Method of detecting OTFS SCMA signals and receiver implementing the method
A method of detecting superimposed SCMA signals from multiple user equipment in a receiver of an OTFS communication system includes initializing an executing an iteration loop, in which a mean of all a posteriori estimates of the transmitted signal determined so far is calculated, which a posteriori estimates are based on the OTFS-demodulated received signal, the corresponding channel matrix, and the mean vectors and variances determined for each UE. The mean of all a posteriori estimates determined so far is used for determining vectors and variances for each UE, further using the probabilities of the non-zero elements of the respective UEs codebooks. The iteration is repeated until a termination criterion is met.
1 . A method for detecting superimposed sparse code multiple access (SCMA) signals from multiple user equipment (UE) received by radio from a receiver of an orthogonal time frequency space communication system, comprising:
receiving an orthogonal time frequency space (OTFS) demodulated signal representing the received signals of all UEs,
receiving a corresponding channel matrix,
initialising and executing an iteration loop, wherein the iteration loop comprises:
a) determining an a posteriori estimate of the transmitted signal using the demodulated signal, the channel matrix and the respective mean vectors and associated variances that were determined for each UE in a respective immediately preceding iteration or were determined in the first iteration for each UE in the initialisation as input signals,
b) generating an extrinsic mean value of the current iteration from all a posteriori estimates determined so far and corresponding extrinsic variances of the current iteration,
c) Determining a posteriori probabilities for each UE and for each of the non-zero elements of the SCMA codebook of the respective UE, based on the extrinsic mean value of the current iteration and the corresponding extrinsic variances of the current iteration,
d) Calculating an a posteriori Gaussian distribution of the a posteriori probabilities of the current iteration and the corresponding variance for each UE and over all non-zero elements of the SCMA codebook of the respective UE,
e) updating the elements of the respective mean vector and the corresponding extrinsic variances for each UE based on the a posteriori Gaussian distribution,
and
repeating steps a) to e) until a termination criterion is met.
2 . The method according to claim 1 , wherein the initialisation comprises setting the mean vectors of the first iteration and the extrinsic mean of the first iteration to zero and/or setting the extrinsic variances (η 0,0 ) to
η
0
,
0
=
(
1
y
H
y
-
σ
2
)
/
a
0
,
where
=
M
N
J
D
K
and =UMN, with D being the number of non-zero entries of the SCMA code word, J is the number of independent UEs, K is the dimension of the SCMA code word, M and N are the number of columns and rows of the OTFS delay-Doppler plane, and U is the number of receiving antennas of the base station, and where σ 2 is the variance of the Gaussian distribution.
3 . The method according to claim 1 , wherein the initialisation comprises receiving at least one attenuation length, a maximum number of iterations and/or the minimum and maximum eigenvalues of the product of the channel matrix and its conjugate complex transpose as further input variables.
4 . The method according to claim 3 , wherein the initialisation comprises setting the iteration counter to 1 and/or setting a positive relaxation eigenvalue parameter to the mean value of the minimum and maximum eigenvalues of the product of the channel matrix and its complex conjugate transpose.
5 . The method according to claim 1 , wherein the determination of the a posteriori estimate of the transmitted signal comprises the use of finite terms of matrix Taylor series to approximately determine the matrix inverse with a linear minimum mean square error.
6 . The method according to claim 1 , wherein the update comprises applying a Gaussian message combination.
7 . The method according to claim 1 , wherein, for updating the elements of the respective mean vector and the corresponding extrinsic variances, the variances of the current iteration of the a posteriori probabilities of the current iteration are averaged.
8 . The method according to claim 1 , wherein the iteration is terminated after a predetermined number of iterations if the difference between an a posteriori estimate of the transmitted signal of a current iteration and an immediately preceding iteration is below a predetermined value, when the a posteriori variance falls below a predetermined value and/or if the difference between an a posteriori estimate of the transmitted signal of a current iteration and an extrinsic mean value of the current iteration is below a predetermined value.
9 . The method according to claim 1 , further comprising dynamically adjusting the attenuation length based on the signal-to-noise ratio of the received signal.
10 . A detector of a receiver set up to receive superimposed OTFS-modulated SCMA signals from multiple UEs, wherein the detector comprises one or more software and/or hardware blocks or modules for receiving an OTFS-demodulated signal representing the received signals of all UEs, a corresponding channel matrix, for initialising and executing an iteration loop implementing steps a) to e) of the method according to claim 1 , for detecting SCMA signals of individual UEs in the received superimposed OTFS-modulated SCMA signals, and for outputting the detected SCMA signals to an SCMA inverse mapper.
11 . A radio receiver of an OTFS communication system, comprising one or more antennas for receiving superimposed OTFS-modulated SCMA signals from multiple UEs on an OTFS communication channel, wherein the received signals are fed to an OTFS demodulator configured to output a received signal representing the received signals of all UEs to a channel estimator, wherein the channel estimator is configured to output an estimate of the coefficients of the channel to a signal detector according to claim 10 , wherein the signal detector is configured to detect SCMA signals from individual UEs and for outputting detected SCMA signals to an SCMA inverse mapper, wherein the SCMA inverse mapper supplies inverse mapped signals to a channel decoder, the output of which is a reconstructed version of the binary data sequences transmitted by the respective UEs.
12 . The radio receiver according to claim 11 , wherein the OTFS demodulator, the channel estimator, the signal detector), the SCMA inverse mapper and/or the channel decoder are implemented as software or hardware blocks or modules or as a combination thereof.
13 . The radio receiver according to claim 11 , which further comprises one or more microprocessors, volatile and non-volatile memory, which are physically or logically connected to the software or hardware blocks or modules or a combination thereof, which implement the OTFS demodulator, the channel estimator, the signal detector, the SCMA demodulator, the channel estimator, the signal detector, the SCMA remapper and the channel decoder, wherein the non-volatile memory stores computer program instructions which, when executed by the one or more microprocessors, cause the one or more microprocessors to control the software or hardware blocks or modules or a combination thereof to perform a method for detecting superimposed sparse code multiple access signals from multiple user equipment received by radio from a receiver of an orthogonal time frequency space communication system, the method comprising:
receiving an OTFS demodulated signal representing the received signals of all UEs,
receiving a corresponding channel matrix,
initialising and executing an iteration loop, wherein the iteration loop comprises:
a) determining an a posteriori estimate of the transmitted signal using the demodulated signal, the channel matrix and the respective mean vectors and associated variances that were determined for each UE in a respective immediately preceding iteration or were determined in the first iteration for each UE in the initialisation as input signals,
b) generating an extrinsic mean value of the current iteration from all a posteriori estimates determined so far and corresponding extrinsic variances of the current iteration,
c) Determining a posteriori probabilities for each UE and for each of the non-zero elements of the SCMA codebook of the respective UE, based on the extrinsic mean value of the current iteration and the corresponding extrinsic variances of the current iteration,
d) Calculating an a posteriori Gaussian distribution of the a posteriori probabilities of the current iteration and the corresponding variance for each UE and over all non-zero elements of the SCMA codebook of the respective UE,
e) updating the elements of the respective mean vector and the corresponding extrinsic variances for each UE based on the a posteriori Gaussian distribution,
and
repeating steps a) to e) until a termination criterion is met.
14 . A non-transitory computer program product comprising computer program instructions which, when executed by a microprocessor, cause the computer and/or hardware blocks, modules or components of a receiver according to claim 11 of an OFTS transmission system to execute a method for detecting superimposed sparse code multiple access signals from multiple user equipment received by radio from a receiver of an orthogonal time frequency space communication system, the method comprising:
receiving an OTFS demodulated signal representing the received signals of all UEs,
receiving a corresponding channel matrix,
initialising and executing an iteration loop, wherein the iteration loop comprises:
a) determining an a posteriori estimate of the transmitted signal using the demodulated signal, the channel matrix and the respective mean vectors and associated variances that were determined for each UE in a respective immediately preceding iteration or were determined in the first iteration for each UE in the initialisation as input signals,
b) generating an extrinsic mean value of the current iteration from all a posteriori estimates determined so far and corresponding extrinsic variances of the current iteration,
c) Determining a posteriori probabilities for each UE and for each of the non-zero elements of the SCMA codebook of the respective UE, based on the extrinsic mean value of the current iteration and the corresponding extrinsic variances of the current iteration,
d) Calculating an a posteriori Gaussian distribution of the a posteriori probabilities of the current iteration and the corresponding variance for each UE and over all non-zero elements of the SCMA codebook of the respective UE,
e) updating the elements of the respective mean vector and the corresponding extrinsic variances for each UE based on the a posteriori Gaussian distribution,
and
repeating steps a) to e) until a termination criterion is met.
15 . A non-transitory computer-readable medium that retrieves or stores the computer program product according to claim 14 .
16 . A non-transitory computer program product comprising computer program instructions which, when executed by a microprocessor, cause the computer and/or hardware blocks, modules or components of a detector according to claim 10 to execute a method for detecting superimposed sparse code multiple access signals from multiple user equipment received by radio from a receiver of an orthogonal time frequency space communication system, the method comprising:
receiving an OTFS demodulated signal representing the received signals of all UEs,
receiving a corresponding channel matrix,
initialising and executing an iteration loop, wherein the iteration loop comprises:
a) determining an a posteriori estimate of the transmitted signal using the demodulated signal, the channel matrix and the respective mean vectors and associated variances that were determined for each UE in a respective immediately preceding iteration or were determined in the first iteration for each UE in the initialisation as input signals,
b) generating an extrinsic mean value of the current iteration from all a posteriori estimates determined so far and corresponding extrinsic variances of the current iteration,
c) Determining a posteriori probabilities for each UE and for each of the non-zero elements of the SCMA codebook of the respective UE, based on the extrinsic mean value of the current iteration and the corresponding extrinsic variances of the current iteration,
d) Calculating an a posteriori Gaussian distribution of the a posteriori probabilities of the current iteration and the corresponding variance for each UE and over all non-zero elements of the SCMA codebook of the respective UE,
e) updating the elements of the respective mean vector and the corresponding extrinsic variances for each UE based on the a posteriori Gaussian distribution,
and
repeating steps a) to e) until a termination criterion is met.
17 . A method for receiving binary data sequences transmitted simultaneously by multiple UEs as OTFS-modulated SCMA signals, comprising:
a) subjecting the received OTFS signal to OTFS demodulation,
b) performing a channel estimation on the demodulated OTFS signal,
c) detecting the superimposed SCMA signals by applying the method according to claim 1 ,
d) remapping the detected SCMA signals, and
e) reconstructing the binary data from the remapped detected SCMA signals.
18 . A radio communication device comprising one or more microprocessors, volatile and non-volatile memory, a radio interface circuit configured to transmit and/or receive electromagnetic signals via one or more antennas, wherein the non-volatile memory stores computer program instructions which, when executed by the microprocessor, configure the radio device to perform the methods according to claim 1 .