CN102833019A - Method for acquiring signal-to-noise ratio from cognitive radio system - Google Patents
Method for acquiring signal-to-noise ratio from cognitive radio system Download PDFInfo
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- CN102833019A CN102833019A CN2012103216403A CN201210321640A CN102833019A CN 102833019 A CN102833019 A CN 102833019A CN 2012103216403 A CN2012103216403 A CN 2012103216403A CN 201210321640 A CN201210321640 A CN 201210321640A CN 102833019 A CN102833019 A CN 102833019A
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Abstract
The invention discloses a method for acquiring a signal-to-noise ratio from a cognitive radio system. Cognitive radio comprises three major elements, which are perception, self-adaption and learning respectively. The method relates to the fields of self-adaptive control and self-adaptive selection of the cognitive radio system. The invention provides a quick blind signal-to-noise ratio estimation method. The signal-to-noise ratio can be quickly estimated by using any signal in a communication process, and the estimated signal-to-noise is uploaded to a corresponding node, and the signal-to-noise estimation of the node is finished while the uploaded information is received by the node. In order to realize self-adaption of rate and frequency to realize effective transmission, self-adaptive control is realized by estimating and learning the channel state in real time; the optimal communication frequency point and the communication rate can be self-adaptively selected; and the communication is performed with the optimal rate and the optimal frequency point by the system under the condition of uninterrupted communication.
Description
Technical field
The present invention relates to the self adaptation of cognitive radio technology, relate in particular to the channel estimation technique and the method for cognition wireless electrical domain.
Background technology
Cognitive radio system is a kind of system's its operating environment knowledge relevant with geographical environment of acquisition that allows, and confirms the radio system of policy and its internal state; In order to realize predefined target, it can be according to the knowledge of obtaining dynamic, autonomous its operating parameter of adjustment and agreement, and from the result who obtains, learns.The purpose that cognitive radio proposes is in order more effectively to utilize resource such as frequency spectrum, realizes more effectively and communicates by letter reliably with Limited resources.
Signal to noise ratio (snr) is the ratio of signal strength signal intensity and background noise, is the important parameter that characterizes the characteristic of channel.In the practical application of communication system, functions such as the iterative decoding of the identification of modulation signal, Turbo Code, power control, Adaptive Modulation switching, self adaptation handover all need SNR estimation accurately.
Estimated snr is generally handled the back through data analysis to received signal and is obtained.These data maybe be for known for receiver, perhaps the unknown.Through unknown data or analyze to received signal and draw SNR estimation, be referred to as blind estimation, the general not throughput of busy channel.This type of estimator is non-data-aided, when SNR estimation depends on the priori of transmission data, is referred to as the auxiliary estimator of data.Performance based on data-aided estimator is more superior.
In this system, its application background is to make system pass through the perception of surrounding environment and foresee self communication capacity; Can be according to the variation and/or the autonomous adjustment transmission parameter and the agreement of self communication target of environment.Node at first initiatively carries out the channel cognition; Through the cognitive waveform of special channel these 5 alternative channels are carried out cognition (each terminal all cognitive a time); The channel of selecting a best through adaptive strategy is as communication channel, and confirms that the traffic rate between each terminal and the node reaches the purpose of Adaptive Transmission.
Summary of the invention
The objective of the invention is to be to provide a kind of method that cognitive radio system obtains signal to noise ratio that is used for.This method still can be used for the system of broadband wireless communication of other modulation system equally to the linear FM signal design.This method is through the SNR estimation of carrying out to the signal optimum sampling point, and is uploaded to node after averaging and makes node reach the purpose of effective transmission according to Adaptive Transmission and selection strategy.
The present invention is achieved in that its workflow is following:
(1) the node transmitting channel is estimated signaling, and channel estimating is also carried out to the terminal in the terminal that poll has inserted;
(2) linear FM signal received of end-on is carried out the demodulation despreading, and obtains optimum sampling point through bit timing;
(3) obtain the second order distance and the quadravalence distance of linear FM signal respectively through optimum sampling point, and calculate the mean value of linear FM signal second order distance and quadravalence distance by the time average of receiving sequence;
(4) obtain the SNR estimation value of this section period receiving sequence according to the mean value calculation of the second order distance of linear FM signal and quadravalence distance;
(5) repeating step (3) obtains N SNR estimation value to (4), and N SNR estimation value averaged obtains SNR estimation mean value, is the channel signal to noise ratio of current frequency; Wherein, N is the positive integer greater than 1;
(6) node carries out above-mentioned SNR estimation respectively to a plurality of frequencies at terminal, obtains each frequency SNR estimation value;
(7) terminal is uploaded to node with the SNR estimation value of a plurality of frequencies; Through the same SNR estimation of accomplishing a plurality of frequencies of incidental information node; Node is through frequency and the rate selection strategy is estimated by this locality and the estimated result at terminal is selected a best frequency; And notify all terminals, and each terminal polling registration, registration begins to begin to communicate by letter with speed according to the frequency of the best after finishing.
Wherein in the step (4) according to the SNR estimation value of the mean value picked up signal of the second order distance of the signal that obtains and quadravalence distance, be to adopt following formula calculating:
M wherein
2, M
4Be respectively the second order anomaly average and the quadravalence anomaly average of signal.
In order better to represent snr value with limited bit wide, generally be translated into the form of dBm in the Project Realization, and be used as final signal to noise ratio transmission numerical value according to traffic rate and the certain correction value of pattern adding in transmission course.
Δ wherein
ModifyRevise according to channel situation, the value that need revise for different traffic rates and pattern can have change.
Wherein, the waveform of the channel estimating signaling in the step (1) is 80kbps.
The present invention compared with prior art has following beneficial effect:
1, the channel estimating of utilization of the present invention need not sent training sequence, does not take the throughput of any channel, utilizes the transmission information of channel to carry out channel estimating, has improved bandwidth availability ratio to a certain extent.During with respect to the channel estimating of the prior information that depends on data, slightly descend on the performance, must cause overall system capacity to descend, improved bandwidth availability ratio and need not to send training but need to send training sequence.
2, in the SNR estimation computing of the present invention; In computational process, need not with signal power with just can calculate after noise power is separated; But utilize the formula of snr computation, and through getting the second order distance that receives signal and the mode of quadravalence distance noise energy is eliminated, directly calculate signal to noise ratio; Such compute mode simply and to random noise has certain mean effort, more can accurately calculate signal to noise ratio.
3, the method for obtaining signal to noise ratio of the present invention, it is further characterized in that and can be used for burst, need not synchronizing information, after obtaining the optimum sampling point of signal, can carry out SNR estimation at any time.
4, the present invention is directed to and feed back to node after application in the cognitive radio system is estimated the terminal to finish; Node utilizes the transmission information at terminal to carry out channel estimating again in this transmission course; What carry out designing when adaptation rate and frequency are selected is to select according to terminal and the two-way estimated result of node; Thereby change speed and frequency, better utilization channel information.
Description of drawings
Fig. 1 is realization flow figure of the present invention.
Fig. 2 is a signal-to-noise ratio estimation algorithm step sketch map.
Fig. 3 is a signal to noise ratio simulation performance curve.
Embodiment
With reference to Fig. 1, Fig. 1 is the realization flow figure of system of the present invention.
(1) behind the system boot, the node transmitting channel is estimated signaling, and channel estimating is also carried out to the terminal in the terminal that poll has inserted; Usually in order to guarantee that the terminal can receive information, can in standby message, carry out strong error correction coding to station number.
(2) linear FM signal received of end-on is carried out the demodulation despreading, and obtains optimum sampling point through bit timing;
The linear FM signal that end-on is received at first carries out being divided into two paths of signals after the down-conversion; Once more through obtaining the spread-spectrum signal of four samplings behind low pass filter and the matched filter; That need do this moment carries out despreading and bit timing to signal exactly; And carry out bit timing through flywheel and obtain optimum sampling point, so just accomplished bit timing, utilize the information of best sampling point just can carry out SNR estimation.
(3) obtain the second order distance and the quadravalence distance of linear FM signal respectively through optimum sampling point, and calculate the mean value of linear FM signal second order distance and quadravalence distance by the time average of receiving sequence;
(4) obtain the SNR estimation value of this section period receiving sequence according to the mean value calculation of the second order distance of linear FM signal and quadravalence distance;
Fig. 2 is a signal-to-noise ratio estimation algorithm step sketch map.
A: the SNR estimation module is at first carried out second order distance, quadravalence apart from computing after receiving demodulating information, and the summation of noise energy and signal energy is done certain mean value.
In practical application, second order and quadravalence amount are that the time average by receiving sequence calculates, and wherein L is the length of receiving sequence.
B: the further computing of carrying out of signal second order distance, quadravalence distance is at first drawn its mean-square value
C: for modulating modes such as mpsk signal under the complex channel condition and linear FM signals; In calculating process with signal energy and energy square through second order distance and quadravalence distance square and extracting operation eliminate the independent signal energy and the noise energy of the unknown; So just can utilize the gross energy of the signal of reception to obtain the SNR estimation value, be referred to as blind estimation.
D: in order in transmission course, better to represent snr value, ask the form of dBm, and add certain correction value and be used as final signal to noise ratio transmission numerical value with its conversion with limited bit wide.
Δ wherein
ModifyRevise according to channel situation, the value that need revise for different communication environments can have change.
(5) repeating step (3) obtains N SNR estimation value to (4), and N SNR estimation value averaged obtains SNR estimation mean value, is the channel signal to noise ratio of current frequency;
Wherein, N is the positive integer greater than 1;
(6) node carries out above-mentioned SNR estimation respectively to a plurality of frequencies at terminal, obtains each frequency SNR estimation value, when sending information owing to node station number is had strong error correction coding, and therefore value and the station number for SNR estimation has good corresponding relation;
(7) terminal is uploaded to node with the SNR estimation value of a plurality of frequencies; Through the same SNR estimation of accomplishing a plurality of frequencies of incidental information node; Node through frequency and rate selection strategy this locality is estimated and the estimated result of terminal end is selected a best frequency and subsidiary suggested rate, and notifies all user terminals.Each terminal polling registration, registration begins to communicate according to the frequency and the speed of the best after finishing.
In the present invention, system carries out computing with carrier synchronization and the synchronous optimum sampling signal of timing, and modulation system is a linear frequency modulation.Send into demodulator after the signal additional noise that modulation is come out, record signal power and noise power through power meter respectively herein, the SNR that therefore sends into the signal of demodulating unit is known.
Carrier synchronization is left the txt text with the optimum sampling point that regularly recovers synchronously; The SNR of these sampling points is known; These texts are used Matlab emulation; Draw the estimated value SNR that obtains with the M2M4 algorithm, can obtain the SNR estimation value shown in Figure 3 and the comparison diagram of actual SNR estimation.
Claims (4)
1. one kind is used for the method that cognitive radio system obtains signal to noise ratio, it is characterized in that: this method realizes based on linear FM signal, specifically may further comprise the steps:
(1) the node transmitting channel is estimated signaling, and channel estimating is also carried out to the terminal in the terminal that poll has inserted;
(2) linear FM signal received of end-on is carried out the demodulation despreading, and obtains optimum sampling point through bit timing;
(3) obtain the second order distance and the quadravalence distance of linear FM signal respectively through optimum sampling point, and calculate the mean value of linear FM signal second order distance and quadravalence distance by the time average of receiving sequence;
(4) obtain the SNR estimation value of this section period receiving sequence according to the mean value calculation of the second order distance of linear FM signal and quadravalence distance;
(5) repeating step (3) obtains N SNR estimation value to (4), and N SNR estimation value averaged obtains SNR estimation mean value, is the channel signal to noise ratio of current frequency; Wherein, N is the positive integer greater than 1;
(6) node carries out above-mentioned SNR estimation respectively to a plurality of frequencies at terminal, obtains each frequency SNR estimation value;
(7) terminal is uploaded to node with the SNR estimation value of a plurality of frequencies; Through the same SNR estimation of accomplishing a plurality of frequencies of incidental information node; Node is through frequency and the rate selection strategy is estimated by this locality and the estimated result at terminal is selected a best frequency; And notify all terminals, and each terminal polling registration, registration begins to begin to communicate by letter with speed according to the frequency of the best after finishing.
2. a kind of method that cognitive radio system obtains signal to noise ratio that is used for according to claim 1; It is characterized in that; According to the SNR estimation value of the mean value picked up signal of the second order distance of the signal that obtains and quadravalence distance, be to adopt following formula calculating in the step (4):
Wherein, M
2Be the second order anomaly average of signal, and M
4Quadravalence anomaly average for signal.
3. a kind of method that cognitive radio system obtains signal to noise ratio that is used for according to claim 2; It is characterized in that: in order in transmission course, better to represent snr value with limited bit wide; Be translated into the form of dBm, and add certain correction value and be used as final signal to noise ratio transmission numerical value
Δ wherein
MkdifyRevise according to channel situation.
4. a kind of method that cognitive radio system obtains signal to noise ratio that is used for according to claim 1, it is characterized in that: the waveform of the channel estimating signaling in the step (1) is 80kbps.
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CN103944605A (en) * | 2014-04-24 | 2014-07-23 | 重庆大学 | Signal to noise ratio estimation method for direct spread system |
CN105119666A (en) * | 2015-07-13 | 2015-12-02 | 中国电子科技集团公司第十研究所 | Channel quality adaptive joint estimation method |
CN112953676A (en) * | 2019-12-11 | 2021-06-11 | 鹤壁天海电子信息***有限公司 | Rate self-adaption method and node of multi-bandwidth frequency hopping equipment |
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CN103944605A (en) * | 2014-04-24 | 2014-07-23 | 重庆大学 | Signal to noise ratio estimation method for direct spread system |
CN105119666A (en) * | 2015-07-13 | 2015-12-02 | 中国电子科技集团公司第十研究所 | Channel quality adaptive joint estimation method |
CN105119666B (en) * | 2015-07-13 | 2017-08-04 | 中国电子科技集团公司第十研究所 | The method that adaptive combined channel estimates channel quality |
CN112953676A (en) * | 2019-12-11 | 2021-06-11 | 鹤壁天海电子信息***有限公司 | Rate self-adaption method and node of multi-bandwidth frequency hopping equipment |
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