CN101136898B - Quadrature amplitude modulated soft decision method and apparatus - Google Patents

Abstract

Being applicable to solve the issue that in current technique, demodulation procedure is too complex, the invention discloses simplified schemes for two algorithms. Scheme 1 is that using LLR algorithm and MAX-log algorithm simplifies current demodulation procedure into piecewise functions. Scheme 2 is that using minimum distance between the received signal and hard decision boundary determines amplitude of soft bits to simplify demodulation procedure further. First, the invention decomposes signal in orthogonal into first branch component, and second branch component, and then calculates their soft bits so as to accomplish soft decision-making procedure. In scheme 1, the equipment includes communication interface (CI), decomposition module (DM), judgment module (JM), computing module (CM), and output module (OM). In scheme 2, the equipment includes CI, DM, JM, CM, and OM.

Description

A kind of quadrature amplitude modulated soft decision method and device

Technical field

The present invention relates to the implementation method and the device of the computer and the communications field, particularly a kind of quadrature amplitude modulated soft decision.

Background technology

In order to improve signal transmission quality, digital modulation technique is widely used, and corresponding demodulation techniques are also in development.Quadrature amplitude modulation (QAM, Quadrature Amplitude Modulation) be the two-dimensional modulation technology, when realizing, adopt the mode of quadrature amplitude modulation, the amplitude that the projection of certain constellation point on I coordinate (first branch road) removes to modulate the homophase carrier wave, the amplitude that the modulation orthogonal carrier wave is removed in projection on Q coordinate (second branch road) is exactly required phase-modulated signal with two amplitude-modulated signal additions then.

For the information that makes full use of received signal realizes channel-decoding, the channel decoding module of current communication system is used soft inputting and soft output (SISO) decoder usually, the bit that its requirement receives lives through soft decision processes, and this soft-decision output bit can reflect the soft-decision data of the value probability that receives bit.With respect to the hard bit of hard decision output, the output of soft-decision is called soft bit.

The soft bit input of SISO decoder requires to obtain by log-likelihood ratio (LLR) algorithm, and through the output of LLR algorithm is that the demodulation input bit gets 0 or the logarithm value of getting the ratio of 1 posterior probability.Be modulated to example (1 bit modulation is a signal) with simple second-order, the incident that receives deterministic signal is designated as C, this signal is that 0 o'clock posterior probability is P (0|C), and the posterior probability that is at 1 o'clock is P (1|C), and then the soft bit of this signal output can be expressed as $S=\log \left(\frac{P\left(0\right|C)}{P\left(1\right|C)}\right).$ As can be seen, it is big more that this signal is got 0 the big more then soft bit of probability, and it is more little to get 1 the big more then soft bit of probability.The size of soft bit can reflect the value probability of this signal, and its signal (positive and negative) is directly corresponding with the result of hard decision again, therefore can keep the amount of information of received signal as far as possible, avoids because the amount of information loss that hard decision causes.

Mainly adopt qam mode at present in the prior art.For 16QAM, at first calculate to receive constellation point and 16 standard constellation point distance square; Then, choose this bit respectively and be 0 and 1 standard constellation point, and ask the absolute value of the difference of two minimum values apart from the minimum value that receives the constellation point square distance; At last, with absolute difference extraction of square root output amplitude (absolute value), be the signal of soft bit with the signal map of difference as soft bit.Adopt this scheme, not only amount of calculation is big, and system realizes also more complicated.

Summary of the invention

The invention provides a kind of quadrature amplitude modulated soft decision method and device, have the big and realization complicated problems of amount of calculation in the prior art in order to solve.

The invention provides following technical scheme:

A kind of method that realizes quadrature amplitude modulated soft decision in communication system comprises step:

Quadrature decomposes the signal that receives, and obtains first branch component and second branch component;

With the piecewise interval at first branch component and second branch component and definite its place of threshold ratio, obtain to be used for calculating at this piecewise interval the piecewise function of soft bit respectively, wherein, described threshold value is determined by the long-pending of a minimum Eustachian distance and a constant;

Calculate and export corresponding soft bit respectively according to described piecewise function, described first branch component and second branch component.

Described piecewise function obtains based on log-likelihood ratio LLR algorithm and the maximum approximate MAX-log algorithm of logarithm.By described MAX-log algorithm the result of LLR algorithm is carried out approximate calculation and obtain piecewise function.

The number of described soft bit is corresponding with the exponent number of quadrature amplitude modulation.

Described communication system is WCDMA or TD-SCDMA system.

A kind of method that realizes quadrature amplitude modulated soft decision in communication system comprises step:

Quadrature decomposes the signal that receives, and obtains first branch component and second branch component;

Respectively described first branch component and second branch component are calculated each soft bit as the input of soft-decision function, wherein, the signal that the amplitude of the soft bit of described soft-decision function output is proportional to this soft bit correspondence is determined the sign of the soft bit of described soft-decision function output to the marginal minimum range of hard decision by the hard decision result;

Export each described soft bit.

The number of described soft bit is corresponding with the exponent number of quadrature amplitude modulation.

Described communication system is WCDMA or TD-SCDMA system.

A kind of quadrature amplitude modulated soft decision device comprises:

Decomposing module is used for quadrature and decomposes the signal that receives, and obtains first branch component and second branch component;

Judge module, be used for respectively with first branch component of described decomposing module acquisition and the piecewise interval at second branch component and definite its place of threshold ratio, acquisition is used for calculating at this piecewise interval the piecewise function of soft bit, wherein, described threshold value is determined by the long-pending of a minimum Eustachian distance and a constant;

Computing module is used for calculating corresponding soft bit respectively according to piecewise function, described first branch component and second branch component that described judge module is determined;

Output module is used to export the soft bit that described computing module is determined.

The piecewise function that described judge module is determined obtains based on log-likelihood ratio LLR algorithm and the maximum approximate MAX-log algorithm of logarithm.

A kind of quadrature amplitude modulated soft decision device comprises:

Decomposing module is used for quadrature and decomposes the signal that receives, and obtains first branch component and second branch component;

Computing module, first branch component and second branch component that are used for respectively described decomposing module being obtained are calculated each soft bit as the input of soft-decision function, wherein, the signal that the amplitude of the soft bit of described soft-decision function output is proportional to this soft bit correspondence is determined the sign of the soft bit of described soft-decision function output to the marginal minimum range of hard decision by the hard decision result;

Output module is used to export the soft bit that described computing module is determined.

Beneficial effect of the present invention is as follows:

Because the present invention adopts LLR algorithm and Max-log algorithm that existing soft-decision algorithm is simplified, and the value of signal is carried out segmentation calculate, so significantly reduced amount of calculation and computing time; The present invention further determines the output amplitude of soft bit on this basis to the marginal minimum range of hard decision by received signal, use straight line that the broken line in preceding a kind of scheme is similar to, further simplified computational process, simplified soft decision processes simultaneously, reduced amount of calculation significantly, and device is realized also comparatively simple.And the present invention is applicable to multiple qam mode, and shows almost not influence of actual performance through emulation experiment.

Description of drawings

The 16QAM planisphere of Fig. 1 in WCDMA, using in the embodiment of the invention;

The 16QAM planisphere of Fig. 2 in TD-SCDMA, using in the embodiment of the invention;

Fig. 3 is the flow chart of segmentation soft decision method in the embodiment of the invention;

Fig. 4 is the structural representation of segmentation soft-decision device in the embodiment of the invention;

Fig. 5 be in the embodiment of the invention in TD-SCDMA the marginal schematic diagram of 16QAM hard decision;

Fig. 6 be in the embodiment of the invention in TD-SCDMA piecewise function and simplify the image schematic diagram of function;

Fig. 7 is a method flow diagram of simplifying soft-decision in the embodiment of the invention;

Fig. 8 is a structural representation of simplifying the soft-decision device in the embodiment of the invention;

Fig. 9-Figure 13 is for adopting the effect emulation figure of technical scheme in different models that describes in the embodiment of the invention.

Embodiment

Excessive in order to solve in the prior art demodulating process soft-decision amount of calculation, realize than complicated problems.The present invention adopts LLR algorithm and Max-log (logarithm is maximum approximate) algorithm that existing algorithm is improved, in soft decision processes, the received signal quadrature is decomposited first branch component and second branch component, determine the computing formula of each soft bit according to each component and the comparative result of corresponding threshold value, obtain corresponding soft bit; The present invention determines the amplitude that soft bit is exported by received signal to the marginal minimum range of hard decision, and preceding a kind of method is further simplified.

With the 16QAM modulation system is that example illustrates the present invention.Stipulated the combination of 16 kinds of carrier amplitude and phase place among the 16QAM.Each modulation can be transmitted 4 bits among the 16QAM, and these bits are by 16 kinds of amplitudes of carrier wave and the incompatible transmission of phase-group.Demodulator is judged the information bit that transmitting terminal sends according to the amplitude and the phase place of planisphere and the carrier signal that receives.

Embodiment one

Present embodiment is that example describes to calculate soft bit by definite piecewise function mode.

At first in Wideband Code Division Multiple Access (WCDMA) (WCDMA, Wideband Code Division MultipleAccess) system, to obtain the method for the piecewise function of the soft bit of calculating based on LLR algorithm and Max-log algorithm for the example explanation.

In the 16QAM of WCDMA system modulation, each signal all corresponding real part (I branch road) and two components of imaginary part (Q branch road), wherein the amplitude of transmitting terminal I component has four kinds of values $\{-\frac{3}{2}d,-\frac{1}{2}d,\frac{1}{2}d,\frac{3}{2}d\},$ Wherein d represents the minimum Eustachian distance in the planisphere, for the standard 16QAM planisphere in the WCDMA system $d=\frac{2}{\sqrt{10}},$ Described planisphere sees also Fig. 1, and 4 of each standard constellation point bit-order are followed successively by i shown in Fig. 1 ₁, q ₁, i ₂And q ₂

For the transmitting terminal I component that knows, the distribution of receiving terminal I component meets Gaussian Profile, and its probability density satisfies following formula:

$y=\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\mathrm{\&mu;})}^2]$

Wherein, μ is an average, and σ is a standard deviation.Four kinds of values for the transmitting terminal I component $\{-\frac{3}{2}d,-\frac{1}{2}d,\frac{1}{2}d,\frac{3}{2}d\},$ σ is identical, respectively corresponding these the four kinds of values of μ.The prior probability of these four kinds of values equates, is 1/4.

Each signal is determined by 4 bits in the 16QAM modulation, is followed successively by i ₁, q ₁, i ₂And q ₂, establishing received signal R=x+jy event is A, the first bit i ₁With the second bit i ₂Corresponding to the real component of received signal R, corresponding x, the 3rd bit q ₁With the 4th bit q ₂Corresponding to the imaginary part component of received signal R, corresponding y.

With the first bit i ₁For soft bit is calculated in example explanation segmentation

Method:

Work as i ₁Value is that 1 o'clock incident is designated as B, and the value of transmitting terminal I component is i ₁Value is that 0 o'clock incident is designated as C, and the value of transmitting terminal I component is For binary bit stream have only 0,1 two kind of value.

Ask i ₁Value is 1 o'clock posterior probability P (B|A).By new probability formula as can be known $P\left(B\right|A)=\frac{P\left(\mathrm{AB}\right)}{P\left(A\right)},$ Launch according to the probability density formula, and the substitution parameter gets:

$\frac{\frac{1}{4}\left\{\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2\left]\right\}\mathrm{\&Delta;<figure-callout\; id="1"\; label="d"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">d</figure-callout>}}{\frac{1}{4}\left\{\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{{2\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2\left]\right\}\mathrm{\&Delta;d}}$

On the molecule The prior probability that the expression transmitting terminal takes place, because the probability of receiving terminal will be subjected to the restriction of transmitting terminal, $\frac{1}{4}\left\{\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2\left]\right\}$ Expression receiving terminal incident A and the simultaneous probability density of incident C multiply by Δ d and obtain probability afterwards; On the denominator

Expression is asked on average the contingent four kinds of probability density of incident A, multiply by Δ d and obtains corresponding probability afterwards.

Following formula simplified:

$\frac{\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2]}{\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{{2\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2]}---\left(1\right)$

Ask i ₁Value is 0 o'clock posterior probability P (C|A).By new probability formula as can be known $P\left(C\right|A)=\frac{P\left(\mathrm{AC}\right)}{P\left(A\right)},$ Launch according to the probability density formula, and the substitution parameter gets:

$\frac{\frac{1}{4}\left\{\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2\left]\right\}\mathrm{\&Delta;<figure-callout\; id="1"\; label="d"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">d</figure-callout>}}{\frac{1}{4}\left\{\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{{2\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2]+\frac{1}{\sqrt{2\mathrm{\&pi;\&sigma;}}}\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2\left]\right\}\mathrm{\&Delta;d}}$

Further be reduced to:

$\frac{\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2]}{\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{{2\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2]}---\left(2\right)$

Can get according to the LLR algorithm ${S_i}_{}$ ${{}_{}}_1=\log \frac{P\left(C\right|A)}{P\left(B\right|A)}---\left(3\right)$

Formula (1) and (2) substitution formula (3) back conversion can be got formula (4):

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=\log \left\{\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2\left]\right\}-\log \left\{\exp \right[-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2]+\exp [-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2]\}$

The result be on the occasion of the time, the expression i ₁Get 0 posterior probability greater than the posterior probability of getting 1, be worth greatly more, it is big more that 0 posterior probability is got in expression; During for negative value, expression i ₁Get 1 posterior probability greater than the posterior probability of getting 0, be worth more for a short time, it is big more that 1 posterior probability is got in expression.I no matter ₁Getting 0, also to get 1 o'clock posterior probability big, and signal is still got 1 point near getting at 0, illustrates that all the confidence level of this signal is very big, is easy to accurately demodulate the signal that transmitting terminal sends; If

Absolute value very little, illustrate that signal is situated between between 1,0, is difficult to accurately demodulate this signal.Need to prove that molecule and denominator can exchange in the formula, only need the signal map relation of corresponding modify decoding and hard decision to get final product, to essence did not influence of the present invention, the absolute value of soft bit is exported in fact more care.

Use the MAX-log approximate data, formula (4) can be reduced to:

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1\&ap;\mathrm{MAX}(-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2,-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2)-\mathrm{MAX}(-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2,-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2)$

$=\left\{\begin{array}{c}\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}(4d\&CenterDot;x+2d^2),x<-\mathrm{<figure-callout\; id="2"\; label="d\; E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">d</figure-callout>}& \\ \frac{E_b}{}\frac{{}_{}}{2{\mathrm{\&sigma;}}^2}\&CenterDot;2d\&CenterDot;x,-d\&le;x\&le;\mathrm{<figure-callout\; id="2"\; label="d\; E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">d</figure-callout>}& \\ \frac{E_b}{}\frac{{}_{}}{2{\mathrm{\&sigma;}}^2}(4d\&CenterDot;x-{2d}^2),x>d\end{array}\right.---\left(5\right)$

Because only need to guarantee that the proportionate relationship between the different soft bits is constant, concrete value does not have influence to actual performance, so can give up constant coefficient, formula is further simplified.Can cast out positive constant coefficient to formula (5) thus

2 and d obtain piecewise function:

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=\left\{\begin{array}{c}2x+d,x<-d\\ x,-d\&le;x\&le;d\\ 2x-d,x>d\end{array}\right.---\left(6\right)$

Select corresponding function according to the span of x, the function of visible this moment is very simple, and functional image is a broken line, and for the break in the formula, promptly x=d can be divided into ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=2x-d$ In, same x=-d can be divided into ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=2x+d$ In, to not influence of result of calculation.

For the second bit i ₂, work as i ₂Value is 1 o'clock, and the value of transmitting terminal I component is

i ₂Value is 0 o'clock, and the value of transmitting terminal I component is

Soft bit Computational methods with

Computational methods, can get in derivation through LLR algorithm and MAX-log approximate data:

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1\&ap;\mathrm{MAX}(-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{1}{2}d)}^2,-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{1}{2}d)}^2)-\mathrm{MAX}(-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x+\frac{3}{2}d)}^2,-\frac{{\mathrm{<figure-callout\; id="2"\; label="E\; b"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">E</figure-callout>}}_b}{2{\mathrm{\&sigma;}}^2}{(x-\frac{3}{2}d)}^2)$

Further derive piecewise function:

${{\mathrm{<figure-callout\; id="2"\; label="S\; i"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_2=\left\{\begin{array}{c}d+x,x<0\\ d-x,x\&GreaterEqual;0\end{array}\right.---\left(7\right)$

Because i ₂Value With All be about 0 point symmetry, so the span in the formula (7) is according to 0 division.

According to the symmetry of planisphere, the 3rd bit q ₁Calculate soft bit

Method with calculating soft bit Method, can get piecewise function:

${{\mathrm{<figure-callout\; id="1"\; label="S\; q"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_q}_1=\left\{\begin{array}{c}2y+d,y<-d\\ y,-d\&le;y\&le;d\\ 2y-d,y>d\end{array}\right.---\left(8\right)$

According to the symmetry of planisphere, the 4th bit q ₂Calculate soft bit

Method with calculating soft bit

Method, can get piecewise function:

${{\mathrm{<figure-callout\; id="2"\; label="S\; q"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_q}_2=\left\{\begin{array}{c}d+y,y<0\\ d-y,y\&GreaterEqual;0\end{array}\right.---\left(9\right)$

Obviously, the theoretical derivation process of the computing formula by above-mentioned introduction, the result who calculates soft bit as can be seen in the present embodiment can not have influence on existing demodulation performance.

Secondly, the formula of the soft bit of calculating can be obtained through rotation of coordinate by the result in the WCDMA system in TD SDMA (TD-SCDMA, Time Division Synchronized CodeDivision Multiple Access) system.

Because the 16QAM planisphere that uses among the TD-SCDMA can be by 45 ° of acquisitions of 16QAM planisphere rotation of using among the WCDMA, referring to planisphere shown in Figure 2, therefore the soft bit in the TD-SCDMA system can utilize the conclusion in the WCDMA system to obtain by the conversion reference coordinate.Soft bit computing formula also can be described in WCDMA in the TD-SCDMA system, pushes away from the probability angle, and the mode that adopts rotational coordinates do not influence the result of soft-decision just in order to obtain the computing formula of soft bit faster.

If the coordinate that the 16QAM planisphere among the WCDMA uses is X, Y, the coordinate that the 16QAM planisphere among the TD-SCDMA uses is x, y, then has: $(x+\mathrm{jy})\&CenterDot;e^{-j\frac{\mathrm{\&pi;}}{4}}=X+\mathrm{jY},$ Further obtain:

$\left\{\begin{array}{c}X=\frac{\sqrt{2}}{2}(x+y)\\ Y=\frac{\sqrt{2}}{2}(y-x)\end{array}\right.$

The method that obtains piecewise function in TD-SCDMA does not repeat them here with described in the WCDMA.Equally with i ₁Be the method for the soft bit of example explanation calculating, directly the piecewise function formula (6) that the following formula substitution is last obtains the piecewise function under the TD-SCDMA system:

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=\left\{\begin{array}{c}2\&times;\frac{\sqrt{2}}{2}(x+y)+d,x+y<-d\\ x+y,-d<x+y<\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">d</figure-callout>}\\ 2\&times;\frac{\sqrt{2}}{2}(x+y)+d,x+y>d\end{array}\right.$ With this formula divided by

Obtain computing formula:

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=\left\{\begin{array}{c}2(x+y)+\sqrt{2}d,x+y<-\sqrt{2}d\\ x+y,-\sqrt{2}d\&le;x+y\&le;\sqrt{2}d\\ 2(x+y)-\sqrt{2}d,x+y>\sqrt{2}d\end{array}\right.$

In soft decision processes, only need to calculate soft bit according to this formula, do not calculate again after not needing again the planisphere in the TD-SCDMA system to be transformed into the planisphere in the WCDMA system, what just quadrature decomposited in the quadrature decomposable process is first branch component and second branch component, rather than real component and imaginary part component.

In like manner can obtain i ₂, q ₁And q ₂Soft bit

With

Corresponding piecewise function is as follows:

${\mathrm{<figure-callout\; id="2"\; label="S\; i"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_{i_{}}=\left\{\begin{array}{c}\sqrt{2}d+(x+y),x+y<0\\ \sqrt{2}d-(x+y),x+y\&GreaterEqual;0\end{array}\right.$

${\mathrm{<figure-callout\; id="1"\; label="S\; q"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_{q_{}}=\left\{\begin{array}{cc}2(y-x)+\sqrt{2}d,& y-x<-\sqrt{2}d\\ y-x,& -\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">d</figure-callout>}\sqrt{2}\&le;y-x\&le;\sqrt{2}d\\ 2(y-x)-\sqrt{2}d,& y-x>\sqrt{2}d\end{array}\right.$

${\mathrm{<figure-callout\; id="2"\; label="S\; q"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_{q_{}}=\left\{\begin{array}{c}\sqrt{2}d+(y-x),(y-x)<0\\ \sqrt{2}d-(y-x),(y-x)\&GreaterEqual;0\end{array}\right.$

Based on the piecewise function of above-mentioned acquisition, present embodiment is the method for example explanation soft-decision with the WCDMA system, and method is identical in the TD-SCDMA system, repeats no more.

Referring to Fig. 3, the method step that carries out the segmentation soft-decision in the present embodiment to received signal is as follows:

Step 301: received signal, and signal is done quadrature decompose, decomposite first branch component x (in WCDMA, being real component) and the second branch component y (in WCDMA, being the imaginary part component), corresponding 2 bits of each component in 16QAM, totally 4 bits are respectively the i of real component correspondence ₁And i ₂, the q of imaginary part component correspondence ₁And q ₂

Step 302: according to the zone of described signal mapped constellation points on planisphere, be about to the first branch component x and the second branch component y respectively with threshold ratio, judge each bit is corresponding to which section, the Dui Ying selection computing formula again in the piecewise function.

With formula (6) is example, the first bit i ₁Corresponding real component value x respectively with threshold value-d (d with-1 product) and d (d with 1 product) comparison, when comparative result when being x greater than-d and less than d, the computing formula of the soft bit of correspondence is ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=x,$ Wherein d is a minimum Eustachian distance, in the present embodiment $d=\frac{2}{\sqrt{10}};$ In formula (7) for the second bit i ₂, corresponding real component value x and corresponding threshold 0 (d with 0 product) comparison, when comparative result is x less than 0 the time, the computing formula of the soft bit of correspondence is ${{\mathrm{<figure-callout\; id="2"\; label="S\; i"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_2=d+x;$ The 3rd bit q ₁With the 4th bit q ₂By imaginary part component y and threshold value relatively determine scope under it, and determine that further the method for computing formula is same as above.

Step 303: the soft bit that the first branch component x and the second branch component y substitution computing formula is calculated each bit respectively.

Step 304: 4 soft bits exporting each component correspondence

With

Referring to Fig. 4, the segmentation soft-decision device that is used to carry out soft decision processes in the WCDMA system comprises: communication interface 401, decomposing module 402, judge module 403, computing module 404 and output module 405.

The signal that communication interface 401 receives from transmitting terminal, and send it to decomposing module 402.Decomposing module 402 is decomposed the signal in orthogonal that communication interface 401 receives, and decomposites 4 bits on real component and the imaginary part component, and 4 bits are sent to judge module 403.Judge module 403 is according to the zone of described signal mapped constellation points on planisphere, with each component and corresponding threshold ratio, judges the affiliated scope of each bit, and the piecewise function in this scope.The computing formula correspondence that computing module 404 is selected according to judge module 403 calculate 4 soft bits.The soft bit of 4 bits that output module 405 output computing modules 404 calculate.

Embodiment two

Calculate the mode of soft bit in the present embodiment simplified embodiment one, in the WCDMA system, to determine that to the marginal minimum range of hard decision it is that example describes that the amplitude of soft bit output obtains soft bit by received signal.

The absolute value of soft bit is big more, and the erroneous judgement of this signal is more little, so the mapping point of signal in planisphere is far away more apart from the hard decision line of demarcation, and easy more demodulation, confidence level is also just high more.

The first bit i ₁The hard decision line of demarcation be straight line x=0, i ₂The hard decision line of demarcation be | x|=d, q ₁The hard decision line of demarcation be y=0 and q ₂The hard decision line of demarcation be | y|=d, wherein $d=\frac{2}{\sqrt{10}}.$

Determine the amplitude of soft-decision output according to the mapping point of received signal on planisphere to the marginal minimum range of hard decision, and the bit 0 or 1 of hard decision output is mapped as the positive sign or the negative sign of soft bit.The amplitude of soft bit is proportional to described distance in definite method of this amplitude, and its absolute size can be adjusted according to actual needs, but the relative amplitude between soft bit do not change, to not influence of actual performance.

With i ₁For example describes simplifying the method for calculating soft bit.i ₁The hard decision line of demarcation be x=0, so the constellation point of received signal on planisphere is exactly the absolute value of the abscissa x of this point to the distance of the longitudinal axis, promptly | x|, and as the i of hard decision output ₁Be 0 o'clock, corresponding soft bit ${S_i}_{}$ ${{}_{}}_1>0,$ i ₁Be 1 o'clock, corresponding ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1<0,$ So obtain calculating the formula of soft bit be ${S_i}_1=x,$ (consulting Fig. 1) do not need again x to be carried out segmentation, so adopt the formula after simplifying to save affiliated this step of scope of judgement component.

In like manner, i ₂, q ₁And q ₂Soft bit

With

The simplification computing formula as follows:

${{\mathrm{<figure-callout\; id="2"\; label="S\; i"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_2=\frac{2}{\sqrt{10}}-\left|x\right|$

${{\mathrm{<figure-callout\; id="1"\; label="S\; q"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_q}_1=y$

${{\mathrm{<figure-callout\; id="2"\; label="S\; q"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_q}_2=\frac{2}{\sqrt{10}}-\left|y\right|$

Obviously computing formula has obtained further simplification.

To be that the example explanation determines that to the marginal distance of hard decision the amplitude of soft bit output obtains the computational methods of soft bit by received signal in the TD-SCDMA system, this method is a transformed coordinate system with method described in the WCDMA, referring to Fig. 5, and i in the present embodiment ₁The hard decision line of demarcation be straight line x+y=0, i ₂The hard decision line of demarcation be $|x+y|=\frac{2}{\sqrt{5}},$ q ₁The hard decision line of demarcation be x-y=0 and q ₂The hard decision line of demarcation be $|x-y|=\frac{2}{\sqrt{5}}.$ The simplification computing formula of corresponding soft bit is as follows:

${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=x+y$

${{\mathrm{<figure-callout\; id="2"\; label="S\; i"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_2=\frac{2}{\sqrt{5}}-|x+y|$

${{\mathrm{<figure-callout\; id="1"\; label="S\; q"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_q}_1=y-x$

${\mathrm{<figure-callout\; id="2"\; label="S\; q"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_{q_{}}=\frac{2}{\sqrt{5}}-|y-x|$

With i ₁Be example, with the value of x+y as abscissa, with

Value get new coordinate system as ordinate, it is in alignment with the piecewise linear approximation in the soft-decision algorithm described in the embodiment one as can be seen from Figure 6 to simplify the soft-decision algorithm, makes soft decision processes simpler, the time spent is less, and actual performance does not descend.

Present embodiment is the method that soft-decision is simplified in the example explanation with the WCDMA system, and method is identical in the TD-SCDMA system, repeats no more.

Referring to Fig. 7, the method concrete steps of simplifying soft-decision in the present embodiment are as follows:

Step 701: received signal, and signal is done quadrature decompose, decomposite I branch component x and Q branch component y, corresponding 2 bits of each component in 16QAM, totally 4 bits are respectively the i of I branch component correspondence ₁And i ₂, the q of Q branch component correspondence ₁And q ₂

Step 702: respectively described I branch component and Q branch component are calculated each soft bit as the input of soft-decision function, wherein, the amplitude of the soft bit of described soft-decision function output is proportional to the signal and the marginal minimum range of hard decision of this soft bit correspondence, is determined the sign of the soft bit of described soft-decision function output by hard decision result (0 or 1).

With the first bit i ₁Be example, the formula that I branch component x substitution is calculated soft bit is ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=x$ Obtain soft bit.Wherein, the hard decision line of demarcation is x=0, i.e. the longitudinal axis,

Size be exactly the absolute value of the abscissa x of this point for the received signal mapped constellation points to the distance of the longitudinal axis, promptly | x|, and as the i of hard decision output ₁Be 0 o'clock, corresponding soft bit ${S_i}_{}$ ${{}_{}}_1>0,$ i ₁Be 1 o'clock, corresponding ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1<0,$ So the formula that obtains is ${{\mathrm{<figure-callout\; id="1"\; label="S\; i"\; filenames="H061B2657220060904E000032.png,H061B2657220060904E000052.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_1=x.$

For the second bit i ₂, the formula that I branch component x substitution is calculated soft bit is ${{\mathrm{<figure-callout\; id="2"\; label="S\; i"\; filenames="H061B2657220060904E000031.png,H061B2657220060904E000032.png"\; state="\{\{state\}\}">S</figure-callout>}}_i}_2=\frac{2}{\sqrt{10}}-\left|x\right|$ Obtain soft bit.Wherein, the hard decision line of demarcation is | x|=d, when x＞0, this constellation point to the distance of x=d less than distance to x=-d, so

Size be the distance of this constellation point to x=d, promptly

Also can be write as

X＜0 o'clock, this constellation point to the distance of x=-d less than distance to x=d, so

Size be the distance of this constellation point to x=-d, promptly

I when hard decision output ₂Be 0 o'clock, corresponding soft bit ${S_i}_{}$ ${{}_{}}_2>0,$ Be 1 o'clock, corresponding soft bit ${S_i}_{}$ ${{}_{}}_2<0,$ So obtain calculating the formula of soft bit be ${S_i}_2=\frac{2}{\sqrt{10}}-\left|x\right|.$

The 3rd bit q ₁With the 4th bit q ₂The method of calculating its corresponding soft bit is identical.

Step 703: the soft bit of exporting each component correspondence

With

This shows, omitted the step 302 described in the embodiment one, accordingly the soft-decision device is further simplified.As long as the proportionate relationship between each soft bit is constant, just can not have influence on actual performance.

Referring to Fig. 8, the simplification soft-decision device that is used to carry out soft decision processes in the present embodiment comprises: communication interface 801, decomposing module 802, computing module 803 and output module 804.

Communication interface 801 is used to receive the signal from transmitting terminal, and sends it to decomposing module 802.Decomposing module 802 is used for the received signal quadrature from communication interface 801 is decomposed, and decomposites 4 bits on I branch component and the Q branch component.4 bits that 803 pairs of decomposing module 802 of computing module decomposite calculate, and adopt corresponding computing formula to calculate 4 soft bits.The soft bit of 4 bits that output module 804 output computing modules 803 calculate.

In BF561 (a kind of model of instrument) emulation experiment based on ADI (Analog Devices Inc), prior art needs about 90 cycles (instruction cycle) to the demodulation of each signal, segmentation soft decision method among the embodiment one needs about 30 cycles, and the simplification soft decision method among the embodiment two only needs 9 cycles.Can obviously find out beneficial effect of the present invention from testing numeral.

Block Error Rate under several channels (Block Error Rate now is provided, BLER) simulation result illustrates the beneficial effect that adopts such scheme, wherein, AWGN is the white noise channel, and PA3, PB3, VA30, VA120 are respectively several channel models (consulting 3GPP TS25.102 R5 version) of ITU definition.The Method1 correspondence be the performance curve of the scheme described of embodiment one, the Method2 correspondence be the performance curve of the scheme described of embodiment two.Extremely shown in Figure 13 as Fig. 9, the performance curve of the scheme of embodiment one description overlaps substantially with the performance curve of the scheme of embodiment two descriptions as can be seen, illustrate that the embodiment one that adopts among the present invention or embodiment two can shorten the time significantly separating timing, but to almost not influence of actual performance, and device is realized more simple.

The present invention is equally applicable to more the modulation system of high-order signal is carried out soft-decision.Derive the computing formula of each soft bit according to soft bit computational methods of the present invention, in soft decision processes, signal in orthogonal is decomposited a plurality of bits on first branch component and second branch component, adopt the computing formula that draws, respectively each bit is carried out soft-decision output.Emulation experiment shows uses the present invention to the almost not influence of actual signal transmission performance in high order modulation.

Because the present invention adopts LLR algorithm and Max-log algorithm that existing soft-decision algorithm is simplified, and the value of signal is carried out segmentation calculate, so significantly reduced amount of calculation and computing time; The present invention further determines the output amplitude of soft bit on this basis to the marginal minimum range of hard decision by received signal, use straight line that the broken line in preceding a kind of scheme is similar to, further simplified computational process, simplified soft decision processes simultaneously, reduced amount of calculation significantly, and then device is realized also comparatively simple.And the present invention is applicable to multiple qam mode, further shows by emulation experiment and adopts the present invention to almost not influence of actual performance.

Obviously, those skilled in the art can carry out various changes and modification to the present invention and not break away from the spirit and scope of the present invention.Like this, if of the present invention these are revised and modification belongs within the scope of claim of the present invention and equivalent technologies thereof, then the present invention also is intended to comprise these changes and modification interior.

Claims (6)

1. a method that realizes quadrature amplitude modulated soft decision in communication system is characterized in that, may further comprise the steps:

Quadrature decomposes the signal that receives in WCDMA system or TD-SCDMA system, obtains first branch component and second branch component;

In WCDMA system or TD-SCDMA system, respectively first branch component and second branch component and threshold ratio are determined the piecewise interval at its place, acquisition is used for calculating at this piecewise interval the piecewise function of soft bit, wherein, described threshold value determines that by the long-pending of a minimum Eustachian distance and a constant wherein piecewise function is as follows in WCDMA:

$S_{i_1}=\left\{\begin{array}{c}2x+d,x<-d\\ x,-d\&le;x\&le;d\\ 2x-d,x>d\end{array}\right.,$ $S_{i_2}=\left\{\begin{array}{c}d+x,x<0\\ d-x,x\&GreaterEqual;0\end{array}\right.,$ $S_{q_1}=\left\{\begin{array}{c}2y+d,y<-d\\ y,-d\&le;y\&le;d\\ 2y-d,y>d\end{array}\right.,$ $S_{q_2}=\left\{\begin{array}{c}d+y,y<0\\ d-y,y\&GreaterEqual;0\end{array}\right.;$

Piecewise function is as follows in TD-SCDMA:;

$S_{i_1}=\left\{\begin{array}{c}2(x+y)+\sqrt{2}d,x+y<-\sqrt{2}d\\ x+y,-\sqrt{2}d\&le;x+y\&le;\sqrt{2}d\\ 2(x+y)-\sqrt{2}d,x+y>\sqrt{2}d\end{array}\right.,$ $S_{i_2}=\left\{\begin{array}{c}\sqrt{2}d+(x+y),x+y<0\\ \sqrt{2}d-(x+y),x+y\&GreaterEqual;0\end{array}\right.,$

$S_{q_1}=\left\{\begin{array}{c}2(y-x)+\sqrt{2}d,y-x<-\sqrt{2}d\\ y-x,-\sqrt{2}d\&le;y-x\&le;\sqrt{2}d\\ 2(y-x)-\sqrt{2}d,y-x>\sqrt{2}d\end{array}\right.,$ $S_{q_2}=\left\{\begin{array}{c}\sqrt{2}d+(y-x),(y-x)<0\\ \sqrt{2}d-(y-x),(y-x)\&GreaterEqual;0\end{array}\right.,$

Wherein d represents the minimum Eustachian distance in the planisphere, received signal R=x+jy, the first bit i ₁With the second bit i ₂Corresponding to the real component of received signal R, the real component of received signal R is this first branch component, the 3rd bit q ₁With the 4th bit q ₂Corresponding to the imaginary part component of received signal R, the imaginary part component of received signal R is this second branch component;

In WCDMA system or TD-SCDMA system, calculate and export corresponding soft bit respectively according to described piecewise function, described first branch component and second branch component.

2. quadrature amplitude modulated soft decision method as claimed in claim 1 is characterized in that, described piecewise function obtains based on log-likelihood ratio LLR algorithm and the maximum approximate MAX-log algorithm of logarithm.

3. quadrature amplitude modulated soft decision method as claimed in claim 2 is characterized in that, by described MAX-log algorithm the result of LLR algorithm is carried out approximate calculation and obtains piecewise function.

4. quadrature amplitude modulated soft decision method as claimed in claim 1 is characterized in that the number of described soft bit is corresponding with the exponent number of quadrature amplitude modulation.

5. a quadrature amplitude modulated soft decision device is characterized in that, comprising:

Decomposing module is used for decomposing the signal that receives in WCDMA system or TD-SCDMA system quadrature, obtains first branch component and second branch component;

Judge module, the piecewise interval that is used for first branch component that respectively described decomposing module obtained in WCDMA system or TD-SCDMA system and second branch component and definite its place of threshold ratio, acquisition is used for calculating at this piecewise interval the piecewise function of soft bit, wherein, described threshold value determines that by the long-pending of a minimum Eustachian distance and a constant wherein piecewise function is as follows in WCDMA:

$S_{i_1}=\left\{\begin{array}{c}2x+d,x<-d\\ x,-d\&le;x\&le;d\\ 2x-d,x>d\end{array}\right.,$ $S_{i_2}=\left\{\begin{array}{c}d+x,x<0\\ d-x,x\&GreaterEqual;0\end{array}\right.,$ $S_{q_1}=\left\{\begin{array}{c}2y+d,y<-d\\ y,-d\&le;y\&le;d\\ 2y-d,y>d\end{array}\right.,$ $S_{q_2}=\left\{\begin{array}{c}d+y,y<0\\ d-y,y\&GreaterEqual;0\end{array}\right.;$

Piecewise function is as follows in TD-SCDMA:;

$S_{i_1}=\left\{\begin{array}{c}2(x+y)+\sqrt{2}d,x+y<-\sqrt{2}d\\ x+y,-\sqrt{2}d\&le;x+y\&le;\sqrt{2}d\\ 2(x+y)-\sqrt{2}d,x+y>\sqrt{2}d\end{array}\right.,$ $S_{i_2}=\left\{\begin{array}{c}\sqrt{2}d+(x+y),x+y<0\\ \sqrt{2}d-(x+y),x+y\&GreaterEqual;0\end{array}\right.,$

$S_{q_1}=\left\{\begin{array}{c}2(y-x)+\sqrt{2}d,y-x<-\sqrt{2}d\\ y-x,-\sqrt{2}d\&le;y-x\&le;\sqrt{2}d\\ 2(y-x)-\sqrt{2}d,y-x>\sqrt{2}d\end{array}\right.,$ $S_{q_2}=\left\{\begin{array}{c}\sqrt{2}d+(y-x),(y-x)<0\\ \sqrt{2}d-(y-x),(y-x)\&GreaterEqual;0\end{array}\right.,$

Wherein d represents the minimum Eustachian distance in the planisphere, received signal R=x+jy, the first bit i ₁With the second bit i ₂Corresponding to the real component of received signal R, the real component of received signal R is this first branch component, the 3rd bit q ₁With the 4th bit q ₂Corresponding to the imaginary part component of received signal R, the imaginary part component of received signal R is this second branch component;

Computing module is used for calculating corresponding soft bit in WCDMA system or TD-SCDMA system respectively according to described judge module definite piecewise function, described first branch component and second branch component;

Output module is used at WCDMA system or the definite soft bit of the described computing module of TD-SCDMA system output.

6. quadrature amplitude modulated soft decision device as claimed in claim 5 is characterized in that, the piecewise function that described judge module is determined obtains based on log-likelihood ratio LLR algorithm and the maximum approximate MAX-log algorithm of logarithm.

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