JP2002314435A - Receiver and receiving method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a receiver that realizes an excellent tracking characteristic even when fluctuations in a transmission line are rapid by realizing reduction of the state number of a Viterbi algorithm. SOLUTION: The receiver of this invention is configured that it is in operation on the basis of the Viterbi algorithm and provided with an inverse modulation signal generating circuit 8 that uses a received signal and candidates of a plurality of data prepared in advance to generate different inverse modulation signals and with a branch metric generating circuit 6 that generates a branch metric on the basis of the present and past inverse modulation signals corresponding to a plurality of the data candidates.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a receiver used for an automobile telephone or the like, and more particularly to a receiver and a receiving method which may be affected by fading as the vehicle moves.

[0002]

2. Description of the Related Art A conventional receiver and receiving method will be described below. 2. Description of the Related Art In a wireless communication such as an automobile telephone, a phase of a received signal or a level of the received signal fluctuates at a high speed with a movement of a receiver. As a receiving technique for overcoming this fading, there are techniques such as differential detection and adaptive equalization.

FIG. 9 is a diagram showing a configuration of a Viterbi equalizer used in a conventional receiver. Here, a Viterbi equalizer of a type for estimating transmission path characteristics according to data candidates of the Viterbi algorithm is shown. This type of Viterbi equalizer
For example, H. Kubo et al .: "An adaptive maximum-likel
ihood sequence estimator for fast time-varying int
ersymbol interference channels ”(IEEE Tra
ns. Commun. Pp. 1872-1880,1
994) and H. Kubo et al .: "Adaptive maximum-likeli
hood sequence estimation by means of combined equa
lization and decoding in fading environments ”(I
EEE JSAC, pp. 102-109, 1995)
Is described in detail.

In FIG. 9, 1 is a reception signal input terminal, 2 is a judgment value output terminal, and 7-1, 7-2, 7-
N is an N number of ACS circuits, 10 is a judgment value creation circuit, 101 is a plurality of transmission line characteristic input terminals, and 10
Reference numeral 2 denotes a branch metric generation circuit.
−2, 103-N are N transmission line update circuits,
4 is a storage circuit, and 115 is a branch metric output terminal.

First, basic matters relating to the Viterbi equalizer shown in FIG. 9 will be described. The Viterbi algorithm has a plurality of different data sequence candidate patterns. This is called a “state”. Further, a data sequence candidate is uniquely determined from the time transition between the two states. This is called a "branch". In addition, the number of states N of the Viterbi algorithm is a power of the memory length of a data candidate when a branch metric described later is created with respect to the multilevel number M at the time of modulation. The Viterbi equalizer in FIG. 9 corresponds to the above state,
It has the feature of retaining the estimated value of the transmission path characteristics. It should be noted that a continuous connection of the branches is called a path, and a cumulative addition of the branch metrics corresponding to this path is called a path metric.

Here, the operation of the Viterbi equalizer will be described. First, the operation of the branch metric creation circuit 102 will be described. FIG. 10 is a diagram showing a configuration of the branch metric generation circuit 102 of the Viterbi equalizer. In FIG. 10, reference numeral 111 denotes a transmission line characteristic / data candidate distribution circuit.
Reference numerals 112-1, 112-2, and 112-M denote M branch metric calculation circuits, 113 denotes a selected transmission line characteristic input terminal, and 114 denotes a data candidate input terminal.

The transmission line characteristic / data candidate distribution circuit 111 receives a plurality of transmission line characteristics from the transmission line characteristic input terminal 101, and determines the transmission line characteristics and data candidates according to a table held in each branch metric calculation circuit. Distribute to Branch metric calculation circuits 112-1, 112-2, 1
In 12-M, the branch metric corresponding to the multi-value number M is output from the branch metric output terminal 115.

FIG. 11 is a diagram showing a configuration of a branch metric calculation circuit (one branch metric creating portion). FIG.
1, reference numeral 121 denotes an estimated transmission channel model;
Is a square error generation circuit.

FIG. 11 shows a branch metric calculation circuit when the number of estimated taps is three. In the estimated transmission path model 121, the estimated transmission path characteristic held by the state one time in the past corresponding to each branch is received from the selected transmission path characteristic input terminal 113, and the data candidate determined by the branch is input to the data candidate input terminal 114. And creates a replica of the received signal based on these. Square error generation circuit 1
At 22, a square error between the received signal and the replica of the received signal is created and output from the output terminal 115 as a branch metric.

FIG. 12 is a diagram showing a configuration of a branch metric calculation circuit different from that of FIG. In FIG.
Reference numeral 123 denotes an estimated transmission channel model in which the estimated number of taps is one.
This is a condition in the case where there is no intersymbol interference. In this case, the condition does not require adaptive equalization, but the demodulation process is called adaptive equalization in a broad sense.

For the transmission channel estimation in each of the above estimated transmission channel models, for example, an adaptive algorithm such as an LMS algorithm is used. In this algorithm, past detection values are weighted and averaged (the more the distance goes to the past, the more the weight decreases, but the weight never becomes zero). However, under the transmission path conditions shown in FIG. 12, demodulation can be performed by using differential detection.

Next, the ACS (addition / comparison / selection) circuits 7-1 to 7-N in FIG. 102, and receives a path metric one time past from the storage circuit 104, and performs the following processing. First, a branch metric is added to a path metric one time earlier to create a path metric at the current time (addition processing). Next, a plurality of path metrics obtained by the addition processing are compared (comparison processing). Next, a path metric having the highest reliability is selected, and at the same time, a data sequence (path) corresponding to this path metric is also selected (selection processing).

Next, the transmission line update circuits 103-1 to 103-1
In 3-N, the received signal is received from the received signal input terminal 1, and further, the selected path and the estimated transmission path characteristic corresponding to the selected path one time ago are received from the storage circuit 104, and the estimated transmission is performed based on them. After updating the road characteristics, the update result is output to the storage circuit 104.

Next, the storage circuit 104 stores an estimated transmission path characteristic, a path metric, and its path corresponding to each state. Finally, the judgment value creation circuit 10 receives the path metric corresponding to each state and its path from the storage circuit 104, and outputs the path in the state with the highest reliability as the judgment value.

[0015]

SUMMARY OF THE INVENTION However,
The conventional receiver has the following problems.

FIG. 13 is a diagram showing the time variation of transmission path characteristics when the estimated number of taps is one. If the transmission path characteristics fluctuate from time 1 to time 2 and the transmission path is estimated at time 2 using the LMS algorithm, the estimated value at time 2 becomes a value slightly past (time 1) than the detected value at time 2. It will be a close value. Then, the transmission path estimation value is used for data determination at time 3. On the other hand, in the delay detection, the transmission path estimation value at time 2 is used for data determination at time 3. As described above, in the transmission path estimation using the LMS algorithm, data determination is performed using a value closer to the past transmission path characteristics than the transmission path estimation using delay detection. Will receive it.

That is, in the transmission channel estimation using the above adaptive algorithm, since the current transmission channel characteristics are estimated by averaging the past values, a following delay relating to the transmission channel fluctuation occurs.
In particular, when the transmission path fluctuation is high, the tracking delay in the transmission path estimation becomes large, and the tracking characteristic deteriorates.
There was a problem.

Further, in the transmission path estimation using the adaptive algorithm, since the past data is stored indefinitely, the memory length required for the Viterbi algorithm becomes infinite (the number of states is proportional to a power of this memory length). There is a problem that the number of states of the Viterbi algorithm in the conventional Viterbi equalizer increases.

The present invention has been made in view of the above, and has been made to reduce the number of states of the Viterbi algorithm, and furthermore, to realize a good tracking characteristic even when the transmission line fluctuations are high. Machine and its receiving method.

[0020]

Means for Solving the Problems The above-mentioned problems are solved,
In order to achieve the object, the receiver according to the present invention is configured to operate based on a Viterbi algorithm (including a generalized list Viterbi algorithm),
Further, an inverse modulation unit (described later) that creates different inverse modulation (processing of normalizing the reception signal with a transmission signal or its estimated value) signals using the reception signal and a plurality of data candidates prepared in advance. A branch metric generating means (corresponding to the inverse modulation signal generating circuit 8 of the embodiment) and a branch metric generating means (branch metric generating circuit 6) for generating a branch metric based on current and past reverse modulation signals corresponding to the plurality of data candidates ) Is provided.

[0021] In the receiver according to the next invention, the branch metric generating means includes a first calculating means (inverse modulation signal distribution circuit 11, weighting addition circuit 21) for performing weighting addition using the plurality of received inverse modulation signals. And a second calculating means (squaring circuit 2) for calculating a square value of the weighted addition value and outputting the calculation result as a branch metric.
2)).

In the receiving method according to the next invention,
It is assumed that a Viterbi algorithm (including a generalized List Viterbi algorithm) is employed. For example, using a received signal and a plurality of data candidates prepared in advance, different inverse modulation (reception signal A process of normalizing a transmission signal or its estimated value) a reverse modulation step of generating a signal; and a branch metric generation step of generating a branch metric based on current and past reverse modulation signals corresponding to the plurality of data candidates. And characterized in that:

In the receiving method according to the next invention, in the branch metric creating step, a first calculating step of performing weighted addition using the received plurality of inverse modulation signals, and a square of the weighted added value And a second calculating step of calculating a value.

[0024]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of a receiver according to the present invention will be described in detail with reference to the drawings. The present invention is not limited by the embodiment.

Embodiment 1 FIG. 1 is a diagram showing a configuration of a receiver according to the present invention. In FIG. 1, 1 is a received signal input terminal, 2 is a judgment value output terminal, 3 is an inverse modulation signal input terminal, 4 is a surviving path input terminal, 5 is a branch metric output terminal, Reference numeral 6 denotes a branch metric generation circuit, 7-1, 7-2, and 7-N denote N ACS circuits, 8 denotes an inverse modulation signal generation circuit, and 9
Is a storage circuit, and 10 is a judgment value creation circuit. N indicates the number of states.

In the present embodiment, the description will focus on the differences from the Viterbi equalizer. The Viterbi algorithm is described in Takeshi Hashimoto et al .: “Generalization of the Viterbi algorithm” (Transactions of the Institute of Electronics, Information and Communication Engineers (A), pp. 1064-1).
071, 1983), and the use of this generalized Viterbi algorithm is also treated as a type of Viterbi equalizer. In addition, when a general Viterbi algorithm is used instead of the generalized Viterbi algorithm, it is not necessary to use a surviving path for creating a branch metric.

Here, the operation of the receiver according to the present embodiment will be described. First, the operation of the branch metric creation circuit 6 will be described. FIG. 2 is a diagram illustrating a configuration of the branch metric generation circuit 6 according to the present embodiment. In FIG. 2, reference numeral 11 denotes an inverse modulation signal distribution circuit, which includes 12-1, 12-2, 12-N
Is an N branch metric calculation circuit, and 13 is a selective inverse modulation signal input terminal. In addition, about the structure similar to the said FIG. 1, the same code | symbol is attached | subjected and the description is abbreviate | omitted.

The inverse modulation signal distribution circuit 11 receives a plurality of inverse modulation signals from the inverse modulation signal input terminal 3 and, based on the surviving path received from the surviving path input terminal 4 and the internally held table, divides the data candidate into each branch metric. Distribute to the calculation circuit. Branch metric calculation circuit 12-
In 1, 12-2 and 12-N, a branch metric corresponding to the number of states is output from the branch metric output terminal 5 based on the received data candidate signal. Note that the surviving path is not used in the normal Viterbi algorithm. The difference from FIG. 9 is that a surviving path is input when a branch metric is created, and that a received signal is not input.

FIG. 3 is a diagram showing a configuration (one branch metric generation portion) of the branch metric calculation circuit of the present embodiment. In FIG. 3, reference numeral 21 denotes a weighting addition circuit.
22 is a squaring circuit. In addition, about the structure similar to the said FIG. 2, the same code | symbol is attached | subjected and the description is abbreviate | omitted.

FIG. 3 shows a branch metric calculation circuit when the number of additions is three. The weighting addition circuit 21 receives an inverse modulation signal corresponding to a past state (plurality) corresponding to each branch from the inverse modulation signal input terminal 3 and creates a weighted addition value using these inverse modulation signals. The squaring circuit 22 creates a square value of the received weighted addition value, and uses the square value as a branch metric.
Output from The difference between the above operation and the conventional technique will be described later.

Next, in each of the ACS (addition / comparison / selection) circuits 7-1, 7-2, and 7-N shown in FIG. The path metric received from the creation circuit 6 and the path metric one time past are received from the storage circuit 9 and the following processing is performed. First, a branch metric is added to a path metric one time earlier to create a path metric at the current time (addition processing). Next, a plurality of path metrics obtained by the addition processing are compared (comparison processing). Finally, the path metric with the highest reliability is selected, and at the same time, the data series (path) corresponding to this path metric is also selected (selection processing).

Next, the inverse modulation signal generation circuit 8 generates a plurality of inverse modulation signals based on a plurality of transmission signal candidates existing in a table prepared in advance for the reception signal. Here, the process of creating the inverse modulation signal will be briefly described.

FIG. 4 is a diagram showing an example of the received signal, and FIG. 5 is a diagram showing a process of creating an inverse modulation signal when QPSK is assumed. Inverse modulation is a value obtained by dividing a received signal by a transmitted signal, in other words, a detected value of the transmission path characteristic at each time. For example,
Assuming QPSK as shown in FIG. 5, the reverse modulation signal when the black circle of the modulation signal is set as a transmission signal candidate is shown in the right diagram.

FIGS. 6 and 7 are diagrams showing a process of generating an inverse modulation signal when 16 QAM is assumed. Here, it is shown that when the amplitude of the modulation signal is large, the amplitude of the inverse modulation signal becomes small even if the phase of the modulation signal is the same.

Next, the storage circuit 9 in FIG. 1 stores an inverse modulation signal, a path metric, and a path corresponding to each state. That is, the difference from the conventional technique is that the transmission path characteristic has an inverse modulation value over a plurality of times in the past. Finally, the judgment value creation circuit 10 receives the path metric and the path corresponding to each state from the storage circuit 9, and outputs the path leading to the state with the highest reliability as the judgment value.

In the above description of the operation of the receiver, the most significant difference between the present embodiment and the prior art is the processing related to the creation of a branch metric. That is, in the related art, the branch metric is created from the transmission path characteristics obtained by the transmission path estimation and the received signal, but in the present embodiment, the square value of the weighted sum of the inverse modulation values is used as the branch metric. I have. In particular, as shown in FIG. 3, the inverse modulation value is used only up to a finite past value, so that the memory length of the Viterbi algorithm does not increase. As the branch metric, as described above, in addition to deriving a square value for the weighted addition value, for example, an absolute value may be derived (Manhattan metric).

FIG. 8 is a diagram showing the time variation of the transmission path characteristics of the present embodiment. Here, similarly to the transmission path fluctuation of FIG. 13 described above, the fluctuation of the inverse modulation signal when the fluctuation occurs at times 1, 2, and 3 is shown. In the case of FIG. 8, for example, the weights in FIG. 3 are set so that the average of the inversely modulated signals at time 3 and time 1 becomes the inversely modulated signal at time 2 (weights are 1, -2, 1). As a result, in the present embodiment, even when the transmission path fluctuations are high, the square error of the weighted signal becomes a small value, and correct data determination can be performed even under high-speed transmission path fluctuations.

As described above, in the present embodiment, the configuration is such that a plurality of inverse modulation signals received from the inverse modulation signal input terminal 3 are processed, that is, the square value of the weighted addition value of the inverse modulation value is divided. Since the configuration is a metric, the storage for data can be set finitely, and the number of states of the Viterbi algorithm can be set small. Also,
Even when the transmission line fluctuation is high speed, deterioration of the data determination accuracy due to the transmission line fluctuation can be reduced, so that good tracking characteristics can be obtained.

[0039]

As described above, according to the present invention, a plurality of inverse modulation signals received from the inverse modulation signal input terminal are processed, that is, the square value of the weighted sum of the inverse modulation values is obtained. Is set as a branch metric, so that the storage for data can be set finitely.
There is an effect that a receiver capable of setting the number of states of the Viterbi algorithm small can be obtained.
Further, even when the transmission line fluctuation is high speed, the deterioration of the data determination accuracy due to the transmission line fluctuation can be reduced, so that it is possible to obtain a receiver capable of realizing a good tracking characteristic. Play.

According to the next invention, for example, the weight can be set so that the average of the inversely modulated signals at time 3 and time 1 becomes the inversely modulated signal at time 2, so that the transmission line fluctuation can be reduced at high speed. Even in such a case, it is possible to obtain a receiver capable of performing correct data determination.

According to the next invention, the configuration is such that a plurality of inverse modulation signals received from the inverse modulation signal input terminal are processed, that is, the square value of the weighted sum of the inverse modulation values is used as the branch metric. As a result, the storage of data can be set finitely, and the number of states of the Viterbi algorithm can be set small. In addition, even when the transmission line fluctuation is high speed, deterioration of data determination accuracy due to transmission line fluctuation can be reduced,
There is an effect that good tracking characteristics can be realized.

According to the next invention, for example, the weight can be set so that the average of the inversely modulated signals at time 3 and time 1 becomes the inversely modulated signal at time 2, so that the transmission line fluctuation can be reduced at high speed. Even in such a case, there is an effect that correct data determination can be performed.

[Brief description of the drawings]

FIG. 1 is a diagram showing a configuration of a receiver according to the present invention.

FIG. 2 is a diagram illustrating a configuration of a branch metric generation circuit according to the first embodiment;

FIG. 3 is a diagram illustrating a configuration of a branch metric calculation circuit according to the first embodiment;

FIG. 4 is a diagram illustrating an example of a received signal.

FIG. 5 is a diagram showing a process of creating an inverse modulation signal when QPSK is assumed.

FIG. 6 is a diagram illustrating a process of creating an inverse modulation signal when 16 QAM is assumed.

FIG. 7 is a diagram showing a process of creating an inverse modulation signal when 16 QAM is assumed.

FIG. 8 is a diagram illustrating a time variation of transmission path characteristics according to the first embodiment.

FIG. 9 is a diagram illustrating a configuration of a Viterbi equalizer used in a conventional receiver.

FIG. 10 is a diagram illustrating a configuration of a conventional branch metric generation circuit.

FIG. 11 is a diagram showing a configuration of a conventional branch metric calculation circuit.

FIG. 12 is a diagram showing a configuration of a conventional branch metric calculation circuit.

FIG. 13 is a diagram showing a time variation of conventional transmission path characteristics.

[Explanation of symbols]

1 reception signal input terminal, 2 judgment value output terminal, 3 inverse modulation signal input terminal, 4 survivor path input terminal, 5 branch metric output terminal, 6 branch metric generation circuit, 7-1,
7-2, 7-N ACS circuit, 8 inverse modulation signal generation circuit, 9 storage circuit, 10 decision value generation circuit, 11 inverse modulation signal distribution circuit, 12-1, 12-2, 12-N branch metric calculation circuit, 13 Selective reverse modulation signal input terminal, 2
1 Weighted addition circuit, 22 squared circuit.

Claims (4)

[Claims] 1. A receiver operating based on the Viterbi algorithm (including a generalized list Viterbi algorithm), using a received signal and a plurality of data candidates prepared in advance to perform different inverse modulation. (Process of normalizing a received signal with a transmission signal or its estimated value) Inverse modulation means for generating a signal, and a branch metric based on current and past inverse modulation signals corresponding to the plurality of data candidates A receiver comprising: a branch metric creating unit. 2. The branch metric creating means: first calculating means for performing weighted addition using the plurality of received inverse modulation signals; calculating a square value of the weighted added value; The receiver according to claim 1, further comprising: a second calculation unit that outputs the metric. 3. A receiving method of a receiver employing a Viterbi algorithm (including a generalized list Viterbi algorithm), wherein a different inverse signal is used by using a received signal and a plurality of data candidates prepared in advance. An inverse modulation step of creating a modulated (normalized received signal with a transmission signal or its estimated value) signal; and creating a branch metric based on current and past inverse modulation signals corresponding to the plurality of data candidates. And a branch metric creating step. 4. The branch metric creating step includes: a first calculating step of performing weighted addition using the received plurality of inverse modulation signals; and a second calculating step of calculating a square value of the weighted added value. The receiving method according to claim 3, comprising: a calculating step.