JP3970545B2 - Receiver and receiving method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a receiver used for a car phone or the like, and more particularly to a receiver and a receiving method that may be affected by fading with movement.
[0002]
[Prior art]
A conventional receiver and reception method will be described below. In wireless communication such as a car phone, the phase and level of a received signal are greatly affected by fading that fluctuates at a high speed as the receiver moves. As reception techniques for overcoming this fading, there are techniques such as delay detection and adaptive equalization.
[0003]
FIG. 9 is a diagram showing a configuration of a Viterbi equalizer used in a conventional receiver. Here, a Viterbi equalizer of the type that estimates transmission path characteristics according to data candidates of the Viterbi algorithm is shown. This type of Viterbi equalizer is described in, for example, H. Kubo et al .: “An adaptive maximum-likelihood sequence estimator for fast time-varying intersymbol interference channels” (IEEE Trans. Commun., Pp. 1872-1880, 1994) and H. Kubo et al .: “Adaptive maximum-likelihood sequence estimation by means of combined equalization and decoding in fading environments” (IEEE JSAC, pp. 102-109, 1995).
[0004]
In FIG. 9, 1 is a received signal input terminal, 2 is a judgment value output terminal, 7-1, 7-2, 7-N are N ACS circuits, and 10 is a judgment value creation circuit. , 101 are a plurality of transmission line characteristic input terminals, 102 is a branch metric creation circuit, 103-1, 103-2, 103-N are N transmission line update circuits, and 104 is a storage circuit. 115 are branch metric output terminals.
[0005]
First, basic matters regarding the Viterbi equalizer of FIG. 9 will be described. The Viterbi algorithm has a plurality of different data sequence candidate patterns. This is called a “state”. Further, the data series candidate is uniquely determined from the time transition of the two states. This is called a “branch”. The number of states N of the Viterbi algorithm is a power of the memory length related to the data candidate when creating a branch metric described later with respect to the multilevel number M at the time of modulation. Each of the Viterbi equalizers in FIG. 9 has a characteristic that each channel has an estimated value of a transmission path characteristic corresponding to the above state. In addition, what connected the branch continuously is called a path | pass, and what added the branch metric cumulatively corresponding to this path | pass is called a path metric.
[0006]
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 creation circuit 102 of the Viterbi equalizer. In FIG. 10, 111 is a transmission path characteristic / data candidate distribution circuit, 112-1, 112-2, 112-M are M branch metric calculation circuits, 113 is a selected transmission path characteristic input terminal, Reference numeral 114 denotes a data candidate input terminal.
[0007]
The transmission path characteristics / data candidate distribution circuit 111 receives a plurality of transmission path characteristics from the transmission path characteristics input terminal 101, and distributes the transmission path characteristics and data candidates to each branch metric calculation circuit according to a table held therein. . The branch metric calculation circuits 112-1, 112-2, and 112 -M output branch metrics corresponding to the multilevel number M from the branch metric output terminal 115.
[0008]
FIG. 11 is a diagram showing a configuration of a branch metric calculation circuit (one branch metric creation part). In FIG. 11, 121 is an estimated transmission path model, and 122 is a square error creating circuit.
[0009]
FIG. 11 shows a branch metric calculation circuit when the estimated number of taps is 3. In the estimated transmission path model 121, the estimated transmission path characteristics possessed by the state of one time past corresponding to each branch are received from the selected transmission path characteristics input terminal 113, and data candidates determined by the branches are further received as data candidate input terminals 114. And a replica of the received signal is created based on these. The square error creation circuit 122 creates a square error between the received signal and the replica of the received signal, and outputs this as a branch metric from the output terminal 115.
[0010]
On the other hand, FIG. 12 is a diagram showing a configuration of a branch metric calculation circuit different from FIG. In FIG. 12, 123 is an estimated transmission path model with an estimated number of taps of 1. This is a condition when there is no intersymbol interference, and in this case, it is not a condition that requires adaptive equalization, but the demodulation process is called adaptive equalization in a broad sense.
[0011]
For the transmission path estimation in each estimated transmission path model, for example, an adaptive algorithm such as the LMS algorithm is used. This algorithm weights and averages past detection values (the weight decreases as the distance to the past increases, but the weight does not become zero at all). However, in the transmission path condition shown in FIG. 12, it is also possible to execute demodulation by using delay detection.
[0012]
Next, in each of the states (N), ACS (addition / comparison / selection) circuits 7-1 to 7-N in FIG. 9 receive branch metrics of a plurality of branches corresponding to the current state from the branch metric creation circuit 102. Further, the path metric of one time past is received from the storage circuit 104, and the following processing is performed. First, a branch metric is added to a path metric that is one hour earlier to create a path metric at the current time (addition process). Next, a plurality of path metrics obtained by the addition process are compared (comparison process). Next, a path metric with the highest reliability is selected, and at the same time, a data series (path) corresponding to the path metric is also selected (selection process).
[0013]
Next, the transmission path update circuits 103-1 to 103 -N receive the received signal from the received signal input terminal 1, and further, the estimated transmission of one time past corresponding to the selected path and the path from the storage circuit 104. After receiving the path characteristics and updating the estimated transmission path characteristics based on them, the update result is output to the storage circuit 104.
[0014]
Next, the storage circuit 104 stores estimated transmission path characteristics, path metrics, and paths corresponding to the respective states. Finally, the determination value generation circuit 10 receives a path metric corresponding to each state and its path from the storage circuit 104, and outputs a path with the highest reliability state as a determination value.
[0015]
[Problems to be solved by the invention]
However, the conventional receiver has the following problems.
[0016]
FIG. 13 is a diagram illustrating temporal variation in transmission path characteristics when the estimated number of taps is one. When the transmission path characteristics fluctuate between time 1 and 2, when transmission path estimation is performed at time 2 using the LMS algorithm, the estimated value at time 2 is slightly past (time 1) than the detection value at time 2. A close value. The transmission path estimated 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 line estimation using the LMS algorithm, data determination is performed using a value closer to the past transmission line characteristics than the transmission line estimation using the delay detection. Will receive.
[0017]
That is, in the channel estimation using the above adaptive algorithm, the past values are averaged to estimate the current channel characteristics, so that a follow-up delay related to the channel variation occurs, especially when the channel variation is high speed. There is a problem that the tracking delay in the transmission path estimation becomes large and the tracking characteristics are deteriorated.
[0018]
Further, in the transmission path estimation using the adaptive algorithm, since past data is stored infinitely, the memory length required for the Viterbi algorithm becomes infinite (the number of states is proportional to the power of the memory length), and the conventional Viterbi There has been a problem that the number of states of the Viterbi algorithm in the equalizer increases.
[0019]
The present invention has been made in view of the above, and realizes a reduction in the number of states of the Viterbi algorithm, and further achieves a good tracking characteristic even when the transmission path fluctuation is high-speed, and The purpose is to obtain the receiving method.
[0020]
[Means for Solving the Problems]
In order to solve the above-described problems and achieve the object, the receiver according to the present invention is configured to operate based on the Viterbi algorithm (including a generalized list Viterbi algorithm), and further receives signals. Inverse modulation means (embodiment to be described later) for creating different inverse modulation signals (processing for normalizing a received signal with a transmission signal or its estimated value) using signals and a plurality of data candidates prepared in advance And a branch metric creation means for creating a branch metric based on the current and past inverse modulation signals corresponding to the plurality of data candidates (corresponding to the branch metric creation circuit 6). And.
[0021]
In the receiver according to the next invention, the branch metric generating means is a first calculating means for performing weighted addition using a plurality of received inverse modulation signals (corresponding to the inverse modulation signal distribution circuit 11 and the weighting addition circuit 21). And a second calculation means (corresponding to the square circuit 22) for calculating a square value of the weighted addition value and outputting the calculation result as a branch metric.
[0022]
In the receiving method according to the next invention, it is assumed that a Viterbi algorithm (including a generalized list Viterbi algorithm) is adopted. For example, a received signal and a plurality of data candidates prepared in advance are obtained. And using different inverse modulation (processing for normalizing the received signal with the transmission signal or its estimated value) signal, and the present and past inverse modulation signals corresponding to the plurality of data candidates. And a branch metric creating step for creating a branch metric based on the branch metric.
[0023]
In the reception method according to the next invention, in the branch metric creation step, a first calculation step of performing weighted addition using a plurality of received inverse modulation signals, and calculating a square value of the weighted addition value And a second calculation step.
[0024]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of a receiver according to the present invention will be described below in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.
[0025]
Embodiment 1 FIG.
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 survival path input terminal, 5 is a branch metric output terminal, 6 is a branch metric creation circuit, 7-1, 7-2, 7-N are N ACS circuits, 8 is an inverse modulation signal creation circuit, 9 is a storage circuit, and 10 is a judgment value. This is a creation circuit. N represents the number of states.
[0026]
In the present embodiment, description will be made centering on differences from the Viterbi equalizer. The Viterbi algorithm is generalized by Takeshi Hashimoto et al .: “Generalization of the Viterbi algorithm” (Electronic Communication Society paper (A), pp. 1064-1071, 1983), and this generalized Viterbi algorithm. Is used as a type of Viterbi equalizer. Further, when the normal Viterbi algorithm is used instead of the generalized Viterbi algorithm, it is not necessary to use the surviving path for creating the branch metric.
[0027]
Here, the operation of the receiver of this 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 creation circuit 6 according to the present embodiment. In FIG. 2, 11 is an inverse modulation signal distribution circuit, 12-1, 12-2 and 12-N are N branch metric calculation circuits, 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.
[0028]
In the inverse modulation signal distribution circuit 11, a plurality of inverse modulation signals are received from the inverse modulation signal input terminal 3, and data candidates are sent to each branch metric calculation circuit according to the surviving path received from the surviving path input terminal 4 and a table held therein. Distribute. The branch metric calculation circuits 12-1, 12-2, and 12-N output branch metrics corresponding to the number of states from the branch metric output terminal 5 based on the received data candidate signals. In the normal Viterbi algorithm, the surviving path is not used. Also, the difference from FIG. 9 is that a surviving path is input when a branch metric is created, and in addition, no received signal is input.
[0029]
FIG. 3 is a diagram showing a configuration of a branch metric calculation circuit (one branch metric creation part) according to the present embodiment. In FIG. 3, 21 is a weighted addition circuit, and 22 is a square 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.
[0030]
FIG. 3 shows a branch metric calculation circuit when the addition number is 3. The weighted addition circuit 21 receives inverse modulation signals corresponding to past states (plural) corresponding to each branch from the inverse modulation signal input terminal 3, and creates weighted addition values using these inverse modulation signals. The square circuit 22 creates a square value of the received weighted addition value and outputs it as a branch metric from the branch metric output terminal 5. The difference between the above operation and the prior art will be described later.
[0031]
Next, in the ACS (addition / comparison / selection) circuits 7-1, 7-2, 7 -N in FIG. 1, in each state (N), a plurality of branch metrics corresponding to the current state are obtained from the branch metric creation circuit 6. In addition, a path metric of one time past is received from the storage circuit 9, and the following processing is performed. First, a branch metric is added to a path metric that is one hour earlier to create a path metric at the current time (addition process). Next, a plurality of path metrics obtained by the addition process are compared (comparison process). Finally, the path metric with the highest reliability is selected, and at the same time, a data series (path) corresponding to this path metric is also selected (selection process).
[0032]
Next, the inverse modulation signal creation circuit 8 creates a plurality of inverse modulation signals based on a plurality of transmission signal candidates existing in a table prepared in advance for the received signal. Here, the creation process of the inverse modulation signal will be briefly described.
[0033]
FIG. 4 is a diagram illustrating an example of the received signal, and FIG. 5 is a diagram illustrating 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 transmission path characteristics 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 a candidate for the transmission signal is shown on the right side.
[0034]
FIGS. 6 and 7 are diagrams illustrating a process of creating an inverse modulation signal when 16QAM is assumed. Here, it is shown that when the amplitude of the modulation signal is large, the amplitude of the inverse modulation signal is small even if the phase of the modulation signal is the same.
[0035]
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 prior art is that the transmission path characteristic is an inverse modulation value over a plurality of times. Finally, the determination value creation circuit 10 receives the path metric and path corresponding to each state from the storage circuit 9, and outputs the path leading to the state with the highest reliability as the determination value.
[0036]
As described above, in the description of the operation of the receiver so far, when the present embodiment is compared with the prior art, the biggest difference is the processing related to the creation of the branch metric. That is, in the prior art, a branch metric is created from the transmission path characteristics obtained by transmission path estimation and the received signal, but in this embodiment, the square value of the weighted addition value of the inverse modulation value is used as the branch metric. Yes. In particular, as shown in FIG. 3, since only the finite past value is used for the inverse modulation value, the memory length of the Viterbi algorithm does not increase. As the branch metric, in addition to deriving the square value for the weighted addition value as described above, for example, an absolute value may be derived (Manhattan metric).
[0037]
Moreover, FIG. 8 is a figure which shows the time fluctuation of the transmission-line characteristic of this Embodiment. Here, similarly to the transmission path fluctuation of FIG. 13 described above, the fluctuation of the inverse modulation signal when it fluctuates at times 1, 2, and 3 is shown. In the case of FIG. 8, for example, the weights of FIG. 3 are set so that the average of the inverse modulation signals at time 3 and time 1 becomes the inverse modulation signal at time 2 (weights are 1, -2, 1). As a result, in this embodiment, even when the transmission path fluctuation becomes high speed, the square error of the weighted signal becomes a small value, and correct data determination is possible even under high speed transmission path fluctuation.
[0038]
As described above, in the present embodiment, since 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 used as a branch metric. Since the configuration is adopted, the memory for data can be set finitely and the number of states of the Viterbi algorithm can be set small. Further, even when the transmission path fluctuation is high speed, it is possible to reduce the deterioration of the data determination accuracy due to the transmission path fluctuation, so that a good tracking characteristic can be obtained.
[0039]
【The invention's effect】
As described above, according to the present invention, since a plurality of inverse modulation signals received from the inverse modulation signal input terminal are processed, that is, the square value of the weighted addition value of the inverse modulation value is used as the branch metric. Since the configuration is adopted, it is possible to obtain a receiver capable of setting a finite amount of data storage and further capable of setting the number of states of the Viterbi algorithm to be small. In addition, even when the transmission path fluctuation is high speed, it is possible to reduce the deterioration of the data determination accuracy due to the transmission path fluctuation, so that it is possible to obtain a receiver capable of realizing good tracking characteristics. Play.
[0040]
According to the next invention, for example, since the weight can be set so that the average of the inverse modulation signal at time 3 and time 1 becomes the inverse modulation signal at time 2, the transmission path fluctuation becomes high speed. Even so, it is possible to obtain a receiver capable of performing correct data determination.
[0041]
According to the next invention, since it is configured to process a plurality of inversely modulated signals received from the inversely modulated signal input terminal, that is, since it is configured to use the square value of the weighted addition value of the inversely modulated value as a branch metric, data There is an effect that the memory for can be set finitely and the number of states of the Viterbi algorithm can be set small. In addition, even when the transmission path fluctuation is high speed, the deterioration of the data determination accuracy due to the transmission path fluctuation can be reduced, so that an excellent tracking characteristic can be realized.
[0042]
According to the next invention, for example, since the weight can be set so that the average of the inverse modulation signal at time 3 and time 1 becomes the inverse modulation signal at time 2, the transmission path fluctuation becomes high speed. Even so, 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 creation 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 illustrating 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 16QAM is assumed.
FIG. 7 is a diagram illustrating a process of creating an inverse modulation signal when 16QAM is assumed.
FIG. 8 is a diagram illustrating temporal variation of transmission path characteristics according to the first embodiment.
FIG. 9 is a diagram showing a configuration of a Viterbi equalizer used in a conventional receiver.
FIG. 10 is a diagram illustrating a configuration of a conventional branch metric creation 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 a conventional transmission path characteristic.
[Explanation of symbols]
1 reception signal input terminal, 2 judgment value output terminal, 3 inverse modulation signal input terminal, 4 survival path input terminal, 5 branch metric output terminal, 6 branch metric creation circuit, 7-1, 7-2, 7-N ACS circuit , 8 Inverse modulation signal creation circuit, 9 Storage circuit, 10 Determination value creation circuit, 11 Inverse modulation signal distribution circuit, 12-1, 12-2, 12-N branch metric calculation circuit, 13 Select inverse modulation signal input terminal, 21 Weighted addition circuit, 22 square circuit.

Claims (2)

In a receiver that operates based on the Viterbi algorithm (including the generalized list Viterbi algorithm)
Inverse modulation means for creating different inverse modulation (processing for normalizing the reception signal with the candidate transmission signal) signal using the reception signal and a plurality of transmission signal candidates prepared in advance;
Using a plurality of inverse modulation signals up to a predetermined time corresponding to the transmission signal candidates for each branch, weighted addition is performed for each branch, and the square value of the weighted addition value is calculated. Branch metric creating means having as many branch metric calculation circuits as the branch metric for each branch corresponding to the state as many as the number of states ;
Equipped with a,
The receiver for setting the weight when performing the weighted addition so that the inverse modulation signal at a specific time becomes an average of the inverse modulation signals at the preceding and succeeding times . In a receiving method of a receiver that employs a Viterbi algorithm (including a generalized list Viterbi algorithm)
Using the received signal and a plurality of transmission signal candidates prepared in advance, respectively, different inverse modulation (processing for normalizing the received signal with the transmission signal candidate ) signal, a reverse modulation step,
Using a plurality of inverse modulation signals up to a predetermined time corresponding to the transmission signal candidates for each branch, weighted addition is performed for each branch, and the square value of the weighted addition value is calculated. A branch metric creation step for executing the process of outputting as a branch metric for each branch corresponding to a state by the number of states ;
Only including,
A receiving method, characterized in that a weight for performing the weighted addition is set so that an inverse modulation signal at a specific time becomes an average of inverse modulation signals at times before and after that .

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