JPH06338914A - Viterbi equalizer - Google Patents

Abstract

PURPOSE:To propose a viterbi equalizer capable of obtaining efficient equivalent characteristic. CONSTITUTION:The viterbi equalizer is composed of a first synchronizing signal data detection means 3 detecting the synchronizing signal data part of a first time slot from a reception signal data group, a second synchronizing signal data detection means 3 detecting the synchronizing signal data part of a second time slot from the reception signal data group, a transmission line characteristic estimating means 4 identifying first and second impulse responses between a transmitter and a receiver by respectively using the method of least squares by setting synchronizing signal data of the first and second time slots detected by the first and second synchronizing signal data detection means 3 to be a reference signal, an impulse response interpolation means 5 obtaining an impulse response between synchronizing signal data of the first and second time slots by linear-interpolating the first and second impulse responses and a decoding means 2 decoding a transmission data group by using viterbi algorithm based on the impulse response from the impulse response interpolation means 5.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a Viterbi equalizer suitable for use in, for example, automobile telephones.

[0002]

2. Description of the Related Art In the United States, Europe and Japan, car telephone system digitalization is in progress. In mobile communication such as this car telephone, due to the influence of so-called multipath due to the presence of a high-rise building between the mobile station and the base station at high speed like a car, the transmission characteristics between the base station and the mobile station However, data transmission with few errors was difficult. Moreover, this equivalent transmission characteristic changes from moment to moment.

In such a mobile communication system, an equalization technique for correcting such transmission characteristics is indispensable in order to realize reception with few errors.

As a conventional equalization technique, a Viterbi equalizer has been proposed which decodes transmission data based on maximum likelihood sequence estimation by using transmission characteristics between a base station and a mobile station.

The basic configuration of this Viterbi equalizer is as shown in FIG. 3. Here, the Viterbi equalizer shown in FIG. 3 is used in a European car telephone, GSM (Group Special Moval). An example applied to the method will be described.

In FIG. 3, the received signal supplied to the input terminal 1 is supplied to the branch metric calculation circuit 21 constituting the Viterbi estimation unit 2 and the received signal is supplied to the synchronization signal data detection unit 3 for synchronization. The synchronization signal data from the signal data detector 3 is supplied to the transmission line characteristic estimator 4.

The communication channel from the GSM system base station adopted in Europe to the mobile station (automobile) has a frame structure as shown in FIGS. 4A and 4B. As shown in FIG. 4B, a sync signal pattern (SYNC pattern) having a known pattern is added to the central portion of each time slot, and the time slot is used by the transmission path characteristic estimator 4. Then, the impulse response (hereinafter referred to as the channel response) of the transmission system interposed between the transmitter and the receiver is estimated (identified).

In the case of this GSM system, a modulation system called GMSK (Gaussian minimum shift keying) is adopted, but since the high frequency transmission system is converted into a baseband signal by passing through a demodulator, it will be explained below. In order to simplify, we will proceed with signal processing in the baseband.

In this GSM system, eight types of data series are designated in advance as the synchronization signal pattern,
One of them is shown in FIG. A conventional general procedure for modeling a channel response using this synchronization signal pattern will be described.

Now, the case where the channel response is as shown in FIG. 6 is taken as an example (in reality, this channel response is unknown). In FIG. 6, the unit in the time axis direction is equal to the symbol transmission interval. The sync signal pattern of FIG. 6 is the sync signal pattern of FIG. The synchronization signal data received when passing through the transmission system having such a channel response is expressed by the following equation.

[0011]

[Equation 1]

Here, y _i represents a received signal, x _i represents a synchronization signal pattern, and h _i represents a channel response. The values are sampled at the symbol time intervals T, respectively.

When the received signal corresponding to the sync signal pattern portion is calculated according to equation 1, an output signal as shown in FIG. 6 is obtained. On the receiver side, the known information is the sync signal pattern x _i and the received signal y _i .

In the conventional modeling procedure of the transmission path characteristic estimating section 4, first, the sync signal data section is detected by taking the correlation between the received signal and the sync signal pattern.

Next, the cross-correlation function r _j between the sync signal data portion and the sync signal pattern is calculated.

[0016]

[Equation 2]

Next, normalization is performed using the maximum value of the cross-correlation function r _j . The cross-correlation function calculated in this way is shown in FIG. The branch metric calculation circuit 21 estimates the channel response by this cross-correlation function.
Supply to.

After estimating this channel response, the transmission data sequence is decoded using the Bideby algorithm. FIG. 7 shows a generalized transmission line equivalent model. Here, the example of FIG. 8 in which the generalized transmission path equivalent model of FIG. 7 is modeled by specifically limiting its channel response length will be described.

When modeled as shown in FIG. 8, it can be regarded as a convolutional encoder with constraint length = 4 and coding rate r = 1/1. However, the difference from the normal convolutional encoder is that the adder 71 performs a linear operation and the shift registers T ₀ , T ₁ , T ₂ and T ₃
The symbol input to is a binary value of <+1> and <-1>, and each output of the shift register is weighted corresponding to the channel responses h _-1 , h ₀ , h ₊₁ and h _+2. These are two points that are added by the adder 71 after the addition.

The symbol G sent in the case of modeling in this way is expressed by the following equation.

[0021]

[Equation 3] Here, <T _j > represents the contents stored in the register T _j .

FIG. 9 is a trellis diagram showing transitions of the internal states of the transmission line in the transmission line equivalent model shown in FIG. The three-letter alphabet corresponding to each state contact S _i in FIG. 9 represents the internal state of the shift register in each time slot. Here, since the shift register takes the values of <+1> and <-1>, they are represented as H and L for convenience of expression. In addition, in FIG. 9, a grid structure diagram that is normally used is modified so that a solid line is used when the information input symbol <-1> is input, and a broken line is used when the information input symbol <+1> is input. It indicates that the transition as shown occurs.

On the other hand, the received signal data Y _k is input to the branch metric calculation circuit 21 to calculate the likelihood of its transition. Although some metrics have been proposed for measuring the likelihood, the Hamming distance, which is the most general evaluation measure in Viterbi decoder, is applied in a broad sense.

The branch metric at the time slot t (k) is calculated by the following equation.

[0025]

Equation 4] _{b (k, S i → S} n) = | Y k -G k | , where, Y _k is the received signal data and a symbol G _k is transmitted from the equivalent transmission path model , Takes the value calculated by Equation 3.

The branch metric obtained by the branch metric calculation circuit 21 is referred to as ACS (Add Compare Sele).
ct) Supply to the circuit 22. The ACS circuit 22 is composed of an adder, a comparator, and a selector. In each state, the branch metric and the path metric of one time slot before stored in the path metric storage circuit 23 are added to obtain the value. The smaller one is selected as the likely survival path. Here, the path metric is a value obtained by adding the branch metrics in the surviving paths.

The output signal of the ACS circuit 22 is supplied to the path metric storage circuit 23 via the normalization circuit 24, and the output signal of the ACS circuit 22 is supplied to the maximum likelihood path detection circuit 25.

The maximum likelihood path detection circuit 25 detects a path having the smallest path metric value and outputs the contents of the path memory 26 corresponding to the path as decoded data. The path memory 26 is a memory for estimating and storing an information bit string.

FIG. 10 shows a logic unit which constitutes this Viterbi equalizer. In FIG. 10, each metric represents the following contents.

P (k-1, S _i ): Time slot t
Path metric P (k-1, _Sj ) of the surviving path reaching the state node S _i at (k-1): Path of the surviving path reaching the state node S _j at the time slot t (k-1) Metric b (k, S _i → S _n ): Branch metric b (k, S _j → S _n ): time slot t corresponding to the transition from the state node S _i to the state node S _n in the time slot t (k). The branch metric corresponding to the transition from the state node S _j to the state node S _n in (k)

M (k-1, S _i ): Time slot t
Path memory M (k-1, _Sj ) of the surviving path reaching the state node S _i at (k-1): Path of the surviving path reaching the state node S _j at the time slot t (k-1) memory <-1>, <+1>: time slot t (k) information symbols are estimated to have been delivered in P (k, S _n): survivor path reaching the state node S _n in time slot t (k) Path metric possessed M (k, S _n ): Path memory possessed by the surviving path reaching the state node S _n at time slot t (k)

Here, assuming that the constraint length is k, the number of states is 2
Since there are only ^k−1, the number of logical units shown in FIG. 10 basically requires the number of states 2 ^k−1 . Further, as in the block configuration of the Viterbi equalizer shown in FIG.
In general, 4 is provided to reduce the scale of the path metric storage circuit 23 and prevent overflow during the calculation of the path metric.

As a concrete process of this normalization, first, the minimum value of the path metric is detected, and then the value is subtracted from each path metric amount. The number of remaining paths selected in this way is 2 ^{k−1, which} is the same as the number of states.

In each time slot, the operation of selecting the remaining path and the operation of updating the path metric and the path memory 26 corresponding to the path are repeated. It is known that, if this operation is performed for a sufficiently long time, it is merged into the same path before a certain time, and this state is shown in FIG. The length of the path from the latest processing time point to the time when the paths are merged is called the truncated path length.

The method of updating the path memory shown in FIG. 10 is determined according to each state. For example, the logical unit of "LLL" is determined as <-1>, the logical unit of "HLL" is determined as <+1>, and so on.

In the maximum likelihood determination, the path having the minimum path metric value is detected, and the contents of the path memory corresponding to the path are cut off and traced back by the path length (normally set to about 3 to 4 times the constraint length). It is output as an information symbol at that time.

The signal processing flow of this conventional Viterbi equalizer will be described with reference to the flowchart of FIG. First, a sync signal pattern is detected when the received signal data _Yk is supplied to the input terminal 1 (step S1), and the cross-correlation between the sync signal pattern of the received signal data _Yk and the previously stored sync signal pattern is detected. The function is calculated in the transmission path characteristic estimation unit 4 (step S2) and the channel response is estimated (step S3). Next, the branch metric calculation circuit 21 calculates a branch metric (step S4), and then starts calculation for the Nth state (step S5).

Next, the address of the state-1 one time slot before is set (step S6), then the path metric stored in the path metric storage circuit 23 of this set address is read (step S7), and this path is read. The metric is added to the branch metric calculated in step S4 by the ACS circuit 22, and the addition output is added to the register P.
1 (step S8).

Next, at step S9, the address of the state-2 one time slot before is set, and the path metric stored in the path metric storage circuit 23 of this set address is read (step S10). Is added to the branch metric calculated in step S4 by the ACS circuit 22, and the added output is stored in the register P2 (step S11).

Next, the ACS circuit 22 compares and selects the values stored in the registers P1 and P2 (steps S12 and S13) and outputs the selected value (step S14). The metric storage circuit 23 is updated (step S15) and the path memory 26 is updated (step S16).

Steps S5 to S16 described above
The processes up to are repeated by the number of states 2 ^k-1 (step S
17). After the above processing is completed, the maximum likelihood path detection circuit 2
The path having the minimum path metric value is detected by 5 (step S18), and the normalization processing is performed by subtracting the minimum value of the path metric from each path metric amount (step S19).

Then, the maximum likelihood path detection circuit 25 sets the address of the maximum likelihood path (step S20) and outputs the contents of the path memory 26 as decoded data (step S).
21).

[0043]

In the conventional Viterbi equalizer, it can be confirmed that the channel response can be estimated with a certain degree of accuracy by comparing the channel response shown in FIG. 6 with the cross-correlation function r _j. It is revealed that a "fake impulse response", which should not appear in the first place, is also detected. The cause of this is apparent when the autocorrelation function a _j of the synchronization signal pattern is calculated.

[0044]

[Equation 5]

The autocorrelation function calculated in this way is shown in FIG. As is apparent from FIG. 6, there are some peaks having a considerably large level other than the main peak, which is a factor that deteriorates the accuracy when estimating the channel response.

First, as a maximum likelihood receiver, Japanese Patent Laid-Open No. 4-8
Some of them are disclosed in Japanese Patent No. 8726, but even such a maximum likelihood receiver has a disadvantage that accurate reception cannot be performed.

In view of the above points, the present invention proposes a Viterbi equalizer capable of obtaining an accurate equalization characteristic.

[0048]

A Viterbi equalizer according to the present invention includes a first sync signal for detecting a sync signal data portion of a first time slot in a received signal data sequence as shown in FIGS. 1 and 2, for example. The data detecting means 3, the second synchronizing signal data detecting means 3 for detecting the synchronizing signal data part of the second time slot in the received signal data series, and the first and second synchronizing signal data detecting means. Channel characteristics for identifying the first and second impulse responses between the transmitter and the receiver by using the least squares method by using the synchronization signal data of the first and second time slots detected in 3 as a reference signal. The impulse response between the estimating means 4 and the synchronization signal data of the first and second time slots is calculated as the first and second impulse responses.
The impulse response interpolating means 5 for linearly interpolating the impulse response and the decoding means 2 for decoding the transmission data sequence using the Viterbi algorithm based on the impulse response from the impulse response interpolating means 5. .

[0049]

According to the present invention, the first and second impulse responses H ₁ between the transmitter and the receiver are obtained by using the least squares method with the synchronization signal data of the first and second time slots as reference signals, respectively. and j th of the first impulse response Hj corresponding to the symbol and the second impulse response data of the first time slot that is assigned to the user H ₁ and H ₂ linearly interpolated with obtaining of H ₂ Therefore, the impulse response between the transmitter and the receiver can be identified from moment to moment with the smallest error, and good equalization characteristics can be obtained.

[0050]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the Viterbi equalizer of the present invention will be described below with reference to FIGS. In FIG. 1, parts corresponding to those in FIG. 3 are designated by the same reference numerals, and detailed description thereof will be omitted.

In the example of FIG. 1 as well, the received signal supplied to the input terminal 1 is supplied to the branch metric calculation circuit 21 of the Viterbi estimation unit 2 and the received signal is supplied to the synchronization signal data detection unit 3.

In this example, in the sync signal data detection section 3, the sync signal data section of the time slot assigned to the user, for example, the time slot-1 of FIG. 4A and the sync data of the next time slot-2, for example. And the parts are detected.

For example, the synchronization signal data portion of time slot-1 and the synchronization signal data portion of time slot-2 detected by the synchronization data detecting portion 3 are respectively transmitted to the transmission path characteristic estimating portion 4.
Supply to.

In this example, the transmission line characteristic estimation unit 4
, The synchronization signal data of this time slot-1 and
And the reference signal for the synchronization signal data of time slot-2
As the first between the transmitter and the receiver using the method of least squares.
Channel response H of 1 ₁And the second channel
Spawn H₂To ask for.

In this case, in this GSM system, synchronization is performed.
As signal patterns, there are eight types of data systems as shown in FIG.
The column is pre-specified and this pre-specified synchronization
Channel response H using signal pattern₁as well as
H₂Are modeled as shown in FIG. Like this
Signal y which is expected to be received if _i
Is expressed by the above-mentioned equation 1.

On the other hand, when the signal actually received is represented by Y _i , the error ε _i regarding the i-th symbol is represented by the following equation.

[0057]

Ε _i = y _i −Y _i The sum of squares E of this error is obtained.

[0058]

[Equation 7]

The impulse train h _n is determined so as to minimize the error E. In this example, the least squares method is applied. Therefore, the equation 7 is partially differentiated with respect to h _n .

[0060]

[Equation 8] In this number 8, n = -km,-(km-1), ... 0, ...
By substituting + (kp-1), + kp, simultaneous equations shown in the following equation can be obtained.

[0061]

[Equation 9]

Since the coefficient matrix of this simultaneous equation is a symmetric matrix, it is not necessary to carry out the calculation for each element. Furthermore, in order to solve this simultaneous equation, it is general to first perform LU decomposition of the coefficient matrix and then solve. The transmission line characteristic estimation unit 4 according to this example can accurately determine the channel response by the above means.

[0063] In the present example as determining the channel response H ₂ in the channel response H ₁ and time slot 2 in the time slot -1 in this way.

The channel response H ₁ of time slot-1 previously calculated by the transmission line characteristic estimating unit 4 is supplied to the channel response interpolating circuit 5 via the channel response memory 6, and the transmission line characteristic estimating unit 4 is used later. the channel response of H ₂ calculation time slot -2 as supplied to the channel response interpolation circuit 5.

In the channel response interpolation circuit 5, the channel response H _j assigned to the user, for example, corresponding to the j-th symbol of the data portion in time slot -1 is given by the following equation of the channel responses H ₁ and H _2. Determined by linear interpolation.

[0066]

[Equation 10]

Here, J represents the total number of symbols sent in one time slot. In the case of the GSM system of this example, J = 1
56.25. In the equation 10, the channel response H _j is calculated by linearly interpolating every symbol, but the calculation amount may be reduced by performing the calculation every several symbols.

The channel response H _j obtained at the output side of the channel response interpolation circuit 5 is supplied to the branch metric calculation circuit 21 of the Viterbi estimation unit 2.

Others are the same as those of the conventional Viterbi equalizer described with reference to FIG. This detailed description is omitted.

The flow of signal processing of the Viterbi equalizer of this example will be described with reference to the flowchart of FIG. First, when the received signal data Y _k is supplied to the input terminal 1, the sync signal pattern portion of the time slot-1 is detected (step S
1). The detection of the sync signal pattern portion is performed by correlating the received signal data Y _k with the sync signal pattern stored in advance.

Next, in the transmission path characteristic estimating section 4, a minimum of 2 is obtained by using the detected synchronization signal pattern section as a reference signal.
The impulse response between the transmitter and the receiver is modeled (formulated) by using the multiplication method (step S2), and the channel response H ₁ is identified (step S3).

Further, the sync signal pattern portion of the time slot-2 of the received signal Y _k is detected by taking a correlation with the sync pattern stored in advance (step S4).
Next, in the transmission path characteristic estimation unit 4, the impulse response between the transmitter and the receiver is formulated by using the least square method with the synchronization signal pattern portion of this time slot-2 as a reference signal (step S5). Channel response H
Identify ₂ .

Next, the channel response H _j of the j-th symbol in the data portion of the time slot-1 is obtained by linearly interpolating according to equation 10 (step S7).

Next, the branch metric calculation circuit 21 calculates the branch metric (step S8), and then starts the calculation for the Nth state (step S9).

Next, the address of the state-1 one time slot before is set (step S10), and the path metric stored in the path metric storage circuit 23 of the set address is read (step S11). The metric and the branch metric calculated in step S8 are added by the ACS circuit 22, and the added output is stored in the register P1 (step S12).

Next, in step S13, the address of the state-2 one time slot before is set, the path metric stored in the path metric of the set address is read (step S14), and this path metric is read in step S8. Calculated branch metric and ACS
The circuit 22 performs addition, and the addition output is stored in the register P2 (step S15).

Next, the ACS circuit 22 compares and selects the values stored in the registers P1 and P2 (steps S16 and S17), outputs the selected value (step S18), and passes the value. The metric storage circuit 23 is updated (step S19) and the path memory 26 is updated (step S20).

Steps S9 to S20 described above
The processes up to are repeated by the number of states 2 ^k-1 (step S
21). After the above processing is completed, the maximum likelihood path detection circuit 2
The path having the minimum path metric value is detected by 5 (step S22), and the normalization process is performed by subtracting the minimum value of the path metric from each path metric amount (step S23).

Then, the maximum likelihood path detection circuit 25 sets the address of the maximum likelihood path (step S24) and outputs the contents of the path memory 26 as decoded data (step S).
25).

In this example, as described above, time slot-1 and
The synchronization signal pattern portion of time slot-2 is used as a reference signal.
Then, the least squares method is used to check the channel between the transmitter and the receiver, respectively.
Channel response H₁And H₂Get with user
Of the data part of time slot-1 assigned to
Channel response H corresponding to the jth symbol _j
This channel response H₁And H₂Linearly interpolating
The channel relay between the transmitter and receiver is required.
Spawn H_jThe one with the smallest error corresponds to
Can be set and there is an advantage that good equalization characteristics can be obtained.

In this example, the minimum transmission model is 2 as described above.
Since it is estimated by the multiplication method, it is a model with a minimum error, and has the advantage of obtaining good equalization characteristics.

In the above embodiment, the channel response H _j to be used is obtained by linearly interpolating from the channel responses H ₁ and H _{2 of the} time slot-1 and the next time slot-2 assigned to the user. The time slot which is not assigned to the user may be another time slot, and the time slot assigned to the user of the subsequent frame −
It can be easily understood that the same effect as the above can be obtained even if the channel response of 1 is used. Further, the present invention is not limited to the above-described embodiments, and it goes without saying that various other configurations can be adopted without departing from the gist of the present invention.

[0083]

According to the present invention, the first and second times
Least-squares method using lot synchronization signal data as a reference signal
Impulse response H between transmitter and receiver respectively₁
And H ₂And get assigned to the user
It corresponds to the j-th symbol in the data part of 1
Corresponding impulse response H_jThis impulse response H₁Over
And H₂Is calculated by linear interpolation of
The impulse response between the
There is an advantage that a thing can be identified and a good equalization characteristic can be obtained.

Further, according to the present invention, since the transmission model is estimated by the method of least squares, it is a model with a minimum error, and there is an advantage that a good equalization characteristic can be obtained.

[Brief description of drawings]

FIG. 1 is a configuration diagram showing an embodiment of a Viterbi equalizer of the present invention.

FIG. 2 is a flowchart for explaining an embodiment of the Viterbi equalizer of the present invention.

FIG. 3 is a configuration diagram showing a Viterbi equalizer.

FIG. 4 is a diagram for explaining the present invention.

FIG. 5 is a diagram for explaining the present invention.

FIG. 6 is a diagram used for explaining the present invention.

FIG. 7 is a diagram showing a generalized transmission line equivalent model.

FIG. 8 is a diagram showing an embodied transmission line equivalent model.

FIG. 9 is a diagram showing a trellis representation.

FIG. 10 is a diagram showing a logical unit of a Viterbi equalizer.

FIG. 11 is a diagram showing metric calculation and survivor paths.

FIG. 12 is a flowchart for explaining a conventional Viterbi equalizer.

[Explanation of symbols]

 1 Input Terminal 2 Viterbi Estimator 3 Synchronous Signal Data Detector 4 Channel Characteristic Estimator 5 Channel Response Interpolator 6 Channel Response Memory

Claims (2)

[Claims] 1. A first synchronization signal data detecting means for detecting a synchronization signal data part of a first time slot in a received signal data sequence, and synchronization of a second time slot in the received signal data sequence. A second sync signal data detecting means for detecting the signal data part, and a minimum of two sync signal data of the first and second time slots detected by the first and second sync signal data detecting means as a reference signal. Transmission path characteristic estimating means for identifying first and second impulse responses between a transmitter and a receiver by using a multiplication method; and impulse response between synchronization signal data of the first and second time slots. An impulse response interpolation means for linearly interpolating the first and second impulse responses, and a Viterbi algorithm based on the impulse response from the impulse response interpolation means. There Viterbi equalizer, characterized by comprising more and decoding means for decoding the transmission data series. 2. The Viterbi equalizer according to claim 1, wherein the second time slot is the same time slot as the first time slot of a subsequent frame.