ES2332840B2 - METHOD OF ESTIMATION IN BASE BAND OF COMPLEX CHANNELS THROUGH SEQUENTIAL AND SIMULTANEOUS TRANSMISSION OF ORTOGONAL COUPLES OF COMPLEMENTARY SEQUENCES. - Google Patents

Abstract

Channel baseband estimation method complexes by sequential and simultaneous transmission of pairs Orthogonal complementary sequences.

A method of estimation in baseband of complex channels by sequential and simultaneous transmission of orthogonal pairs of complementary sequences. The
Estimating the frequency spectrum of a transmission channel allows obtaining information of high interest to analyze its characteristics and extract important information from it, or correct the distortion effects that it introduces in a communication system. This invention presents a method for encoding an s [n] signal by convolving said signal with a pair of complementary sequences (CSC). These sequences, when received, allow the temporal and frequency characteristics of the medium that they pass through to be extracted by correlation with an accuracy that depends on the length of the sequences used N in the coding with respect to the length of the channel (L).

Description

Channel baseband estimation method complexes by sequential and simultaneous transmission of pairs Orthogonal complementary sequences.

Technical sector

The present invention relates to the method of optimal temporal framework of the training sequences that allow the baseband estimation of the characteristics temporal and frequency of the media in systems of transmission and reception of information on complex channels. Understanding by complex those real channels pass-band whose equivalent Low pass in baseband has real components and imaginary These channels are given in systems with two branches independent that are modulated with orthogonal phases to be transmitted to the medium (commonly represented by the letters I of English "In-phase" and Q of English "Quadrature").

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State of the art

In digital communications systems the transmitted signal is distorted by distortion effects of the medium and the information received is severely affected by Ignorance of such distortion. Much of the innovation in the new Digital Transmission Systems it is based on the search for optimal methods to estimate the distortion introduced by means of communication.

Several methods have been proposed lately for estimation using training sequences, such as [Yeh, CS; Lin, Y; and Wu, Y, "OFDM System Channel Estimation Using Time-Domain Training Sequence for Mobile Reception of Digital Terrestrial Broadcasting" IEEE Trans. On Broadcasting, Vol. 46, No. 3, Sep. 2000. pp 215-220] , or using pilots in the frequency domain, such as [Yeh, CS; Lin, Y. "Channel Estimation using Pilot Tons in OFDM Systems", IEEE Trans. On Broadcasting, Vol. 45, No .: 4, Dec 1999. pp. 400-409].

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According to [Tellambura, C; Guo, Y. J; BArton, SK "Channel Estimation Using Aperiodic Binary Sequences" IEEE Communications Setteres, Volume: 2 No .: 5, May 1998. pp. 140-142] and [Spasojevic, P .; Georghiades, CN "Complementary sequences for ISI channel estimation" IEEE Transactions on Information Theory, Volume: 47 Issue: 3, March 2001. pp 1145-1152.] , The optimal method is the use of Complementary Sequence Sets (CSC). These methods are based on a framework like the one described in Figure 1. These sets of sequences allow maximizing the Signal to Noise ratio of the channel estimate:

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one

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Where is / is not the signal to noise ratio by symbol, L the length of the channel response, K the number of sequences in each set and N the length of each sequence. From this equation is obtained that the improvement in the estimate is proportional to the L / KN factor.

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In the two previous references sets are used that have two components (K = 2), also called Golay sequences [MARCEL JE Golay "Complementary Series". IRE Transactions on Information Theory, April 1961, pp. 82-87.] , But it is possible to work with K> 2 [C.-C. Tseng, CL Liu, "Complementary Sets of Sequences", IEEE Trans. Inform. Theory, Vol. IT-18, No. 5, pp. 644-651, Sept. 1972.] . This patent will work with CSC with K = 2.

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The main property of the CSC is:

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2

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Where r_ {xx} is aperiodic autocorrelation of x. The sum of the autocorrelation of all the sequences of the set is equal to KN for n = 0 and 0 for n \ neq0 (delta of Krönecker multiplied by the KN factor).

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Another interesting property is that there are K sequence sets that are mutually incorrect (also called orthogonal sets):

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3

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This allows K sets to be transmitted simultaneously.

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The generation and detection of Golay sequences can be done efficiently by applying the systems defined in [SZ Budisin. "Efficient Pulse Compressor for Golay Complementary Sequences"; Elec. Lett. Vol 27, No 3, pp. 219-220, 31st Jan., 1991.] and [Popovic, BM "Efficient Golay correlator". Electronics Letters, Volume: 35, Issue: 17, 19 Aug. 1999 Pages: 1427–1428.] . These structures are only valid for K = 2. An optimal algorithm for K? 2 is described in (Jose María Insenser et al . "Method and System for Estimating Multiple Input and Multiple Output Channels" Spanish Patent Application No. P200601942. July 20, 2006.] .

There is a previously patented method that describes how to estimate by complementary transmission of pairs complementary sequences [Vicente Díaz et al . "Device and Method for Optimally Estimating the Transmission Spectrum with the Simultaneous Modulation of Complementary Sequences". WO 2005107200] . This method only allows estimating a real channel. The fabric used in this method can be seen in Figure 2.

Another method that describes how to estimate by sequential transmission of pairs of complementary sequences is [Vicente Díaz et al . "Device and Method for the optimal Estimation of Distorsion of a Transmission Medium, comprising the Sequential Emission of Pairs of Quadrature Complementary Sequences." WO 2005122513] . This method allows estimating complex channels but with temporarily oversized training sequences. The fabric used in this method can be seen in Figure 3.

The method described here allows to improve the estimation of complex channels with an optimal time frame. The systems that can be used to generate in transmission and correlate in reception the pairs of complementary sequences they can be those described above or any other.

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Explanation of the invention.

As explained above the properties The main CSCs are:

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4

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Where r_ {xx} is aperiodic autocorrelation of x. The sum of the autocorrelation of all the sequences of the set is equal to a delta of Krönecker multiplied by the KN factor.

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The interesting property is that there are K sequence sets that are mutually incorrect (also called orthogonal sets):

5

This allows to transmit 2 simultaneously sets using phases I and Q of a complex modulation as can be seen in figure 4.

To facilitate the understanding of the method here proposed based on the framework of figure 4 are particularized the results for N = 4 and K = 2.

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Being {a0, a1} and {b0, b1} complementary pairs mutually orthogonal map to a0 in (1), b0 in (2), to in (3) and b1 in (4) in the framework of figure 4. To particularize Results The following sequences are used as an example:

6

Using the properties seen in <4> and <5>:

7

When K = 2, {a0, b0} and {a1, b1} are also pairs complementary:

8

Another property is:

9

where \ overleftarrow {x} is the inverted sequence x. For the so much:

10

The impulse response of the equivalent step Under the channel is:

eleven

The transmission medium convolves in a way complex the transmitted signal Identifying in the receiver each of the sequences transmitted in the preamble:

12

At the receiver operations are performed correlation to detect response components impulsion of the complex environment. Using the properties CSC <9> and <10>:

13

If the channel inserted noise, paying attention to the properties of the correlation, the Signal to Noise ratio of Estimate will be:

14

Where is / is not the signal to noise ratio by symbol, L the length of the channel response, K the number of sequences in each set and N the length of each sequence. From this equation is obtained that the improvement in the estimate is proportional to the L / KN factor. Profit similar to solutions raised above, but with the advantage that the fabric is optimal for the estimation of complex channels.

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Brief description of the drawings

Figure 1 shows the framework for the sequential transmission of complementary sequences.

Figure 2 shows the framework for the Simultaneous transmission of complementary sequences.

Figure 3 shows the framework for the sequential transmission of orthogonal pairs of sequences complementary.

Figure 4 shows the framework for the sequential and simultaneous transmission of orthogonal pairs of complementary sequences.

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Preferred Embodiment of the Invention

The different parts that make up the fabric for the sequential transmission of complementary sequences that Sample in Figure 1 are detailed below:

one.

Complementary Sequence a0

2.

Complementary Sequence a1

3.

Temporary separations between sequences and data to avoid reception overlaps

Four.

Burst of data.

The pair {a0, a1} being a pair of sequences complementary. Method A is a preamble structure and the Method B is a preamble and epilogue structure.

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The different parts that make up the fabric for the simultaneous transmission of complementary sequences that Sample in Figure 2 are detailed below:

one.

Complementary Sequence a0

2.

Complementary Sequence a1

3.

Temporary separations between sequences and data to avoid reception overlaps

Four.

Data burst

The pair {a0, a1} being a pair of sequences complementary.

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The different parts that make up the fabric for sequence transmission) of orthogonal sequence pairs Complementary shown in Figure 3 are detailed to continuation:

one.

Complementary Sequence a0

2.

Complementary Sequence a1

3.

Complementary Sequence b0

Four.

Complementary Sequence b1

5.

Temporary separations between sequences and data to avoid reception overlaps

6.

Data burst

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Being:

?

The pair {a0, a1} a pair of complementary sequences.

?

The pair {b0, b1} a pair of complementary sequences.

?

The pair {a0, b0} a pair of complementary sequences.

?

The pair {al, b1} a pair of complementary sequences.

?

The pairs {a0, a1} and {b0, b1} orthogonal pairs

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The different parts that make up the fabric for the sequential and simultaneous transmission of orthogonal pairs of Complementary sequences shown in Figure 4 are detailed then:

one.

Complementary Sequence a0

2.

Complementary Sequence b0

3.

Complementary Sequence a1

Four.

Complementary Sequence b1

5.

Temporary separations between sequences and data to avoid reception overlaps

6.

Data burst

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Being:

?

The pair {a0, a1} a pair of complementary sequences.

?

The pair {b0, b1} a pair of complementary sequences.

?

The pair {a0, b0} a pair of complementary sequences.

?

The pair {a1, b1} a pair of complementary sequences.

?

The pairs {a0, a1} and {b0, b1} orthogonal pairs

?

The pairs {a0, b0} and {a1, b1} orthogonal pairs

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The channel baseband estimation method complexes according to the invention is characterized in that it is used an optimal timeframe of training sequences based in sequential and simultaneous transmission of orthogonal pairs of complementary sequences that allow baseband estimation of the temporal and frequency characteristics of the medium of communication in systems of transmission and reception of information over complex channels, understanding those channels as complex real pass-band whose equivalent Low pass in baseband has real components and imaginary

You can use a fabric based on complementary sequences a0, b0, a1 and b1, whose property main is that the sum of autocorrelations grouped in Complementary couples equals a delta of Krönecker multiplied by a gain factor by understanding Delta of Krönecker a discrete time sequence in which only one of his Samples have a non-zero value.

The sequences can be grouped into following complementary pairs: {a0, b0}, {a1, b1}, {a0, a1} and {b0, b1} and where the pairs {a0, b0} and {a1, b1} are mutually orthogonal and the pairs {a0, a1} and {b0, b1} are mutually orthogonal, meaning orthogonal that the sum of the correlation  crossed of these sequences is zero in all samples of the Outcome.

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The pairs of complementary sequences are can transmit sequentially) and simultaneously using the two branches in baseband (I and Q) of the following way:

?

Branch I: sequentially) first a0 and then b0

?

Branch Q: sequentially first a1 and then b1

?

a0 and a1 are transmitted simultaneously by both branches

?

b0 and b1 are transmitted simultaneously by both branches

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Temporary separations may or may not be inserted between the different sequences to avoid temporary overlaps in reception.

The transmission of said fabric can be Repeat periodically.

Alternatively the transmission of said Lattice is done only once.

Between successive network transmissions, They can insert bursts of data.

After an emission of the fabric they can be emitted data indefinitely or until the estimate is invalid due to temporary variations in the impulse response of channel.

Alternatively after a broadcast of the no data is emitted, only the channel is evaluated for Any subsequent application.

You can use any system of generation, modulation, detection, demodulation and / or correlation.

Claims (11)

1. A method of baseband estimation of complex channels, characterized in that an optimal time lattice of training sequences based on sequence transmission) and simultaneous orthogonal pairs of complementary sequences that allow baseband estimation of temporal characteristics are used and frequencies of the communication medium in systems of transmission and reception of information on complex channels, complexes being understood as those real pass-band channels whose base-pass equivalent in baseband has real and imaginary components. 2. The method, according to the first claim, characterized in that a framework based on complementary sequences a0, b0, a1 and b1 is used, whose main property is that the sum of autocorrelations grouped in complementary pairs is equivalent to a Krönecker delta multiplied by a gain factor, understood by Krönecker Delta as a discrete time sequence in which only one of its samples has a nonzero value. 3. The method, according to the first claim and using the sequences described in the second claim, characterized in that the sequences can be grouped into the following complementary pairs: {a0, b0}, {a1, b1}, {a0, a1} and { b0, b1} and where the pairs {a0, b0} and {a1, b1} are mutually orthogonal and the pairs {a0, a1} and {b0, b1} are mutually orthogonal, meaning orthogonal that the sum of the cross correlation of these sequences is zero in all samples of the result. 4. The method according to claims 1, 2 and 3, characterized in that the pairs of complementary sequences are transmitted sequentially and simultaneously using the two baseband branches (I and Q) as follows:

?

Branch I: sequentially first a0 and then b0

?

Branch Q: sequentially first a1 and then b1

?

a0 and a1 are transmitted simultaneously by both branches

?

b0 and b1 are transmitted simultaneously by both branches

5. The method described in the first, second, third and fourth claims characterized in that temporary separations between the different sequences are inserted or not to avoid temporary overlaps in reception. 6. The method described in the first, second, third, fourth and fifth claims characterized in that the transmission of said fabric is repeated periodically. 7. The method described in the first, second, third, fourth and fifth claims characterized in that the transmission of said fabric is performed only once. 8. The method described in the first, second, third, fourth and fifth claims characterized in that between successive transmissions of the network bursts of data are inserted. 9. The method described in the first, second, third, fourth and fifth claims characterized in that after an emission of the fabric data is emitted indefinitely or until the estimate is invalid due to temporary variations of the impulse response of the channel. 10. The method described in the first, second, third, fourth and fifth claims characterized in that after an emission of the fabric no data is emitted, only the channel is evaluated for any subsequent application. 11. The method described in the first, second, third, fourth and fifth claims characterized in that any generation, modulation, detection, demodulation and / or correlation system is used.