CN104734818A - Self-adaption switchover method and device of MIMO receiving algorithm - Google Patents

Abstract

The invention relates to the field of wireless communications, and discloses a self-adaption switchover method and device of an MIMO receiving algorithm. Under different configuration combinations of various factors of influencing the complexity of a maximum-likelihood criterion detecting algorithm and the error rate performance gain of the maximum-likelihood criterion algorithm relative to a linear detecting algorithm, the receiving algorithm enabling the error rate performance to be optimal as far as possible is obtained through simulation; when the error rate performance difference is not large, the receiving algorithm with low complexity is selected; therefore, the corresponding relations between different configuration combinations of a receiving end and the MIMO receiving algorithm are obtained; when the receiving algorithm is actually selected, one of the linear detecting algorithm and the maximum-likelihood criterion detecting algorithm is selected for data receiving according to the current configuration of the receiving end, therefore, the receiving end can reasonably select the receiving algorithm according to the actual configuration condition, the error rate performance is optimal as far as possible, or the complexity of the algorithm is as low as possible, and the aim of simultaneously improving the error rate performance and the complexity of the algorithm is achieved.

Description

Adaptive switching method and device for MIMO receiving algorithm

technical field

The invention relates to the field of wireless communication, in particular to an adaptive switching method and device for MIMO receiving algorithms.

Background technique

Generally, multiple-input multiple-output ("MIMO") receivers use a single receiving algorithm, such as linear detection, such as zero-forcing (Zero-Forcing, "ZF"), minimum mean square error ( Minimum Mean-Squared Error, referred to as "MMSE"), serial interference cancellation based on ZF/MMSE sorting (Ordered Successive Interference Cancellation, referred to as "OSIC") or detection algorithms based on maximum likelihood criteria, such as spherical decoding (Sphere Decoding, referred to as "SD"), Lattice Reduction Algorithm (referred to as "LRA"), a single receiving algorithm has the following disadvantages (for convenience, the linear detection in the background technology is described by MMSE, and the maximum likelihood detection is Indicated by SD):

Single use of linear detection, although the complexity is low, but the bit error rate performance is also poor; single use of OSIC, there will be wrong transmission under certain channel conditions, which will reduce performance; single use of SD, the complexity is high, and The performance gain relative to linear detection is not significant under certain channel conditions.

There are also some MIMO receivers that use linear detection and SD adaptive receiving algorithms, but the adaptive conditions are not comprehensive, and only simple switching is performed according to the channel condition number. There is a certain probability that the switching is unreasonable, and the performance and complexity cannot be clearly matched. A good compromise.

Specifically, assume that the MIMO system model is y=Hs+n, y is the received signal, s is the transmitted signal, H is the channel matrix, and n is Gaussian white noise with variance ^σ2 .

If the linear detection MMSE algorithm is used:

${\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}_{\mathrm{<span\; class="notranslate">\; MMSE</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; G</span>}}_{\mathrm{<span\; class="notranslate">\; MMSE</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; h</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; h</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; I</span>}}_{{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}}<span\; class="notranslate">\; )</span>}^{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; h</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}$

If the maximum likelihood (Maximum Likelihood, referred to as "ML") detection algorithm:

${\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}_{\mathrm{<span\; class="notranslate">\; ML</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; C</span>}}^{{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}}}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; min</span>}}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Hs</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; C</span>}}^{{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}}}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; min</span>}}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Rs.</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span>$

Throughout Find the optimal solution in the space, where C represents the number of symbols contained in the modulation constellation point, _NT represents the number of transmitting antennas, R is the upper triangular matrix obtained by QR decomposition of the channel matrix H (requiring H columns to be linearly independent), and Q is the pair The orthogonal matrix obtained by QR decomposition of H, (·) ^H represents the conjugate transpose of the matrix, (·) ^-1 represents the inverse of the matrix, and ||·|| represents the norm of the matrix.

Since the complexity of ML is exponentially distributed with the number of transmitting antennas, the early MIMO terminal detection algorithms generally adopt linear detection. Recent research on sphere decoding technology shows that: sphere decoding can achieve error performance close to or equal to maximum likelihood detection under the premise of significantly reducing the complexity (and the number of transmitting antennas has a polynomial relationship), so sphere decoding begins It is applied in MIMO system.

SD cites the idea of maximum likelihood detection, but it searches for all possible transmitted symbol vectors in a ball whose center is the received vector y and whose radius is r, that is, all transmitted symbol vectors that satisfy the following inequality, rather than in the entire Search in the space, thereby reducing the amount of calculation.

$\begin{array}{c}{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; Q</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Rs.</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>\mathrm{<span\; class="notranslate">\; R</span>}\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; Rs.</span>}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; r</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ <span\; class="notranslate">\; \&DoubleRightArrow;</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>{\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; -</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span>{\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; /</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; r</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\\ <span\; class="notranslate">\; \&DoubleLeftRightArrow;</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{{\mathrm{<span\; class="notranslate">\; N</span>}}_{\mathrm{<span\; class="notranslate">\; T</span>}}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; \&rho;</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; r</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\end{array}$

An existing adaptive strategy performs SD and MMSE adaptation mainly according to the degree of orthogonality of the channel matrix H, which can be characterized by the condition number α or the orthogonality defect od(H). in σ _max , σ _min are the maximum and minimum singular values of H respectively; For any H, there are α≥1,0≤od(H)≤1. The smaller α or od(H), the more orthogonal H tends to be, and the closer the linear detection is to the performance of ML. An adaptive strategy based on the channel condition number is as follows:

If the channel condition number α is less than or equal to the condition number lower limit threshold α _TH1 , the channel condition is considered to be good at this time, and the receiving end can consider using the MMSE algorithm with the lowest decoding complexity but relatively poor performance; if the condition number is greater than If the condition number upper limit threshold value α _TH2 is considered to be very bad at this time, the receiving end adopts the SD detection algorithm with the highest decoding complexity but the best performance; otherwise, adopts the OSIC detection algorithm with intermediate complexity and performance.

But in fact, there are many factors that affect the performance of SD relative to MMSE, and the channel condition number is only one of them. Handover control based solely on the channel condition number will lead to unreasonable handover with a high probability. Either switch to MMSE when the performance difference between MMSE and SD is large, and the performance is not optimal, or switch to MMSE when the performance difference between MMSE and SD is small. to SD thus adding unnecessary complexity.

In short, the existing MIMO receiving technology mainly has the following disadvantages:

1. Using a single MIMO receiving scheme, the performance is poor or the complexity is very high.

2. If a simple adaptive switching based on the condition number is used, although it can save a little power compared with a single SD, it will lead to unnecessary power consumption or suboptimal performance due to unreasonable switching.

Contents of the invention

The purpose of the present invention is to provide a method and device for adaptive switching of MIMO receiving algorithms, so that the receiving end can reasonably select the receiving algorithm according to the actual configuration, so that the bit error rate performance is as optimal as possible or the algorithm complexity is as low as possible.

In order to solve the above-mentioned technical problem, the embodiment of the present invention provides a kind of adaptive switching method of MIMO receiving algorithm, comprises the following steps:

A. Pre-simulation to obtain the corresponding relationship between different configuration combinations of the receiving end and the MIMO receiving algorithm;

B. Obtain the current configuration of the receiving end, and select one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception according to the corresponding relationship;

Wherein, the configuration combination is: a configuration combination of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm;

The MIMO receiving algorithm includes: a linear detection algorithm and a maximum likelihood criterion detection algorithm.

Embodiments of the present invention also provide an adaptive switching device for MIMO reception algorithms, including: a mapping storage module, a configuration acquisition module, and a detection algorithm selection module;

The mapping storage module is used to store the corresponding relationship between different configuration combinations and MIMO receiving algorithms, wherein the corresponding relationship is obtained through pre-simulation; the configuration combination is: affecting the complexity of the maximum likelihood criterion detection algorithm and the maximum The configuration combination of various factors of the bit error rate performance gain of the likelihood criterion algorithm relative to the linear detection algorithm; the MIMO receiving algorithm includes: a linear detection algorithm, a detection algorithm of the maximum likelihood criterion

The configuration obtaining module is used to obtain the current configuration;

The detection algorithm selection module selects one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception according to the current configuration obtained by the configuration acquisition module and the corresponding relationship stored in the mapping storage module.

Compared with the prior art, the embodiment of the present invention, under the different configuration combinations of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm, through Simulation, to obtain the receiving algorithm that maximizes the performance of the bit error rate as much as possible; when the performance of the bit error rate is not much different, select the receiving algorithm with low complexity; thus obtain the correspondence between different configuration combinations of the receiving end and the MIMO receiving algorithm relationship; and when actually selecting the receiving algorithm, according to the current configuration of the receiving end, choose one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception, so that the receiving end can reasonably select the receiving algorithm according to the actual configuration, so that errors The bit rate performance is as optimal as possible or the algorithm complexity is as low as possible, so as to achieve the purpose of taking into account both bit error rate performance and algorithm complexity.

In addition, the various factors affecting the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm include: diversity gain, channel coding rate, modulation mode, space parallel transmission Data flow; wherein, the diversity includes: frequency diversity and space diversity;

The configuration of the diversity gain, channel coding rate, and modulation mode is any one of the following: low, medium, and high;

The number of data streams transmitted in parallel space is greater than or equal to 2.

Considering comprehensively the various factors affecting the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm, and simply distinguishing each factor, the switching strategy of the present invention can be made simple and easy. OK, the complexity of the receiving algorithm will not be increased due to complex switching judgments.

In addition, the low, medium and high configurations of frequency diversity correspond to 1.4M, 10M and 20M respectively;

The low, medium, and high configurations of the spatial diversity correspond to high spatial correlation, medium spatial correlation, and low spatial correlation, respectively;

The low, medium and high configurations of the modulation modes correspond to QPSK, 16QAM and 64QAM respectively;

The low, medium, and high configurations of the channel coding rate correspond to 1/3, 1/2, and 3/4, respectively;

The number of data streams transmitted in parallel in space is two.

In the actual receiving end, various configuration combinations can be further refined or combined according to system requirements, so as to make the adaptive switching strategy more reasonable.

In addition, the corresponding relationship between the configuration combination and the MIMO receiving algorithm includes:

The configuration combination is: the modulation mode is low or medium, the channel coding rate is medium or high, and the corresponding MIMO receiving algorithm is a detection algorithm of maximum likelihood criterion;

The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is low, and the corresponding MIMO receiving algorithm is a detection algorithm of maximum likelihood criterion;

The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm;

The configuration combination is: the modulation mode is high, the channel coding rate is low, the frequency diversity is low, the space diversity is low, and the corresponding MIMO receiving algorithm is a detection algorithm of the maximum likelihood criterion;

The configuration combination is: the modulation mode is high, the channel coding rate is medium or high, the frequency diversity is medium or high, the space diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm.

Although the above adaptive switching strategy is relatively rough, compared with a single detection algorithm, it can facilitate the compromise between complexity and bit error performance; and compared with the scheme of switching detection algorithms based solely on the channel condition number, it comprehensively considers the influence of SD relative to MMSE. Various factors can ensure that the adaptive switching of the terminal is more reasonable in different environments, and it is better to avoid switching to MMSE when the performance difference between MMSE and SD is large, so that the performance is not optimal, and the performance difference between MMSE and SD is different. Minor switching to SD, adding unnecessary complexity, allows for a better trade-off between performance and power savings.

In addition, the various factors affecting the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm also include: the ratio SINR of the signal to interference and noise;

In said step A, the following steps are also included:

Pre-simulation to obtain the SINR value range of the maximum likelihood criterion detection algorithm under each configuration in various configuration combinations;

In said step B, the following sub-steps are also included:

Obtain the current configuration and current SINR of the receiving end, and judge whether the current SINR belongs to the SINR value interval under the current configuration; if so, select the maximum likelihood criterion detection algorithm for data reception; if not, select the linear detection algorithm for data reception Data reception.

The adaptive switching strategy is further refined by using the signal-to-interference-noise ratio SINR to make the adaptive switching more reasonable, and further make the bit error rate performance as optimal as possible or the algorithm complexity as low as possible

In addition, the method is applied to the LTE system, and the modulation method and the channel coding rate are directly and uniformly judged by the modulation and coding strategy MCS; the frequency diversity is directly judged by the number of resource blocks RB allocated to the user in the frequency domain ; The spatial diversity is judged by the ratio between the eigenvalues of the channel correlation matrix. The parameter values of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm are very easy to obtain, and the reception will not be increased due to the difficulty of obtaining various factors The complexity of the algorithm also makes the present invention easy to popularize and use.

Description of drawings

FIG. 1 is a flow chart of an adaptive switching method of a MIMO receiving algorithm according to a first embodiment of the present invention;

FIG. 2 is a flowchart of an adaptive switching method of a MIMO receiving algorithm according to a second embodiment of the present invention;

3 is a schematic structural diagram of an adaptive switching device for a MIMO receiving algorithm according to a third embodiment of the present invention;

Fig. 4 is a schematic structural diagram of an adaptive switching device for a MIMO receiving algorithm according to a fourth embodiment of the present invention.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, various embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, those of ordinary skill in the art can understand that, in each implementation manner of the present invention, many technical details are provided for readers to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solution claimed in each claim of the present application can be realized.

The first embodiment of the present invention relates to an adaptive switching method for MIMO receiving algorithms, which comprehensively considers various factors affecting the relative performance of linear detection and maximum likelihood in OFDM systems and the complexity of spherical decoding (SD) , an adaptive strategy of SD and linear detection is proposed, which can make a good trade-off between MIMO receiving performance and algorithm complexity.

Specifically, through simulation in advance, the corresponding relationship between different configuration combinations of the receiving end and the MIMO receiving algorithm is obtained; when the receiving end actually receives data, it obtains the current configuration, and according to the above corresponding relationship, chooses to use the linear detection algorithm or the maximum likelihood One of the criterion detection algorithms receives data; wherein, the configuration combination is: the configuration combination of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm; MIMO The receiving algorithm includes: linear detection algorithm, detection algorithm of maximum likelihood criterion (also includes: detection algorithm similar to maximum likelihood criterion).

Various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm can be: diversity gain, channel coding rate (referred to as "code rate"), modulation method, Data streams transmitted in parallel in space. The configuration of diversity gain, channel coding rate, and modulation mode is any one of the following: low, medium, and high; the number of data streams transmitted in parallel in space is greater than or equal to 2. By comprehensively considering various factors affecting the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm, and simply distinguishing each factor, the switching strategy of the present invention can be made simple It is easy to implement, and the complexity of the receiving algorithm will not be increased due to complex switching judgments.

Those skilled in the art can understand that diversity gain mainly refers to the following three types:

Frequency diversity gain: multipath fading, determined by the ratio of the system bandwidth Bs to the channel coherence bandwidth Bc, the larger the ratio, the higher the diversity gain;

Time diversity gain: Doppler, determined by the ratio of the symbol period Ts to the channel coherence time Tc, the larger the ratio, the higher the diversity gain;

Space diversity gain: multi-antenna, determined by the eigenvalue (Eigenvalue) extension σ _EV , that is, the ratio of the largest eigenvalue to the smallest eigenvalue; the larger the eigenvalue extension, the higher the channel correlation, and the parallel data that can be transmitted during spatial multiplexing The fewer streams, the lower the space diversity gain.

In a MIMO-OFDM system, the interval between subcarriers is generally much larger than the Doppler spread, and the symbol period Ts is much smaller than the coherence time Tc. Therefore, the time diversity gain is quite limited and has limited impact on the performance of SD relative to MMSE. In this embodiment, the main consideration is Frequency and space diversity gain.

For the sake of simplicity, this embodiment takes the transmission of 2-stream data as an example, and the code rate, modulation method, frequency diversity gain, space diversity gain, and SINR are all described with three code rates: low, medium, and high:

When specifically determining the adaptive switching strategy, it is necessary to comprehensively consider the complexity of SD and the relative performance of MMSE (expressed in △ _dB ). When the value reaches a certain threshold (this threshold can be obtained by simulation), it is considered that the gain Larger, you can choose SD. In addition, when considering different modulation methods, the complexity of SD is different, and the △ _dB requirements of different modulation methods are different. Specifically, the higher the modulation method, the higher the △ _dB threshold. That is to say, under the same conditions, the complexity of high-order SD is higher than that of low-order modulation, so the demand for performance differences is also high. For example, when SD is 0.5dB better than MMSE at low-order, SD is considered, but it may be used at high-order Only use SD when it is 0.8dB better, so as to ensure that the complexity of the terminal can be controlled within a more suitable range and save power better.

In this embodiment, a relatively rough adaptive switching strategy is obtained through simulation, that is, in terms of affecting the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm Under different configuration combinations of various factors, through simulation, obtain the receiving algorithm (such as the maximum likelihood detection algorithm) that maximizes the performance of the bit error rate; when the performance of the bit error rate is not much different, the selection complexity is low The receiving algorithm (such as the linear detection algorithm); thereby obtaining the corresponding relationship between different configuration combinations of the receiving end and the MIMO receiving algorithm. In this embodiment, a corresponding relationship between a configuration combination and a MIMO receiving algorithm is obtained through simulation as follows:

The configuration combination is: the modulation mode is low or medium, the channel coding rate is medium or high, and the corresponding MIMO receiving algorithm is the detection algorithm of the maximum likelihood criterion, abbreviated as: low-medium order modulation mode + medium-high code rate -> adopt SD;

The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency domain diversity is low, and the corresponding MIMO receiving algorithm is the detection algorithm of the maximum likelihood criterion, abbreviated as: low-medium order modulation mode + low code rate + Frequency domain low diversity -> adopt SD;

The configuration combination is: the modulation mode is high, the channel coding rate is low, the frequency diversity is low, the space diversity is low, and the corresponding MIMO receiving algorithm is the detection algorithm of the maximum likelihood criterion, abbreviated as: high-order modulation mode + low code rate + Low diversity in frequency domain + Low diversity in space -> adopt SD.

The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm, which is abbreviated as: low-medium order modulation mode + low code rate + medium-high frequency domain Diversity -> Adopt MMSE.

The configuration combination is: the modulation mode is high, the channel coding rate is medium or high, the frequency diversity is medium or high, the space diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm. The abbreviation is: high-order modulation mode + medium-high code Rate + high diversity in frequency domain + high diversity in space -> adopt MMSE.

Although the above adaptive switching strategy is relatively rough, compared with a single detection algorithm, it can facilitate the compromise between complexity and bit error performance; and compared with the scheme of switching detection algorithms based solely on the channel condition number, it comprehensively considers the influence of SD relative to MMSE. Various factors can ensure that the adaptive switching of the terminal is more reasonable in different environments, and it is better to avoid switching to MMSE when the performance difference between MMSE and SD is large, so that the performance is not optimal, and the performance difference between MMSE and SD is different. Minor switching to SD, adding unnecessary complexity, allows for a better trade-off between performance and power savings.

When actually receiving data at the receiving end, the receiving algorithm can be selected according to the flow shown in Figure 1 according to the current modulation method, code rate, bandwidth, and channel correlation matrix of the receiving end, that is, to find the combination of the above configurations and MIMO The process of receiving the corresponding relationship between algorithms is relatively easy to understand, and will not be repeated here. In addition, it is worth mentioning that if this embodiment is applied to the LTE system, the modulation method and code rate can be directly and uniformly judged by the Modulation and Coding Strategy (MCS); the frequency domain diversity can directly use the resources allocated to users in the frequency domain The number of blocks (RB) is used as the judgment; the spatial diversity can be judged by the ratio between the eigenvalues of the channel correlation matrix. For example, the desirable MCS of LTE (36.101) is stipulated, and the coding rate and modulation can be directly obtained according to a certain MCS mode; at different frequencies, the number of RBs allocated to users is also specified (for example, 1.4M, 10M, and 20M contain 6, 50, and 100 RBs respectively), and the frequency of frequency diversity can be directly distinguished according to the number of RBs allocated to users ;Set the upper limit and lower limit for the eigenvalue ratio (according to the simulation), if it is less than the lower limit, it can be determined that the airspace diversity configuration is high; if it is greater than the upper limit, it can be determined that the airspace diversity configuration is low; Between the limits, it can be determined that the airspace diversity configuration is medium. It can be seen that the parameter values of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm are very easy to obtain, and will not increase the reception rate due to the difficulty of obtaining various factors. The complexity of the algorithm also makes the present invention easy to popularize and use.

In addition, it is worth noting that in the actual receiving end, various configuration combinations can be further refined or combined according to system requirements, which can make the adaptive switching strategy more reasonable; for example, some common The parameters are refined, and the low frequency, medium and high diversity can be 1.4M, 10M and 20M respectively; the spatial low, medium and high diversity can be respectively high spatial correlation, medium correlation and low correlation; High-order modulation methods can take QPSK, 16QAM, and 64QAM as examples; low, medium, and high code rates can be taken as examples of 1/3, 1/2, and 3/4, respectively, and the above parameters can be combined through simulation. A specific adaptive receiving algorithm switching strategy is obtained for the receiving end to select when receiving data. Or, in the actual receiving end, the configuration of diversity gain, channel coding rate, and modulation mode is not roughly divided into low, medium, and high, but the segmental value of diversity gain, channel coding rate, and specific modulation The method and the like are used as specific configurations, which will make various configuration combinations more refined, and further make the adaptive switching strategy more reasonable. In addition, when >2-stream data is transmitted, the process of determining the adaptive handover strategy is the same as that of 2-stream, and will not be repeated here.

Compared with the prior art, in this embodiment, under the different configuration combinations of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm, through simulation, Obtain the receiving algorithm that maximizes the performance of the bit error rate as much as possible; when the performance of the bit error rate is not much different, select the receiving algorithm with low complexity; thus obtain the corresponding relationship between different configuration combinations of the receiving end and the MIMO receiving algorithm; And when actually selecting the receiving algorithm, according to the current configuration of the receiving end, choose one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception, so that the receiving end can reasonably select the receiving algorithm according to the actual configuration, so that the bit error rate The performance is as optimal as possible or the algorithm complexity is as low as possible, so as to achieve the purpose of taking into account both bit error rate performance and algorithm complexity.

The second embodiment of the present invention relates to a method for adaptively switching MIMO receiving algorithms. The second embodiment is further improved on the basis of the first embodiment, and the main improvement is that in the second embodiment of the present invention, the adaptive switching strategy is further refined by using the ratio SINR of the signal to interference and noise, Make the adaptive switching more reasonable, and further make the bit error rate performance as optimal as possible or the algorithm complexity as low as possible.

Specifically, various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm also include: the signal-to-interference and noise ratio SINR.

When obtaining the corresponding relationship between different configuration combinations and MIMO receiving algorithms by simulation, it is also necessary to obtain the SINR value intervals of the maximum likelihood criterion detection algorithm under each configuration in each configuration combination, that is, it is necessary to obtain various Under the configuration, the upper and lower limits of SINR of SD are used. For example, one of the configurations such as: low-order modulation mode, medium code rate, low frequency diversity, and low space diversity corresponds to the upper and lower limits of SINR.

When actually selecting a specific receiving algorithm at the receiving end, it is also necessary to determine whether the current SINR belongs to the corresponding configuration and determine whether the SINR value interval of the maximum likelihood criterion detection algorithm is used. Criterion detection algorithm. That is to say, as shown in Figure 2, obtain the current configuration and current SINR of the receiving end, and judge whether the current SINR belongs to the SINR value interval under the current configuration; if so, then choose to use the maximum likelihood criterion detection algorithm for data reception; if not , choose to use the linear detection algorithm for data reception.

The division of steps in the above methods is only for the sake of clarity of description. During implementation, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they contain the same logical relationship, they are all within the scope of protection of this patent. ; Adding insignificant modifications or introducing insignificant designs to the algorithm or process, but not changing the core design of the algorithm and process are all within the scope of protection of this patent.

The third embodiment of the present invention relates to an adaptive switching device for MIMO reception algorithms, as shown in FIG. 3 , including: a mapping storage module, a configuration acquisition module, and a detection algorithm selection module.

The mapping storage module is used to store the corresponding relationship between different configuration combinations and MIMO receiving algorithms, wherein the corresponding relationship is obtained through pre-simulation; the configuration combination is: affecting the complexity of the maximum likelihood criterion detection algorithm and the relative linearity of the maximum likelihood criterion algorithm The configuration combination of various factors of the bit error rate performance gain of the detection algorithm; the MIMO receiving algorithm includes: a linear detection algorithm, a detection algorithm of the maximum likelihood criterion.

The above-mentioned various factors affecting the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm include: diversity gain, channel coding rate, modulation method, data stream of spatial parallel transmission; Wherein, the diversity includes: frequency diversity and space diversity; and the configuration of diversity gain, channel coding rate, and modulation mode is any one of the following: low, medium, and high; the number of data streams transmitted in parallel in space is greater than or equal to 2.

The mapping relationship stored in the storage module can include:

The configuration combination is: the modulation mode is low or medium, the channel coding rate is medium or high, and the corresponding MIMO receiving algorithm is the detection algorithm of the maximum likelihood criterion;

The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is low, and the corresponding MIMO receiving algorithm is the detection algorithm of the maximum likelihood criterion;

The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is medium or high, and the corresponding MIMO receiving algorithm is linear detection algorithm;

The configuration combination is: the modulation mode is high, the channel coding rate is low, the frequency diversity is low, the space diversity is low, and the corresponding MIMO receiving algorithm is the detection algorithm of the maximum likelihood criterion;

The configuration combination is: the modulation mode is high, the channel coding rate is medium or high, the frequency diversity is medium or high, the space diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm.

The configuration acquisition module is used to obtain the current configuration.

The detection algorithm selection module selects one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception according to the current configuration obtained by the configuration acquisition module and the corresponding relationship stored in the mapping storage module.

It is not difficult to find that this embodiment is an embodiment of the device corresponding to the first embodiment, and this embodiment can be implemented in cooperation with the first embodiment. The relevant technical details mentioned in the first embodiment are still valid in this embodiment, and will not be repeated here in order to reduce repetition. Correspondingly, the relevant technical details mentioned in this implementation manner can also be applied in the first implementation manner.

It is worth mentioning that all the modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, or a part of a physical unit, or multiple physical units. Combination of units. In addition, in order to highlight the innovative part of the present invention, units that are not closely related to solving the technical problems proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

The fourth embodiment of the present invention relates to a device for adaptively switching MIMO receiving algorithms. The fourth embodiment has been further improved on the basis of the third embodiment. The main improvement is that in the fourth embodiment of the present invention, the complexity of the maximum likelihood criterion detection algorithm and the relative linearity of the maximum likelihood criterion algorithm are affected. The various factors of the bit error rate performance gain of the algorithm also include: the ratio SINR of the signal to interference and noise; the adaptive switching strategy is further refined by using the ratio SINR of the signal to interference and noise, so that the adaptive switching is more reasonable and further Make the bit error rate performance as optimal as possible or the algorithm complexity as low as possible.

Specifically, as shown in Figure 4, the mapping storage module also stores the SINR value interval of the maximum likelihood criterion detection algorithm under each configuration in various configuration combinations; wherein, the SINR value interval is obtained through pre-simulation;

The detection algorithm selection module includes: parameter acquisition sub-module, comparison sub-module and determination sub-module;

The parameter acquisition sub-module is used to obtain the current configuration and current SINR of the receiving end;

Compare whether the current SINR of the sub-module belongs to the SINR value range under the current configuration;

When the comparison result is yes, the comparison sub-module triggers the determination sub-module to select the maximum likelihood criterion detection algorithm for data reception; when the comparison result is no, the comparison sub-module triggers the determination sub-module to select the linear detection algorithm for data reception.

Since the second embodiment corresponds to the present embodiment, the present embodiment can be implemented in cooperation with the second embodiment. The relevant technical details mentioned in the second embodiment are still valid in this embodiment, and the technical effects that can be achieved in the second embodiment can also be achieved in this embodiment, and in order to reduce repetition, details are not repeated here. Correspondingly, the relevant technical details mentioned in this embodiment mode can also be applied in the second embodiment mode.

Those of ordinary skill in the art can understand that the above-mentioned embodiments are specific examples for realizing the present invention, and in practical applications, various changes can be made to it in form and details without departing from the spirit and spirit of the present invention. scope.

Claims (10)

1. an adaptive switching method of MIMO receiving algorithm, is characterized in that, comprises the following steps: A. Pre-simulation to obtain the corresponding relationship between different configuration combinations of the receiving end and the MIMO receiving algorithm; B. Obtain the current configuration of the receiving end, and select one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception according to the corresponding relationship; Wherein, the configuration combination is: a configuration combination of various factors that affect the complexity of the maximum likelihood criterion detection algorithm and the bit error rate performance gain of the maximum likelihood criterion algorithm relative to the linear detection algorithm; The MIMO receiving algorithm includes: a linear detection algorithm and a maximum likelihood criterion detection algorithm. 2. the adaptive switching method of MIMO receiving algorithm according to claim 1, is characterized in that, the complexity of described influence maximum likelihood criterion detection algorithm and the bit error rate performance gain of maximum likelihood criterion algorithm relative linear detection algorithm The various factors include: diversity gain, channel coding rate, modulation method, and data streams transmitted in parallel in space; wherein, the diversity includes: frequency diversity and space diversity; The configuration of the diversity gain, channel coding rate, and modulation mode is any one of the following: low, medium, and high; The number of data streams transmitted in parallel space is greater than or equal to 2. 3. The adaptive switching method of the MIMO receiving algorithm according to claim 2, wherein the low, medium and high configurations of the frequency diversity correspond to 1.4M, 10M and 20M respectively; The low, medium, and high configurations of the spatial diversity correspond to high spatial correlation, medium spatial correlation, and low spatial correlation, respectively; The low, medium and high configurations of the modulation modes correspond to QPSK, 16QAM and 64QAM respectively; The low, medium, and high configurations of the channel coding rate correspond to 1/3, 1/2, and 3/4, respectively; The number of data streams transmitted in parallel in space is two. 4. the adaptive switching method of MIMO receiving algorithm according to claim 2, is characterized in that, the corresponding relation between described configuration combination and MIMO receiving algorithm comprises: The configuration combination is: the modulation mode is low or medium, the channel coding rate is medium or high, and the corresponding MIMO receiving algorithm is a detection algorithm of maximum likelihood criterion; The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency domain diversity is low, and the corresponding MIMO receiving algorithm is a detection algorithm of maximum likelihood criterion; The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm; The configuration combination is: the modulation mode is high, the channel coding rate is low, the frequency diversity is low, the space diversity is low, and the corresponding MIMO receiving algorithm is a detection algorithm of the maximum likelihood criterion; The configuration combination is: the modulation mode is high, the channel coding rate is medium or high, the frequency diversity is medium or high, the space diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm. 5. the adaptive switching method of MIMO reception algorithm according to claim 2, is characterized in that, the complexity of described influence maximum likelihood criterion detection algorithm and the bit error rate performance gain of maximum likelihood criterion algorithm relative linear detection algorithm The various factors also include: signal to interference and noise ratio SINR; In said step A, the following steps are also included: Pre-simulation to obtain the SINR value range of the maximum likelihood criterion detection algorithm under each configuration in various configuration combinations; In said step B, the following sub-steps are also included: Obtain the current configuration and current SINR of the receiving end, and judge whether the current SINR belongs to the SINR value interval under the current configuration; if so, select the maximum likelihood criterion detection algorithm for data reception; if not, select the linear detection algorithm for data reception Data reception. 6. according to the self-adaptive switching method of the MIMO receiving algorithm described in any one of claim 2 to 5, it is characterized in that, described method is applied to LTE system, and described modulation mode and described channel coding rate directly adopt modulation and The coding strategy MCS judges; the frequency diversity is judged directly by the number of resource blocks RB allocated to the user in the frequency domain; the air domain diversity is judged by the ratio between the eigenvalues of the channel correlation matrix. 7. An adaptive switching device of a MIMO receiving algorithm, comprising: a mapping storage module, a configuration acquisition module, and a detection algorithm selection module; The mapping storage module is used to store the corresponding relationship between different configuration combinations and MIMO receiving algorithms, wherein the corresponding relationship is obtained through pre-simulation; the configuration combination is: affecting the complexity of the maximum likelihood criterion detection algorithm and the maximum The configuration combination of various factors of the bit error rate performance gain of the likelihood criterion algorithm relative to the linear detection algorithm; the MIMO receiving algorithm includes: a linear detection algorithm, a detection algorithm of the maximum likelihood criterion; The configuration obtaining module is used to obtain the current configuration; The detection algorithm selection module selects one of the linear detection algorithm or the maximum likelihood criterion detection algorithm for data reception according to the current configuration obtained by the configuration acquisition module and the corresponding relationship stored in the mapping storage module. 8. The adaptive switching device of MIMO receiving algorithm according to claim 7, is characterized in that, the complexity of described influence maximum likelihood criterion detection algorithm and the bit error rate performance gain of maximum likelihood criterion algorithm relative linear detection algorithm The various factors include: diversity gain, channel coding rate, modulation method, and data streams transmitted in parallel in space; wherein, the diversity includes: frequency diversity and space diversity; The configuration of the diversity gain, channel coding rate, and modulation mode is any one of the following: low, medium, and high; The number of data streams transmitted in parallel space is greater than or equal to 2. 9. The adaptive switching device of the MIMO reception algorithm according to claim 8, wherein the correspondence stored in the mapping storage module includes: The configuration combination is: the modulation mode is low or medium, the channel coding rate is medium or high, and the corresponding MIMO receiving algorithm is a detection algorithm of maximum likelihood criterion; The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is low, and the corresponding MIMO receiving algorithm is a detection algorithm of maximum likelihood criterion; The configuration combination is: the modulation mode is low or medium, the channel coding rate is low, the frequency diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm; The configuration combination is: the modulation mode is high, the channel coding rate is low, the frequency diversity is low, the space diversity is low, and the corresponding MIMO receiving algorithm is a detection algorithm of the maximum likelihood criterion; The configuration combination is: the modulation mode is high, the channel coding rate is medium or high, the frequency diversity is medium or high, the space diversity is medium or high, and the corresponding MIMO receiving algorithm is a linear detection algorithm. 10. The adaptive switching device of MIMO receiving algorithm according to claim 8, is characterized in that, the complexity of described influence maximum likelihood criterion detection algorithm and the bit error rate performance gain of maximum likelihood criterion algorithm relative linear detection algorithm The various factors also include: signal to interference and noise ratio SINR; The mapping storage module also stores the SINR value interval of the maximum likelihood criterion detection algorithm under each configuration in various configuration combinations; wherein, the SINR value interval is obtained through pre-simulation; The detection algorithm selection module includes: a parameter acquisition submodule, a comparison submodule and a determination submodule; The parameter acquisition submodule is used to acquire the current configuration and current SINR of the receiving end; The comparison submodule judges whether the current SINR belongs to the SINR value interval under the current configuration; When the comparison result is yes, the comparison submodule triggers the determination submodule to select the maximum likelihood criterion detection algorithm for data reception; when the comparison result is no, the comparison submodule triggers the determination submodule to select Linear detection algorithm for data reception.