CN101795168B - Approaching method of signal-to-noise ratio flexible message used for communication system - Google Patents

Abstract

The invention relates to an approaching method of a signal-to-noise ratio flexible message used for the transmission end of a communication system, which comprises the following steps: generating a condition probability density function corresponding to a response message; using a probability distribution model for approaching the condition probability density function for obtaining the probability density function, and the average value and the variance of the probability density function; and generating the second average value and the second variance of a second probability density function according to the average value, the variance, and a first average value and a first variance of a first probability density function. The first probability density function approaches to and corresponds to the condition probability density function of the signal-to-noise ratio of a front data packet, and the second probability density function approaches to and correspond to the condition probability density function of the signal-to-noise ratio of the data packet.

Description

The approaching method that is used for the signal-to-noise ratio flexible message of communication system

Technical field

The present invention is meant a kind of approaching method that is used for the signal-to-noise ratio flexible message of communication system, refers to a kind of method with probability Distribution Model convergence signal-to-noise ratio flexible message especially.

Background technology

In wireless telecommunication system; In order to reach preset communication function; Can the many groups of definition modulate and encoding mechanism (Modulation and Coding Scheme in the related specifications; MCS), include settings such as modulation technique, encoding rate and message transmission rate, and different modulation and encoding mechanism are to distinguish with call number.With IEEE 802.11n wireless telecommunication system standard is example, and MCS-15 representes that the modulation technique of using is 64-QAM, and encoding rate is 5/6, and message transmission rate then has difference according to the frequency range that uses as 20MHz or 40MHz.According to defined multiple modulation of related specifications and encoding mechanism, wireless telecommunication system can be selected suitable one group of modulation and encoding mechanism, to obtain best transmission usefulness.

On the other hand, with regard to wireless telecommunication system, actual transmission channel is also imperfect, and possibly receive various factors, like the interference of multipath propagation, noise or other electronic system, causes error of transmission.Environment in transmission channel changes, and wireless telecommunication system need be reselected suitable modulating and encoding mechanism, and when avoiding transmission channel can accept to be superior to the transmission rate of initial setting, wireless telecommunication system is new settings and cause transmission resource waste more not yet; Perhaps, when transmission channel status was not good, wireless telecommunication system was still kept higher transmission rate and is set, and causes throughput of transmissions (Throughput) to decline to a great extent.

When the state of transmission channel can't be learnt in the transmission end of wireless telecommunication system; The transmission end only can be according to the transmission result of data packet; Be the affirmation payment received message (Acknowledgement that receiving terminal returned of wireless telecommunication system; ACK) or (Non-acknowledgement NACK), does not judge the state of transmission channel to payment received message.In order to judge the state of transmission channel; Known technology has used automatic rate to retreat (Auto Rate Fallback; ARF) algorithm, adaptability automatic rate are retreated (Adaptive ARF; AARF) algorithm, sampling rate (Sample Rate) algorithm, Onoe algorithm, the multiple speed retry of adaptability (Adaptive Multi Rate Retry; AMRR) algorithm, Madwifi (Multiband AtherosDriver for WiFi) algorithm and robust speed adjustment algorithm (Robust Rate AdaptationAlgorithm, RRAA).Automatic rate backward algorithm and adaptability automatic rate backward algorithm are to send probe packets (Probe Packets), whether can accept higher transmission rate with decision, or at the situation decline low transmission rate that continuous bust this takes place.The sampling rate algorithm is periodically to transmit probe packets with the transmission rate of selecting at random, and according to testing result, selects one of them can obtain the transmission rate of high-transmission throughput, is used for the transmission of normal data package.The Onoe algorithm is in a period of time, with specific transmission rate transmissioning data package, if the packet error at this moment is lower than 10%, promptly improves transmission rate to next level, otherwise then downgrades the level of transmission rate.Multiple speed retry algorithm of adaptability and Madwifi algorithm are to send probe packets equally, and receive the critical value of success rates with two packages, and decision improves or downgrades transmission rate.Robust speed adjustment algorithm then is to receive success rate according to the affirmation payment received message of transmission signals and package, the decision transmission rate.

By on can know that the known transmission rate adjusting method need send extra probe packets, or the statistics a period of time transmission quality, could determine the renewal transmission rate.For the Communications service that requires real-time, if wireless telecommunication system uses said method, the convergence rate of then upgrading transmission rate is slow excessively, can't effectively promote throughput of transmissions.Therefore; This case applicant discloses a kind of transmission rate adjusting method No. 97146118 in the TaiWan, China patent application; It is that the transmission end of wireless telecommunication system is according to corresponding to the response message of the data packet that has transmitted and corresponding to the signal to noise ratio (Signal-to-noiseRatio of last data package; SNR) conditional probability density function (Conditional Probability DensityFunction) upgrades the conditional probability density function of signal to noise ratio, and according to the conditional probability density function of the signal to noise ratio of having upgraded; Select suitable modulation and encoding mechanism, next data packet can be transmitted with preferable transmission rate.The conditional probability density function of signal to noise ratio is claimed signal-to-noise ratio flexible message (SNR Softinformation) again.

The conditional probability density function of signal to noise ratio is at known reception signal strength signal intensity indication (ReceivedSignal Strength Indication; RSSI), known transmission speed and known corresponding to the affirmation payment received message of data packet or the conditional probability density function of not tried to achieve under the condition of payment received message; It is to confirm payment received message or not during payment received message, upgrade in receiving each time.The conditional probability density function of signal to noise ratio is represented as follows:

$p\left(\mathrm{SNR}\right|\mathrm{RSSI},\mathrm{MCSs},\mathrm{ACKs}\left|\mathrm{NACKs}\right)$

$=p\left(\mathrm{SNR}\right|\mathrm{RSSI})\underset{i=0}{\overset{N}{\mathrm{\Π}}}\frac{p\left(\mathrm{ACKi}\right|\mathrm{NACKi}|\mathrm{SNR},\mathrm{MCSi})}{p\left(\mathrm{ACKi}\right|\mathrm{NACKi}\left|\mathrm{MCSi}\right)}---\left(1\right)$

Wherein N is that MCSi is modulation and the encoding mechanism that is used in i data package, mainly representes transmission rate at this to the package quantity that has transmitted so far.ACKi/NACKi representes the response message corresponding to i data package that the transmission end receives, and is to confirm payment received message or payment received message not.Not note that if affirmation payment received message is received in the transmission end in the scheduled time at this, also be regarded as receiving not payment received message.P (SNR|RSSI) is not for receiving the affirmation payment received message of any data packet or not during payment received message, the conditional probability density function of the signal to noise ratio under the different received signal strength indication value.P (ACKi/NACKi|MCSi) is when transmitting i data package with known modulation and encoding mechanism MCSi, receives to confirm the payment received message or the probability of payment received message not.(ACKi/NACKi|SNR is when transmitting i data package with known modulation and encoding mechanism MCSi MCSi) to p, under each signal to noise ratio, receives to confirm the payment received message or the conditional probability density function of payment received message not.Formula (1) can be expressed as following formula (2) and formula (3) in addition, is respectively corresponding to the response message of N data package to confirming the payment received message or the conditional probability density function of the signal to noise ratio during payment received message not:

$p{\left(\mathrm{SNR}\right|\mathrm{RSSI},\mathrm{MCSs},\mathrm{ACKs}\left|\mathrm{NACKs}\right)}_N$

$=p{\left(\mathrm{SNR}\right|\mathrm{RSSI},\mathrm{MCSs},\mathrm{ACKs}\left|\mathrm{NACKs}\right)}_{N-1}\×\frac{p\left({\mathrm{ACK}}_N\right|\mathrm{SNR},{\mathrm{MCS}}_N)}{p\left({\mathrm{ACK}}_N\right|{\mathrm{MCS}}_N)}---\left(2\right)$

$p{\left(\mathrm{SNR}\right|\mathrm{RSSI},\mathrm{MCSs},\mathrm{ACKs}\left|\mathrm{NACKs}\right)}_N$

$=p{\left(\mathrm{SNR}\right|\mathrm{RSSI},\mathrm{MCSs},\mathrm{ACKs}\left|\mathrm{NACKs}\right)}_{N-1}\×\frac{1-p\left({\mathrm{ACK}}_N\right|\mathrm{SNR},{\mathrm{MCS}}_N)}{1-p\left({\mathrm{ACK}}_N\right|{\mathrm{MCS}}_N)}---\left(3\right)$

In other words, the transmission end when receiving the response message of N data package, according to corresponding to the conditional probability density function p of the signal to noise ratio of (N-1) individual data package (SNR|RSSI, MCSs, ACKs/NACKs) _N-1Reach the conditional probability density function p (ACK of the response message that under each signal to noise ratio, receives N data package _N| SNR, MCS _N) or 1-p (ACK _N| SNR, MCS _N), obtain conditional probability density function p corresponding to the signal to noise ratio of N data package (SNR|RSSI, MCSs, ACKs/NACKs) _N

In addition, after the conditional probability density function of obtaining corresponding to the signal to noise ratio of (N-1) individual data package, the transmission end promptly selects to be used for the modulation and the encoding mechanism MCS of N data package according to this _N,, upgrade transmission rate through changing modulation and encoding mechanism.Then, the transmission end behind the response message that receives corresponding to N data package, obtain corresponding to N data package the conditional probability density function of signal to noise ratio, and then select to be used for the modulation and the encoding mechanism MCS of (N+1) individual data package according to this _(N+1), to upgrade transmission rate, the rest may be inferred.About the modulation and the system of selection of encoding mechanism, please refer to Chinese platform] No. the 97146118th, gulf patent application, do not detail at this.Compared to known technology; The transmission rate adjusting method that this case applicant is proposed is in real time according to the response message of each data packet; Select best modulation and encoding mechanism; Make the transmission rate optimization, and under the situation that does not influence throughput of transmissions, converge to best transfer rate more quickly.

Can know by formula (1), (2) or (3), in order to upgrade the conditional probability density function of signal to noise ratio, the transmission end must with p (SNR|RSSI, MCSs, ACKs/NACKs) _N-1With p (ACK _N| SNR, MCS _N) multiply each other.In other words, the phase multiplication of conditional probability density function must be carried out based on the sampling point of each signal to noise ratio in the transmission end.Please refer to Fig. 1, Fig. 1 uses a known modulation and an encoding mechanism for the transmission end of a known IEEE 802.11n wireless telecommunication system, under each signal to noise ratio, receives the sketch map of the conditional probability density function of confirming payment received message.With Fig. 1 is example, and the scope of signal to noise ratio is 0～30dB, and as if the 0.1dB that is spaced apart of the signal to noise ratio of taking a sample, the system of transmission end need carry out the phase multiplication of hundreds of times conditional probability density function, just can obtain the conditional probability density function of signal to noise ratio.Under this situation, the complexity of system's computing is quite high, and the operational data amount is also big, effectively the operational paradigm of elevator system.

Summary of the invention

Therefore, main purpose of the present invention promptly is to provide a kind of approaching method of signal-to-noise ratio flexible message.

The present invention is the approaching method that discloses a kind of signal-to-noise ratio flexible message of the transmission end that is used for communication system, includes the conditional probability density function of generation corresponding to response message; This conditional probability density function of probability of use distributed model convergence is with mean value and the variance of obtaining this probability density function and this probability density function; And according to first mean value and first variance of this mean value, this variance and first probability density function; Produce second mean value and second variance of second probability density function; This first probability density function convergence is corresponding to the conditional probability density function of the signal to noise ratio of last data package, and this second probability density function convergence is corresponding to the conditional probability density function of the signal to noise ratio of this data packet.

Description of drawings

Fig. 1 uses a known modulation and an encoding mechanism for the transmission end of a known IEEE 802.11n wireless telecommunication system, under each signal to noise ratio, receives the sketch map of the conditional probability density function of confirming payment received message.

Fig. 2 is the sketch map of the embodiment of the invention one flow process.

Fig. 3 is the sketch map of the embodiment of the invention one Gaussian probability-density function.

[main element label declaration]

20 flow processs

200,202,204,206,208,210 steps

Embodiment

Please refer to Fig. 2, Fig. 2 is the sketch map of the embodiment of the invention one flow process 20.Flow process 20 is used for the transmission end of communication system, is used for improving the transmission rate adjusting method that this case applicant is disclosed for No. 97146118 in the TaiWan, China patent application, the system loading when obtaining the conditional probability density function of signal to noise ratio with reduction.Flow process 20 comprises following steps:

Step 200: beginning.

Step 202: in not receiving any affirmation payment received message as yet or not during payment received message; Use the initial condition probability density function of Gaussian distribution (Gaussian Distribution) convergence one signal to noise ratio, level off to Gaussian probability-density function and the mean value M of this Gaussian probability-density function of initial condition probability density function of this signal to noise ratio to obtain ₀And variance V ₀

Step 204: detect response message, N >=1 corresponding to N the data package that has transmitted.

Step 206: produce conditional probability density function corresponding to this response message.

Step 208: use this conditional probability density function of Gaussian distribution convergence, with mean value and the variance of obtaining Gaussian probability-density function and this Gaussian probability-density function.

Step 210: according to the mean value M of this mean value, this variance and first Gaussian probability-density function _N-1And variance V _N-1, produce the mean value M of second Gaussian probability-density function _NAnd variance V _N, and get back to step 204; Wherein, this first Gaussian probability-density function convergence is corresponding to the conditional probability density function of the signal to noise ratio of (N-1) individual data package, and this second Gaussian probability-density function convergence is corresponding to the conditional probability density function of the signal to noise ratio of N data package.

The formula (1) of the conditional probability density function of citation signal to noise ratio, as follows:

$p\left(\mathrm{SNR}\right|\mathrm{RSSI},\mathrm{MCSs},\mathrm{ACKs}\left|\mathrm{NACKs}\right)$

$=p\left(\mathrm{SNR}\right|\mathrm{RSSI})\underset{i=0}{\overset{N}{\mathrm{\Π}}}\frac{p\left(\mathrm{ACKi}\right|\mathrm{NACKi}|\mathrm{SNR},\mathrm{MCSi})}{p\left(\mathrm{ACKi}\right|\mathrm{NACKi}\left|\mathrm{MCSi}\right)}---\left(1\right)$

Meaning about each variable in the formula (1) please refer to aforementioned.Please note; P (SNR|RSSI) is the transmission end in the affirmation payment received message of not receiving any data packet or not during payment received message; The conditional probability density function of the signal to noise ratio under the different received signal strength indication value, i.e. the initial condition probability density function of the signal to noise ratio in the step 202.When the transmission end of wireless telecommunication system begins to transmit data packet, relative, the transmission end can receive that also the data packet by the receiving terminal passback receives the response message of success or not, comprises and confirms that payment received message reaches not payment received message.P (ACKi/NACKi|SNR; MCSi) be when transmitting i data package with known modulation and encoding mechanism MCSi; Under each signal to noise ratio, receive and confirm the payment received message or the conditional probability density function of payment received message not, be called for short the conditional probability density function of response message among the Yu Houwen.

At first, the transmission end is not received any response message as yet, selects transmission rate according to the conditional probability density function of signal to noise ratio yet, and (SNR/RSSI, ACKs MCSs) equal p (SNR/RSSI) to p at this moment.In step 202, Gaussian distribution convergence p (SNR/RSSI) is used in the transmission end, levels off to Gaussian probability-density function and the mean value M thereof of p (SNR/RSSI) to obtain ₀And variance V ₀Please note the characteristic of Gaussian distribution earlier at this, a Gaussian probability-density function and another Gaussian probability-density function multiplied result still are Gaussian probability-density function; The mean value of the Gaussian probability-density function of result of product and variance can be obtained according to the mean value and the variance calculating of two Gaussian probability-density functions that multiply each other; In addition, if obtained mean value and variance, the Gaussian probability-density function that can push away correspondingly.

The transmission end is when receiving the response message of each data packet, and execution in step 204 is to step 210.When the transmission end receives the response message of N data package, in step 204, response message is detected for confirming payment received message or payment received message not in the transmission end.If response message is for confirming payment received message, in step 206, the transmission end produces the conditional probability density function p (ACK that confirms payment received message _N| SNR, MCS _N); If response message is payment received message not, or in Preset Time, do not receive affirmation payment received message, the transmission end produces the not conditional probability density function p (NACK of payment received message _N| SNR, MCS _N), equal 1-p (ACK _N| SNR, MCS _N).In step 208, the conditional probability density function p (ACK of Gaussian distribution convergence response message is used in the transmission end _N/ NACK _N| SNR, MCS _N), to obtain corresponding Gaussian probability-density function and mean value and variance, be expressed as mean (MCS respectively _N, ACK/NACK) and var (MCS _N, ACK/NACK).

Please refer to the characteristic of aforesaid formula (1), (2), (3) and Gaussian distribution probabilistic model, with further understanding step 210.In step 210, the transmission end is according to the mean value mean (MCS of step 208 gained _N, ACK/NACK), variance var (MCS _N, ACK/NACK) and convergence corresponding to the conditional probability density function p of the signal to noise ratio of (N-1) individual data package (SNR/RSSI, ACKs, MCSs) _(N-1)The mean value M of Gaussian probability-density function _N-1And variance V _N-1, produce mean value M _NAnd variance V _NMean value M _NAnd variance V _NFor convergence corresponding to the conditional probability density function p of the signal to noise ratio of N data package (SNR/RSSI, ACKs, MCSs) _NThe mean value and the variance of Gaussian probability-density function.Mean value M _NAnd variance V _NRepresent respectively as shown in the formula (4) and formula (5):

$M_N=\frac{M_{N-1}\×\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})+V_{N-1}\×\mathrm{mean}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})}{\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})+V_{N-1}}---\left(4\right)$

$V_N=\frac{V_{N-1}\×\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})}{\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})+V_{N-1}}---\left(5\right)$

In mean value M _NAnd variance V _NAfter the generation, step 204 is got back in the transmission end, detects the response message of next data packet.With the 1st data package is the example explanation, N=1, MCS ₁The expression transmission end is used for transmitting the modulation and the encoding mechanism of the 1st data package.When the transmission end received the response message of the 1st data package, response message was detected for confirming payment received message or payment received message not in the transmission end, and produces the conditional probability density function p (ACK of a response message according to this ₁/ NACK ₁| SNR, MCS ₁), it possibly equal p (ACK ₁| SNR, MCS ₁) or equal 1-p (ACK ₁| SNR, MCS ₁).Next, Gaussian distribution convergence p (ACK is used in the transmission end ₁/ NACK ₁| SNR, MCS ₁), level off to p (ACK to obtain ₁/ NACK ₁| SNR, MCS ₁) the mean value mean (MCS of Gaussian probability-density function ₁, ACK/NACK) and variance var (MCS ₁, ACK/NACK).Next, according to step 210, the transmission end produces mean value M ₁And variance V ₁, it is mean value and the variance of convergence corresponding to the Gaussian probability-density function of the conditional probability density function of the signal to noise ratio of the 1st data package.Mean value M ₁And variance V ₁Represent respectively as shown in the formula (6) and formula (7):

$M_1=\frac{M_0\×\mathrm{var}({\mathrm{MCS}}_1,\mathrm{ACK}/\mathrm{NACK})+V_0\×\mathrm{mean}({\mathrm{MCS}}_1,\mathrm{ACK}/\mathrm{NACK})}{\mathrm{var}({\mathrm{MCS}}_1,\mathrm{ACK}/\mathrm{NACK})+V_0}---\left(6\right)$

$V_1=\frac{V_0\×\mathrm{var}({\mathrm{MCS}}_1,\mathrm{ACK}/\mathrm{NACK})}{\mathrm{var}({\mathrm{MCS}}_1,\mathrm{ACK}/\mathrm{NACK})+V_0}---\left(7\right)$

Therefore; When the transmission end receives the response message corresponding to the 2nd data package; The transmission end is according to step 204; Detect response message for confirming payment received message or payment received message not,, produce the mean value M of convergence corresponding to the Gaussian probability-density function of the conditional probability density function of the signal to noise ratio of the 2nd data package then according to step 206 to step 210 ₂And variance V ₂, the rest may be inferred.

Please refer to Fig. 3, Fig. 3 is the sketch map of the embodiment of the invention one Gaussian probability-density function E (SNR).Can know that by Fig. 3 the curve of Gaussian probability-density function E (SNR) levels off to conditional probability density function p (ACK|SNR, curve MCS=2) among Fig. 1.Generally, (ACK|SNR, curve MCS=2) are also dissimilar, but (with Fig. 3, be p (ACK|SNR, scope MCS=2)=0.6～0.95), the curve approximation of E (SNR) is in p (ACK|SNR, curve MCS=2) in critical range with p for E (SNR).Therefore, Gaussian probability-density function can be used to the conditional probability density function of convergence corresponding to the response message of data packet.

In brief; According to the embodiment of the invention; The conditional probability density function of Gaussian distribution convergence response message is used, the mean value of the Gaussian probability-density function of convergence and variance to obtain in the transmission end when the response message that receives corresponding to data packet; And then, convert the mean value of Gaussian probability-density function and the phase multiplication of variance into the phase multiplication between the conditional probability density function.It should be noted that; Use the conditional probability density function of Gaussian distribution convergence response message to be merely one embodiment of the invention; In other embodiment of the present invention, other suitable probability Distribution Model, the conditional probability density function of convergence response message can be used in the transmission end.

This case applicant in the transmission rate adjusting method that the TaiWan, China patent application is disclosed for No. 97146118; In order to upgrade the conditional probability density function of signal to noise ratio; The transmission end must be based on the sampling point of each signal to noise ratio; Carry out the phase multiplication of conditional probability density function, can upgrade the conditional probability density function of signal to noise ratio, to select best transfer rate.Relatively; According to the embodiment of the invention; The transmission end only need be obtained and level off to the mean value and the variance of Gaussian probability-density function of conditional probability density function of response message, can produce to level off to the mean value and the variance of Gaussian probability-density function of conditional probability density function of signal to noise ratio.Further; The transmission end can be according to this mean value and variance; Try to achieve corresponding Gaussian probability-density function, and Gaussian probability-density function is selected the modulation and the encoding mechanism of the data packet that next tendency to develop send in view of the above, and next data packet can be transmitted with best transfer rate.In other words, the phase multiplication of conditional probability density function must not carried out based on the sampling point of each signal to noise ratio in the transmission end.In comparison, the data operation quantity the when embodiment of the invention can significantly reduce the conditional probability density function that upgrades signal to noise ratio reduces system loading.About the system of selection of modulation with encoding mechanism, be exposed in the TaiWan, China patent application No. 97146118, run at this.

In sum; When the embodiment of the invention is the response message that receives in the transmission end of wireless telecommunication system corresponding to data packet; Use the conditional probability density function of suitable probability Distribution Model convergence corresponding to the response message of data packet; And then, convert the mean value of Gaussian probability-density function and the phase multiplication of variance into the phase multiplication between the conditional probability density function.Thus, the data operation quantity the when embodiment of the invention significantly reduces the conditional probability density function that upgrades signal to noise ratio reduces system loading.

The above is merely preferred embodiment of the present invention, and all equalizations of being done according to claim scope of the present invention change and modify, and all should belong to covering scope of the present invention.

Claims (6)

1. the approaching method of the signal-to-noise ratio flexible message of a transmission end that is used for communication system includes:

Generation is corresponding to the conditional probability density function of the response message of N data package;

This conditional probability density function of this response message of probability of use distributed model convergence is with mean value and the variance of obtaining probability density function and this probability density function; And

First mean value and first variance according to this mean value, this variance and first probability density function; Produce second mean value and second variance of second probability density function; This first probability density function convergence is corresponding to the conditional probability density function of the signal to noise ratio of last data package, and this second probability density function convergence is corresponding to the conditional probability density function of the signal to noise ratio of this N data package;

Wherein this second mean value represent as shown in the formula:

$M_N=\frac{M_{N-1}\×\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})+V_{N-1}\×\mathrm{mean}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})}{\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})+V_{N-1}}$

Wherein N is the transmission sequence number of this N data package, (N-1) is the transmission sequence number of this previous data packet, MCS _NBe to use modulation and encoding mechanism in this N data package, ACK/NACK is this response message corresponding to this N data package, mean (MCS _N, ACK/NACK) be this mean value, var (MCS _N, ACK/NACK) be this variance, M _N-1Be this first mean value, V _N-1It is this first variance;

Wherein this second variance represent as shown in the formula:

$V_N=\frac{V_{N-1}\×\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})}{\mathrm{var}({\mathrm{MCS}}_N,\mathrm{ACK}/\mathrm{NACK})+V_{N-1}}.$

2. approaching method according to claim 1; Before generation this conditional probability density function corresponding to the response message of N data package; Also include the initial condition probability density function that uses this probability Distribution Model convergence one signal to noise ratio, the initial condition probability density function of this signal to noise ratio is the probability density function of the signal to noise ratio under the different received signal strength indication value.

3. approaching method according to claim 1, wherein this probability Distribution Model is a Gaussian distribution, this probability density function, this first probability density function and this second probability density function are Gaussian probability-density functions.

4. approaching method according to claim 1, wherein this response message is to confirm payment received message ACK or payment received message NACK not.

5. approaching method according to claim 1; When wherein this conditional probability density function of this response message is the known modulation of this transmission end use and this data packet of encoding mechanism transmission, under each signal to noise ratio, receive the conditional probability density function of this response message.

6. approaching method according to claim 1, wherein this response message is corresponding to a data packet that has transmitted.

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