoding when orthogonal space-time coding is used in a MIMO-OFDM system. details as follows:

After receiving the signal, the receiving end performs channel estimation to obtain the channel matrix H of M _r ×M _f . H can be obtained by any known channel estimation method, and will not be repeated here; according to the number of transmitting antennas and the number of feedback bits, the optimal decision can be made on the precoding matrix in the corresponding beamforming codebook set, and the optimal Launch vector v, the judgment is based on the following formula:

$\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; \&zeta;</span>}}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; max</span>}}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; h</span>}{\mathrm{<span\; class="notranslate">\; v</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Wherein, v _i is a precoding vector in a beamforming codebook, that is, a codebook in which the number of data streams is equal to 1. The beamforming codebook may be a codebook given in any current document, and the present invention refers to the beamforming codebook in the IEEE802.16e protocol draft.

After obtaining the optimal transmit vector, the optimal precoding matrix can be constructed

F=[v...v](4)

Equation (4) indicates that the optimal precoding matrix F is formed by paralleling n optimal precoding vectors v, and the value of n is the same as the number of data streams. The sending end only needs to use F to perform precoding.

Specific implementation mode two:

In the following, the precoding method involved in the present invention will be specifically described by taking the Alamouti orthogonal space-time block coding of closed-loop 2-transmit and 1-receive as an example. In order to compare the performance of the specific implementation of the present invention with the prior art below, it is assumed here that: the optimal precoding matrix determined according to the prior art is F _I , and the method determined according to the specific implementation of the present invention produces The optimal precoding matrix for is F _II .

In the MIMO-OFDM system using closed-loop 2-transmit-1-receive Alamouti orthogonal space-time block coding, the number of transmit antennas is 2, because this specific implementation is based on the optimal precoding vector in the beamforming codebook to construct the optimal Precoding matrix, so when the number of feedback bits is 3 bits, select a vector in the (2, 1, 3) codebook set as the optimal precoding vector v, when the number of feedback bits is 6 bits, in (2, 1, 6) Select a vector in the codebook set as the optimal precoding vector v. In the embodiment of the present invention, the judgment criterion of v follows formula (3).

The codebook is further explained here. When the number of feedback bits is 3 bits, it means that there are 8 different precoding vectors (or matrices) in the corresponding codebook. For example, there are 8 different precoding vectors in the (2, 1, 3) codebook. By analogy, there are 64 different precoding vectors in the (2, 1, 6) codebook, and the subscript _i of vi in formula (3) represents the sequence number of the vector in the codebook.

After judging and generating the optimal transmission vector v, the receiving end feeds back the decision result, that is, the serial number of the optimal transmitting vector v, to the transmitting end through the feedback channel.

After receiving the judgment result fed back by the receiving end, the sending end constructs the optimal precoding matrix F _II according to the principle described in formula (4), and uses this matrix for precoding.

The beneficial effect of the precoding method described in the specific embodiment of the present invention will be described below by taking the MIMO-OFDM system using closed-loop 2-transmission-1-reception Alamouti orthogonal space-time block coding described in the second specific embodiment as an example.

Because the theoretical performance analysis of limited feedback is very difficult, the lower limit of the bit error rate is given here, which is the performance analysis under ideal feedback. We call the precoding scheme in the prior art IEEE802.16e protocol I-type closed-loop ideal feedback precoding, and its precoding matrix is F _I , which is taken from (2, 2, 3) or (2, 2,6) Codebook, F _I =[v ₁ v ₂ ], both v ₁ and v ₂ are 2×1 vectors, and are orthogonal to each other; the precoding scheme described in the specific embodiment of the present invention is called a type II closed loop Ideal feedback precoding, its precoding matrix is F _II , F _II =[v v], v is taken from (2, 1, 3) or (2, 1, 6) codebook according to the number of feedback bits, and is the most The optimal transmit vector obtained by the optimal decision is also a 2×1 vector.

The codeword structure of Alamouti Orthogonal Space-Time Block Coding with 2 transmissions and 1 reception is

$\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}& {<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; *</span>}\\ {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}& {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{<span\; class="notranslate">\; *</span>}\end{array}\right]<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 5</span>}<span\; class="notranslate">\; )</span>$

Among them, the first column of vectors is the signal transmitted from the two transmitting antennas at time _t1 , and the second column of vectors is the signal transmitted from the two transmitting antennas at time _t2 , namely ${{\mathrm{the\; s}}_t}_1={\left[\begin{array}{cc}{\mathrm{the\; s}}_1& {\mathrm{the\; s}}_2\end{array}\right]}^T,$ ${{\mathrm{the\; s}}_t}_2={\left[\begin{array}{cc}{-\mathrm{the\; s}}_2^{*}& {\mathrm{the\; s}}_1^{*}\end{array}\right]}^T,$ (·) T means seeking transposition. According to the Alamouti orthogonal space-time block coding assumption, t ₁ and t ₂ experience the same channel fading, then in the case of limited feedback precoding, the signal received by the receiving end can be expressed as

${{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}{{\mathrm{<span\; class="notranslate">\; HFs</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; +</span>{{\mathrm{<span\; class="notranslate">\; no</span>}}_{\mathrm{<span\; class="notranslate">\; t</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1,2</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

表示高斯白噪声。本发明的实施方式中，假设衰落系数独立，服从均值为0、方差为1的复高斯分布，即H为瑞利衰落信道。Among them, H is the actual channel matrix of 1×2, H=[h ₁ h ₂ ], h ₁ and h ₂ represent the channel fading coefficients between transmitting antenna 1, 2 and receiving antenna respectively,

represents white Gaussian noise. In the embodiments of the present invention, it is assumed that the fading coefficients are independent and obey a complex Gaussian distribution with a mean value of 0 and a variance of 1, that is, H is a Rayleigh fading channel.

According to precoding and Alamouti orthogonal space-time block coding theory, equation (6) can be equivalent to the following form

$\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; =</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}\\ {\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}^{<span\; class="notranslate">\; *</span>}\end{array}\right]<span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; eff</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\left[\begin{array}{cc}{\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}& {\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ {\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{<span\; class="notranslate">\; *</span>}& {\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{<span\; class="notranslate">\; *</span>}\end{array}\right]<span\; class="notranslate">\; \&Center\; Dot;</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]<span\; class="notranslate">\; +</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}\\ {\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}^{<span\; class="notranslate">\; *</span>}\end{array}\right]<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

in, Perform singular value (Singular Value Decomposition, SVD) decomposition on the 2×2 equivalent channel matrix H _eff in formula (7), get H _eff =U∑V ^H , where U=1, V is a 2×2 unitary matrix , Σ=[λ 0], λ is the non-zero singular value of the equivalent channel matrix H _eff (λ is a real number), according to the matrix singular value decomposition theory, we have $\mathrm{\&lambda;}=\sqrt{{\left|{\tilde{h}}_1\right|}^2+{\left|{\tilde{h}}_2\right|}^2}.$

In the case of type I closed-loop ideal feedback precoding, F _I =V=[v ₁ v ₂ ], HF _I =[λ 0], and the decoded result is

${\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; S</span>}}}_{\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; eff</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}$

$<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; \&lambda;</span>}\end{array}\right]<span\; class="notranslate">\; \&Center\; Dot;</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; \&lambda;</span>}\end{array}\right]<span\; class="notranslate">\; \&Center\; Dot;</span>{\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; +</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; \&lambda;</span>}\end{array}\right]<span\; class="notranslate">\; \&Center\; Dot;</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 8</span>}<span\; class="notranslate">\; )</span>$

$<span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& {\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]<span\; class="notranslate">\; \&Center\; Dot;</span>{\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; +</span>\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}\\ \mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}^{<span\; class="notranslate">\; *</span>}\end{array}\right]$

的第一行和第二行为译码支路，每支路的信号在译码后送入解调器解调，而误码率性能则取决于解调信噪比。根据(8)式，以及假设发射符号功率归一，即ε_s＝1和噪声功率为1，即 ${\mathrm{\&sigma;}}_n^2=1$ 可知，译码后每支路解调信噪比为Among them, (·) ^H represents the matrix transpose conjugate matrix, we call (8) where

The first row and the second row are decoding branches, and the signal of each branch is sent to the demodulator for demodulation after decoding, and the bit error rate performance depends on the demodulation signal-to-noise ratio. According to formula (8), and assuming that the transmitted symbol power is normalized, that is, ε _s =1 and the noise power is 1, that is ${\mathrm{\&sigma;}}_{\mathrm{no}}^2=1$ It can be seen that after decoding, the demodulation signal-to-noise ratio of each branch is

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}<span\; class="notranslate">\; =</span>\frac{{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; /</span>\sqrt{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; \&epsiv;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

In the case of type II closed-loop ideal feedback precoding, F _II ＝V＝[v v], HF _II ＝[λ λ], the decoded result is

${\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; S</span>}}}_{\mathrm{<span\; class="notranslate">\; I</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; eff</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}$

$<span\; class="notranslate">\; =</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}& \mathrm{<span\; class="notranslate">\; \&lambda;</span>}\\ \mathrm{<span\; class="notranslate">\; \&lambda;</span>}& <span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}\end{array}\right]<span\; class="notranslate">\; \&Center\; Dot;</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}& \mathrm{<span\; class="notranslate">\; \&lambda;</span>}\\ \mathrm{<span\; class="notranslate">\; \&lambda;</span>}& <span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}\end{array}\right]<span\; class="notranslate">\; \&CenterDot;</span>{\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; +</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}& \mathrm{<span\; class="notranslate">\; \&lambda;</span>}\\ \mathrm{<span\; class="notranslate">\; \&lambda;</span>}& <span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}\end{array}\right]<span\; class="notranslate">\; \&CenterDot;</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; )</span>$

$<span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&Center\; Dot;</span>\left[\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; 0</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]<span\; class="notranslate">\; \&CenterDot;</span>{\left[\begin{array}{cc}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}\right]}^{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; +</span>\left[\begin{array}{c}\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; )</span>\\ \mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; no</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; )</span>\end{array}\right]$

After decoding, the signal-to-noise ratio of each branch is

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; II</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}}<span\; class="notranslate">\; =</span>\frac{{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; /</span>\sqrt{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; \&epsiv;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&CenterDot;</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 11</span>}<span\; class="notranslate">\; )</span>$

It can be seen that the use of type II closed-loop ideal feedback precoding can double the demodulation signal-to-noise ratio compared with type I, that is, the system performance can be improved by 3dB. Since the traditional precoding method and the precoding method described in the specific embodiments of the present invention are actually the quantization of Type I and Type II closed-loop ideal feedback precoding respectively, if the quantization error is the same, the performance difference between the two limited feedback precoding is also 3dB. That is to say, type II closed-loop ideal feedback precoding has better bit error rate performance than type I.

Fig. 2, Fig. 3, Fig. 4 have given the bit error rate performance comparison of the method described in the embodiment of the present invention and the traditional precoding method under the low-speed mobile environment that the maximum Doppler frequency shift is 40, and Fig. 2 is ideal feedback The performance comparison under the status, Fig. 3 is the performance comparison of the scheme provided by the present invention and the prior art when 3bit feedback, Fig. 4 is the performance comparison of the scheme provided by the present invention and the prior art when 6bit feedback. It can be seen that, compared with the traditional precoding method, the method described in the specific embodiment of the present invention has a gain of about 3dB when the signal-to-noise ratio is high under an independent single-path Rayleigh fading channel. In order to further verify the performance of the inventive solution under independent multi-path channels, Fig. 5 and Fig. 6 show the bit error rate performance comparison between the inventive solution and the traditional solution when the moving speed is 3km/h under the independent 12-path TU channel , where the system carrier frequency is 3.5GHz, the bandwidth is 10MHz, and the points of Fourier transform and cyclic prefix are 1024 and 128 respectively. Wherein, FIG. 5 is a performance comparison between the solution provided by the present invention and the prior art when 3-bit feedback is used, and FIG. 6 is a performance comparison between the solution provided by the present invention and the prior art when 6-bit feedback is used. It can be seen from FIG. 5 and FIG. 6 that the solution of the present invention is still effective under independent multipath channels, and can still achieve a gain of about 3dB compared with the traditional solution under high signal-to-noise ratio.

At the same time, the improvement of SNR by Type II closed-loop ideal feedback precoding is not at the expense of increasing the total transmission power. According to the structure of Alamouti orthogonal space-time coding, the total transmission power at time t ₁ is

${<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\sqrt{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; Fs</span>}}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\frac{{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; vs</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; vs</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}$

$<span\; class="notranslate">\; \&le;</span>\frac{{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; vs</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; vs</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 11</span>}<span\; class="notranslate">\; )</span>$

$<span\; class="notranslate">\; =</span>\frac{{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; v</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}$

Among them, S _t represents the transmitted signal vector of Alamouti orthogonal space-time block coding at time _t1 , and the same reasoning can be proved at time _t2 . It can be seen that the use of type II closed-loop ideal feedback precoding does not increase the total transmission power compared with type I closed-loop ideal feedback precoding.

In addition, adopting the precoding method described in the specific embodiments of the present invention can also reduce the decoding complexity while reducing the bit error rate of the system, which is caused by the fact that the column vectors of the precoding matrix are the same. Table 2 shows the comparison in decoding complexity between the traditional precoding method and the precoding method described in the specific embodiment of the present invention when there are two data streams.

Table 2 Comparison of Aloumouti Orthogonal Space-Time Block Coding and Decoding Complexity

In order to implement the above method, specific implementation manners of corresponding wireless communication systems and devices are provided below.

The specific embodiment three of the present invention is described below in conjunction with accompanying drawing 7:

Embodiment 3 of the present invention provides a MIMO system using limited feedback precoding, and the system includes a transmitter 710 and a receiver 720 . The system adopts orthogonal space-time coding and adopts more than two data streams, and the receiver 720 includes:

The channel estimation unit 721 is used to perform channel estimation and provide the channel estimation result to the decision unit 723; in addition, the channel estimation unit also provides the channel estimation result to the decoder, but the role of the channel estimation unit in this respect It is not directly related to the technical solutions involved in the present invention, so it should not be regarded as a part of the technical solutions described in this specific embodiment;

The codebook list storage unit 722 is configured to provide a precoding matrix or a precoding vector to the decision unit 723; the precoding vector is actually a precoding matrix, and in the embodiment of the present invention, the precoding vector can be obtained from Select from the codebook to construct the precoding matrix;

The judging unit 723 is configured to select the optimal precoding vector from the beamforming codebook of the codebook list storage unit 722 according to the channel estimation result provided by the channel estimating unit 721 and the set decision criterion, and store the optimal precoding vector The information of the optimal precoding vector is fed back to the transmitter 710; the decision criterion for selecting the optimal precoding vector may follow formula (3).

Generally speaking, different precoding vectors can be represented by different values, and only the value corresponding to the selected precoding vector needs to be fed back during feedback, and it is not necessary to feed back the precoding vector itself to the transmitter. Of course, the information of the precoding vector described in this embodiment is not limited to the corresponding value mentioned above, as long as the content of the feedback can correctly indicate the selected precoding vector.

The transmitter 710 includes:

A codebook list storage unit 711, configured to provide a precoding matrix or a precoding vector to the precoding matrix construction unit 712;

The precoding matrix construction unit 712 is configured to select the corresponding precoding vector in the codebook list storage unit 711 according to the optimal precoding vector information fed back by the decision unit 723 of the receiver 720, and construct a precoding matrix; The vector construction precoding matrix follows the principle of formula (4).

The precoding unit 713 is configured to perform precoding according to the precoding matrix constructed by the precoding matrix construction unit 712 .

The third specific embodiment above also provides a transmitter and a receiver applied to the method of the present invention.

For the methods, systems and devices described in the specific embodiments of the present invention, any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the specific embodiments of the present invention shall be included in the protection scope of the present invention Inside.

Claims (10)

1. A precoding method in a MIMO system is characterized by adopting orthogonal space-time coding and more than two data streams, and comprises the following steps:

selecting an optimal precoding vector from a beam forming codebook;

constructing a precoding matrix by adopting the optimal precoding vector;

and precoding by adopting the precoding matrix.

2. The method of precoding in a MIMO system of claim 1, wherein the optimal precoding vector is selected from the beamforming codebook according to the following principle,

<math><mrow> <mi>v</mi> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>max</mi> </mrow> <mrow> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>&Element;</mo> <mi>&zeta;</mi> </mrow> </munder> <msub> <mrow> <mo>|</mo> <mo>|</mo> <mi>H</mi> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> </mrow> <mtext>2</mtext> </msub> </mrow></math>

wherein v is an optimal precoding vector; v. of_iA precoding vector in a beam forming codebook, namely a codebook with the data stream number equal to 1; h is a channel matrix; i | · | purple wind₂The expression takes the vector 2 norm.

3. The method of precoding in a MIMO system of claim 2, wherein the beamforming codebook is a beamforming codebook in an ieee802.16e protocol.

4. The precoding method in the MIMO system of claim 1, wherein the constructing the precoding matrix using the optimal precoding vector is performed by arranging n optimal precoding vectors in parallel to form a precoding matrix, and a value of n is the same as a number of data streams.

5. A MIMO system adopting limited feedback precoding comprises a transmitter and a receiver, and is characterized in that the system adopts orthogonal space-time coding and adopts more than two data stream numbers; and,

the receiver includes:

the channel estimation unit is used for carrying out channel estimation and providing a channel estimation result to the judgment unit;

a codebook list storage unit for providing a precoding matrix or a precoding vector to the decision unit;

a decision unit, configured to select an optimal precoding vector from the beamforming codebook in the codebook list storage unit according to the channel estimation result provided by the channel estimation unit and a set decision criterion, and feed back information of the optimal precoding vector to the transmitter;

the transmitter includes:

a codebook list storage unit for providing a precoding matrix or a precoding vector to the precoding matrix construction unit;

a precoding matrix constructing unit, configured to select a corresponding precoding vector from a codebook list storage unit of the transmitter according to the optimal precoding vector information fed back by the receiver decision unit, and construct a precoding matrix;

and the precoding unit is used for precoding according to the precoding matrix constructed by the precoding matrix construction unit.

6. The MIMO system with limited feedback precoding of claim 5, wherein the information of the optimal precoding vector fed back by the feedback unit is a value corresponding to each precoding vector.

7. A receiver for use in a MIMO system, the receiver comprising:

the channel estimation unit is used for carrying out channel estimation and providing a channel estimation result to the judgment unit;

a codebook list storage unit for providing a precoding matrix or a precoding vector to the decision unit;

a decision unit, configured to select an optimal precoding vector from the beamforming codebook in the codebook list storage unit according to the channel estimation result provided by the channel estimation unit and a set decision criterion, and feed back information of the optimal precoding vector to the transmitter;

8. the receiver of claim 7, wherein the decision unit selects the optimal precoding vector in the beamforming codebook according to the following principle:

<math><mrow> <mi>v</mi> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>max</mi> </mrow> <mrow> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>&Element;</mo> <mi>&zeta;</mi> </mrow> </munder> <msub> <mrow> <mo>|</mo> <mo>|</mo> <mi>H</mi> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>|</mo> </mrow> <mtext>2</mtext> </msub> </mrow></math>

wherein v is an optimal precoding vector; v. of_iA precoding vector in a beam forming codebook, namely a codebook with the data stream number equal to 1; h is a channel matrix; i | · | purple wind₂The expression takes the vector 2 norm.

9. A transmitter for use in a MIMO system, the transmitter comprising:

a codebook list storage unit for providing a precoding matrix or a precoding vector to the precoding matrix construction unit;

a precoding matrix constructing unit, configured to select a corresponding precoding vector from a codebook list storage unit of the transmitter according to the optimal precoding vector information fed back by the receiver decision unit, and construct a precoding matrix;

and the precoding unit is used for precoding according to the precoding matrix constructed by the precoding matrix construction unit.

10. The transmitter of claim 9, wherein the precoding matrix construction unit constructs a precoding matrix using the optimal precoding vector information, and comprises:

determining an optimal precoding vector according to the optimal precoding vector information;

and paralleling n optimal precoding vectors to form a precoding matrix, wherein the value of n is the same as the number of data streams.

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