Title of Invention

" METHOD OF REDUCING THE VARIENCE OF THE SIGNAL-TO-NOISE RATE ESTIMATED FOR A SIGNAL WITH AMPLITUDE DIFFERENTIAL PHASE-SHIFT KEYING MODULATION

Abstract ABSTRACT METHOD OF REDUCING THE VARIANCE OF THE SIGNAL-TO-NOISE RATE ESTIMATED FOR A SIGNAL WITH AMPLITUDE DIFFERENTIAL PHASE- SHIFT KEYING MODULATION. This method reduces the variance of the estimation of the signal-to-noise rate in a multiuser digital communications system. These communications require a sending of a phase reference symbol prior to sending a information, where the estimation is made of the signal-to- noise rate in order to use a modulation with a maximum number of bits per symbol, maintaining a bit error probability in reception within certain given margins. The method minimizes and equalizes the variance of the samples obtained for the different values, even and odd of bits per carrier, which the system uses. The estimation is necessary for selecting the number of bits per carrier in order to be adapted to the channel and as back-up information in the event of using a receiver with diversity.
Full Text

OBJECT OF THE INVENTION
As stated in the title of this specification, the
present invention refers to a procedure for reduction of
the variance of the estimation of the signal to noise ratio
of a signal with phase differential amplitude coherent
modulation.
The procedure of the invention is applicable to
communications systems independently of the physical medium
used for the communication.
This procedure permits the variance of the estimations
to be reduced and to equalize that variance among the
optimum constellations of odd and even bits per symbol. In
this way, the system can be adapted to the maximum data
transfer rate offered by the channel.
BACKGROUND TO THE INVENTION
In telecommunications systems for sending information
via a communications channel, the information needs to be
modulated; in other words, it needs to be adapted and
matched to the channel.
Some of the main problems which a receiver of digital
communications encounters are equalization, which entails
an estimation of the channel, and frequency deviation of
the receiver clock with respect to the transmitter. When
QAM (square amplitude modulation) coherent modulations are
used, where the point of the constellation is determined by
the amplitude and phase of the signal sent, the demodulator
has to be made much more complex in order to tackle the
problems stated above. One solution consists of using
differential modulations or DAPSK (amplitude and phase differential modulation) where the information is coded in
the amplitude and phase increments. This differential
coding eliminates the need for estimation of the channel in
reception and to a large degree minimizes the effects of
frequency deviation between the clocks. But this reduction

in the complexity of the receiver when using a totally
differential modulation is associated with an increase in
the bit error probability for the same SNR (signal to noise
ratio) value compared to the performance of QAM
modulations. ADPSK modulation (phase differential amplitude
coherent modulation) is known in the state of the art as it
appears in "Comparison and optimization of differentially
encoded transmission on fading channels", L. Lampe and R.
Fischer, Proceedings ISPLC'99; "Performance evaluation of
non-coherent transmission over power lines", L. Lampe, R.
Fischer and R. Schober, Proceedings ISPLC'OO; "Differential
encoding strategies for transmission over fading channels",
R. Fischer, L. Lampe and S. Calabro, International Journal
on Electronics and Communications; as a mixed modulation
between the above two and which represents the intermediate
point in terms of performance and complexity of receiver
between them both. In other words, it minimizes the problem
implied by frequency deviation between the clocks of the
transmitter and receiver in a digital communications system
and decreases the complexity of estimation of the channel
since it is only necessary to estimate the channel in
amplitude. So, ADPSK modulation represents the best
compromise between performance and complexity of the
receiver for a practical implementation.
Moreover, in order to obtain at all times the maximum
data transfer rate, the bits per carrier of the modulation
need to be adapted to the capacity offered by the channel.
In other words, given a target bit error probability, the
aim is to use the maximum number of bits per carrier that
ensure an error probability equal to or less than that
value. Also, in a point to multipoint or multipoint to
multipoint multiuser communication, a transmitter can send
information to several receivers with different channels
between that transmitter and each of the receivers in a
single data frame. Therefore, different constellations will
be used in the same frame. So, it is necessary to estimate
the signal to noise ratio (SNR) perceived by the receiver

in order to choose the number of bits per carrier to use.
Another important factor for achieving that maximum
data transfer rate is to minimize the overhead (control
information on the system necessary for a correct reception
of the data and which is sent along with it). This overhead
is more important if transmission strategies are used based
on the use of multiple carriers such as OFDM (orthogonal
frequency division multiplexing) where the symbol times are
much greater and contain a lot more information than in a
digital communication in which a single information carrier
frequency is used.
ADPSK modulation has two important requirements. The
first is that, owing to the fact that part of the
information is coded in the phase increments, a symbol
previously needs to be sent constituting a phase reference
for the receiver. Also, the rest of the information is
coded in the value of the amplitude of the received symbol.
So, the second requirement implies estimating the value of
the amplitude of the response from the channel in order to
correct its effect in the receiver. Moreover, real channels
display a certain variation in their characteristics with
time, which compels the receiver to conduct a monitoring
and updating of that initial estimation. In addition, this
time variation also requires a continual updating of the
estimation of the SNR.
The articles cited above describe the functioning of
the ADPSK modulator and demodulator and its performance,
without considering the possibility of employing different
constellations within a single data frame. This
possibility is. considered and resolved in the Spanish
patent application P-200301120 (unpublished), referring to
a "Procedure for phase differential amplitude coherent
modulation standardized for multiuser communication", which
permits the sending of a single phase reference at the
beginning of the frame and facilitates a practical
implementation of the low-complexity modulator.
Moreover, this procedure permits the insertion of data

symbols in the frame in such a way that users to which the
data from the transmitter is not directed, and who do not
know the constellation with which it is modulated, can
monitor the channel and follow its variations in both
amplitude and SNR.
Therefore, in order to optimize the data transfer in a
multiuser communication, it is necessary to make an
estimation of the SNR perceived by the receiver. This
estimation can only be made when the constellation in which
the received data is modulated is known by the receiver.
Also, the period during which the SNR is estimated can
include symbols modulated with different constellations.
Thus, the problem to. solve consists of estimating' the
SNR in the receiver of a signal with ADPSK modulation
during a period comprising reception of a certain number of
data symbols with the possibility that they are modulated
using different constellations. In the article "A
comparison of SNR estimation techniques for the AWGN
channel", D. Pauluzzi and N. Beaulieu, IEEE Transactions on
Communication, vol. 48, N° 10, October 2000, various
techniques are presented for estimating the SNR of a signal
with coherent phase modulation (PSK). Also, it is stated
how to extend those techniques to a QAM modulation. In both
cases, no account is taken of the fact that the
constellation can change during the estimation time.
The average power of the transmitted signal can be
known if the constellation is normalized in power and the
effect of the channel in reception is equalized. Then, in
order to estimate the SNR in the receiver, it is merely
necessary to estimate the noise power in the received
constellation. This estimation of the noise power is easily
done by means of averaging the samples
of the noise power. So, the problem consists of calculating
those samples in the receiver. But another added problem is
the differential character of the phase in ADPSK
modulation; in this case the constellation received is the
constellation formed by the amplitudes and the phase

increments that are received. If the value of the samples
of the noise power is obtained by means of calculating the
modulus squared of the noise vector given by the error in
amplitude and by the error in phase increment, without any
modification, it is observed that the estimation presents a
greater variance in the constellations of odd bits per
symbol. This effect is not admissible because the period
during which the SNR is estimated can include symbols
modulated with different constellations in an optimum
multiuser communications system. This communications system
also includes transmissions aimed at multiple users
(multicast) or at all of them (broadcast) , as well as
transmission to a single user (unicast).
The procedure of the proposed invention presents a
method of estimating the SNR of a signal with ADPSK
modulation which equalizes the variances of the estimation
in constellations with even and odd bits per symbol,
furthermore. reducing the variance of that estimation for
all cases.
DESCRIPTION OF THE INVENTION
In order to achieve the objectives and avoid the
drawbacks stated in the above sections, the invention
consists of a procedure for reduction of the variance of
the estimation of the signal to noise ratio of a signal
with phase differential amplitude coherent modulation.
Said procedure is applicable to two-way communication of
multiple sets of user equipment in which a modulation is
used that is differential in phase and coherent in
amplitude, which requires the sending of a phase reference
symbol prior to sending the information, and where an
estimation is made of the signal to noise ratio with the
aim of using a modulation with the maximum number of bits
per symbol, maintaining the bit error probability in
reception within certain given margins. The procedure of
the invention is characterized in that, starting from the
amplitude error and the error in the phase increment
corresponding to the received point of the constellation, a

translation is performed of those errors to the
corresponding point of the first ring of the constellation
as if this had been the one that was transmitted and
without those errors undergoing any modification, and later
on the modulus squared of the error vector is calculated.
This characteristic permits samples of noise to be
calculated, the variance of the values obtained to be
reduced and that variance to be equalized among the optimum
constellations of odd and even bits per symbol.
Moreover, an average can be taken of the modulus
squared of the noise samples in order to estimate the
average value of the noise power, the number of samples to
average being a configurable value of the system.
In reception, first of all the amplitude and the phase
increment are detected, and then those values are
subtracted from the received amplitude or phase increment,
or vice versa, in other words, the detected amplitude and
phase increment are respectively subtracted from the
received amplitude and phase increment; thus, an initial
form of calculating the noise samples is done in blind
mode, without knowing the symbol transmitted in the
calculation of the amplitude and phase increment errors.
Another way of obtaining the modulus squared of the-
noise vector consists of respectively subtracting the
received amplitude and phase increment from the amplitude
and phase increment of the transmitted symbols previously
known in reception, or vice versa, in other words, the
amplitude and phase increment of the transmitted previously
symbols known in reception are respectively subtracted from
the received amplitude and phase increment; thus, the
samples of noise are calculated using a sequence of symbols
previously known in reception for the calculation of the
amplitude and phase increment errors.
In order to improve the final estimation, the
invention provides for combining the above estimations, in
such a way that the receiver equipment which estimates the
signal to noise ratio combines blind estimations with

estimations with a known sequence of symbols.
Also, as this is a multiuser communications system,
the samples of the noise power to average can belong to
different constellations. So, in order to correct the bias
of the estimator due to the differential character of the
modulation and of different value in each constellation,
each of the samples of the noise power being averaged is
multiplied by the corresponding value.
Below, in order to facilitate a better understanding
of this specification and forming an integral part thereof,
some figures are included in which the object of the
invention has been represented in a manner that is
illustrative rather than limiting.
BRIEF DESCRIPTION OF THE FIGURES
Figure 1.- Represents a constellation formed by the
amplitudes and phase increments of an ADPSK constellation
of 6 bits per symbol.
Figure 2.- Schematically represents the magnitudes
involved in calculating a sample of noise power.
Figure 3.- Schematically represents the magnitudes
involved in calculating a sample of noise power and its
translation to the first ring.
Figure 4.- Represents an example of a block diagram of
a receiver implementing the procedure of the invention.
DESCRIPTION OF AN EMBODIMENT OF THE INVENTION
Given below is a description of an example of the
invention, making reference to the numbering adopted in the
figures.
As has been mentioned in the section on the background
to the invention, the basic operations which an ADPSK
receiver has to perform are compensating for the effect of
attenuation of the channel in amplitude and calculating the
phase increment in the received signal. After that, the
detector is what is responsible for obtaining the
transmitted information. All these operations are known in
the state of the art and appear in the references cited
earlier.

Figure 1 shows an example in which the constellation
is formed from the equalized amplitude and the phase
increment of the received signal for a constellation of 6
bits per symbol with an SNR of 27.9 decibels (dB) and a
frequency error of 5 parts per million (ppm). The
continuous radial lines represent the optimum thresholds of
decision for the phase increments. It is also observed that
the received points are grouped into clouds of points with
an elliptical shape, which becomes more pronounced when the
amplitude of the rings is greater, due to the differential
nature of the modulation. These clouds of points are
centred on each of the points of the constellation and are
due to the noise which is added to the signal. But, as can
be seen, the clouds of points are not centred between the
optimum thresholds but are instead displaced by a certain
number of radians. This fixed displacement is determined by
the frequency error in the receiver.
Given that the power of the transmitted signal is
known, the SNR estimator only has to estimate the noise
power which the receiver suffers. For this, an average is
taken of N samples of noise power in different symbols:

Where \e(k) \2 is the kth sample of the noise power
affecting the receiver. Figure 2 shows a schematic
presentation of the magnitudes involved in calculating the
samples of that power. The starting data will be the
amplitude error ek (1), and the error in the phase
increment eϴk (4) of the received point of the
constellation (3), with respect to the detected point (8),
which are calculated as follows:


Where Ak is the detected amplitude, Ak is the received
amplitude equalized in order to compensate the attenuation
of the channel, Δφk is the detected phase increment and Δφk is
the received phase increment. The sample of the noise power
is obtained by calculating the modulus squared of the
vector (2):

Where r3 (7) is the detected amplitude Ak for the
example shown in figure 2. Therefore the formula would
become:

Which represents the modulus squared of the error
vector (2). This is the simplest and most immediate way of
calculating the samples of the noise power, but it provokes
differences between the variance of the estimator of the
constellations with odd and even bits per symbol. As
explained earlier, when the amplitude of the ring is
greater, so the cloud of points acquires a more pronounced
elliptical shape. As the optimum constellations with an odd
number of bits per symbol proportionally present more rings
than phases compared with those with an even number of bits
per symbol, they show the effect described above in a way
that is more visible. For the same value of SNR, the
greater the amplitude of the detected point, the greater
will be the average of the modulus squared of the noise
vector. So, N samples of noise power calculated starting
from a constellation with an odd number of bits per symbol
will present a greater scattering than N samples calculated
starting from a constellation with an even number of bits.
Therefore, the variance which the estimator will present in
the constellations of odd bits per symbol will be greater.
Also, that same effect of increment in the size of the
ellipses of points as the amplitude of the ring increases
also causes an increase in the variance for a given

constellation.
Therefore, the objective is to make the samples
independent of the noise power of the ring to which the
detected point belongs.
So, one could think of projecting the error vector (2)
onto the first ring of radius r1 (6), with which the kth
sample of the noise power of projected onto the first ring
e'(k) (5) is obtained, using for this the theory of similar
triangles. Therefore, for the example of embodiment
described in figure 2, the new sample of the noise power
can be calculated as:

But in this way, none of the problems set out earlier
are solved, since the amplitude error (1) is modified as a
function of the ring of the constellation to which the
detected point belongs.
The procedure of the invention that is presented
solves these problems by translating the phase error and
the amplitude error to the corresponding point of the first
ring of the constellation as if this was the one that had
been detected. Figure 3 represents an example of embodiment
in which this translation is made. So, the samples of the
noise power, which is the modulus squared of the new error
vector (9), are calculated as follows:

Where r1 (6) is the amplitude of the first ring of the
corresponding constellation. Also, as explained earlier,
the average of N samples is taken for calculating the noise
power in the same way:

Figure 4 shows an example of a block diagram of a
receiver implementing the procedure of the invention that

is presented. The starting data needed by the block
calculating the samples of the noise power (12) are the
amplitude error ek (1), the phase error eϴk (4) and the
number of bits of the constellation (14). The amplitude and
phase errors are calculated by an amplitude detector (10)
and by a phase detector (11), respectively. In order to
calculate these two errors, the equalized amplitude Ak
(19), the received phase increment Δφk (20) and the number
of bits per symbol of the constellation (14) are required.
Moreover, the calculation of the phase (4) and amplitude
(1) errors can be done in two ways. The first consists of
calculating those errors on the basis of the detection of
the amplitude (19) and of the phase increment (20) that are
received; in other words, the sequence of symbols sent by
the transmitter is not known. This mode is known as blind
estimation and is affected by detection errors, which
prevents the SNR from being estimated properly when these
errors occur, since the calculated errors will be smaller
in magnitude than those which have actually taken place and
the estimation of the SNR will be greater than that which
is really affecting the system. The second way of
calculating the phase and amplitude errors is based on a
knowledge of the transmitted sequence, due to which those
errors will correspond exactly to those produced when there
is no detection involved in the process. In this example of
embodiment, both are done, so by means of a block (21) the
values of amplitude Aki (23) and of phase increment Δφki (24)
that are transmitted are generated. There has to exist an
identical block in the transmitter so that the sequences in
transmission and reception can be equal. A signal (22)
informs on the type of estimation being done, blind mode or
with known sequence. So, the amplitude (10) and phase (11)
detectors will in this case only have to carry out
subtraction between the values (19) and (23) in the case of
amplitude, and between the values (24) and (20) in the case
of phase increment.
As this concerns a multiuser communications system,

the receiver will not always recognise the constellation
with which the data being received is modulated. It will
only know it in a unicast communication when it is the
destination of the transmitted data or when a multicast
communication is made which includes it in the group of
recipients or in a broadcast; for that reason, the N
samples of the noise power which are averaged can belong to
different constellations. A signal (15) indicates that the
constellation is known and that the samples of the noise
power can be calculated.
By means of simulations, it is confirmed that the
estimator described so far in this invention procedure is
biased. This bias is due to the differential character of
the modulation, since the phase increment is affected by
the noise of two symbols and is detailed in the following
table as a function of the constellation:

The block (12) has to apply this correction factor K
to the samples of the noise power in order to correct the
biased nature of the estimator, by means of:

The number of bits per symbol (14) serves to determine
the value of r1 (6) and of the correction factor K to use
in the calculation. This correction has to be made sample
by sample since these samples can belong to different
constellations. As an average of the samples of taken, a
memory (13) is needed for storing the partial value of the
summation presented earlier. So, the operation carried out
by the block (12) is as follows:


Where the value E' (k) (18) is stored in the memory
(13) once it has been calculated. Before calculating the
value (18), the block (12) has to read the term (17)
from the memory (13) . When the value of k is equal to N,
which is a configurable parameter of the system and which
can be different in the two possible estimation modes, the
block (12) generates a signal (16) indicating that there is
an estimation of noise power available. A signal (22) again
indicates the estimation mode, blind or with known
sequence, which will determine the number of samples N to
accumulate. When the signal (16) so indicates, the memory
is read and the value is divided by the corresponding value
N.
The estimation mode with known sequence is more
reliable than the blind mode, though it has the drawback of
not permitting data to be sent to the receivers. Also, the
SNR of the channel needs to be monitored so that the system
can adapt the number of bits per symbol to use. Moreover,
it is also necessary to detect sudden changes of channel
and change the constellation as far as possible so that the
minimum number of packets are lost. These considerations
are much more important in a multiuser OFDM communications
system where each symbol contains a lot of information. For
this reason, both estimations are combined.
Furthermore, the larger the value of Nr the smaller
will be the variance of the estimation. But in a system
like the . above, this value cannot be arbitrarily large,
because each OFDM symbol can, depending on the number of
carriers and on the bits with which each of them is being
modulated, contain a large quantity of data. Therefore, an
estimation with . known sequence implies sending N symbols without information (since the sequence is known, it does
not contain information) and increasing the overhead, and
an estimation in blind mode requires that the information

sent by the emitter to the receiver should occupy more than
N OFDM symbols, which is not always possible. So, in this
example of embodiment, in blind mode N = 16 has been chosen
and in known sequence N = 32.
As an initial estimation, a estimation with known
sequence is made. After that, new estimations with known
sequence are made with a periodicity of seconds. Between
these estimations, blind mode estimations can be made
(depending on the data traffic), which are used for
determining whether any sudden change of channel has taken
place. In the event that the change of channel causes a
significant worsening of the real SNR, an estimation will
need to be made with known sequence in order to prevent the
error from occurring in the blind estimation, described
earlier.

We Claim:
1. A method of reducing the variance of the signal-to-noise rate estimated for a
signal with amplitude differential phase-shift keying modulation , applicable to a two-
way communication system of multiple sets of user equipment in which amplitude
differential phase-shift keying modulation (ADPSK) is used, which requires a sending of
a phase reference symbol prior to sending an information, and where an estimation is
made of the signal- to- noise rate in order to use a modulation with a maximum number
of bits per symbol, maintaining a bit error probability in reception within certain given
margins; said method comprising:
receiving a symbol with known modulation (bits per carrier);
measuring an amplitude error using an amplitude detected by an amplitude
detector, that is the detected amplitude, over the symbol received;
measuring an error in the phase increment using a phase increment detected by a
phase detector, that is the detected phase increment, over the symbol received;
translocating the amplitude error and the error in the phase increment to a first
ring of the constellation, as if the received symbol had been transmitted in that ring;
calculating a noise power as the square of the modulus of the error vector, where
said error vector is formed by the amplitude error and the error in the phase increment,
where said noise-power is accumulated and averaged;
estimating the signal-to-noise-rate with the noise-power previously calculated and
the known power of the sent signal; and
selecting the modulation with the maximum number of bits per symbol keeping
probability error of bit in reception inside the given margins using the estimated signal-
to-noise rate previously calculated; in order to calculate noise samples, reduce the
variance of the values obtained and equalize said variance among optimum constellations
of odd and even bits per symbol.
2. The method as claimed in claim 1, wherein an average of the square of the
modulus of the noise samples is taken in order to estimate the average value of the noise
power, the number of samples to average being a configurable value of the system.

3. The method as claimed in claim 1, wherein the amplitude and phase increment
are detected in reception, and the detected amplitude and phase increment are selectively
subtracted from a received amplitude and a received phase increment, respectively, or a
received amplitude and a received phase increment are subtracted from the detected
amplitude and the detected phase increment, respectively; in order to calculate the
noise- power samples in blind mode.
4. The method as claimed in claim 1, wherein a sequence of symbols known in
reception is sent and selectively a received amplitude and a received phase increment are
subtracted from the amplitude and the phase increment of the signals previously
transmitted and known in reception, respectively, or the amplitude and phase increment
of the signals previously transmitted and known in reception are subtracted from a
received amplitude and a received phase increment, respectively; in order to calculate the
amplitude and phase increment errors and, thereafter , the noise-power samples.
5. The method as claimed in claims 2, 3, and 4, wherein in the estimation of the
signal- to- noise rate in reception, estimations in blind mode are combined with
estimations with known sequence of symbols, in order to improve the estimation.
6. The method as claimed in claim 2, wherein the samples of the noise- power to
average belong to different constellations.
7. The method as claimed in claim 6, wherein the bias of the estimators, due to the
differential character of the modulation and to the different value in each constellation, is
corrected independently in each of the noise-power samples being averaged, multiplying
each sample by a correction factor, where this correction factor, which is unique to each
sample, is the inverse function of the bias of the estimator.


ABSTRACT
METHOD OF REDUCING THE VARIANCE OF THE SIGNAL-TO-NOISE RATE
ESTIMATED FOR A SIGNAL WITH AMPLITUDE DIFFERENTIAL PHASE-
SHIFT KEYING MODULATION.
This method reduces the variance of the estimation of
the signal-to-noise rate in a multiuser digital
communications system. These communications require a
sending of a phase reference symbol prior to sending a
information, where the estimation is made of the signal-to-
noise rate in order to use a modulation with a maximum
number of bits per symbol, maintaining a bit error
probability in reception within certain given margins. The
method minimizes and equalizes the variance of the samples
obtained for the different values, even and odd of bits per
carrier, which the system uses. The estimation is necessary
for selecting the number of bits per carrier in order to be
adapted to the channel and as back-up information in the
event of using a receiver with diversity.


Documents:

02717-kolnp-2005-abstract.pdf

02717-kolnp-2005-claims.pdf

02717-kolnp-2005-description complete.pdf

02717-kolnp-2005-drawings.pdf

02717-kolnp-2005-form 1.pdf

02717-kolnp-2005-form 3.pdf

02717-kolnp-2005-form 5.pdf

02717-kolnp-2005-international publication.pdf

2717-KOLNP-2005-(14-12-2011)-ASSIGNMENT.pdf

2717-KOLNP-2005-(14-12-2011)-CORRESPONDENCE.pdf

2717-KOLNP-2005-AMANDED CLAIMS.pdf

2717-KOLNP-2005-AMANDED PAGES OF SPECIFICATION.pdf

2717-KOLNP-2005-ASSIGNMENT.pdf

2717-kolnp-2005-assignment1.1.pdf

2717-KOLNP-2005-CORRESPONDENCE 1.1.pdf

2717-KOLNP-2005-CORRESPONDENCE.pdf

2717-kolnp-2005-correspondence1.2.pdf

2717-KOLNP-2005-DRAWINGS 1.1.pdf

2717-KOLNP-2005-ENGLISH TRANSLATED OF PRIORITY DOCUMENT.pdf

2717-kolnp-2005-examination report.pdf

2717-KOLNP-2005-FORM 1 1.1.pdf

2717-kolnp-2005-form 13.1.pdf

2717-KOLNP-2005-FORM 13.pdf

2717-kolnp-2005-form 18.pdf

2717-KOLNP-2005-FORM 2.pdf

2717-kolnp-2005-form 26.pdf

2717-KOLNP-2005-FORM 3 1.1.pdf

2717-kolnp-2005-form 3.pdf

2717-kolnp-2005-form 5.pdf

2717-kolnp-2005-form 6.1.pdf

2717-KOLNP-2005-FORM 6.pdf

2717-kolnp-2005-gpa.pdf

2717-kolnp-2005-granted-abstract.pdf

2717-kolnp-2005-granted-claims.pdf

2717-kolnp-2005-granted-description (complete).pdf

2717-kolnp-2005-granted-drawings.pdf

2717-kolnp-2005-granted-form 1.pdf

2717-kolnp-2005-granted-form 2.pdf

2717-kolnp-2005-granted-specification.pdf

2717-KOLNP-2005-OTHER PCT FORM.pdf

2717-KOLNP-2005-OTHERS 1.1.pdf

2717-kolnp-2005-others.pdf

2717-kolnp-2005-others1.2.pdf

2717-KOLNP-2005-PA.pdf

2717-KOLNP-2005-PCT IPRB.pdf

2717-KOLNP-2005-PETITION UNDER RULE 137-1.1.pdf

2717-KOLNP-2005-PRIORITY DOCUMENT.pdf

2717-KOLNP-2005-REPLY TO EXAMINATION REPORT.pdf

2717-kolnp-2005-reply to examination report1.1.pdf

abstract-02717-kolnp-2005.jpg


Patent Number 253332
Indian Patent Application Number 2717/KOLNP/2005
PG Journal Number 28/2012
Publication Date 13-Jul-2012
Grant Date 12-Jul-2012
Date of Filing 26-Dec-2005
Name of Patentee MARVELL HISPANIA, S.L
Applicant Address PLAZA DE PABLO RUIZ PICASO, NUMBER 1, TORRE PICASO, 38TH FLOOR, MADRID
Inventors:
# Inventor's Name Inventor's Address
1 RIVEIRO INSUA, JUAN CARLOS BEATA GENOVEVA TORRES, 30-ESC. B-10°, PUERTA 43, E-46019, VALENCIA, SPAIN
2 BÁDENES CORELLA, AGUSTÍN GOBERNADOR, 21-1° E-12003, CASTELLÓN
3 BLASCO CLARET, JORGE VICENTE GUARDIA CIVIL, 23-2° 38, E-46020, VALENCIA
PCT International Classification Number H04L 1/20
PCT International Application Number PCT/ES2004/000233
PCT International Filing date 2004-05-19
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 P 2003 01229 2003-05-26 Spain