JP2862083B1 - Receiving method and receiving device - Google Patents

Abstract

An object of the present invention is to provide a method and apparatus for improving characteristics of a path diversity receiving system when the number of incoming waves is large. When a steering vector array using an estimated impulse response of a desired wave as a constraint vector is controlled together with an array output replica generator from a candidate signal and an estimated channel impulse response, a delayed wave that is not a desired wave is also controlled as a candidate signal. By reducing the number of delayed waves to be suppressed by capturing and improving the array output SINR, for the captured unnecessary delayed wave components, the decision data is fed back in the Viterbi algorithm and canceled by the metric calculation. Improve reception quality without increasing the number of states.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a receiving method and a receiving apparatus, and more particularly to a digital mobile communication and a wireless LAN.
TECHNICAL FIELD The present invention relates to a multipath countermeasure technique which becomes a problem in the above, and relates to a receiving method and a receiving apparatus which can overcome frequency selective fading.

[0002]

2. Description of the Related Art In recent years, a path diversity receiving system combining an adaptive array antenna and a Viterbi algorithm has been proposed as a multipath countermeasure technology. FIG.
The present inventor has established a conference (1997 IEEE 6th International Co.
nferrence on Universal Personal Communications, 12-
FIG. 16 is a functional block diagram showing a signal processing content of a conventional example announced in 16 October 1997).

This technique prepares not only a direct wave but also a candidate signal for a one-symbol delayed wave when calculating a steering vector array weight for direct wave extraction.
When calculating a steering vector array weight for extracting a symbol delayed wave, by preparing a candidate signal for not only a one-symbol delayed wave but also a direct wave, a directivity null point is not formed for another desired wave. Takes in the desired wave component and outputs multiple array outputs using a maximum likelihood sequence estimator (Maximum Likel
ihood Sequence Estimation (hereinafter referred to as MLSE) performs branch metric synthesis to estimate a transmission signal sequence. The MLSE is described in, for example, "Waveform Equalization Technology for Digital Mobile Communication", published by Trikefs, June 1996, pp. 77-100.

[0004]

In the above-described conventional path diversity receiving system, when the delay wave from the direct wave to several symbol delay is considered, the number of states of the Viterbi algorithm increases, and the amount of calculation increases exponentially. However, the desired wave is limited to a direct wave and a one-symbol delayed wave. Further, when the number of arriving delayed waves increases, the BER (bit error rate) characteristic deteriorates due to lack of array flexibility. SUMMARY OF THE INVENTION It is an object of the present invention to solve the above-mentioned problems of the prior art and to provide a receiving method and a receiving apparatus in which quality does not deteriorate even when the number of delayed waves is large.

[0005]

In the present invention, in order to solve the above-mentioned problems, a delayed decision feedback type maximum likelihood decoding method (hereinafter referred to as DDFSE (Delayed Decision Feedback Feedback) instead of MLSE is used.
Sequence Estimation). ). DDFSE is M
This is a method to reduce the amount of calculation by introducing the concept of decision feedback into LSE. In the present invention, by using DDFSE, a long delay wave is suppressed by an array process, a delay wave of about a medium delay is canceled by metric correction by DDFSE decision data feedback, and a DDFSE is used by using a short delay wave.
To estimate the transmission data sequence. Therefore, according to the present invention, it is possible to realize a receiving method that slightly increases the amount of calculation but improves the error rate.

[0006]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 6 is a block diagram illustrating an example of a hardware configuration of the receiving device of the present invention. As the adaptive array antenna 1, for example, a linear array antenna or a planar array antenna having about 4 to 8 elements is used. The linear demodulator 2 amplifies a received signal, performs frequency conversion, performs quadrature detection, and downconverts the signal to a baseband. The A / D converter 3 A / D converts the received baseband signal. The signal processing unit 4 is configured by, for example, a DSP (Digital Signal Processor), and executes an adaptive array antenna process and a process related to a decision feedback type maximum likelihood sequence estimator according to the present invention, as described later.

FIG. 1 is a functional block diagram showing the signal processing function of the present invention in the signal processing section 4 of FIG. Also,
FIG. 2 is an explanatory diagram illustrating an example of power of a direct wave and a delayed wave received by each antenna. In the embodiment, as shown in FIG. 2, a direct wave and a one-symbol delayed wave are set as desired waves, a two-symbol delayed wave is canceled by decision data feedback in a Viterbi algorithm, and a three-symbol delayed wave and a four-symbol delayed wave are arrayed. The following describes an example in which the number of waves to be suppressed, the number of waves to be canceled, the number of waves to be suppressed in the array, and the like are arbitrary. As a signal type in the embodiment, it is assumed that a known training signal is added before a data portion to be transmitted, and the signal is transmitted by a TDMA method.

The channel impulse response estimator 24 estimates the channel impulse response of the direct wave and the one-symbol delayed wave for each branch using the signals received from all the antennas during the training period. The direct wave extraction array processing unit includes a direct wave extraction steering vector array 10 and a constrained condition application algorithm 11, and operates to extract a direct wave from a demodulated signal of each array antenna. Although various teaching principles are known as a control method of the adaptive antenna, a feedback type is generally used, and an array algorithm is used to adjust an array weight so as to minimize a mean square error between an array output and a reference signal. When the control is performed, the null point of the directivity is directed to the arrival direction of the delayed wave, and the delayed wave is suppressed. The adaptive antenna has a feature that the effect of suppressing a delayed wave having a long delay time is high.

As a weight determination algorithm used for an adaptive antenna, LMS ((Least Mean Square)
e) Adaptive array, RLS (Recursive Least Squares)
There are adaptive arrays and SMI (Sample Matrix Inversion) arrays. Such an adaptive antenna signal processing method is described in, for example, Kazuaki Takao: “Adaptive Antenna Theory System”, IEICE (B-II), Vol.J75-B-II, N
o.11, pp.713-720 (Issued November 1992), Yasutaka Ogawa, Nobuyoshi Kikuma: “Progress and Future Prospects of Adaptive Antenna Theory”, IEICE (B-II), Vol.J75-B- II, No.11, pp.721-
732 (issued in November 1992) or "Waveform Equalization Technology for Digital Mobile Communication", published by Trikefs in June 1996, 101-
It is well known as described on page 116.

As the application algorithm 11 with the constraint condition, a simple LMS algorithm, an RLS algorithm having excellent convergence characteristics, and the like can be used, and the weight of the adaptive array is controlled based on an error between an array output and a reference signal.

The 1-symbol delayed wave extraction array processing section comprises:
As with the direct wave extraction array processing unit, it comprises a 1-symbol delayed wave extraction steering vector array 16 and a constrained condition application algorithm 17. The algorithm 17 is the same as the algorithm 11, and operates to extract a one-symbol delayed wave from the demodulated signal of each array antenna.

FIG. 3 is an explanatory diagram showing the operation in the array processing section. The output of the direct wave extraction array 10 has 3
The 4-symbol delayed wave is suppressed, and the direct wave and the 1- and 2-symbol delayed wave components are output. Also, the 1-symbol delayed wave extraction array suppresses the 3-symbol and 4-symbol delayed waves and outputs the 1-symbol delayed wave, the direct wave component, and the 2-symbol delayed wave component. In FIG. 3, the solid line shows the directivity of the direct wave extraction array, and the dotted line shows the directivity of the one-symbol delayed wave extraction array. In an array antenna, the maximum value of independent null points that can be set to suppress a signal is limited to (the number of antenna elements minus 1). That is, if the number of antenna elements is 4, the number of delayed waves that can be suppressed is 3, but
In the present invention, since the number of delayed waves to be suppressed in the array processing unit decreases, the delayed waves to be suppressed can be more reliably suppressed even when the number of delayed waves increases.

The joint processing unit for array processing and DDFSE includes replica generators 12 and 18 which are array output estimators and DD generators.
FSE23 etc. The replica generators 12, 18 convolve the obtained channel impulse response (CIR) with a known training signal or candidate signal using a transversal filter or the like to generate a reference signal or a replica for a desired wave.

The adders 13 and 19 subtract the outputs of the replica generators 12 and 18 from the outputs of the arrays 10 and 16 and output an error signal. The error signal is input to the application algorithms 11 and 17 with constraint conditions, respectively, and is also input to the absolute value square calculators 14 and 20. Output signals of the absolute value square calculators 14 and 20 are input to multipliers 15 and 21, respectively, multiplied by weight coefficients # 0 and # 1 described later, and output as branch metrics in the respective arrays. The adder 22 adds the output signals of the respective multipliers and outputs the result to the DDFSE 23. DDFSE 23 estimates a received signal sequence based on the combined branch metrics, and outputs the sequence and a candidate signal.

[0015] DDFSE is defined as a section 0 to receive intersymbol interference.
L (for example, 0 to 2) is replaced by 0 to L ′ (0 to 1) and L ′ + 1 to L
(2), the intersymbol interference of 0 to L ′ is compensated by the maximum likelihood sequence estimation Viterbi algorithm, and L ′ + 1 to
The intersymbol interference of L is a method of compensating by performing decision feedback. That is, in the section from L '+ 1 to L, only the surviving paths for each state that have already been determined by the past Viterbi algorithm processing are considered, and the other paths are ignored. As a result, the number of states of the Viterbi algorithm can be reduced from M to the L-th power, and the amount of calculation in the Viterbi equalizer can be reduced.

The details of DDFSE are described in, for example, A. Duel and
C.Heegard: "Delayed decision feedback sequence esti
mation ", IEEE Trans.Commun. 37, 5, pp. 428-436 (May 198
9) Or, Okada et al. “D using interpolation-based channel estimation
Frequency selective fading compensation characteristics of DFSE equalizer "
IEICE Transactions Vol.J-73-B-II, No.11, pp.727-7
35 (November 1990).

FIG. 5 is an explanatory diagram showing the operation of the replica generator. The DDFSE unit generates candidate signals for the direct wave and the one-symbol delayed wave, and employs surviving path information as the candidate signal for the two-symbol delayed wave. The array output replica generators 12 and 18 are composed of, for example, transversal filters, and include candidate signals corresponding to a direct wave and a one- or two-symbol delayed wave and their estimated channel impulse responses ((hh0 (k) to h ^). 2 (k)) to generate a replica for each array output.

Next, the operation during the training period will be described. During the training period, the array weight, the impulse response of the transmission path, and the weight coefficient are determined.
First, channel impulse responses of a direct wave and a one- or two-symbol delayed wave are estimated for each branch using received signals from all antennas. Next, the array weight and the channel impulse response of the maximum likelihood sequence estimator are simultaneously controlled and estimated by the constraint-based least squares method, using the impulse response of the direct wave as a constraint vector that determines the response of the direct wave component in the array output. In addition, the same operation is performed similarly for the one-symbol delayed wave. That is, the response of the one-symbol delayed wave is constrained to extract the one-symbol delayed wave. At this time, the array output response is performed not only for the direct wave and the one-symbol delayed wave but also for the two-symbol delayed wave.

Therefore, as shown in FIG. 2, in an array in which the estimated channel impulse response of the direct wave is controlled as a constraint vector, the three-symbol delayed wave and the four-symbol delayed wave are suppressed, and the direct wave and the one-symbol delayed wave component are suppressed. And a two-symbol delayed wave component, and similarly, the array in which the estimated channel impulse response of the one-symbol delayed wave is controlled as a constraint vector suppresses the three-symbol delayed wave and the four-symbol delayed wave,
The one-symbol delayed wave, the direct wave component, and the two-symbol delayed wave component are output. Further, the accumulated error power is calculated from the error signal by using the received signal in the training section again using the obtained array weight and output response, and is normalized (divided) by the cumulative number of symbols at the end of training to obtain the average error power. Ask for. Then, by calculating the power of the channel impulse response vector and dividing by the average error power,
Estimate the quality of the array output signal. This operation is similarly performed for the one-symbol delayed wave extraction array. Using the estimated quality (SINR) of each path diversity branch,
Weight coefficients # 0 and # 1 proportional to the quality of the direct wave extraction array output signal and the one-symbol delayed wave extraction array output signal are obtained.

In the data section, as shown in FIG. 5, an array output replica is generated from a candidate signal composed of a direct wave, a one-symbol delayed wave and a two-symbol delayed wave, and an array output response. At this time, the surviving path in the Viterbi algorithm is used as the candidate signal for the two-symbol delayed wave. Therefore, the number of states of the Viterbi algorithm does not increase. next,
Calculate the error between each array output and each replica. Then, the absolute square of these errors is calculated, weighted using the path diversity combining coefficient calculated in the training section, and branch metric combining is performed.
FIG. 4 is a functional block diagram illustrating the branch metric synthesis processing. After that, the transmission signal sequence is estimated using the Viterbi algorithm.

FIG. 8 is a functional block diagram showing the configuration of the embodiment. Here, the adaptive algorithm is a single constraint LMS
An algorithm or a single constraint SMI algorithm can be used. FIG. 7 is a graph showing an example of the characteristic improvement of the embodiment by computer simulation. The vertical axis represents the bit error rate, and the horizontal axis represents the ratio of received signal power to noise power per bit. The conditions are that the modulation method is 4-phase QPSK and the demodulation method is quasi-synchronous detection. The algorithm calculates the array weight and array output response using the single constraint SMI algorithm during the training period. The average error power is calculated using the last 16 symbols of the training period, and a path diversity combining weight coefficient is obtained and used in the data section.

The DDFSE unit generates a replica consisting of a direct wave component, a one-symbol delayed wave component, and a two-symbol delayed wave component for the array output signal. The taps for replica generation are three taps at symbol intervals. Candidate signals are generated for the direct wave and the one-symbol delayed wave, and the surviving path of the Viterbi algorithm is used for the candidate signal for the two-symbol delayed wave. The number of antennas is four. The condition of the arriving wave is 5 waves, the delay time of each wave is 0,
One symbol, two symbols, three symbols, and four symbols are used, and it is assumed that fading of each incoming wave is independent for each antenna.

Although the embodiments have been disclosed above, the following modified examples are also conceivable. As an embodiment, an example in which a direct wave and a delayed wave are respectively taken in the array processing and the branch metric is synthesized is disclosed. However, in the embodiment of the present invention, the branch metric synthesis processing is not an essential component. It is also effective to provide only an extraction array and perform DDFSE processing using an error as a branch metric.

[0024]

As described above, according to the present invention,
The amount of computation increases because the vector size of the array output response increases, but the incoming wave canceled by DDFSE does not need to be suppressed by the array, so the desired wave component can be captured at a higher SINR ratio. There is an effect that BER characteristics can be improved. Therefore, it greatly contributes to the improvement of transmission quality.

[Brief description of the drawings]

FIG. 1 is a functional block diagram showing a signal processing function of the present invention.

FIG. 2 is an explanatory diagram illustrating an example of received power of a direct wave and a delayed wave.

FIG. 3 is an explanatory diagram showing an operation in an array processing unit.

FIG. 4 is a functional block diagram illustrating a branch metric synthesis process.

FIG. 5 is an explanatory diagram showing an operation of a replica generator.

FIG. 6 is a block diagram illustrating a hardware configuration example of a receiving apparatus according to the present invention.

FIG. 7 is a graph showing a characteristic improvement example of the example.

FIG. 8 is a functional block diagram illustrating a configuration of an embodiment.

FIG. 9 is a functional block diagram showing signal processing content of a conventional example.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Array antenna, 2 ... Linear demodulator, 3 ... A / D converter, 4 ... Signal processing part, 10, 16 ... Adaptive array processing part, 11, 17 ... Adaptive algorithm, 12, 18 ...
Replica generators, 13, 19 ... adders, 14, 20 ... absolute value square calculators, 15, 21 ... multipliers, 22 ... adders,
23 ... DDFSE

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-10-13262 (JP, A) JP-A-9-260941 (JP, A) JP-A-6-29890 (JP, A) JP-A-6-29890 23870 (JP, A) JP-A-4-35546 (JP, A) JP-A-4-45626 (JP, A) Masaaki Fujii, A study on multipath separation / synthesis method by joint processing of adaptive array antenna and MLSE , IEICE Technical Report, VOL. 95, NO. 390 (RCS95 97-111), PAGE1-6 Masaaki Fujii, A Study on Characteristics of Joint Processing Method of Adaptive Array and MLSE in Frequency Selective Fading Channel, IEICE Technical Report, Vol. 96, NO. 212 (RCS96 52-65), PAGE 21-26 (58) Fields investigated (Int. Cl. ⁶ , DB name) H04B 7/00 H04B 7/02-7/12 H04L 1/02-1/06 H01Q 3 / 00-3/46 H01Q 21/00-21/30 H01Q 23/00 H01Q 25/00-25/04

Claims (4)

(57) [Claims] 1. A receiving method combining adaptive array antenna processing and maximum likelihood sequence estimation processing, wherein a steering vector array using a channel impulse response of a desired signal as a constraint vector is generated from a candidate signal and an estimated channel impulse response. When controlling together with the array output replica generator, the delayed wave that is not the desired wave is controlled and taken in as a candidate signal, and the unnecessary delay wave component is canceled by the metric calculation by feeding back the decision data in the maximum likelihood decoder. A receiving method, characterized in that: 2. The method comprises the following steps (1) to (5):
A receiving method in which adaptive array antenna processing and decision feedback type maximum likelihood sequence estimation processing are combined. (1) A step of estimating a channel impulse response of a desired wave with respect to a signal received from an antenna. (2) Simultaneously controlling the array weight and the channel impulse response of the maximum likelihood sequence estimator so that the impulse response of the desired wave is used as a constraint vector for determining the response of the desired wave component in the array output, and a delayed wave that is not a desired wave is also captured. And the step of estimating. (3) calculating the error between the output of the array for extracting the desired signal and the replica from the maximum likelihood sequence estimator for the candidate signal; (4) A step of estimating a transmission signal sequence using a decision feedback type maximum likelihood sequence estimator. (5) A step of simultaneously updating the array weight and the channel impulse response in the maximum likelihood sequence estimator according to the surviving path for each state of the maximum likelihood sequence estimator. 3. It comprises the following steps (1) to (5):
A receiving method in which adaptive array antenna processing and decision feedback type maximum likelihood sequence estimation processing are combined. (1) A step of estimating channel impulse responses of a direct wave and a delayed wave for a signal received from an antenna. (2) The impulse response of the direct wave and the delayed wave is used as a constraint vector for determining the response of the direct wave and the delayed wave component in the array output, and the array weight and the maximum likelihood sequence estimator are used so as to take in the delayed wave which is not a desired wave. Simultaneously controlling and estimating the channel impulse response. (3) calculating the error between the output of the array for direct wave extraction and the array for delay wave extraction and the replica from the maximum likelihood sequence estimator for the candidate signal; (4) A step of performing weighted synthesis on branch metrics that are error information based on the quality information, and estimating a transmission signal sequence using a decision feedback type maximum likelihood sequence estimator. (5) A step of simultaneously updating the array weight and the channel impulse response in the maximum likelihood sequence estimator according to the surviving path for each state of the maximum likelihood sequence estimator. 4. A receiving device comprising a receiving means for executing the receiving method according to claim 1.