Approximation method for signal-to-noise ratio soft information for a communications system

1. An approximation method for signal-to-noise ratio (SNR) soft information for a transmitter of a communications system, the approximation method comprising:

obtaining a conditional probability density function (PDF) corresponding to a response message;

obtaining a PDF of a probability distribution model, and a mean and a variance of the PDF, by approximating the conditional PDF corresponding to the response message with the probability distribution model;

calculating a second mean and a second variance of a second PDF approximated to a conditional PDF of SNR corresponding to the transmitted packet according to the mean and the variance of the PDF, and a first mean and a first variance of a first PDF approximated to a conditional PDF of SNR corresponding to another transmitted packet immediately preceding the transmitted packet; and

transmitting a packet according to the second mean and the second variance.

2. The approximation method of claim 1 further comprising approximating an initial conditional PDF of SNR with the probability distribution model before the step of obtaining the conditional PDF corresponding to the response message, wherein the initial conditional PDF of SNR is a conditional PDF of SNR given various received signal strength indication (RSSI) values.

3. The approximation method of claim 1 , wherein the probability distribution model is a Gaussian distribution, and the PDF obtained by approximating the conditional PDF corresponding to the response message, the first PDF, and the second PDF are Gaussian PDFs.

4. The approximation method of claim 1 , wherein the second mean is denoted as M N and is given by:

M

N

=

M

N

-

1

×

var

⁡

(

MCS

N

,

ACK

/

NACK

)

+

V

N

-

1

×

mean

⁡

(

MCS

N

,

ACK

/

NACK

)

var

⁡

(

MCS

N

,

ACK

/

NACK

)

+

V

N

-

1

,

where N is an order of the transmitted packet, (N−1) is an order of the another transmitted packet immediately preceding the transmitted packet, MCS N is a modulation and coding scheme used for the transmitted packet, ACK/NACK indicates the response message of the transmitted packet, mean(MCS N , ACK/NACK) is the mean, var(MCS N , ACK/NACK) is the variance, M N−1 is the first mean, and V N−1 is the first variance.

5. The approximation method of claim 1 , wherein the second variance is denoted as V N and is given by:

V

N

=

V

N

-

1

×

var

⁡

(

MCS

N

,

ACK

/

NACK

)

var

⁡

(

MCS

N

,

ACK

/

NACK

)

+

V

N

-

1

,

where N is an order of the transmitted packet, (N−1) is an order of the another transmitted packet immediately preceding the transmitted packet, MCS N is a modulation and coding scheme used for the transmitted packet, ACK/NACK indicates the response message of the transmitted packet, var(MCS N , ACK/NACK) is the variance, and V N−1 is the first variance.

6. The approximation method of claim 1 , where the response message is a positive acknowledgement (ACK) or a negative acknowledgement (NACK).

7. The approximation method of claim 1 , wherein the conditional PDF corresponding to the response message is a conditional PDF of the transmitter receiving the response message given a modulation and coding scheme with various SNRs.

8. The approximation method of claim 1 , wherein the response message corresponds to the transmitted packet.