CN1674482A - Method and apparatus for detecting normalized iterative soft interference cancelling signal - Google Patents
Method and apparatus for detecting normalized iterative soft interference cancelling signal Download PDFInfo
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Abstract
The normalized iterative soft interference cancellation signal detection method relates to a signal detection method of multiaerial wireless communication system iterative receiver. Said detection method is characterized by that it makes the received multiaerial signal undergo the processes of interative detection, decoding and receiving treatment based on iterative soft interference cancellation detection. Said invention also provides the equipment for implementing said detection method.
Description
Technical Field
The present invention relates to a broadband mobile communication system for transmitting high-speed data by using a plurality of transmission/reception antennas, and more particularly, to a signal detection method for an iterative receiver of a multi-antenna wireless communication system. The wireless communication system involved has one or more receive antennas and one or more transmit antennas.
Background
Under the condition of a certain fault tolerance, the multi-antenna transmission and multi-antenna reception technology is now used to improve the transmission efficiency of the wireless communication system, reduce the transmission power under the condition of a given transmission rate, or improve the transmission rate of signals under the condition of a given transmission power. In the case where the carrier frequency is high and the distance between the antennas is long, the path loss from each transmitting antenna to each receiving antenna can be regarded as approximately independent, and in this case, there are many kinds of transmission/reception methods of multiple antennas, mainly space division multiplexing and space time coding. The space division multiplexing system transmits independent data streams such as V-BLAST (vertical bell labs layered space-time structure) at each transmit antenna, so that high-altitude time-space coding utilizes orthogonality design, and the same signal is transmitted in different forms at each transmit antenna to obtain transmit diversity and simplify the complexity of a receiver.
In a wideband system, the symbol time interval is less than the multipath delay spread of a multipath channel, and thus the received signal may have intersymbol interference in time. Multi-carrier systems such as orthogonal frequency division multiplexing, etc., can solve this problem to some extent. Due to the presence of multiple transmit antennas, interference between the signals of the multiple antennas may be present at each receive antenna. Let the number of transmitting antennas be N, the number of receiving antennas be M, the maximum multipath delay spread of the channel be L, and use sn(k) Indicating the transmission signal of the nth transmitting antenna at time k, using rm(k) And zm(k) Respectively representing the signal received by the mth receiving antenna at the kth moment and additive white Gaussian noise, hm，n(l) And the channel impulse response coefficient from the nth transmitting antenna to the mth receiving antenna when the time delay is l. Then there are:
the iterative detection decoding method is an effective method for obtaining near-optimal joint detection decoding with low complexity in a multi-antenna system. In this method, the transmitted information bits are decided after a number of iterations between the detector and the decoder. In the non-last iteration process, the decoder calculates soft information (usually represented by log-likelihood ratio) of each bit and feeds the soft information back to the detector to assist the detector in detection, and under the condition that the decoder provides the soft information, the detector can obtain a more accurate output result, so that the decoder obtains better decoding performance, and the decoder iterates successively to obtain better performance. At present, a plurality of detectors are researched based on an iterative detection decoding method, and a Maximum A Posteriori (MAP) algorithm, a Minimum Mean Square Error (MMSE) algorithm, an approximate maximum likelihood method such as sphere decoding and the like are mainly researched, and the methods have relatively good performance but still have high complexity. The invention provides an iterative soft interference cancellation detection method based on matching combination, which is an effective detection method for reducing complexity.
Disclosure of Invention
The technical problem is as follows: the invention aims to provide a normalized iteration soft interference cancellation signal detection method and a device for a wireless communication receiver, wherein the method and the device have the advantages that space-time matching combination and iteration soft interference cancellation have lower complexity compared with other multi-antenna receiving methods; the iterative detection decoding method has higher performance; the normalization method not only reduces the dynamic range of data in the calculation process and is beneficial to realizing fixed points, but also reduces the number of variables in the process of mapping and is beneficial to realizing table lookup.
The technical scheme is as follows: in the multi-antenna wireless transmission iterative receiver, the detector can use the iterative soft interference cancellation detection method of the normalized space-time matching combination, firstly, the normalized matching combination on the space-time domain is carried out on the received multi-antenna signal at the receiving end, then, the iterative interference cancellation detection is carried out to obtain the estimated value of the signal and the estimated interference noise variance, then, the demodulation and the decoding are carried out, the decoder carries out the decoding to obtain the soft information of the bit, the mean value and the variance reconstruction are carried out on the signal, the soft information is fed back to the detector to carry out the interference cancellation, the demodulation and the decoding again.
The Turbo receiving method based on the iterative soft interference cancellation detection comprises the following steps:
step 1: normalization space-time matching and merging;
step 2: if the first detection decoding iteration is carried out, the following sub-steps are executed, and the step 3 is executed in the subsequent iteration;
21) the signal mean variance is initialized to mean 0, variance 1,
22) a multi-stage serial interference cancellation is performed,
23) the bit likelihood ratios are calculated and,
24) entering the step 4;
and step 3:
31) the signal mean and variance are reconstructed from the bit likelihoods fed back by the decoder,
32) the first-stage parallel interference cancellation is carried out,
33) the bit likelihood ratios are calculated and,
34) entering the step 4;
and 4, step 4:
41) de-interleaving the bit likelihood ratios, decoding,
42) and if the last detection decoding iteration is carried out, the step 5 is carried out. If not, the step 3 is carried out,
43) carrying out iterative decoding for a certain number of times, and reserving intermediate soft information for initializing decoding of next decoding iteration detection; outputting the decoded bit likelihood ratio and performing de-interleaving,
44) entering the step 3;
and 5:
and judging the bit likelihood ratio to obtain a judged output bit sequence.
The detection device comprises: soft input and soft output detector, interweaving and inverse interweaving device, soft input and soft output decoder, decision device; the soft-input soft-output detector comprises a space-time combining unit, an interference cancellation unit, a soft demodulation unit and a mean variance unit, wherein the input end of the space-time combining unit is connected with an input signal rm(K) The output end of the space-time merging unit is connected with an interference cancellation unit, the output end of the interference cancellation unit is connected with a soft demodulation unit, the output end of the soft demodulation unit is divided into two paths, one path is connected with a mean value variance unit, the output end of the mean value variance unit is connected with the interference cancellation unit, the other path at the output end of the soft demodulation unit is connected with an inverse interleaver in an interleaver and inverse interleaver, the output end of the inverse interleaver is connected with a soft input soft output decoder, the output end of the soft input soft output decoder is divided into two paths, one path is connected with the interleaver in the interleaver and inverse interleaver, and the other path is output to a decision device.
Space-time merging unit: and matching and combining the multi-antenna signals, and matching and combining the multi-path signals under a multi-path channel. Wherein the space-time combining unit uses a normalized space-time combining method.
A detector unit: the interference is removed, the variance of the de-interfered signal and the estimated interference noise is obtained, and soft information (usually expressed in log-likelihood ratios) for each bit is calculated. The detection method in which the detector unit uses soft input and soft output, i.e. the detector unit can use the soft information fed back by the decoder. The detector unit uses iterative soft interference cancellation detection, and the mean variance of the signal is quickly realized by using a table look-up method during first detection.
Interleaver and deinterleaver units: the de-interleaver arranges the detected bit likelihood ratios into the order of the decoder. And the interleaver rearranges the likelihood ratios of the decoder outputs as required by the detector.
Soft-input soft-output decoder unit: decoding the bit likelihood ratio after de-interleaving according to the constraint of the encoder by the encoding block to obtain a new decoded likelihood ratio, feeding the new decoded likelihood ratio back to the detector in the non-last iteration, and using the new decoded likelihood ratio for the judgment of the information bit in the last iteration.
Iterative receiver based on iterative soft interference cancellation detection
The iterative detection decoding receiving device in the multi-antenna system can be mainly divided into a soft-input soft-output detector, an interleaving and de-interleaving device, a soft-input soft-output decoder and the like.
1. The soft-input soft-output detector can be divided into four parts of normalized space-time matching combination, interference cancellation, bit likelihood ratio calculation and signal mean variance reconstruction. The space-time matching combining part collects signal energy of the received signals according to space and time dimensions to obtain combined signals and coefficients of corresponding signal components and interference signals. The interference cancellation part removes interference according to the signals obtained by space-time combination, corresponding coefficients and reconstructed mean variance, and calculates residual noise and variance of interference. A bit likelihood ratio calculating section calculates a likelihood ratio of a bit based on the interference-removed signal and the variance of the residual noise and interference, and supplies it to a decoder. And the signal mean variance reconstruction module reconstructs the mean variance of the signal according to the likelihood fed back or detected by the decoder.
2. The de-interleaver arranges the detected bit likelihood ratios into the order of the decoder. And the interleaver rearranges the likelihood ratios of the decoder outputs as required by the detector.
3. The decoder decodes the deinterleaved bit likelihood ratios according to the constraints of the encoder to obtain new decoded likelihood ratios, feeds them back to the detector in the non-last iteration, and uses them in the last iteration for the decision of information bits.
Has the advantages that: the iterative receiving method provided by the invention has the following advantages:
1. compared with the traditional receiver for detecting and decoding cascade connection, the performance is greatly improved, and the power efficiency is greatly improved under the condition of unchanged spectrum efficiency. The use of high order modulation can greatly improve spectral efficiency without changing power efficiency.
2. Compared with other iterative detection decoding methods, the iterative soft interference cancellation detection method based on normalized space-time matching combination effectively reduces the complexity of the detector, reduces the dynamic range of data, not only enables the complexity to linearly increase along with the number of transmitting antennas and the number of paths, but also avoids the inverse operation necessary for MMSE, and enables the algorithm to be more stable.
3. The normalization method not only reduces the dynamic range of data in the calculation process and is beneficial to realizing fixed points, but also reduces the number of variables in the process of mapping and is beneficial to realizing table lookup.
The receiving method provided by the invention is suitable for various wireless transmission systems and mainly comprises the following steps
1. The narrow-band multi-antenna transmission system is a frequency flat fading channel for signals.
2. The single carrier multi-antenna transmission system, i.e. the channel is frequency selective fading for the signal, and the transmission adopts the single carrier mode.
3. Multi-carrier multi-antenna transmission systems, such as OFDM, generalized multi-carrier systems.
4. The method can be used for not only spread spectrum systems but also non-spread spectrum systems.
5. The multiple access method can adopt various methods such as CDMA, TDMA, FDMA, etc.
6. May be used for communication between any two multi-antenna wireless devices.
Drawings
Fig. 1 is a block diagram of an iterative receiver for iterative soft interference cancellation detection. Among them are: soft input soft output detector 1, space-time combining unit 11, interference cancellation unit 12, soft demodulation unit 13, mean variance unit 14, interleaving and de-interleaving unit 2, de-interleaving unit 21, interleaving unit 22, soft input soft output decoder 3, and decision unit 4.
Detailed Description
In the multi-antenna wireless transmission iterative receiver, firstly, the normalization matching combination in the space-time domain is carried out on the received multi-antenna signals at the receiving end, then the iterative interference cancellation detection is carried out to obtain the estimated value of the signals and the estimated interference noise variance, then the demodulation and the decoding are carried out, the decoder carries out the decoding to obtain the soft information of bits, the mean value and the variance reconstruction are carried out on the signals, and the soft information is fed back to the detector to carry out the interference cancellation, the demodulation and the decoding again.
The iterative receiving method based on the iterative soft interference cancellation detection comprises the following steps:
step 1: normalization space-time matching and merging;
step 2: if the first detection decoding iteration is carried out, the following substeps are carried out, the subsequent iteration carries out step 3,
21) the signal mean variance is initialized to mean 0, variance 1,
22) a multi-stage serial interference cancellation is performed,
23) the bit likelihood ratios are calculated and,
24) entering the step 4;
and step 3:
31) the signal mean and variance are reconstructed from the bit likelihoods fed back by the decoder,
32) the first-stage parallel interference cancellation is carried out,
33) the bit likelihood ratios are calculated and,
34) entering the step 4;
and 4, step 4:
41) de-interleaving the bit likelihood ratios, decoding,
42) if the last detection decoding iteration is carried out, the step 5 is carried out, if not, the step 3 is carried out,
43) carrying out iterative decoding for a certain number of times, and reserving intermediate soft information for initializing decoding of next decoding iteration detection; outputting the decoded bit likelihood ratio and performing de-interleaving,
44) entering the step 3;
and 5:
and judging the bit likelihood ratio to obtain a judged output bit sequence.
Suppose a system has N transmit antennas and M receive antennas. The information bits are error correction encoded (including concatenated codes using iterative decoding or pattern-based codes), then bit interleaved and modulated, and distributed to the respective transmit antennas. The symbol sequence may be directly transmitted to each transmission antenna, or may be inserted with a cyclic prefix and subjected to IFFT (inverse fast fourier transform) to be transmitted as an OFDM (orthogonal frequency division multiplexing) symbol.
Order:
then the formula [1] can be expressed as
r(k)＝H·u(k)+ z(k) [2]
Wherein,r(k) a fully observed signal vector of ML x 1 signal s (k), H is a channel convolution matrix of ML x (2L-1) N, u (k) is a transmit signal vector of (2L-1) Nx 1,z(k) is a ML × 1 noise vector.
At a receiving end, the channel impulse response needs to be estimated by using a pilot frequency or a known sequence, and after the channel impulse response is obtained, iterative detection decoding is started. The transmitted signals are first combined in a normalized space-time matching manner, i.e.
Formula [3]Middle hN(L-1)+nIs the Nth (L-1) + nth column of the matrix H, <math> <mrow> <msub> <mi>ρ</mi> <mi>n</mi> </msub> <mo>=</mo> <msubsup> <mi>h</mi> <mrow> <mi>N</mi> <mrow> <mo>(</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>n</mi> </mrow> <mi>H</mi> </msubsup> <mo>·</mo> <msub> <mi>h</mi> <mrow> <mi>N</mi> <mrow> <mo>(</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>n</mi> </mrow> </msub> <mo>.</mo> </mrow> </math> and order
1. first time detection
The mean of the initialization signal is 0 and the variance is 1. And utilizing the reconstructed mean variance to counteract the interference of the combined signals, removing the interference, and calculating the variance of residual interference noise.
Wherein <math> <mrow> <msubsup> <mi>F</mi> <mi>n</mi> <mi>H</mi> </msubsup> <mo>=</mo> <msubsup> <mi>ρ</mi> <mi>n</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>·</mo> <msubsup> <mi>h</mi> <mrow> <mi>N</mi> <mrow> <mo>(</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>n</mi> </mrow> <mi>H</mi> </msubsup> <msub> <mover> <mi>H</mi> <mo>~</mo> </mover> <mrow> <mi>N</mi> <mrow> <mo>(</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>+</mo> <mi>n</mi> </mrow> </msub> <mo>.</mo> </mrow> </math> Formula [4]The interference of other signals is removed, formula [5]The variance of the residual interference noise is calculated. We assume that the remaining interference follows a gaussian distribution, then the signal transmission is equivalent to a gaussian channel, as follows:
then, the soft demodulation is carried out according to the signal modulation mode, and the likelihood ratio of each coded bit is obtained. The mean variance for reconstructing the signal using the bit likelihood ratios is as follows:
let the symbol α consist of the bit d0，d1，…dMc-1Is mapped to
After the mean value and the variance of the signals are reconstructed by using the formula [7], the formula [8] and the formula [9], interference cancellation is carried out by using the formula [4] and the formula [5] again, and then soft demodulation is carried out. And performing decoding after the loop iteration is performed for 2-4. It is noted here that the successive interference cancellation is used in the first detection, i.e. the mean and variance of the current symbol are updated after it has been demodulated, and the updated mean variance is used in the interference cancellation of the subsequent symbols.
Using the formula [7]Equation [8]]Equation [9]]The mean variance reconstruction requires soft demodulation of the signal, and has high computational complexity and exponentially increases with the modulation order. We can further simplify the mean variance reconstruction process according to the normalized characteristics, and the mean and variance are only the formula [6 ]]In
And σI，n 2(k) Function, i.e.
Wherein f is1(□) and f2(□) is a two-dimensional function, which can be realized by using a table lookup or a table lookup combined with interpolation in the practical system implementation. The method has the advantages of low complexity, low complexity and constant complexity, and only the mapping table needs to be changed when the system adopts different modulation modes.
2. Subsequent detection
And (3) reconstructing the mean value and the variance of the signal according to the bit likelihood ratio fed back by the decoder according to the formula [7], the formula [8] and the formula [9 ]. And then carrying out interference cancellation on all signals according to a formula [4] and a formula [5 ]. And after the variance between the signal estimation value and the corresponding noise interference is obtained, soft demodulation is carried out to obtain a bit likelihood ratio. In the subsequent detection, 1-stage parallel interference cancellation is used, namely the mean value and the variance of the signal are not updated according to the new detection result before the interference cancellation.
The detection device of the normalized iteration soft interference cancellation signal detection method comprises the following steps: a soft input soft output detector 1, an interleaving and de-interleaving device 2, a soft input soft output decoder 3 and a decision device 4; the soft-input soft-output detector 1 comprises a space-time combining unit 11, an interference cancellation unit 12, a soft demodulation unit 13 and a mean variance unit 14, wherein the input end of the space-time combining unit 11 is connected with an input signal rm(K) ", the output terminal of the space-time merging unit 11 is connected with the interference cancellation unit 12, the interference cancellation unitThe output end of 12 is connected with soft demodulation unit 13, the output end of soft demodulation unit 13 is divided into two paths, wherein one path is connected with mean value variance unit 14, the output end of mean value variance unit 14 is connected with interference cancellation unit 12, the other path of the output end of soft demodulation unit 13 is connected with inverse interleaver 21 in interleaver and inverse interleaver 2, the output end of inverse interleaver 21 is connected with soft input soft output decoder, the output end of soft input soft output decoder is divided into two paths, one path is connected with interleaver 22 in interleaver and inverse interleaver 2, and the other path is output to decision device 4.
The iterative receiving process based on iterative soft interference cancellation detection is that in a multi-antenna wireless transmission iterative receiver, firstly, normalization matching combination on a space-time domain is carried out on a received multi-antenna signal at a receiving end, then iterative interference cancellation detection is carried out to obtain an estimated value of the signal and an estimated interference noise variance, demodulation and decoding are carried out, a decoder carries out decoding to obtain bit soft information, mean value and variance reconstruction is carried out on the signal, the bit soft information is fed back to a detector to carry out interference cancellation, demodulation and decoding again.
The iterative receiving processing steps based on the iterative soft interference cancellation detection are as follows:
step 1: normalization space-time matching and merging;
i.e. according to the formula [3]First, the coefficients are calculated <math> <mrow> <msub> <mi>ρ</mi> <mi>n</mi> </msub> <mo>=</mo> <munderover> <mi>Σ</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <munderover> <mi>Σ</mi> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <mo>·</mo> <mo>|</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>|</mo> </mrow> </math> Sum coefficient <math> <mrow> <msub> <mi>f</mi> <mrow> <mi>n</mi> <mo>,</mo> <msup> <mi>n</mi> <mo>′</mo> </msup> </mrow> </msub> <mrow> <mo>(</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>=</mo> <msubsup> <mi>ρ</mi> <mi>n</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>·</mo> <munderover> <mi>Σ</mi> <mrow> <msup> <mi>l</mi> <mo>′</mo> </msup> <mo>=</mo> <mi>max</mi> <mo>{</mo> <mn>0</mn> <mo>,</mo> <mi>l</mi> <mo>}</mo> </mrow> <mrow> <mi>min</mi> <mo>{</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>,</mo> <mi>l</mi> <mo>+</mo> <mi>L</mi> <mo>-</mo> <mn>1</mn> <mo>}</mo> </mrow> </munderover> <munderover> <mi>Σ</mi> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msubsup> <mi>h</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>n</mi> </mrow> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <msup> <mi>l</mi> <mo>′</mo> </msup> <mo>)</mo> </mrow> <mo>·</mo> <msub> <mi>h</mi> <mrow> <mi>m</mi> <mo>,</mo> <msup> <mi>n</mi> <mo>′</mo> </msup> </mrow> </msub> <mrow> <mo>(</mo> <msup> <mi>l</mi> <mo>′</mo> </msup> <mo>-</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </math> Where L ═ - (L-1), …, L-1, then calculated <math> <mrow> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <msubsup> <mi>ρ</mi> <mi>n</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>·</mo> <munderover> <mi>Σ</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <munderover> <mi>Σ</mi> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msubsup> <mi>h</mi> <mrow> <mi>m</mi> <mo>,</mo> <mi>n</mi> </mrow> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>·</mo> <msub> <mi>r</mi> <mi>m</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>.</mo> </mrow> </math>
Step 2: if the first detection decoding iteration is carried out, the following substeps are carried out, the subsequent iteration carries out step 3,
2.1) initialize the variance of the mean of the signal to 0 and the variance to 1, i.e., sn(k)＝0， <math> <mrow> <msubsup> <mi>σ</mi> <mrow> <mi>s</mi> <mo>,</mo> <mi>n</mi> </mrow> <mn>2</mn> </msubsup> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mn>1</mn> <mo>.</mo> </mrow> </math>
2.2) performing multi-stage successive interference cancellation, where B is the signal block length, T is the interference cancellation stage number, and let n be 0, k be 0, and T be 0.
2.2.1) calculation <math> <mrow> <msub> <mover> <mi>x</mi> <mo>~</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <munderover> <mi>Σ</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>f</mi> <mrow> <mi>n</mi> <mo>,</mo> <msup> <mi>n</mi> <mo>′</mo> </msup> </mrow> </msub> <mrow> <mo>(</mo> <mo>-</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>·</mo> <msub> <mi>s</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>-</mo> <munderover> <mi>Σ</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>f</mi> <mrow> <mi>n</mi> <mo>,</mo> <msup> <mi>n</mi> <mo>′</mo> </msup> </mrow> </msub> <mrow> <mo>(</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>·</mo> <msub> <mi>s</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mi>l</mi> <mo>)</mo> </mrow> </mrow> </math> And
2.2.2) according to <math> <mrow> <mi>P</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>|</mo> <msub> <mi>s</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>α</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mrow> <msqrt> <mn>2</mn> <mi>π</mi> </msqrt> <msub> <mi>σ</mi> <mrow> <mi>I</mi> <mo>,</mo> <mi>n</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>·</mo> <mi>exp</mi> <mrow> <mo>(</mo> <mo>-</mo> <mfrac> <msup> <mrow> <mo>(</mo> <msub> <mover> <mi>x</mi> <mo>~</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>α</mi> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mrow> <msubsup> <mi>σ</mi> <mrow> <mi>I</mi> <mo>,</mo> <mi>n</mi> </mrow> <mn>2</mn> </msubsup> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>)</mo> </mrow> </mrow> </math> Calculating a signal sn(k) For each probability of transmitting a symbol. According to <math> <mrow> <msub> <mover> <mi>s</mi> <mo>‾</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mi>Σ</mi> <mi>α</mi> </munder> <mi>α</mi> <mo>·</mo> <mi>P</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>|</mo> <msub> <mi>s</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>α</mi> <mo>)</mo> </mrow> </mrow> </math> And
k is k +1, if k is B, n is n +1, k is 0; if N > N, N is 1, T is T +1, if T is T, step 2.3 is entered, otherwise step 2.2.1 is entered.
2.3) calculating bit likelihood ratios
2.4) entering the step 4;
and step 3:
3.1) reconstructing the mean and variance of the signal from the bit likelihoods fed back by the decoder, first
3.2) performing one-stage parallel interference cancellation
Computing <math> <mrow> <msub> <mover> <mi>x</mi> <mo>~</mo> </mover> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <munderover> <mi>Σ</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>f</mi> <mrow> <mi>n</mi> <mo>,</mo> <msup> <mi>n</mi> <mo>′</mo> </msup> </mrow> </msub> <mrow> <mo>(</mo> <mo>-</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>·</mo> <msub> <mi>s</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>-</mo> <munderover> <mi>Σ</mi> <mrow> <mi>l</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>L</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <msub> <mi>f</mi> <mrow> <mi>n</mi> <mo>,</mo> <msup> <mi>n</mi> <mo>′</mo> </msup> </mrow> </msub> <mrow> <mo>(</mo> <mi>l</mi> <mo>)</mo> </mrow> <mo>·</mo> <msub> <mi>s</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>+</mo> <mi>l</mi> <mo>)</mo> </mrow> </mrow> </math> And
3.3) calculating the bit likelihood ratio (synchronization step 2.3)
3.4) entering the step 4;
and 4, step 4:
4.1) de-interleaving the bit likelihood ratios, decoding,
4.2) if the last detection decoding iteration is carried out, the step 5 is carried out, if not, the step 3 is carried out,
4.3) carrying out iterative decoding for a certain number of times, and reserving intermediate soft information for initializing decoding of next decoding iteration; outputting the decoded bit likelihood ratio and performing de-interleaving,
4.4) entering the step 3;
and 5:
and judging the bit likelihood ratio to obtain a judged output bit sequence.
Wherein the calculation of the mean variance in step 2.2.2 can be carried out using a look-up table, i.e.
Claims (3)
1. A normalized iterative soft interference cancellation signal detection method is characterized in that the detection method is iterative detection decoding receiving processing based on iterative soft interference cancellation detection, in a multi-antenna wireless transmission iterative receiver, firstly, normalization matching combination on a space-time domain is carried out on a received multi-antenna signal at a receiving end, then, iterative interference cancellation detection is carried out to obtain an estimated value of the signal and an estimated interference noise variance, then, demodulation and decoding are carried out, a decoder carries out decoding to obtain bit soft information, mean value and variance reconstruction is carried out on the signal, the signal is fed back to a detector to carry out interference cancellation again, and demodulation and decoding are carried out.
2. The method of claim 1, wherein the iterative detection decoding receiving processing steps based on iterative soft interference cancellation detection are as follows:
step 1: normalization space-time matching and merging;
step 2: if the first detection decoding iteration is carried out, the following substeps are carried out, the subsequent iteration carries out step 3,
21) the signal mean variance is initialized to mean 0, variance 1,
22) a multi-stage serial interference cancellation is performed,
23) the bit likelihood ratios are calculated and,
24) entering the step 4;
and step 3:
31) the signal mean and variance are reconstructed from the bit likelihoods fed back by the decoder,
32) the first-stage parallel interference cancellation is carried out,
33) the bit likelihood ratios are calculated and,
34) entering the step 4;
and 4, step 4:
41) de-interleaving the bit likelihood ratios, decoding,
42) if the last detection decoding iteration is carried out, the step 5 is carried out, if not, the step 3 is carried out,
43) carrying out iterative decoding for a certain number of times, and reserving intermediate soft information for initializing decoding of next decoding iteration detection; outputting the decoded bit likelihood ratio and performing de-interleaving,
44) entering the step 3;
and 5:
and judging the bit likelihood ratio to obtain a judged output bit sequence.
3. A detection apparatus adapted for use in the normalized iterative soft interference cancellation signal detection method of claim 1, wherein said detection apparatus comprises: a soft input soft output detector (1), an interleaving and de-interleaving device (2), a soft input soft output decoder (3) and a decision device (4); the soft input soft output detector (1) comprises a space-time merging unit (11), an interference counteracting unit (12), a soft demodulating unit (13) and a mean square error unit (14), wherein the input end of the space-time merging unit (11) is connected with an input signal rm (K), the output end of the space-time merging unit (11) is connected with the interference counteracting unit (12), the output end of the interference counteracting unit (12) is connected with the soft demodulating unit (13), the output end of the soft demodulating unit (13) is divided into two paths, one path is connected with the mean square error unit (14), the output end of the mean square error unit (14) is connected with the interference counteracting unit (12), the other path at the output end of the soft demodulating unit (13) is connected with an interleaver (21) in the interleaver and the de-interleaver (2), the output end of the de-interleaver (21) is connected with a soft input soft output decoder, the output end of the soft input soft output decoder is divided into two paths, one path is connected with an interleaver (22), and the other path is output to a decision device (4).
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