CN105846959B - Satellite adaptive code modulation method based on channel quality prediction - Google Patents
Satellite adaptive code modulation method based on channel quality prediction Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1851—Systems using a satellite or space-based relay
- H04B7/18513—Transmission in a satellite or space-based system
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1853—Satellite systems for providing telephony service to a mobile station, i.e. mobile satellite service
- H04B7/18539—Arrangements for managing radio, resources, i.e. for establishing or releasing a connection
- H04B7/18543—Arrangements for managing radio, resources, i.e. for establishing or releasing a connection for adaptation of transmission parameters, e.g. power control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0015—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy
- H04L1/0017—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy where the mode-switching is based on Quality of Service requirement
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0033—Systems modifying transmission characteristics according to link quality, e.g. power backoff arrangements specific to the transmitter
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/024—Channel estimation channel estimation algorithms
- H04L25/025—Channel estimation channel estimation algorithms using least-mean-square [LMS] method
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Abstract
The present invention provides a kind of satellite adaptive code modulation method based on channel quality prediction, first satellite end periodically complete the prediction to channel SNRs using signal-to-noise ratio feedback result combination LMS algorithm；Satellite end is transmitted using the ACM that signal-to-noise ratio predicted value replaces value of feedback to carry out DVB-S2X after LMS algorithm is stablized；When the predicted value of continuous n times SNR both fallen within -5 arrive 5dB regions, then optimize subset ACM adjustment；When the predicted value of continuous m times SNR all dropped out -5 arrive 5dB regions, then exit majorized subset ACM, return to the ACM in traditional DVB-S2X.The present invention overcomes the delay problems of feedback link, the frequency of feedback is effectively reduced by channel estimating, it also avoids since feedback link quality is bad or the larger unmatched problem of bring ACM of time delay, the rain mode that declines is descended quickly be switched to corresponding modulating-coding.
Description
Technical field
The present invention relates to a kind of satellite code modulator approaches.
Background technique
Satellite communication have become for people's lives, scientific research, the indispensable a part in fields such as military affairs, especially in war
In, effectively reliable battlefield communication is to obtain the important leverage of final victory.Complex electromagnetic environment and adaptive coding and modulating skill
Art has higher frequency spectrum resource utilization rate compared to fixed coding modulation technique, but the promotion of this utilization rate has been built upon
Accurately, reliably timely under the precondition of feedback information.International Telecommunication Association's distribution is Ka for the frequency range of Fixed-Satellite Service
Frequency range has 3.5GHz band resource, can provide more message capacities.But since Ka frequency range is affected by what rain declined,
Rainfall generated moment decline in Ka frequency range reaches as high as more than ten dB, this is just to the adjusting range of adaptive strategy and adjustment
Time, more stringent requirements are proposed.
As shown in Figure 1, traditional coded modulation switchover policy is to arrive the instantaneous noise feedback that receiving end (terminal) calculates
Satellite end, but due to the variation of the time variation and reverse link circuit quality of satellite channel in feedback delay, lead to transmitting terminal (satellite
End) optimal code modulation mode can not be selected.It is taken it is therefore possible to use the method for channel estimating obtains channel state prediction value
For the method for transient channel estimated value, time delay adverse effect caused by system of feedback information is effectively reduced.In addition, with most
The granularity of the adaptive coding modulation (ACM) of new satellite standard DVB-S2X increasingly refines, adaptive when rain declines larger
The feedback frequency for answering coding modulation technique to need is higher, and feedback delay influences also bigger.If channel information cannot be timely
Feedback causes satellite end to use the code modulation mode of non-optimal, will cause the reduction of high bit error rate and handling capacity.Therefore,
It needs to establish the ACM Adaptive adjusting algorithm that rain declines under weather, reduces the feedback frequency, promote the timeliness of feedback information.
Summary of the invention
For overcome the deficiencies in the prior art, the present invention provides a kind of satellite adaptive coding and modulating based on channel estimating
Method realizes the prediction of subsequent time signal-to-noise ratio using least mean square algorithm (LMS, Least Mean Square), and using most
Optimize adaptive coding and modulating subset Adjusted Option, promote the accuracy of ACM and reduce feedback time, rapidly by modulating-coding
Mode and rain channel bad border of declining are adapted to, and the time delay and low signal-to-noise ratio bring that can effectively reduce reverse link influence.
The technical solution adopted by the present invention to solve the technical problems the following steps are included:
(1) satellite end predicts the signal-to-noise ratio of subsequent time with the feedback signal-to-noise ratio at several continuous moment based on LMS algorithm,
Obtain prediction signal-to-noise ratioWherein, WnFor weight vector, initial value be include null vector with
Machine vector,The value range of ρ is [1,3]；P is order, value 5
~10；SnFor the vector for feeding back SNR composition closest to the p at n+1 moment continuous moment, i.e. Sn=[sn, sn-1..., sn-p+1]；
(2) ifThen satellite end utilizesReplace snCarry out ACM transmission；Otherwise, s is continued withnIt carries out
ACM transmission；
(3) judge before current time n whether continuous q prediction signal-to-noise ratio and to feed back signal-to-noise ratio be all -5~5dB, q is not
Greater than 10, if so, using the ACM subset scheme that signal-to-noise ratio dynamic adjusting range is 3-5dB for -10dB~10dB, granularity
As majorized subset ACM, (4) are entered step；Otherwise, (5) are entered step；
(4) if continuous m prediction signal-to-noise ratio and feedback signal-to-noise ratio are less than -5dB or are greater than 5dB, m is not more than 7, then exits
Majorized subset ACM enters step (5)；Otherwise, satellite end continues to use majorized subset ACM, and circulation executes this step；
(5) satellite end is transmitted using the ACM of DVB-S2X, return step (1).
The value range that the value range of the q is 5~8, m is 3-5.
The beneficial effects of the present invention are:
1, the present invention overcomes the delay problems of feedback link, and the frequency of feedback is effectively reduced by channel estimating,
It avoids since feedback link quality is bad or the larger unmatched problem of bring ACM of time delay.
2, majorized subset's method of the invention can be well adapted for the rain weather lower channel that declines and quickly change, and increase particle
Degree, can reduce the feedback frequency, and the rain mode that declines is descended quickly be switched to corresponding modulating-coding.
3, inventive algorithm is stablized simple, facilitates hardware realization, may be used in engineering practice.
Detailed description of the invention
Fig. 1 is the schematic diagram of satellite link transmission；
Fig. 2 is implementation flow chart of the invention；
Fig. 3 (a) is that LMS predicts the result of linear signal-to-noise ratio and the comparison schematic diagram of practical signal-to-noise ratio；Fig. 3 (b) is linear
LMS predicts error schematic diagram under the conditions of channel variation；
Fig. 4 (a) is that LMS predicts that the result of signal-to-noise ratio is shown compared with practical signal-to-noise ratio under Rayleigh fading channel conditions
It is intended to；Fig. 4 (b) is LMS prediction error schematic diagram；
Fig. 5 (a) is to obtain using last moment instantaneous signal-to-noise ratio and using the signal-to-noise ratio that LMS algorithm is predicted for criterion
ACM throughput performance comparison schematic diagram；Fig. 5 (b) is to predict to obtain using last moment instantaneous signal-to-noise ratio and using LMS algorithm
Signal-to-noise ratio be the obtained ACM bit error rate performance comparison schematic diagram of criterion.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples, and the present invention includes but are not limited to following implementations
Example.
Reference Fig. 2, the adaptive modulation coding method proposed by the present invention based on LMS algorithm channel estimating, including it is as follows
Step:
(1) satellite end is completed using signal-to-noise ratio feedback result combination LMS algorithm to the pre- of channel SNRs (SNR) first
It surveys:
Satellite end is based on LMS algorithm and carries out channel estimating, according to the correlation between signal-to-noise ratio, with several continuous moment
Signal-to-noise ratio of the signal-to-noise ratio value of feedback based on LMS algorithm prediction subsequent time.Concrete implementation process are as follows: the letter of the n-th moment prediction
It makes an uproar ratioValue:
Wherein, WnFor weight vector (tap coefficient), initial value be it is random, can be set to null vector.P be order or
Tap number (general value 5-10).SnFor the vector for feeding back SNR composition closest to the p at n+1 moment continuous moment, i.e. Sn=
[sn, sn-1..., sn-p+1] weight vector more new formula are as follows:
Above formula is used to update weight vector W, by reaching the mean-square value of the error between true value and predicted value after successive ignition
To minimum.Wherein, the value of μ are as follows:
Wherein, the value range of ρ is [1,3].
When (2) current time feedback signal-to-noise ratio is equal to last moment prediction SNR (), satellite end is using in advance
Survey SNR valueReplace feedback SNR value snCriterion as ACM transmission；Otherwise, feedback SNR value s is continued withnIt is passed as ACM
Defeated criterion.
(3) whether q time continuous (q value suggested range 5-8 does not exceed 10) prediction SNR/ and feeds back before current time n
SNR has both fallen within -5 to 5dB region (signal-to-noise ratio statistical probability is greater than 98% when satellite channel rain declines), optimizes subset
ACM (declines mode) into rain；After declining mode into rain, the signal-to-noise ratio dynamic adjusting range of ACM by without using in DVB-S2X-
10dB to 20dB (granularity about 0.3dB), and it is adjusted to the subset side ACM that range -10dB is 3-5dB to 10dB granularity
Case see the table below, and be optional modulation coding scheme of the range from -10dB to 10dB in DVB-S2X, and it is full to select granularity wherein
The modulation coding scheme of sufficient 3-5dB enters step (4)；Otherwise, (5) are entered step.
(4) (m value suggested range 3-5, the prediction SNR/ feedback SNR not exceeded 7) have dropped out -5 and have arrived when m times continuous
Majorized subset ACM is exited in the region of 5dB, enters step (5)；Otherwise, satellite end continues to use majorized subset ACM.
(5) satellite end is transmitted using the ACM of DVB-S2X.Return step (1).
The specific implementation method of adaptive modulation coding method based on LMS algorithm channel estimating of the invention, illustrates
It is bright as follows:
Step 1, satellite end is periodically completed to channel SNRs using signal-to-noise ratio feedback result combination LMS algorithm first
(SNR) prediction: for example, the signal-to-noise ratio of the 5th moment predictionValue:
Wherein, WnFor weight vector (tap coefficient), it is initially set to null vector, p 5.SnFor closest to 5 of the n+1 moment
The vector of continuous moment signal-to-noise ratio value of feedback composition, i.e. Sn=[sn, sn-1..., sn-4].The more new formula of weight vector are as follows:
Above formula is used to update weight vector W, by reaching the mean-square value of the error between true value and predicted value after successive ignition
To minimum.Wherein, the value of μ are as follows:
Wherein, the value of ρ is 1.5.Assuming that passing through the signal-to-noise ratio that the prediction of the 5th moment is calculated aboveValue be
0.7dB。
Step 2, it is assumed that after 100 weight vector W iteration,Satellite end is predicted using signal-to-noise ratio
ValueReplace value of feedback s100Carry out the ACM transmission of DVB-S2X；
Step 3, it is assumed that continuous 5 SNR values occur is -1dB, 0.2dB, 0dB, 1.1dB, 0.5dB (i.e. continuous 5 SNR
Predicted value both fallen within -5 regions for arriving 5dB), decline mode into rain, it is assumed that ACM project setting is the ACM of granularity 4 or so
Subset scheme (- 10dB arrives 10dB), for example, final choice is the following table 1:
1 rain of the table mode that declines descends ACM subset scheme (granularity 4 or so)
| Modulation coding scheme | Signal-to-noise ratio (dB) |
| BPSK-S 1/5 | -9.9 |
| BPSK 1/5 | -6.1 |
| QPSK 4/15 | -2.24 |
| QPSK 32/45 | 3.66 |
| 8PSK 32/45 | 7.54 |
| 16APSK 32/45 | 9.81 |
Step 4, it is assumed that continuous 3 SNR values occur is 5dB, (the continuous 3 times areas for not arriving 5dB -5 5.6dB, 7dB
Domain), majorized subset ACM is exited, the ACM in traditional DVB-S2X is returned to.
Effect of the invention can be further illustrated by emulation:
A. simulated conditions
The signal-to-noise ratio of subsequent time is predicted in emulation using LMS algorithm.Simulation time is 1000s, it is assumed that every 1s transmitting terminal to
Receiving end sends a data, and every receiving end 1s carries out the feedback transmission of a signal-to-noise ratio (SNR) estimation value, feedback transmission to transmitting terminal
Information is without error code.Signal bandwidth is set as 750MHz.Assuming that signal-to-noise ratio (SNR) estimation precision is 0.3dB.Emulate the ACM scheme such as table used
Shown in 2.It is assumed that the bit error rate of corresponding code modulation mode is 10 in the section SNR-6, in the section SNR more using signal-to-noise ratio
The bit error rate of higher leveled code modulation mode is 10-4(such as QPSK 1/3 bit error rate in -1.79 < SNR≤- 0.77 is 10-6, in SNR≤- 1.79, the bit error rate is 10-4)。
The section table 2SNR and its corresponding coded modulation scheme
| Coded modulation scheme | Spectrum efficiency/(bits-1·Hz-1) | The section SNR/dB |
| QPSK 1/4 | 0.49 | SNR≤-1.79 |
| QPSK 1/3 | 0.65 | - 1.79 < SNR≤- 0.77 |
| QPSK 2/5 | 0.78 | - 0.77 SNR≤0.35 < |
| QPSK 1/2 | 0.98 | 0.35 SNR≤1.61 < |
| QPSK 3/5 | 1.18 | 1.61 SNR≤2.66 < |
| QPSK 2/3 | 1.32 | 2.66 SNR≤3.56 < |
| QPSK 3/4 | 1.48 | 3.56 SNR≤4.35 < |
| QPSK 4/5 | 1.58 | 4.35 SNR≤4.93 < |
| QPSK 5/6 | 1.65 | 4.93 SNR≤5.34 < |
| QPSK 8/9 | 1.76 | 5.34 SNR≤6.31 < |
| QPSK 9/10 | 1.78 | 6.31 SNR≤6.52 < |
| 8PSK 2/3 | 1.98 | 6.52 SNR≤7.26 < |
| 8PSK 3/4 | 2.22 | 7.26 SNR≤8.44 < |
| 16APSK 2/3 | 2.63 | 8.44 SNR≤9.16 < |
| 16APSK 3/4 | 2.96 | 9.16 SNR≤10.45 < |
| 16APSK 4/5 | 3.16 | 10.45 SNR≤11.32 < |
| 16APSK 5/6 | 3.30 | 11.32 SNR≤12.17 < |
| 32APSK 3/4 | 3.70 | 12.17 SNR≤12.81 < |
| 32APSK 4/5 | 3.95 | 12.81 SNR≤13.96 < |
| 32APSK 5/6 | 4.11 | 13.96 SNR≤14.98 < |
| 32APSK 8/9 | 4.39 | 14.98 SNR≤15.87 < |
| 32APSK9/10 | 4.45 | 15.87 < SNR |
B. simulation result
Fig. 3 (a) is that LMS predicts the result of linear signal-to-noise ratio compared with practical signal-to-noise ratio.It can be found that after algorithmic stability,
Predicted value can track the variation of practical signal-to-noise ratio well.
Fig. 3 (b) is that LMS predicts error under linear channel change condition, it can be seen that LMS prediction algorithm is for linearly believing
It makes an uproar than there is good estimated performance after algorithmic stability.
Fig. 4 (a) is that LMS predicts the result of signal-to-noise ratio compared with practical signal-to-noise ratio under Rayleigh fading channel conditions.
It can be found that predicted value can track the variation of practical signal-to-noise ratio well after algorithmic stability.
Fig. 4 (b) is LMS prediction error, it can be seen that LMS prediction algorithm is pre- after algorithmic stability for linear signal-to-noise ratio
It surveys error and is approximately equal to 0.
It is that criterion obtains that Fig. 5 (a), which is using last moment instantaneous signal-to-noise ratio and using the signal-to-noise ratio that LMS algorithm is predicted,
ACM throughput performance compare.Wherein, take the channel situation of 560s~710s period as research object.It can by simulation result
To find out, since prediction signal-to-noise ratio is closer to the true signal-to-noise ratio of subsequent time, in the case where signal-to-noise ratio quickly increases, utilize
It predicts that obtained signal-to-noise ratio can effectively weaken the influence of time delay as criterion, so that ACM system is obtained more preferable throughput performance, mention
The high utilization rate of channel resource.
It is that criterion obtains that Fig. 5 (b), which is using last moment instantaneous signal-to-noise ratio and using the signal-to-noise ratio that LMS algorithm is predicted,
ACM bit error rate performance compare.Wherein, take the channel situation of 260s~430s and 880s~1000s period as research respectively
Object.It is quick in signal-to-noise ratio since prediction signal-to-noise ratio is closer to the true signal-to-noise ratio of subsequent time it can be seen from simulation result
In the case where reduction, the signal-to-noise ratio obtained using prediction can effectively weaken the influence of time delay as criterion, obtain ACM system
More preferable bit error rate performance reduces the handling capacity damage of ACM system.
In conclusion the criterion using signal-to-noise ratio predicted value as ACM can obtain in the case where LMS prediction algorithm is stablized
Obtaining better throughput of system and lower bit error rate performance can be obtained when link signal-to-noise ratio quickly increases using prediction algorithm
Obtain better throughput of system performance；When link signal-to-noise ratio quickly reduces, the lower bit error rate can be obtained using prediction algorithm
Performance, to obtain better service quality.
Claims (2)
1. a kind of satellite adaptive code modulation method based on channel quality prediction, it is characterised in that include the following steps:
(1) satellite end is obtained with the feedback signal-to-noise ratio at several continuous moment based on the signal-to-noise ratio of LMS algorithm prediction subsequent time
Predict signal-to-noise ratioWherein, WnFor weight vector, initial value be include null vector it is random to
Amount,The value range of ρ is [1,3]；P is order, and value is 5~10；
SnFor the vector for feeding back SNR composition closest to the p at n+1 moment continuous moment, i.e. Sn=[sn, sn-1..., sn-p+1]；
(2) ifThen satellite end utilizesReplace snCarry out ACM transmission；Otherwise, s is continued withnCarry out ACM biography
It is defeated；
(3) judge before current time n whether continuous q prediction signal-to-noise ratio and to feed back signal-to-noise ratio be all -5~5dB, q is not more than
10, if so, using the ACM subset scheme conduct that signal-to-noise ratio dynamic adjusting range is 3-5dB for -10dB~10dB, granularity
Majorized subset enters step (4)；Otherwise, (5) are entered step；
(4) if continuous m prediction signal-to-noise ratio and feedback signal-to-noise ratio are less than -5dB or are greater than 5dB, m is not more than 7, then exits optimization
Subset enters step (5)；Otherwise, satellite end continues to use majorized subset, and circulation executes this step；
(5) satellite end is transmitted using the ACM of DVB-S2X, return step (1).
2. the satellite adaptive code modulation method according to claim 1 based on channel quality prediction, it is characterised in that:
The value range that the value range of the q is 5~8, m is 3-5.
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| CN109525299B (en) * | 2018-10-24 | 2020-08-04 | 清华大学 | Satellite communication system and communication method for adaptive coding modulation optimization |
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| CN110505029B (en) * | 2019-07-31 | 2022-01-07 | 北京秋石科技有限公司 | Millimeter wave band dynamic link self-adaption method and management system based on rainfall intensity |
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