Method of discrete digital signal recovery in noisy overloaded wireless communication systems in the presence of hardware impairments
A computer-implemented reconstruction method of discrete digital signal recovery in noisy overloaded wireless communication systems in the presence of hardware impairments that is characterized by a channel matrix of complex coefficients, the method including, receiving the signal from channel by a signal detector, estimation of hardware impairments parameter η is done at the receiver, estimation noise power is done by a noise power estimator, forwarding the detected signal and hardware impairments parameter η and noise power estimation to a decoder that estimates the transmitted symbol, wherein the estimation of the decoder produces a symbol that could probably have been transmitted it is forwarded to a de-mapper, which outputs the bit estimates corresponding to the estimated transmit signal and the corresponding estimated symbol to a microprocessor for further processing.
1. A computer-implemented reconstruction method of discrete digital signal recovery in noisy overloaded wireless communication systems in the presence of hardware impairments that is characterized by a channel matrix of complex coefficients, the method including
Receiving the signal from channel by a signal detector
Estimation of Hardware Impairments parameter η is done at the receiver
Estimation noise power is done by a noise power estimator
Forwarding the detected signal and hardware impairments parameter η and noise power estimation to a decoder that estimates the transmitted symbol (s),
wherein the estimation of the decoder produces a symbol that could have been transmitted it is forwarded to a de-mapper, which outputs the bit estimates corresponding to the estimated transmit signal and the corresponding estimated symbol to a microprocessor for further processing.
2. The method of claim 1 , wherein channel correlation is assumed due to hardware impairments (η), which is incorporated within the covariance matrix capturing this correlation.
3. The method of claim 1 , wherein minimizing the effect of hardware impairments (η) is done by compensating the channel correlation within the objective function used by decoder.
4. The method of claim 1 , wherein the minimizing the effect of channel estimation error to the minimization formulation via a first function, a second function, a third function used to estimate the transmit signal (s)
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5. The method of claim 4 , wherein the fractional programming algorithm is targeted to find a value of the third function that is lower than the global minimum of the first function.
6. The method of claim 4 , wherein the first function is a Euclidian distance function centred around the received signal's vector including the channel correlation effect.
7. The method of claim 4 , wherein the second function is the product of the estimated noise power and transmit signal power.
8. The method of claim 4 , wherein the third function is a function based on or tightly approximating the l 0 -norm.
9. A receiver of a communication system having a processor, volatile and/or non-volatile memory, at least one interface adapted to receive a signal in a communication channel, wherein the non-volatile memory stores computer program instructions which, when executed by the microprocessor, configure the receiver to perform reconstruction of discrete digital signal recovery in noisy overloaded wireless communication systems in the presence of hardware impairments that is characterized by a channel matrix of complex coefficients, by performing operations comprising:
Receiving the signal from channel by a signal detector
Estimation of Hardware Impairments parameter η is done at the receiver
Estimation noise power is done by a noise power estimator
Forwarding the detected signal and hardware impairments parameter η and noise power estimation to a decoder that estimates the transmitted symbol (s),
wherein the estimation of the decoder produces a symbol that could have been transmitted it is forwarded to a de-mapper, which outputs the bit estimates corresponding to the estimated transmit signal and the corresponding estimated symbol to a microprocessor for further processing.
10. The receiver of claim 9 , wherein channel correlation is assumed due to hardware impairments (η), which is incorporated within the covariance matrix capturing this correlation.
11. The receiver of claim 9 , wherein minimizing the effect of hardware impairments (η) is done by compensating the channel correlation within the objective function used by decoder.
12. The receiver of claim 9 , wherein the minimizing the effect of channel estimation error to the minimization formulation via a first function, a second function, a third function used to estimate the transmit signal (s)
min
x
∈
ℂ
N
t
(
y
-
H
x
)
H
∑
n
~
corr
-
1
(
y
-
H
x
)
+
σ
n
2
x
2
2
+
λ
∑
i
=
1
❘
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𝒞
❘
"\[RightBracketingBar]"
x
-
c
i
1
0
13. The receiver of claim 12 , wherein the fractional programming algorithm is targeted to find a value of the third function that is lower than the global minimum of the first function.
14. The receiver of claim 12 , wherein the first function is a Euclidian distance function centred around the received signal's vector including the channel correlation effect.
15. The receiver of claim 12 , wherein the second function is the product of the estimated noise power and transmit signal power.
16. The receiver of claim 12 , wherein the third function is a function based on or tightly approximating the l 0 -norm.