JP3237866B2 - Soft decision decoding method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a soft decision decoding method in wireless communication such as cellular mobile communication employing a phase modulation method such as phase shift keying (PSK).

[0002]

2. Description of the Related Art Conventionally, techniques in such a field include:
For example, there is one described in the following literature.

Reference 1: Murano and Maritime, "Digital Signal Processing in Information and Communication," First Edition (Showa 62-11-25), Shokodo P. 32-91 Literature 2; IEE Transactions on Communications Technology (IEEE T
ransactions On Communications Technology), COM
-19 [5] (1971-10) (US) J. VIT
ERBI “Convolutional Codes and Their Performance in Communication Systems
Communications Systems) "P.751-772 Reference 3; B.SKLAR" DIGITAL COMMUNICATIONS
S) "(1988) PRENTICE HALL (US)
sec. 6.3.4, p. 333-337 Conventionally, there is a method of decoding a phase modulation method described in Document 1, and a PS that allocates a bit string to the phase of a carrier wave.
The K modulation method will be described.

[0004] When θi is a carrier phase and fc is a modulation frequency, and the phase θi changes at every symbol transmission interval T, the modulation wave is represented by the following equation (1). _∞ h (t) is a roll-off filter H that is set so that the impulse response does not interfere with adjacent symbols.
It is a time domain function of (f). This h (t) satisfies the following condition. h (t) = 1 (t = 0) h (t) = 0 (t = nT; t ≠ 0) The m-phase PSK uses m kinds of θi. For example, in the case of 4-phase PSK (QPSK), two bits are allocated to one phase, and when the phase is 0 (0, 0), when the phase is π / 2 (0, 1), and when the phase is π (1). , 1) and (1, 0) at the time of phase 3π / 2 are transmitted. From equation (1), it can be seen that PSK modulation can be obtained by adding sin (θi) and cos (θi), each of which is modulated by orthogonal carriers of frequency fc.

On the receiving side, a haze band signal is obtained by multiplying equation (1) by an orthogonal carrier. S in equation (1)
When (t) is multiplied by the orthogonal carrier wave exp (j2πfct), the expression (2) is obtained.

[0006]

(Equation 1)

The baseband signal wi can be obtained by removing the harmonic components of the equation (2).

However, in actual communication, it is necessary to consider the frequency characteristics of the transmission path, or the effects of phase fluctuations on carrier waves and frequency offsets. Hereinafter, the processing in the receiving unit of the conventional decoding method will be described with reference to FIG.

FIG. 2 is a block diagram showing a configuration of a receiving section of a conventional radio signal transmitting / receiving apparatus.

[0010] The receiving unit demodulates a radio frequency band signal (RF band reception signal) a affected by multipath fading or the like in a radio line to detect coordinate information b in a phase space. A hard-decision decoding unit 20 for correcting a bit error of the baseband signal based on the coordinate information b to obtain a reproduced signal c.

The demodulation unit 10 includes a band pass filter 11,
An analog / digital converter (A / D converter) 12, an automatic gain controller (AGC) 13, a quadrature carrier generator 14,
It comprises low-pass filters 15a and 15b, an equalizer 16, a phase-locked loop 17, and the like. Further, the hard decision decoding unit 20 includes a data decision unit 21, a deinterleave unit 2
2 and a decoding unit 23.

In the processing of the receiving section, the modulated wave of the above formula (1) is affected by the frequency characteristics of the transmission path, the phase fluctuation (jitter) with respect to the carrier, the frequency shift (offset), and the like. The received waveform of a (= r (t)) is expressed as in equation (3). Here, go (t); the product of the time domain function g (t) of the frequency characteristic G (f) of the transmission path and exp (j2πfct) ga; the level fluctuation fo due to the loss in the transmission path fo; Offset θ (t); phase jitter A predetermined frequency band is extracted from the RF band reception signal “a” of the equation (3) by the band-pass filter 11, and the A / D converter 12
Is converted into a digital signal and becomes a discrete signal. (3)
Since the gain constant ga in the equation fluctuates according to the state of the transmission path, the AGC 13 corrects the received signal level so as to keep it constant, so that the subsequent digital signal processing can be executed at the same level. .

In equation (2), the orthogonal carrier is expressed as exp (j2
π fct), but actually, the received wave is divided into two,
Cos (2π fct) and sin (2π
Fct) is multiplied by the value at the sampling point. The orthogonal carrier is generated by the orthogonal carrier generator 14. Low-pass filters 15a and 15b remove harmonic components from each of the received waves multiplied by the orthogonal carrier.

In the case where the influence of a phase variation or a frequency shift on the frequency characteristic or carrier of the transmission path is small, the baseband signal can be used as it is as the coordinate information b. On the other hand, if the influence is large, the equalizer 16 uses the frequency characteristic go (n−
k) is corrected. Further, the phase synchronization circuit 17 causes a phase shift of 2πn fo / fs and a frequency shift θ with respect to the carrier.
Correct (n).

The signal point arrangement on the two-dimensional plane of the received complex baseband signal thus obtained is coordinate information b. The coordinate information b does not always accurately take the transmission phase θi because the correction of the influence of the frequency characteristic of the transmission path or the phase variation with respect to the carrier wave or the frequency shift is not always appropriate. Therefore, the data decision unit 21 in the hard decision decoding unit 20 predicts a transmission symbol by selecting a transmission phase closest to the coordinate information b. The determination of the transmission symbol is uniquely determined by the determination boundary set on the two-dimensional plane and in which area the coordinate information b falls. The uniquely determined data is rearranged by the deinterleaver 22 and then subjected to a decoding process by the decoder 23.

Interleave conversion is a conversion in which signal bits input to a memory are rearranged and output, and has the effect of replacing successively generated bit errors with random errors. As described above, the hard-decision decoding uses the bit string corresponding to the estimated symbol as it is in the decoding process.
The decoding unit 23 performs a decoding process in accordance with encoding such as a block code and a convolutional code. For example, Viterbi decoding is performed on the convolutional code.

Next, the hard decision and the soft decision in the convolutional code and the Viterbi decoding described in the above references 2 and 3 will be described.

Generally, in radio communications such as mobile communications and satellite communications, various measures such as diversity reception, equalization, and code error control are taken in order to improve signal quality deterioration in a radio channel. Convolutional coding, which is a type of code error control, is performed based on a convolutional code generation rule uniquely determined by a coding rate, a constraint length, and a generator polynomial. A graphic representation of this generation rule is a kind of state transition diagram called a trellis graphic. The convolution sign is
At the time of decoding, by comparing the received signal with a possible path (path) on the trellis figure and selecting the most suitable path (optimal path), it is possible to correct a bit error of the received signal. Viterbi decoding is the most common method for decoding a convolutional code. Hard decision is made by comparing a signal value itself with a selectable signal sequence of a trellis figure, and the likelihood that the signal value takes that value (likelihood). And soft decision for comparison.

The Viterbi decoding method is described in the above-mentioned reference 2, and the method will be described with reference to FIGS.

FIG. 3 is an explanatory diagram of convolutional coding.

In performing convolutional coding, when n output bits are generated for m input bits, the coding rate is m / n. When an output is generated from the past k bits including the latest input bits, it is called a constraint length k. In this case, n generator polynomials of length k are required. FIG. 3 shows a coding rate of 1/2, a constraint length of 3, and generator polynomials 111 and 101.
The case of is shown.

In FIG. 3, 3 bits including the latest input bit are stored in the buffer 25, and a 2-bit output is obtained by convolution. Since the generator polynomials are 111 and 101, one of the outputs is the logical sum of all the bits of the buffer 25, and the other is the logical sum of the first and third bits of the buffer 25.

FIG. 4 is a trellis diagram showing a state transition diagram of the generation rule of the convolutional coding shown in FIG.

The vertical direction in FIG. 4 shows a state in the buffer 25 that does not include the latest bit, and a state of 2 ^{k -1} occurs.
In the example, it is 4. In each state, when 0 is input, the state shifts to the next state along the solid line, and two bits on the line are output. When 1 is input, the state shifts to the next state along the broken line, and 2 bits on the line are output.

The most general Viterbi algorithm will be described with reference to FIG. 4 as a method of decoding a convolutionally encoded code.

On the decoding side, a signal corresponding to a bit string on a solid line or a broken line on the trellis diagram is received, and the original signal is reproduced by predicting a path on the trellis diagram. However,
As will be described later, a delay corresponding to the path memory length occurs. As shown in the trellis diagram, there are two paths (branches) input to each state, and a 2-bit branch symbol is assigned to each branch based on the same rules as in the coding.

First, when two bits are input, for each input branch to each state, a branch metric (metric) with the input bit is calculated, and the better of the branch metric is selected. The sum of the branch metric accumulation (path metric) in the state before the selected branch is connected and the metric of the selected branch is taken as a new path metric in each state. In this way, every time a branch leading to each state is determined, path (path) information leading to each state is stored in a memory (path memory). Here, the accumulation of the results of branch selection is a path. Alternatively, the minimum unit of the path is a branch.

When the above processing is repeated for each 2-bit input,
In the course of the path narrowing down described in Document 3, the past paths are eventually narrowed down to one, so that a signal before convolutional coding is obtained from the obtained path. Since the path memory length of the actual device is finite, if the path does not converge even if the path memory length is exceeded, the path with the best path metric will be selected at that time.

Next, the difference between the hard decision and the soft decision will be described.

A method of calculating a metric with a possible path on a trellis diagram using the input bit value itself is called hard decision. On the other hand, a method using the likelihood that an input bit value takes that value is called soft decision.
The soft decision has a higher metric calculation accuracy and a higher bit error correction capability than the hard decision.

For example, not only wireless but also digital signal transmission, in the case of hard decision, a certain reception level is set as a threshold, when the level of the received signal is higher than the threshold, the input bit is set to 1, and when the level is lower, 0 is set. To determine the signal value. On the other hand, in the case of the soft decision, first, a seven-valued threshold is set, divided into eight regions according to the level of the received signal, and a value Ns of 0 to 7 is given to each region. That is, 1
Region where it is certain to be, region where it is certain to be 0,
The region is divided into a region that can take either 0 or 1 and a region that is close to 1 if anything. Here, the branch symbols 0 and 1 on the trellis diagram in FIG. 4 are set to −1 and 1 and the value Ns of 0 to 7 is converted into (2 × Ns−7), so that the product sum of the input bit and the branch symbol is obtained. A Viterbi algorithm that selects a branch having a large (correlation) becomes possible.

[0032]

However, the conventional decoding method has a problem that the transmission bit string is determined and the possibility of taking the phase is not taken into consideration.

That is, the modulated wave is affected by frequency characteristics of the transmission path, phase fluctuation with respect to the carrier wave, frequency shift, and the like. The frequency characteristics of the transmission path are corrected by the equalizer 16 and the phase fluctuation and the frequency shift with respect to the carrier are corrected by the phase locked loop 17, respectively. Then, it may not work. If the correction is successful, the probability that the estimated bit sequence matches the actually transmitted bit sequence is high, but if the correction is not completed, the probability is low. Such high or low credibility of the estimated bit string due to the success or failure of the correction according to the transmission state has not been sufficiently reflected in decoding.

The present invention has a problem that the prior art has a problem that, when decoding in the PSK modulation method, a bit string is determined and the possibility (bit likelihood) of actually transmitting an estimated bit string is not taken into consideration. The present invention provides a soft-decision decoding method that solves this problem.

[0035]

In order to solve the above-mentioned problems, the present invention calculates a bit likelihood from a shift of a detected phase in a phase space from a selected phase and a distance from an origin, and softens this likelihood. It is characterized in that it is used for decision decoding.

That is, the phase / distance calculation processing for calculating the phase and the distance from the origin from the coordinate information on the phase space obtained by demodulating the signal modulated by the phase modulation method, and the phase / distance calculation processing. The phase is compared with a unique phase transmitted by the phase modulation method, a phase selection process of selecting the unique phase having a small absolute value of the phase shift, monotonically decreasing with respect to the magnitude of the phase shift, And the absolute value of the phase shift is 0
In the case of, the maximum value of the likelihood is taken, and the absolute value of the phase shift is (2π
In the case of (/ the number of unique phases transmitted by the phase modulation method), a phase likelihood calculation process for calculating the phase likelihood is executed by a function that takes the minimum value of the likelihood.

Further, as the distance from the origin increases, it monotonically increases, and when the distance from the origin is equal to or less than the first set value, the minimum value of the likelihood is obtained. When the value is equal to or larger than the second set value, a phase likelihood correction process is performed in which a coefficient having a maximum value is multiplied by the phase likelihood to obtain a corrected phase likelihood. Then, the corrected phase likelihood is used in a decoding process as a value indicating the probability of taking a bit value.

[0038]

According to the present invention, since the soft decision decoding method is configured as described above, when coordinate information on a phase space obtained by demodulating a signal modulated by a phase modulation method is input to a phase / distance calculation process. In the phase / distance calculation processing, the phase and distance are calculated from the input coordinate information, and the calculation results are sent to the phase selection processing. In the phase selection processing, the input phase is compared with a unique phase transmitted by the phase modulation method, and the unique phase having a small absolute value of the phase shift is selected. In the phase likelihood calculation process, the phase likelihood is calculated based on the phase shift, and the calculation result is sent to the phase likelihood correction process. In the phase likelihood correction processing, a corrected phase likelihood corresponding to the phase likelihood is obtained based on the distance. If this corrected phase likelihood is used for calculation of a metric or the like in soft decision decoding, an accurate reproduced signal can be obtained. Therefore, the above problem can be solved.

[0039]

FIG. 1 is a flowchart of processing steps of a soft decision decoding method according to an embodiment of the present invention, and FIG. 5 is a block diagram showing a configuration of a receiving unit of a radio signal transmitting / receiving apparatus for implementing the soft decision decoding method. It is. 5, elements common to those in FIG. 2 are denoted by common reference numerals. As a modulation method, a π / 4 shift DQPSK method is assumed.

First, the receiving section of the radio signal transmitting / receiving apparatus shown in FIG. 5 will be described.

This receiving unit includes a demodulation unit 10 which is the same as the conventional demodulation unit in FIG. 2, and a soft decision decoding unit 30 is connected to the output side. The soft decision decoding unit 30 receives the coordinate information b on the phase space output from the demodulation unit 10 and corrects the bit error of the baseband signal to obtain a reproduced signal c.
It is composed of an individual circuit using a large-scale integrated circuit (LSI) or the like, or a program control using a processor.

Although the illustration of the transmitter provided in the radio signal transmitting and receiving apparatus is omitted, the transmitter transmits the original signal by encoding (block encoding, convolutional encoding, etc.) and interleaving conversion. And π / 4 shift DQ
Modulate by the PSK method. The present embodiment is effective even when coding or interleave conversion is not performed, but is more generally performed, and is included in the figure.

The soft decision decoding section 30 has a soft decision data calculation section 40 for calculating soft decision data from the coordinate information b. The soft decision decoding unit 40 includes a phase calculation unit 41, a phase selection unit 42, a phase likelihood calculation unit 43, a distance calculation unit 44, a distance coefficient calculation unit 45, a phase likelihood correction unit 46, a bit likelihood calculation unit 47, A deinterleave unit 50 is connected to the output side.

The deinterleave unit 50 has a function of storing the soft decision data calculated by the soft decision data calculation unit 40, and a decoding unit 60 is connected to its output side. Since the data stored in the deinterleave unit 50 is read out to the decoding unit 60 while returning the bit order rearranged at the time of transmission, the decoding unit 60 uses the read soft decision data. It has a function of performing a decoding process and outputting a reproduction signal c.

Next, the soft-decision decoding method of the present embodiment will be described with reference to FIG.
This will be described with reference to FIG.

The demodulation unit 10 shown in FIG.
Is input, in step S1, coordinates in the phase space of the RF band reception signal a (that is, the in-phase component zp and the quadrature component zq) are detected, and the detected coordinate information b is stored in the soft decision decoding unit 30. Is sent to the soft decision data calculation unit 40. The soft decision data calculation unit 40 performs soft decision data processing S10 in accordance with steps S11 to S18.

That is, when the coordinate information b is input, a phase calculation is performed by the phase calculation unit 41 in step S11. The phase zirad is given by equation (4). The calculated phase takes an arbitrary value from 0 to 2π. zirad = tan ^-1 (zq / zp) (4) In step S12, the phase selection unit 42 performs phase selection. Since the π / 4 shift DQPSK method is assumed, if the detected phase signal is inputted in an odd number, one of four phases (0, π / 2, π, 3π / 2) is selected. However, if an even number is input, (π / 4, 3
One of four phases (π / 4, 5π / 4, 7π / 4) is selected. t-th input phase selection value irad
(T) is the detected phase z as shown in the following equation (5).
Absolute value θ of difference between irad and candidate phase kπ / 4
The phase at which (k) is minimized. irad (t) = k that minimizes kπ / 4 | θ (k) (5) where θ (k) = | zirad−kπ / 4 | k = 0, 2, 4, 6 t = 2n + 1 = 1 , 3,5,7 t = 2n For k satisfying the expression (5), θ (k) is 0 ≦ θ
(K) ≦ (number of unique phases transmitted by π / PSK method)
Meet. The number of unique phases transmitted in the π / 4 shift DQPSK scheme is four.

In step S13, the phase likelihood calculating section 43
, The likelihood of taking the phase selected in step S12 is calculated. The likelihood is the selected phase kπ / 4
And a function of the phase shift θ (k) between the detection phase zirad and
It is expressed as in the following equation (6). Selected phase irad
Let pd (t) be the likelihood of taking (t). prad (t) = (cos2θ (k) +1) / 2 (6) In step S14, the distance calculation unit 44 calculates the distance zz from the origin from the detected coordinates (zp, zq) as shown in equation (7). calculate. zz ² = zp ² + zq ² (7) Next, in step S15, the distance coefficient calculator 45 calculates the distance coefficient plen (t) according to the distance from the origin.
Is calculated from equation (8). plen (t) = 0 (zz 2 ≦ zz 2 th1) = 1 (zz 2> zz 2 th2) ... (8) However, in the present embodiment, the set value zz _th1, zz _th2 the same value, the AGC 13, Assuming that the average of the power is set to 1, zz _th1 and zz _th2 are determined as follows. zz _th1 = zz _th2 = 0.24 zz ² _th1 = zz ² _th2 = 0.0576 Detection coordinates (zp, zq), detection phase zirad, distance zz from origin, selected phase irad (t), set value zz FIG. 6 shows the relationship of _th1 .

FIG. 6 shows the case where t = 2n + 1 and the detected phase z
From the value of irad, irad (t) = 0. In addition,
When the detection phases zirad have the same value and t = 2n, i
rad (t) = π / 4. Equation (8) means that if the coordinates are inside the two-dot chain line, this coordinate information is not trusted and only if it is outside the two-dot chain line is treated as valid information. Solid circles indicate the average power by the AGC 13.

In step S16, the phase likelihood correcting section 46
From the distance coefficient obtained in step S15,
As in Expression (9), the likelihood prad (t) in Expression (6) is corrected to obtain prad2 (t). prad2 (t) = prad (t) * plen (t) (9) In the case of the π / 4 shift DQPSK method, the phase difference between the phase selected in step S16 and the phase selected immediately before is (10 ) Is calculated as in the equation. The previously selected phase and its likelihood are stored in a memory in the phase likelihood correction unit 46. idif = irad (t) -irad (t-1) (10) The likelihood of the phase difference is calculated as the lower likelihood of the phase likelihoods at successive points in time, as in the following equation (11). . However, in the present embodiment, the calculation of the phase difference likelihood is not limited to Expression (11). pdif = min (prd (t), prad (t-1)) (11) In step S17, the bit likelihood calculating unit 47 converts the bit string corresponding to the phase difference selected as described above into the bit likelihood. The data is read from the memory in the arithmetic unit 47. Phase difference π
/ 4 (0, 0), 3π / 4 (0, 1), 5π /
4 (1, 1) and 7π / 4 (1, 0) correspond. Bits corresponding to the phase difference idif are sequentially referred to as ib1, i
b2. ib1 and ib2 take 0 or 1.

The bit likelihoods pb1 and pb2 are calculated by the following equation (12). This bit likelihood was considered to be -1 to 1. When pb1 = 1-2 pdif ib1 = 0 = 2pdif-1 ib1 = 1 When pb2 = 1-2pdif ib2 = 0 When 2bdif-1 ib2 = 1 Bits pb1 and pb2 obtained by the above processing The likelihood is indicated, and the possibility that the bit value is 0 or 1 is indicated. p
b1 takes an arbitrary value between -1 and 1, and is likely to be 1 when pb1 is close to 1, and is likely to be 0 when pb1 is close to -1. The same applies to pb2.

In the final step S18 of the soft decision data processing S10, the soft decision data is output from the decision data output section 48 and sent to the decoding section 60 via the deinterleave section 50. In step S20, the decoding unit 60 performs a decoding process using the input soft decision data, and outputs a reproduced signal c. As a decoding process, for example, if the code is convolutionally coded, Viterbi decoding is performed. High-precision decoding is also possible for block coding.

FIG. 7 shows a simulation result of bit error characteristics when the soft decision decoding method of this embodiment is applied to Viterbi decoding. The horizontal axis is the ratio Eb / No between the average signal energy Eb per bit and the noise power density No, and the vertical axis is the bit error rate. The curve in the figure indicates the case where △ did not perform convolutional coding, the case where □ was soft-decision Viterbi decoding of a conventional convolutional code, and the case where ○ was the case where soft-decision Viterbi decoding of the present embodiment was performed.

The simulation conditions in FIG. 7 will be described. Class 171 bits of original signal per slot
(89 bits) and class 2 (82 bits), and only the signal of class 1 is subjected to convolutional coding. Coding rate of convolutional coding 1/2, constraint length 6, generator polynomial 11
0101 and 101111. After convolutional encoding,
Class 1 signal (178 bits) and class 2 signal (8 bits)
(2 bits) are interleaved by a 26 × 10 array and modulated by a π / 4 shift DQPSK method, and then an error is randomly given to phase information. On the receiving side, the phase information is converted into bit information (bit likelihood in the case of soft decision), then deinterleaved, and Viterbi decoding is performed only for class 1. The above processing is executed for 200 slots, and class 1 and class 2
, Calculate the bit error rate.

As is apparent from FIG. 7, in the present embodiment, when transmitting at the same Eb / No, the bit error rate is smaller than that of the conventional hard decision Viterbi decoding. Conversely, when the same bit error rate is desired, the transmission power can be reduced.

The present embodiment is not limited to the above embodiment, and various modifications are possible. For example, there are the following modifications.

(1) In step S12 of FIG. 1, the equation for calculating the phase likelihood is not limited to equation (6), but monotonically decreases with respect to the magnitude of θ (k), and θ (k) is 0. In the case of (2), the maximum value of the likelihood is obtained, and when θ (k) is (2π / the number of unique phases transmitted by the differential PSK method), a function that takes the minimum value of the likelihood may be used. In the above embodiment, the likelihood is considered to be 0 to 1, but may be 0 to 100 or -1 to 1 depending on the case.

(2) In step S18 in FIG. 1, the bit likelihood obtained in step S17 may be used as soft decision data as it is. However, since the bit likelihood in step S17 is a real number, appropriate quantization is performed. The value may be used as soft decision data. In addition, this bit likelihood can be used as it is when performing a product-sum operation as a metric operation method of the Viterbi algorithm, and can be diverted with a slight change when calculating the metric by another method such as a difference operation It is.

(3) Soft decision data calculation processing S10 in FIG.
Can also be used for a soft decision decoding method of a block code. Also in the case of soft-decision decoding of a block code, the calculation based on bit likelihood improves the bit error correction capability for the same reason as in the case of soft-decision Viterbi decoding. It is also possible to use both block code decoding and Viterbi decoding.

(4) The Viterbi decoding of FIG. 1 can be used in combination with various diversity receptions. A combination with the decision feedback type equalization is also possible. In addition to block codes and interleaving, ARQ (AUTOMATIC REPEAT)
REQUEST) type code error control (a method of retransmitting information when an error is detected) is also possible.

(5) The equation for calculating the amplitude coefficient plen (t) in step S15 in FIG. 1 is not limited to equation (8), but increases monotonously with the magnitude of the distance zz, and zz is set to the first setting. Any function that takes the minimum value of the likelihood when the value is equal to or less than the value and takes the maximum value of the likelihood when zz is equal to or more than the second set value may be used.

[0062]

As described above in detail, according to the present invention, in the phase modulation method, in the process of obtaining the bit likelihood from the received carrier, the difference between the detected phase in the phase space and the selected phase is determined. The bit likelihood is calculated from the distance from the origin, and this likelihood is used for soft-decision decoding. Compared with conventional hard-decision decoding, the bit error rate of the original signal can be reduced and highly accurate decoding can be performed. Can be performed.

[Brief description of the drawings]

FIG. 1 is a flowchart showing processing steps of a soft decision decoding method according to an embodiment of the present invention.

FIG. 2 is a configuration block diagram of a receiving unit in a conventional wireless signal transmitting / receiving apparatus.

FIG. 3 is an explanatory diagram of convolutional coding;

FIG. 4 is a diagram showing a trellis figure.

FIG. 5 is a block diagram illustrating a configuration of a receiving unit in the wireless signal transmitting and receiving apparatus according to the embodiment of the present invention.

FIG. 6 is a diagram showing a relationship between detected coordinates and a selected phase in FIG. 1;

FIG. 7 is a bit error characteristic diagram of FIG. 1;

[Explanation of symbols]

 Reference Signs List 10 demodulation section 30 soft decision decoding section 40 soft decision data calculation section 41 phase calculation section 42 phase selection section 43 phase likelihood calculation section 44 distance calculation section 45 distance coefficient calculation section 46 phase likelihood correction section 47 bit likelihood calculation section 48 Decision data output section 50 deinterleave section 60 decoding section a RF band reception signal b coordinate information c reproduction signal S1 coordinate detection processing S10 soft decision data processing S11 phase calculation processing S12 phase selection processing S13 phase likelihood calculation processing S14 distance calculation processing S15 Distance coefficient calculation processing S16 Phase likelihood correction processing S17 Bit likelihood calculation processing S18 Decision data output processing S20 Soft decision decoding processing

Continuation of the front page (56) References JP-A-1-17947 (JP, A) JP-A-63-59119 (JP, A) JP-A-62-213420 (JP, A) JP-A-62-60339 (JP, A) JP-A-61-137447 (JP, A) JP-A-4-369124 (JP, A) Patent 2710696 (JP, B2) Transactions of the Institute of Electrical Engineers of Japan. System Journal, Vol. 111, No. 11, pp. 563-568, "Soft Decision Decoding in Differential PSK Modulation", November 1991 (58) Fields investigated (Int. Cl. ⁷ , DB name) H03M 13/00 H04L 25/00 H04L 27/00

Claims (1)

(57) [Claims] 1. A phase / distance calculation process for calculating a phase and a distance from an origin from coordinate information in a phase space obtained by demodulating a signal modulated by a phase modulation method, and a phase / distance calculation process. The phase is compared with a unique phase transmitted by the phase modulation method, a phase selection process of selecting the unique phase having a small absolute value of the phase shift, monotonically decreasing with respect to the magnitude of the phase shift, When the absolute value of the phase shift is 0, the maximum value of the likelihood is obtained. When the absolute value of the phase shift is (2π / the number of unique phases transmitted by the phase modulation scheme), the minimum value of the likelihood is calculated. A phase likelihood calculation process for calculating the phase likelihood by a function to be taken, and a case where the distance from the origin increases monotonically and the distance from the origin is equal to or less than a first set value. Take the minimum value of the degree and the distance from the origin is the second When the value is equal to or greater than the set value, a phase likelihood correction process of multiplying the maximum likelihood by the coefficient to obtain a corrected phase likelihood is performed, and the corrected phase likelihood represents a likelihood of taking a bit value. A soft decision decoding method characterized by being used as a value in a decoding process.