SK8898A3 - Digital demodulation and decoding method - Google Patents

Abstract

The receiving device performs N different demodulations (N 2 2) while delivering a set to each demodulation appropriate estimates of subsequent binary symbols one frame. Take some of these symbols with you they carry the redundancy introduced by the coding corrector errors used by the transmission equipment. Receiving device decodes each of the N sets of estimates according to the complementary procedure of this coding corrector errors, decoding each set of estimates includes one degree of error (Qw). Admissions the device separates one of the N sets of estimates, for which is the minimum degree of error measurement.

Description

The invention relates to a method of numerical demodulation and decoding.

It is used in particular in receiving devices carrying out selective reception methods.

BACKGROUND OF THE INVENTION

Selective reception methods are known in the art of numerical transmission. These methods include: spatial, selective reception useful especially in radio transmission if several reception sensors are located at different locations; frequency diversity reception if the same transmitted information is transmitted simultaneously at different frequencies; time sampling if this information is repeated.

These different methods of selective income can also be combined with each other. The advantage of these methods is that they make it possible to reduce the binary error rate in estimates produced by the receiving device. On the other hand, they generally have the disadvantage that they require additional means at the edges of the passing band and / or that the transmission and reception devices are complicated.

In order to combine the multiple estimates obtained by the selection receiver, there are a number of ways among which a selection method can be mentioned, which consists simply of selecting according to the best signal / noise ratio; a method which is called combining equal gain, where it is decided by the sum of the signals after phasing; a method which is called the highest combination ratio, in which the decision is made according to the sum of the squares of the phased signals and divided by the estimated noise value with which the signals are affected. This latter method provides a maximum signal / noise ratio after recombination.

Most numeric transmission systems use a coding / decoding channel that improves their cardinality in faults induced by the transmission channel. The correction encoders introduce redundancy in the transmitted information, which the connected decoders use to correct errors in the received signal. Typically, two large code groups are used: convolutional codes and block codes (Golay, BCH, Reed-Solomon, etc.). The correction properties of these codes are optimal if the error probabilities are decorated with the following symbol, as is the case, for example, with channels with additional Gaussian white noise. Although this condition of decoration is not met, especially in the case of radio channels in Reyleigh or Rice leakage, the coding / decoding channel includes inter alia the linking / unlinking of permutation symbols to be scattered in the input of the repair decoder, with errors occurring in packets in the distribution channel.

In most systems, the channel decoder adjusts the estimates, hard or fine, supplied by the demodulator. In the case of the selection receiver, the receiver processes the estimates obtained by recombining the multiple estimates.

In Channel Coding with Multilevel / Phase Signals (IEEE Trans. On Information Theory, Vol. IT-28, No. 1, January 1982, pp. 55-67), G Ungerboeck introduced the notion of coded modulation that allows collaboration of modulation / demodulation with channel encoding / decoding. At the same time, the receiver demodulates and corrects errors using a grid whose states maintain the number of modulation states and decoding states. This method makes it possible to evaluate the gain because the demodulator draws the gain from the bits protected at the microscopic level by the correction code. The method, as is well known, has had significant success in wire and satellite transmissions, for which the propagation conditions are not at all difficult. However, the disadvantage of this method is that it is not compatible as long as there is a tie because the demodulation grid would thus become unrealistic in size.

It is an object of the present invention to provide a new way to combine multiple estimates of transmitted numeric symbols using the presence of protected symbols between transmitted symbols.

SUMMARY OF THE INVENTION

Thus, the invention provides a numerical demodulation and decoding method in which the receiving apparatus performs N different demodulations, supplying for each of them a set of respective estimates of successive binary frame symbols, some of which contain redundancy introduced by the error coding corrector used by the transmitting apparatus. According to the invention, the receiving apparatus decodes each of the N sets of estimates according to the complementary error correction coding procedure, wherein the decoding of each set of estimates contains a value of one error degree, the receiving device separating one of the N estimation sets for which the degree of error measured.

In this way, the final demodulation result uses the redundancy information provided by the channel coder. It is sufficient that only some of the frame symbols are coded with redundancy so that the whole of the demodulated frame is satisfactory.

This approach can be compared to the Ungerboeck approach, but it considers the framework macroscopic and not microscopically. In contrast to coded demodulations, this is particularly possible by the presence of binding.

The invention is used not only for the recombination of multiple estimates obtained by the sample reception technique, but also for the case where at least two of the N symbol estimation sets are obtained by demodulating the same signal segment received by the sample reception method (or such estimation errors are often correlated) .

In a particular embodiment of the invention, at least two of the N different demodulations are made on the same signal segment corresponding to one frame of the symbol of the numeric signal modulated by the transmitting device, the signal segment being received by the receiving device after transmitting the numeric signal modulated by the transmission channel. demodulation includes the following steps:

- estimating the first demodulation parameters at the first edge of the segment; and

- calculating the first estimates of the frame symbols based on the first estimated demodulation parameters and the signal segments that passed from the first edge to the second edge, and the second of the two demodulations comprises the following steps:

- estimating the second demodulation parameters at the other edge of the segment; and

calculating second estimates of the frame symbols based on the second estimated demodulation parameters and signal segments that passed from the second edge to the first edge.

This method leads to evaluable gains on the binary error value, including by signal capture alone.

Other features and advantages of the invention will become apparent from the following description and non-limiting examples of the invention, and from the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 is a block diagram illustrating a transmitting device and a receiving device made according to the invention; Fig. 2 is a diagram showing the structure of signal frames in an exemplary embodiment of the invention; FIG. 3 and 4 are block diagrams of a demodulation method performed by a receiving device in two directions of demodulation; Fig. 5 is a graph showing examples of probabilities obtained in each direction of demodulation; Fig. 6 to 11 are graphs showing the characteristics of a receiving device according to the invention; and FIG. 12 is another example of an embodiment of a receiving device according to the invention.

DETAILED DESCRIPTION OF THE INVENTION

The invention is further described in its use in numerical radiocommunications between a transmitting device 10 and a receiving device 20. The transmitting device 10 comprises a code source 12 (audio digitizer in the case of a telephone system) that transmits a numeric data stream x _k organized in the following frames. In the embodiment shown in FIG. 2, the signal x _{k is} organized in 126 bit frames at a rate of 1 / T = 8 k bit / s.

The channel coder 14 processes the bits transmitted by the code source to improve transmission fault tolerance. In the example of FIG. The 2-channel coder 14 utilizes a convolutional code CC (2, 1, 3) with an efficiency of 1/2 in the first 26 bits of the frame x _k .

The resulting 52 + 100 = 152 bits e _k is then subjected to a binding designed to cancel a burst of errors that may introduce a Rayleigh escape event. A sync word of 8 bits is inserted for each frame with 152 bits of information coupled to produce a signal c _k , which the encoder 14 sends to the modulator 16. The modulator 16 generates a radio signal s (t) that is amplified, then transmitted to the antenna 18 of the transmission device. 10. In the considered embodiment, the symbols c _{k are} binary (c _k = 0 or 1).

The modulation used is, for example, GMSK modulation with BT = 0.25 (see K. MUROTA et al .: GMSK Modulation for Digital Mobile Radio Telephony, IEEE Trans on Communications, Volume COM-29, No. 7, July 1981, pages 1044). -1050).

The receiving device 20 comprises a demodulator 24 receiving the signal received by the antenna 22 and amplified. The demodulator 24 issues two sets of estimates of transmitted symbols c _k . These estimates are labeled in the case of fine decisions and

6 ^, 6? ^ In case of rough decisions. If the symbols c _k are from the region M and are between 0 and Ml, the choice of possible representation for fine estimation is in the form:

gi = ^. exp ^ 27 ^ (A /), gf = pf.exp (27Wf / A /), that is, in this case his argument 2jnctf, IM or 2jnd ^R ! M is the most likely value f of c _k , whereas its modulus or p ^R is a measure of the probability of this value d ^A or d ^R. In the case of binary symbols (M = 2), the number or gf is a real and named softbit and its designation 2d ^ -1 or 2d ^R -1 gives the most probable value of the symbol labeled 2c _k -l.

The receiving device 20 comprises a channel decoder 26 double to the channel decoder 14 of the transmitter. In an example of a preferred embodiment, the channel decoder 26 executes the frame after permutation bits inverse to the permutation corresponding to the binding used by the transmitter and decodes 52 redundant bits using a Viterbi lattice corresponding to the convolution code used. In the exemplary embodiment, step 26 includes two different decoders, one of 26 ^A working on the first estimates g alebo or d% supplied by the demodulator 24. the other 26 ^R works on the second estimates g f or d ^R. Each decoder 26 ^, ^R 26 returns a corresponding estimated bit X _k. As usual in numerical transmissions,

Viterbi decoding performed by decoder 26 ²⁴ or 26 ^Λ can be in rough decisions if the demodulator 24 delivers only d alebo or d ^R , or in fine decisions where the demodulator 24 delivers g alebo or gf.

As shown in FIG. 1, the demodulator 24 includes a radio stage 30 to convert the received signal into a baseband. By means of two mixers 32, 34, a radio signal is received into two radio waves, in a carrier frequency quadrature transmitted by the local oscillator 36, and the resulting signals pass through the lower band filters 38, 40 to obtain one component in phase and one component in the quadrature. The two components are sampled and quantified by analogue-numeric converters 42, 44 with a frequency at least equal to the frequency of the transmitted bits. R _n complex samples of the numeric baseband signal transmitted by converters 42, 44 are recorded.

In the embodiment shown in FIG. 1, the demodulator 24 operates according to a sequential algorithm for demodulating binary symbols. In the case of GMSK modulation, sequential demodulation can be performed using the following approximation for a base-modulated signal with (t):

(4)

5 (/) = Σ j ^k , and _k .h (t - kT) k = -eo

This expression corresponds to an approximation in the first order of degradation proposed

P. A. Laurent in his paper Accurate and approximate construction of digital phase modulation in superposition of amplitude modulated pulses (AMP), IEEE

Trans. on Communications, Vol. COM-34, no. 2, 2 February 1986, p

150-160. This article also explains how to calculate the function h (t), which in the case of GMSK modulation with BT = 0.25 corresponds to a pulse of 2T, centered on t = 0. In expression (4), the binary symbols a _k values ± 1 correspond to bits c _k differently coded: a _k = a _k -i, (2c _k -1).

The radio channel is affected by outages that correspond to the sum of opposite phase signals coming from multiple paths, which are caused by different reflections of the transmitted signal at near or distant obstacles. The time scattering of these paths is usually in the range of 12μ5, a short time before the time of one bit (Τ = 125μ5 in the considered numerical example). The propagation channel is represented by the variable complex A (t) corresponding to the Rayleigh escape and uniform path phasing. The frequency of failure is 2f _d , where f _d is the Doppler frequency associated with the variation of the distance between the transmitter and the receiver: f _d = f ₀ .v / c, when f ₀ is the center frequency of the channel, is the relative speed of the transmitter and receiver ac is the speed of light . Thus, for a speed of 100 km / h, the Doppler frequency was found to be 41.67 Hz when f ₀ = 450 MHz, from where the failure (83.33 Hz) is a full 12 ms. This therefore allows for a larger frame outage and in particular a higher outage frequency than the synchronization word frequency (50 Hz).

The presence of these rapid outages and, in general, a rapid channel change before the frame time, necessitates frequent channel estimation and thus a serious risk of spreading errors caused by the feedback of the decisions. In fact, if errors occur on the decided binary symbols when demodulating, these errors lead to erroneous channel estimates, which themselves lead to new demodulation errors.

A _k = A ( _k T) (k = 0 to 167), complex channel values propagated sampled at 8 kHz in baseband are recorded. The channel is inter alia affected by Gaussian additional white noise B (t) with a NO / 2 variation labeled B _k after sampling and adjusted filtration. The received signal after the signal has been filtered by the response filter h (t) 46 is thus in the form:

R _a = A (kT) Σ j ⁿ "H (NK) T) + B (kT) = n - <c = _Α Ιι Ι / ^ι '-'αΙι., Η (-Τι,) + / αΙιΗ (Ο) +) ^Μ αΜΗ (+ Γ)] + Β _Ιι where H (t) is a known function of autocorrelation of function h (t). In this expression, an approximation is made of neglecting H (t) for | / | > 2T, which simplifies calculations.

Samples of the output r _{k of the} conditioned filter 46 are stored in memory 48 for processing by the controller 50 of the demodulator 24.

Controller 50 processes the filtered signal r _k using segments, where each segment corresponds to one frame with 168 binary symbols transmitted and _k (0 <£ 168). As shown in FIG. 2, the appropriate framework for different coding includes bits c _k, with 152 bits of information one frame framed 8 bits preceding the synchronization word and the next 8 bits sync word.

Controller 50 performs demodulation according to a sequential algorithm, the first phase of which is shown in the block diagram of FIG. 3. In this first phase, the complex channel response estimate begins at the beginning of the segment, then the segment is demodulated from beginning to end by inserting in the frame at each time bit the complex channel response estimate.

Initializing 60 this first phase bits B ^and A respectively are captured well with the known binary symbols and a _0, and the index is initialized to 2. In step 62, the index compared to the 8, it is the length of the synchronization word. If k <8, bit b ^ is taken as well as the known bit a _{k of the} sync word at step 64, then proceed to step 66, instantly estimating the propagation channel, and performing a complex division:

y ^A - ľtJ_ ^A-1 j ^k ~ ² b ^A k_ ₂ H (-T) + j ^k - ^} ^ Η (0Μ * 1 $ Η (+ Τ) ^1}

Filtration allows instantaneous estimates to smooth out the effects of Gaussian noise to give and estimate of _the _ _t, used for demodulating the bits. In the example illustrated in FIG. 3, this filtration is simply performed by calculating the arithmetic mean of the six most recent instantaneous estimates F *. Other types of filtration can also be used. After step 66, the index k is compared to 167 (frame length) in step 68. If k is < 167, the index k is increased by the unit increment in step 70 before returning to step 62.

The channel estimation at the beginning of the frame is complete when k = 8 in the test 62. Thus, an estimate obtained by knowing the sync word is prepared. For each k> 8, the softbit is estimated in step 72 according to:

(6) a the estimation of b _k bit a _k is obtained by designating the software S ^. In step 72, controller 50 also passes through different decoding the estimate of _the bit c of _the formula g = p _{_}} .s _{of a} soft estimates for (S ^ = Re ^ ry, J ~ ⁷ ^ \ for k = 8), and by of formula = (1 + b _k = _l . b _k 'j / 2 for hard estimates.

Once this bit b 'is obtained, controller 50 again estimates the channel at step 66 as previously exposed. Forward demodulation is complete when k = 167 during test 68 duration.

In FIG. 3, it can be seen that the caused error at bit b ^ in step 72, for example due to a channel failure or inciting noise, causes distortion in the instantaneous estimates V _k -i> Vk ^and t t + i performed in the next three steps 66 and thus leads to errors channel estimates that propagate during a certain period of smoothing filter activity. These errors in ^ 1 may cause further bit estimation errors on their path.

Fig. 5 illustrates a case where the received signal has an energy evolving according to the curve E drawn by the dashed line (with a signal drop appearing at the moment k ₀ ) whose probability | The estimate (dashed line) is good before the failure, but then takes some time to recover the values in proportion to the energy E of the received signal.

To improve performance in the period following the outage, controller 50 performs further demodulation of the signal segment corresponding to the 168 bit frame from the end of the segment to its start. This makes it possible to obtain a probability as expressed by the solid line in FIG. 5. It may be noted that demodulator performance is improved when softbit is preferred to outage and softbit is out of failure.

The back demodulation is performed in a second phase, similar to the first, whose block diagram is shown in FIG. 4th

In this second phase, the complex channel response estimate is started at the end of the segment, then the segment is demodulated from its end to its beginning by placing a grid on each time bit of the complex channel response estimate.

At the build-up 160 of this second phase, the respective bits Z f f ₆₇ and δ f _{66 are taken} equal to the known binary symbols a _{7 a} and ₆ and the index k is set to 165. In step 162 the index k is compared to 159. When k> 159, bit is taken to be equal to the known bit and _k- 16 of the sync word in step 164. then, in step 166, the instantaneous estimation of V% ₊₁ of the propagation channel is continued and makes a complex distribution:

T / R _ikl_ zn \ ^{A + 1} / + 2z, « ₊₂ // ( ₊ 7) ₊ / ₊ l _Ŕ « ₊₁ // (0) + / ó «// (- r) ^{v 7}

Filtering the instantaneous estimates V * allows to smooth out the effect of the Gaussian noise to obtain an estimation of A _{k + 1} used for bit demodulation. In the example illustrated in FIG. 4, this filtration is made simply by calculating the arithmetic mean of the six most recent instantaneous estimates P * ·. After step 166, the index k is compared to 0 at step 168. If k is> 0, the index to k at step 170 is reduced by one unit before returning to step 162.

The channel estimation at the end of the frame is complete when k-159 in test 162. Thus, an estimate of <4f ₆₁ obtained by knowing the sync word occurs. For each value k <159, the softbit s _{k is} estimated in step 172 according to the relation:

s ^R k = Re [r _k A ^R k + 2 ^ j- ¹ '} (8) and the estimate of b _k bit a _k is obtained by marking the softbit with _k . In step 172, the controller also undergoes different decoding for estimating the bits C _{k +} 1 according to the formula g _{+1 +1} = s _{k + i} .s _k in the case of fine estimates (where _{60 60} = 10o f f i 7 ¹⁶⁰ ) for k = 159), and according to the formula d _{k +}} = ^ 1 + Z) f ₊₁ -b _k ^ / 2 for hard estimates.

Once this bit b ^R is obtained, controller 50 again estimates the channel in step 166 as being pre-exposed. Reverse demodulation is complete when k = 0 at test time 168.

In the above example, the re-evaluated demodulation parameters as the demodulated segment traverses in each direction to the complex response A _to the propagation channel is constrained. It will be appreciated that other parameters could be included, such as those representing noise observed on the transmission channels. It is also possible to calculate, for each direction of the center of the square demodulation of deviation ^A in the ^-Α α ^., (Step 66) or W ^ _{i +} N _{k + l} (step 166), the estimate of the instantaneous noise ^ N0, N0 _of the in any direction of demodulation. It is also possible to normalize the softbit value or s% when dividing this quadratic center. Estimates of the value of N0 ^, N0 ^R may be constant to the proposed framework; these are, for example, the midpoints of the whole frame. If these centers are obtained by sliding windows or by filtration, the estimates of the noise value may be constant, that is dependent on the index k.

Although two different channel decoders 26 ^, 26 ^ have been introduced to facilitate reading of FIG. 1, it will be clear that it is equally possible to envisage a single decoder sufficiently ensuring both decoding. The first decoding gives the opportunity the estimated bits y _k and the second decoding the estimated bits y _k . Each channel decoder provides, among other things, a measure of the Q ^A , Q ^R degree of error observed when decoding a received estimation frame.

For example, in a case where a channel decoder uses a Viterbi lattice for a convolutional code (see The Viterbi Algorithm) from GD Forney, proc. IEEE, Volume 61, no. 3, March 1973, p. 268-278), Q ^A or (Q ^R ) may be:

the number of symbols whose Mth value was corrected during decoding;

- the largest metric downward function that can select a path in a lattice when decoding;

- or another measure, which may depend on the algorithm of the respective decoding performed, on the quality of the signal received by the decoder.

By comparing the error rate measures Q ^A and Q ^R , the receiving device selects one or the other of two sets of estimates g ^ and gf (or d ^. Ad ^R ), namely the one for which the error rate is the least as schematically indicated Fig. 1, by a counter 96 and a switch 98, which again maintain the respective decoded bits y ^A or y ^R according to the relative values Q ^A and Q ^R. The maintained bits yk are supplied to the source decoder 28, which converts them into the form of transmitted information.

Thus, the receiving device selects one of the two directions of demodulation that appears to be better in terms of the decoding channel.

It should be noted that it is not necessary for the coding channel to contain redundancy bits for each of the transmitted bits. As in the previous case referring to FIG. 2, where only 26 bits of 126 are coded with redundancy, these 26 bits are sufficient to translate the decision to the quality of the demodulated estimates. In other words, the 152 bits of the frame use the redundancy information contained in the 52 bits transmitted by the convolutional encoder.

As is common in numerical transmissions, the appropriate form of redundancy coding, permutation used to tie and shape the modulating wines must form an object of common optimization to obtain the best results in each particular case. This optimization can be performed in a known manner by computer simulation of channel behavior.

Fig. 6 and 8 show the values obtained by the demodulation method of FIG.

These results were obtained by simulating the numeric signal frames shown in FIG. 2, modulated in GMSK with BT = 0.25. The demodulator is away from the domodulator shown in FIG. 1 differed in that the demodulation was not sequential, but according to a Viterbi lattice having 8 states and 8 matched filters, followed by a wave vector. This lattice corresponds to L = 3 symbols, Rimoldi GMSK signal distribution (see B. E. RIMOLDI CPM Breakdown Procedure, IEEE Trans. On Information Theory, Vol. 34, no.

2, March 1988, pp. 260-270). The grid thus produces hard estimates corresponding to the Ck bits, without differential decoding. Binding of the bits ek (k = 0, ..., 151) performed by the coding channel 14 to fill the bits Ck was performed according to ek - c% + T _and b (k), where [Tab (Q), Tab (T), Tab {\ 51)] = [56, 0, 1, 12, 8, 55, 16, 104, 136, 24, 120, 88, 32, 72, 96, 40, 128, 108, 48, 80, 60, 4, 144, 116, 12, 68, 132, 20, 124, 84, 28, 76, 140, 36, 148, 92, 44, 100, 52, 2, 106, 58, 10, 66, 114, 18, 122 130, 26, 74, 138, 34, 82, 90, 42, 146, 110, 50, 98

62, 6, 70, 118, 14, 126, 134, 22, 78, 86, 30, 142, 94, 38, 150, 54, 46, 102, 57, 1, 113, 9, 65, 17, 105, 129, 25, 121, 137, 33, 73, 89, 41, 81, 109, 49, 145, 61, 5, 97, 117, 13, 69, 133, 21, 125, 85, 29, 77, 141 37, 149, 93, 45, 101, 53, 3, 67, 107, 11, 123, 59, 19, 75, 115, 27, 83, 131, 35, 147, 139, 43, 99, 91, 51 71, 111, 7, 127, 63, 15, 79, 119, 23, 143, 135, 31,151, 87, 39, 103, 95, 47, 64],

The decoding channels 26 and 26 ^Λ ^ performs the inverse permutation to cancel converting, it decodes the 52 bits obtained by the first grating in the Viterbi hard decisions corresponding to the convolutional codes used.

The graph of FIG. 6 shows the binary error value obtained as a function of the signal / noise ratio Eb / NO when the transmitting device and the receiver are static. The graph of FIG. 7 shows a dynamic leak with a relative speed of 70 km / h. The solid line represents the value of the observed binary error with demodulation in one direction, the dotted curve shows the results obtained according to the invention with the demodulation in the back and forth direction and the selection of the direction according to FIG. 1, and finally the dashed curve represents the theoretical results of an ideal demodulator (i.e. one that has perfect channel knowledge and stability). Fig. 8 shows the degree of binary error observed on the same frequency channels. The x-axis indicates the quantity C / Ic, which is the ratio of the power obtained by the receiving device from the transmitting device to the interfering device. In these three cases, a slight improvement in the binary error value is observed.

Fig. Figures 9 to 11 are similar graphs; 6 to 8, which show the results obtained under simulation of similar conditions, differing only by the type of modulation used. It was a quaternary modulation (divisible by four) (M = 4). The Ck bits transmitted by the encoding channel were rearranged in pairs to form quaternary symbols (divisible by four) processed by the modulator. The hard estimates of the symbols transmitted by the demodulator in the forward and backward directions were then broken down into two hard estimates corresponding to the Ck bits. Considered quaternary. modulation was phase modulation (CPM) continuing with the demolding grid parameter according to Rimoldi decomposition. The modulation indicator was h = 1/3, with the demodulator utilizing a grid with 48 states and 64 modified filters.

In FIG. 12 shows another example of a receiving device capable of continuing according to the invention. This device 120 performs a diversity reception challenge, which in this contemplated example is a spatial diversity reception, the device comprising n antennas 22, 22 _n, and n interconnected demodulators.

24, ..... 24 _n . Each demodulator 24 operates in one direction on a respective segment of the signal supplied by its antenna 22, (for example, as described with reference to FIG. 3) and delivers respective fine estimates and / or respective hard estimates (those for each 4 ° Ck symbol). Thus, the device 120 has N = n estimates per symbol originating from different signal segments instead of N = 2 estimates obtained from the same signal segment in the embodiment of Figures 1 to 11.

These n sets of estimates are encoded in accordance with the boundary provided by the coding channel, concurrently with the n channel decoders 26, ... 26 _n (or even more preferably by one decoder). The device 120 thus obtained n sets of decoded symbols and associated error values Q1,

The comparator 196 determines a set of estimates or g \ for which the value of the measured error is minimal, and after decoding, the set is finally taken back by the separator module 198 for delivery to the decoder source 28.

Of course, the invention may also be applied to other selective reception methods or receivers that combine selective reception with multiple demodulation methods as described above.

Claims (10)

A method of numerical demodulation and decoding, in which the receiving device (20; 120) performs N different demodulations (N> 2), supplying each demodulation with a set of respective estimates of the successive binary symbols (Ck) of the frame, some of these symbols containing redundancy introduced by the coding an error corrector used by the transmitting apparatus (10), characterized in that the receiving apparatus (20; 120) decodes each of the N sets of estimates according to the complementary error correction coding procedure, wherein the decoding of each set of estimates includes a one-degree error rate; the device separates one of the N sets of estimates for which the degree of error measurement is minimal. Numeric demodulation and decoding method according to claim 1, characterized in that the degree of error measured (Q ®) at the time of decoding is the number of symbols adjusted during decoding. The numerical demodulation and decoding method of claim 1 or 2, wherein the frame symbols are interconnected, wherein the receiving device (20; 120) performs untied before decoding each of the N sets of estimates. Numeric demodulation and decoding method according to claim 1, 2 or 3, characterized in that at least two of the N different demodulations are performed on the same signal segment corresponding to one symbol frame of the numerical signal modulated by the transmitting device (10), wherein the signal segment ( r (t)) is received by the receiving device (20) after transmission of the modulated numeric signal (s (t)) via the transmission channel and further characterized in that the first of the two demodulations comprises the following steps: estimating the first demodulation parameters at the first edge of the segment ; and calculating the first estimates of the frame symbols I based on the first estimated demodulation parameters and the signal segment that has passed from the first edge to the second edge and wherein the second of the two demodulations comprises the following stages; an estimate of the second demodulation parameters (Α%) at the other edge of the segment; and calculating second estimates (gf) of the frame symbols based on the second estimated demodulation parameters and signal segments passed from the second edge to the first edge. The numerical demodulation and decoding method of claim 4, wherein the first demodulation parameters are re-estimated at least once in a segment pass time from the first edge and the second demodulation parameters are re-estimated at least once during a segment pass from the second edge. I Numeric demodulation and decoding method according to claim 4 or 5, characterized in that the first and second demodulation parameters each comprise at least one parameter (α, Α, predstav) representing the transmission channel response. Numeric demodulation and decoding method according to claim 6, characterized in that the receiving device (20) estimates the parameters representing the transmission channel response at the edges of the segment based on the synchronization sequences embedded in the edges of the numeric signal frames. Numerical demodulation and decoding method according to any one of claims 4 to 7, characterized in that the first and second demodulation parameters each comprise at least one noise-dependent parameter observed on the transmission channel. The numerical demodulation and decoding method of claim 8, wherein the first demodulation parameters include a noise value whose estimate (NO ^) is used to normalize the first estimates of the frame symbols, and wherein the second demodulation parameters include a noise value whose estimate (yVOf ^ is used to normalize second estimates of frame symbols. Numerical demodulation and decoding method according to any one of claims 1 to 9, characterized in that at least two of the N different demodulations are performed on two respective signal segments received by the receiver (120) according to the multicast technique.