CN102158313A - Soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition - Google Patents
Soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition Download PDFInfo
- Publication number
- CN102158313A CN102158313A CN201110068364XA CN201110068364A CN102158313A CN 102158313 A CN102158313 A CN 102158313A CN 201110068364X A CN201110068364X A CN 201110068364XA CN 201110068364 A CN201110068364 A CN 201110068364A CN 102158313 A CN102158313 A CN 102158313A
- Authority
- CN
- China
- Prior art keywords
- soft
- siso
- output
- mmse
- characteristic value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Error Detection And Correction (AREA)
Abstract
The invention relates to a soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition, which is characterized by comprising the following steps of: first, figuring out an equivalent channel matrix and an equivalent transmission correlation matrix by channel estimation and precoding of codebook information; carrying out eigenvalue decomposition on the equivalent transmission correlation matrix to acquire an eigenvalue and an eigenvector; inputting the equivalent channel matrix, the eigenvalue, the eigenvector and received signals into an SISO-MMSE detector, wherein the detector and an SISO decoder iteratively work by utilizing soft information input from the detector and the SISO detector as priori information; and finally, outputting a bit judgment by the decoder after the predefined iterations are reached. In the method of the invention, eigenvalue decomposition is introduced to transform the matrix inversion operation in each SISO-MMSE iteration process into division operation, thus the implementation complexity of the system is effectively reduced.
Description
Technical field
The present invention relates to a kind ofly reach the wide-band mobile communication system of high transfer rate, particularly a kind of wireless signal processing methods that is used for the radio communication receiving terminal by the MIMO-OFDM technology.
Background technology
Many antennas (Multiple Input Multiple Output, MIMO) technology and OFDM (Orthogonal Frequency Division Multiplexing, OFDM) combination of technology, can effectively improve the throughput and the efficiency of transmission of system, satisfy future mobile communication system many-sided demands such as power system capacity, the availability of frequency spectrum, message transmission rates.The MIMO technology can increase exponentially the power system capacity and the availability of frequency spectrum under the prerequisite that does not increase bandwidth, the OFDM technology is converted to several parallel narrow band channels with broad-band channel, can effectively resist multipath fading.(Long Term Evolution LTE) in the standard, has also adopted the transmission plan of MIMO-OFDM technology as down link to the Long Term Evolution of formulating third generation affiliate (3GPP).
In the MIMO-OFDM of reality system, received signal is subjected to channel selectivity decline, interchannel noise and the influence of the inter-antenna interference brought by many antennas.Usually adopt Error-Control Coding to resist channel fading and noise, and eliminate inter-antenna interference by detection technique.The iteration reception technique of joint decoding and detection by mutual soft information between detector and the decoder and iterate and approach optimal solution gradually, can improve receiver performance greatly.At traditional soft inputting and soft output least mean-square error (Soft Input Soft Output Minimum Mean Square Error, SISO-MMSE) in the iteration receiving algorithm, owing to relate to complicated matrix inversion operation in the SISO-MMSE testing process, and the number of times of matrix inversion operation increases with the increase of iterations, have higher computation complexity, limited the extensive use of this algorithm.For this reason, the present invention proposes a kind of soft inputting and soft output least mean-square error iteration receiving algorithm based on characteristic value decomposition, the advantage of this algorithm is to decompose the repeatedly inversion operation of having avoided in traditional SISO-MMSE iteration receiving algorithm by introducing characteristic value decomposition, effectively reduces the computation complexity of system.
Summary of the invention
Technical problem:The present invention proposes a kind of soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition, decompose the matrix inversion operation of avoiding in each SISO-MMSE iterative process by introducing characteristic value decomposition, the present invention guarantee with traditional SISO-MMSE iteration receive have consistent performance in, effectively reduce computation complexity.
Technical scheme:Soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition of the present invention may further comprise the steps: the first step, utilize channel estimating and precoding codebook information to try to achieve equivalent channel matrix and equivalence sends relevant battle array, and described equivalence is sent relevant battle array carry out characteristic value decomposition and obtain characteristic value and characteristic vector; Second step, soft information input soft inputting and soft output least mean-square error SISO-MMSE detector with described channel estimating, characteristic value, characteristic vector, frequency domain received signal and the output of soft inputting and soft output SISO decoder, by balanced estimated value and the variance that obtains to send signal of MMSE, the estimated value and the variance of described transmission signal are imported soft demodulator to obtain bit likelihood ratio information; In the 3rd step, the bit likelihood ratio that deinterleaver is exported described SISO-MMSE detector is arranged in the order of decoder, and the soft information that interleaver is exported the output of SISO decoder with soft inputting and soft is arranged according to the requirement of SISO-MMSE detector again; The 4th step, the soft input soft output decode device utilizes SISO-MMSE to detect the bit likelihood ratio of output as prior information, obtain new bit likelihood ratio by decoding, in non-last iteration, it is fed back to the SISO-MMSE detector and be used to rebuild average and variance, the soft information that described SISO-MMSE detector and the utilization of SISO decoder are exported each other is as the work of prior information iteration, in the last iteration, by soft input soft output decode device output bit decision.
Described characteristic value decomposition comprises that Jacobi Jacobi decomposes, the method for passing through numerical computations acquisition characteristic value and characteristic vector that ORTHOGONAL TRIANGULAR QR decomposes.
Described by the relevant battle array of described equivalence transmission is carried out characteristic value decomposition and preserved characteristic vector and characteristic value, the matrix inversion operation of SISO-MMSE detector in each iterative process is converted to division arithmetic.
Described soft inputting and soft output SISO decoder uses Turbo decoder or LDPC decoding.
Beneficial effect:The present invention proposes a kind of soft inputting and soft output least mean-square error iteration receiving algorithm based on characteristic value decomposition, decompose the matrix inversion operation of avoiding in each SISO-MMSE iterative process by introducing characteristic value decomposition, thereby effectively reduce the implementation complexity of system.
Description of drawings
Fig. 1 is the concrete device for carrying out said block diagram of soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition provided by the present invention.
Fig. 2 is an algorithm flow of exporting the least mean-square error iteration receiving method based on the soft inputting and soft of characteristic value decomposition provided by the present invention.
Embodiment
Soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition relates to a kind of by using multiple-input and multiple-output (Multiple Input Multiple Output, MIMO) technology and OFDM (Orthogonal Frequency Division Multiplexing, OFDM) technology reaches the wide-band mobile communication system of high transfer rate, described soft inputting and soft output least mean-square error iteration receiving method: the first step based on characteristic value decomposition, utilize channel estimating and precoding codebook information to try to achieve equivalent channel matrix and the relevant battle array of equivalence transmission, and the relevant battle array of described equivalence transmission is carried out characteristic value decomposition, and (Eigen Value Decomposition EVD) obtains characteristic value and characteristic vector; Second step, with described channel estimating, characteristic value, characteristic vector, frequency domain received signal and soft inputting and soft output (Soft Input Soft Output, SISO) soft information input soft inputting and soft output least mean-square error (the Soft Input Soft Output Minimum Mean Square Error of decoder output, SISO-MMSE) detector, by balanced estimated value and the variance that obtains to send signal of MMSE, the estimated value and the variance of described transmission signal are imported soft demodulator to obtain bit likelihood ratio information; In the 3rd step, the bit likelihood ratio that deinterleaver is exported described SISO-MMSE detector is arranged in the order of decoder, and interleaver is arranged the soft information of soft input soft output decode device output again according to the requirement of SISO-MMSE detector; The 4th step, the soft input soft output decode device utilizes SISO-MMSE to detect the bit likelihood ratio of output as prior information, obtain new bit likelihood ratio by decoding, in non-last iteration, it is fed back to SISO-MMSE detector and be used to rebuild average and variance, the soft information that described SISO-MMSE detector and the utilization of SISO decoder are exported each other is as the work of prior information iteration, in the last iteration, by soft input soft output decode device output bit decision.
Described soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition, it is characterized in that characteristic value decomposition comprises that Jacobi (Jacobi) decomposes, the different methods of passing through numerical computations acquisition characteristic value and characteristic vector such as ORTHOGONAL TRIANGULAR (QR) decomposition.
Described soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition, it is characterized in that carrying out characteristic value decomposition and preserving characteristic vector and characteristic value, the matrix inversion operation of SISO-MMSE detector in each iterative process is converted to division arithmetic by described equivalence is sent relevant battle array.
Described soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition, it is characterized in that described soft inputting and soft output (SISO) decoder can use comprises the Turbo decoder, the decoder of any soft inputting and soft output such as ldpc decoder.
The specific implementation device of the soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition of the present invention as shown in Figure 1, be divided into characteristic value decomposition, the SISO-MMSE detector, interweave and deinterleaver, SISO decoder four parts specify as follows: 1. characteristic value decomposition is decomposed at first according to channel estimating and pre-coding matrix information, calculates equivalence and sends relevant battle array, and the relevant battle array of this equivalence carried out the characteristic value decomposition decomposition operation, try to achieve characteristic value and characteristic vector.
2. the SISO-MMSE detector utilizes the characteristic value of characteristic value decomposition output and the soft information of characteristic vector, channel estimating, received signal and the output of SISO decoder to calculate the bit likelihood ratio as prior information, in the computational process of SISO-MMSE detector, avoid matrix inversion operation in order to utilize characteristic value decomposition to decompose, made the hypothesis that each layer reconstruction variance equates, this hypothesis influences receiver performance hardly.
3. deinterleaver is arranged in the order of decoder with the bit likelihood ratio of SISO-MMSE detector output, and the soft information that interleaver will decipher output is again according to the requirement arrangement of SISO-MMSE detector.
4. the SISO decoder utilizes SISO-MMSE to detect the bit likelihood ratio of output as prior information, obtain new bit likelihood ratio by decoding, in non-last iteration, it is fed back to the SISO-MMSE detector and be used to rebuild average and variance, in the last iteration, be used to export bit decision.
In order to make those skilled in the art person understand the present invention program better, the soft inputting and soft output iteration receiving method based on characteristic value decomposition that the embodiment of the invention provided is summarized as method flow diagram as shown in Figure 2.
In the embodiment that the application provided, should be understood that disclosed method not surpassing in the application's the spirit and scope, can realize in other way.Current embodiment is a kind of exemplary example, should be as restriction, and given particular content should in no way limit the application's purpose.For example, a plurality of unit or assembly can in conjunction with or can be integrated into another system, or some features can ignore, or do not carry out.
The above; only be the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; can expect easily changing or replacing, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of described claim.
Claims (3)
1. the soft inputting and soft based on characteristic value decomposition is exported the least mean-square error iteration receiving method, it is characterized in that: the first step, utilize channel estimating and precoding codebook information to try to achieve equivalent channel matrix and equivalence sends relevant battle array, and described equivalence is sent relevant battle array carry out characteristic value decomposition and obtain characteristic value and characteristic vector; Second step, soft information input soft inputting and soft output least mean-square error SISO-MMSE detector with described channel estimating, characteristic value, characteristic vector, frequency domain received signal and the output of soft inputting and soft output SISO decoder, by balanced estimated value and the variance that obtains to send signal of MMSE, the estimated value and the variance of described transmission signal are imported soft demodulator to obtain bit likelihood ratio information; In the 3rd step, the bit likelihood ratio that deinterleaver is exported described SISO-MMSE detector is arranged in the order of decoder, and the soft information that interleaver is exported the output of SISO decoder with soft inputting and soft is arranged according to the requirement of SISO-MMSE detector again; The 4th step, the soft input soft output decode device utilizes SISO-MMSE to detect the bit likelihood ratio of output as prior information, obtain new bit likelihood ratio by decoding, in non-last iteration, it is fed back to the SISO-MMSE detector and be used to rebuild average and variance, the soft information that described SISO-MMSE detector and the utilization of SISO decoder are exported each other is as the work of prior information iteration, in the last iteration, by soft input soft output decode device output bit decision.
2. the soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition according to claim 1, it is characterized in that characteristic value decomposition comprises that Jacobi Jacobi decomposes, the method for passing through numerical computations acquisition characteristic value and characteristic vector that ORTHOGONAL TRIANGULAR QR decomposes.
3. the soft inputting and soft output least mean-square error iteration receiving method based on characteristic value decomposition according to claim 1 is characterized in that described soft inputting and soft output SISO decoder uses Turbo decoder or LDPC decoding.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110068364XA CN102158313A (en) | 2011-03-22 | 2011-03-22 | Soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110068364XA CN102158313A (en) | 2011-03-22 | 2011-03-22 | Soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102158313A true CN102158313A (en) | 2011-08-17 |
Family
ID=44439522
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110068364XA Pending CN102158313A (en) | 2011-03-22 | 2011-03-22 | Soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102158313A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102664852A (en) * | 2012-04-19 | 2012-09-12 | 东南大学 | Soft-input soft-output detection method in multi-input multi-output orthogonal frequency division multiplexing system |
| CN104202271A (en) * | 2014-09-02 | 2014-12-10 | 江苏理工学院 | Iterative equalization method based on survivor path-by-survivor path processing in direct sequence spread spectrum communication |
| CN106301390A (en) * | 2016-08-11 | 2017-01-04 | 中国计量大学 | LDPC/Turbo code dual-mode decoding device |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1674482A (en) * | 2005-04-01 | 2005-09-28 | 东南大学 | Method and apparatus for detecting normalized iterative soft interference cancelling signal |
-
2011
- 2011-03-22 CN CN201110068364XA patent/CN102158313A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1674482A (en) * | 2005-04-01 | 2005-09-28 | 东南大学 | Method and apparatus for detecting normalized iterative soft interference cancelling signal |
Non-Patent Citations (1)
| Title |
|---|
| JINHO CHOI: "MIMIO-BICM iterative receiver with the EM based channel estimation and simplified MMSE combining with soft cancellation", 《IEEE TRANSACTIONS ON SIGNAL PROCESSING》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102664852A (en) * | 2012-04-19 | 2012-09-12 | 东南大学 | Soft-input soft-output detection method in multi-input multi-output orthogonal frequency division multiplexing system |
| CN104202271A (en) * | 2014-09-02 | 2014-12-10 | 江苏理工学院 | Iterative equalization method based on survivor path-by-survivor path processing in direct sequence spread spectrum communication |
| CN104202271B (en) * | 2014-09-02 | 2018-04-13 | 江苏理工学院 | Iterative equalization method based on survivor path-by-survivor path processing in direct sequence spread spectrum communication |
| CN106301390A (en) * | 2016-08-11 | 2017-01-04 | 中国计量大学 | LDPC/Turbo code dual-mode decoding device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8218671B2 (en) | Receiving apparatus, receiving method and communication system | |
| KR20050076676A (en) | Decoding apparatus and method of mimo system | |
| CN115021781B (en) | Multi-user multiple-input multiple-output modulation diversity method based on probability shaping | |
| CN101854237B (en) | Transmission method for precoding based on non-codebook in time-varying MIMO system | |
| WO2015112883A1 (en) | System and method for early termination in iterative null-space directed singular value decomposition for mimo | |
| US8660217B2 (en) | Methods and apparatus for low complexity soft-input soft-output group detection | |
| Qiao et al. | Massive access in media modulation based massive machine-type communications | |
| KR20120119935A (en) | Method and apparatus of detecting signal based on minimum mean square error in multiple input multiple output system | |
| WO2007112634A1 (en) | Space domain filter detecting method in multi-antennas wireless communication system | |
| CN105897627B (en) | Iterative soft interference elimination receiving method under large-scale MIMO omnidirectional precoding transmission | |
| Feng et al. | Low complexity iterative detection for a large-scale distributed MIMO prototyping system | |
| CN102123114A (en) | Non-codebook-precoding-based transmission method for multi-input multi-output (MIMO) system | |
| CN105610484B (en) | Extensive MIMO Low-complexity iterative receiver methods | |
| CN101227254A (en) | Method for detecting V-BLAST in MIMO system | |
| CN102215073B (en) | Multipoint-multiuser uplink low-complexity MIMO (Multiple Input Multiple Output) detection method | |
| CN102158313A (en) | Soft-input soft-out (SISO) minimum mean squared error (MMSE) iteration receiving method based on eigenvalue decomposition | |
| Anwar et al. | MIMO spatial turbo coding with iterative equalization | |
| CN103326825B (en) | A kind of quasi-orthogonal space time block code low-complexity decoding method | |
| Ghaffar et al. | Low Complexity BICM MIMO OFDM Demodulator | |
| Meng et al. | Combined transmit antenna selection and detection over spatial correlated MIMO systems | |
| KR101501847B1 (en) | Multi User- Multi Input Multi Output system, and Transmitting/receiving apparatus | |
| Wang et al. | Differential interference suppression for SDMA-OFDM based on joint multiple-symbol filtering and detection | |
| CN100372277C (en) | Space time separation soft inputting and outputting detecting method based on spatial domain prewhitening mergence | |
| US8792595B2 (en) | Wireless communications device and method | |
| Valkanas et al. | Introduction to Space–Time Coding |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20110817 |