CN102638730A - User perception based cross-layer optimization method for wireless video business - Google Patents
User perception based cross-layer optimization method for wireless video business Download PDFInfo
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Abstract
The embodiment of the invention relates to a user perception based cross-layer optimization method for wireless video business. Aiming at a wireless video transmission system, the invention aims at providing the user perception based cross-layer optimization method for the wireless video business, therefore, the minimum network transmission energy consumption can be achieved. The method specially comprises the following steps of: by taking user perception quality as a constraint condition, and the transmission energy consumption of all users as a target function, estimating video distortion from a video application module, obtaining the estimation of information channel distortion from a wireless transmission module, transmitting to a dynamic resource distributing module and computing peak value signal to noise ratio, obtaining the MOS (mean opinion score) value of each user according to a mapping model from PSNR (peak signal to noise ratio) to MOS, carrying out dynamic self-adaptive speed and power distribution on the user who meets an MOS limit value, till that an optimization strategy is obtained, and the whole network is minimum in energy consumption.
Description
Technical field
The present invention relates to the wireless video transmission field, relate in particular to a kind of based on the professional cross-layer optimizing method of the wireless video of user's perception.
Background technology
Along with the development of radio communication, transmit video industry broadcasting service and obtained extensively answering, for example video broadcasting business such as DTV, video conference, long-distance education obtain concern more and more widely.The professional main feature of video broadcasting is exactly from an information source same information flow to be sent to a plurality of information receivers, so how under the air-link resources condition of limited, making full use of bandwidth resources is primary and foremost purposes of present video broadcasting.Be the demand of catering to the green energy conservation network simultaneously, reducing network energy consumption under these conditions as much as possible also is one of development trend.
Usually the factor that influences the video transmission distortion has a lot of aspects, comprising: video coding, decoding, network QoS characteristic, transmission mechanism or the like.Carry out resource allocation from single protocol layer and have certain limitation, especially this resource-constrained, network that time variation is high of wireless network.Therefore, consider that the resource optimization of uniting at the different protocol interlayer distributes, and can obtain better effect through different factors to a plurality of aspects of influencing the video transmission distortion.
Layer resource optimization of striding of video transmission distributes difficult point that the following aspects is arranged: in the different agreement layer, choose the key parameter that influences the video transmission distortion; Set up key parameter and the mapping relations of final video distortion in each protocol layer; Analyze influencing each other and restricting relation of to exist between these parameters between the different agreement layer, set up the relational model of these parameters and final video distortion.Most of before transmission control optimizings of striding layer all concentrate on the combined optimization to physical layer and data link layer, have considered the objective quality parameter requirement fully.And that the video transmission of wireless network is normally specifically used is relevant, more help the optimization of overall network from the performance of the angle evaluation network of domestic consumer, so QoE (Quality of Experience) is decided to be one of evaluation criterion of video transmission quality.QoE is a user-perceptive quality; Through representing that near the method that quantizes the terminal use is to experience and impression professional and network; And research is illustrated under the low QoE situation, and 65% terminal use will initiatively attempt inserting another kind of access technology, and 22% user can abandon inserting; Only have 13% user will attempt inserting same network once more, visible good QoE guarantees the successful key of service operation.MOS (Mean Opinion Score) weighs one of technology as QoE, is used for the subjective food quality of weighing, and evaluates the video quality quality through the grade that picture quality is divided into 1-5, specifically sees table 1.
The present invention just is based on above-mentioned thought, and under the condition of user's perception constraint, energy consumption minimized with whole all users' of network transmission is target, and the wireless video transport service is carried out cross-layer optimizing.
Table 1
| MOS | Quality of service | User experience |
| 5 | Very good | Do not discover |
| 4 | Good | Discover a bit |
| 3 | All right | Dislike a little |
| 2 | Bad | Dislike |
| 1 | Non-constant | Dislike very much |
Summary of the invention
It is constraints based on the professional cross-layer optimizing method of the wireless video of user's perception with the user-perceptive quality that the present invention is intended to propose a kind of, is target function with all users' transmission energy consumption, and the cross-layer optimizing method through resource allocation makes total energy consumption minimum.
A kind of based on the professional cross-layer optimizing method of the wireless video of user's perception, may further comprise the steps:
Step 1: video sequence is stored in the digital server, and each user's in video sequence size, the broadcast multi-broadcasting transmission rate and power is carried out initialization, definition cross-layer optimizing (CLO) unit.
Step 2: calculate video source distortion and channel distortion.
Step 3: than (PSNR), and obtain each user's MOS value according to mapping model according to the distortion computation peak noise that obtains.
Step 4: judge that according to the constraints of each user's who calculates MOS value and given MOS threshold value this user is whether in service range.
Step 5: make the utility function value reach minimum through the self adaptation of transmission rate and power is distributed, promptly minimize the network energy consumption.
Step 6: based on the adaptive process of power and rate-allocation in the last step, we think to find the solution and are tending towards convergence during less than certain specific constant up to the changing value of utility function, and then self-optimizing iterative process finishes.
Step 7: self-optimizing final result-optimisation strategy is exported to wireless transmission unit.
Description of drawings
In order to set forth embodiments of the invention and existing technical scheme more clearly; Below the explanation accompanying drawing of using in technical scheme explanation accompanying drawing of the present invention and the description of the Prior Art is done simple introduction; Conspicuous; Under the prerequisite of not paying creative work, those of ordinary skills can obtain other accompanying drawing through this accompanying drawing.
Shown in Figure 1 is cross-layer optimizing in the embodiment of the invention (CLO) system architecture diagram;
Shown in Figure 2 is wireless video cross-layer optimizing realization flow figure in the embodiment of the invention;
Embodiment
Clearer for what technical scheme advantage of the present invention was described, do further to set forth in detail below in conjunction with the accompanying drawing specific embodiments of the invention, obvious described embodiment is part embodiment of the present invention, rather than whole embodiment.According to embodiments of the invention, those of ordinary skill in the art can realize every other embodiment of the present invention on without the basis of creative work, all belong to protection scope of the present invention.
In the following description, the technology that has nothing to do with the present invention is only done concise and to the point technical descriptioon or directly skip over.
Main thought of the present invention is: be constraints with the user-perceptive quality; Transmission energy consumption with all users is a target function; Estimate video distortion from the Video Applications module, obtain channel quality and video channel aberration estimation from wireless transport module, thereby obtain video distortion; It is sent to the Dynamic Resource Allocation for Multimedia module and calculates Y-PSNR (PSNR); Obtain each user's MOS value according to PSNR to the mapping model of MOS then, carry out dynamic adaptation rate and power division, until being optimized strategy and make whole network energy consumption minimum for the user who satisfies the MOS limit value.
Fig. 1 is cross-layer optimizing in the specific embodiment of the invention (CLO) system architecture diagram.Specifically:
As shown in Figure 1, the CLO system architecture is made up of Video Applications, cross-layer optimizing, Dynamic Resource Allocation for Multimedia and wireless transmission four parts.In order to guarantee the demand of user-perceptive quality, this scheme proposes to carry out to user MOS value the self adaptation distribution of transmission rate and through-put power.And this scheme has considered simultaneously that from application layer, physics and MAC layer extracting parameter value the distortion of video flowing is estimated and the MOS demand.
The Video Applications module is used to estimate that the video source distortion uses for the Dynamic Resource Allocation for Multimedia module; Wireless transport module is used for channel quality and video channel aberration estimation; The Dynamic Resource Allocation for Multimedia module calculates the corresponding peaks signal to noise ratio according to the information source distortion and the channel distortion that obtain, obtains each user's MOS value according to PSNR to the Linear Mapping of MOS then, then according to the MOS critical value; Carry out the distribution of transmission rate for satisfying the user who uses, send allocation result to the cross-layer optimizing module.The cross-layer optimizing unit is according to the power dissipation obj ectives utility function, user's power carried out continuous iteration upgrade, and is tending towards convergence up to the variation of target function less than certain constant.Because the time-varying characteristics of wireless channel environment, the cross-layer optimizing unit can periodically upgrade control to the dynamic resource module, thus the stability of the system of assurance.
Fig. 2 is the wireless video cross-layer optimizing realization flow figure in the embodiment of the present invention.As shown in Figure 2, this video frequency transmission optimizing process comprises following step:
Step 201: video sequence is stored in the digital server, and each user's in video sequence size, the broadcast multi-broadcasting transmission rate and power is carried out initialization, definition cross-layer optimizing unit.
The cross-layer optimizing unit can be realized at server side in this step, and control Dynamic Resource Allocation for Multimedia module periodically is optimized the renewal of strategy.
Step 202: calculate video source distortion and channel distortion.
The video sequence distortion comprises two parts in this step, i.e. video source distortion D
SWith channel distortion D
LThe video source distortion is that the compression because of video sequence causes, therefore channel distortion is also referred to as the packet loss distortion owing to the Network Transmission packet loss causes.Therefore transmission rate R is depended in the video source distortion, and the packet loss distortion then is the function of packet error probability (PEP), so distortion can be expressed as the function of transmission rate and packet error probability.Parameter Extraction is come application layer, physics and MAC layer.
Step 203: than (PSNR), and obtain each user's MOS value according to mapping model according to the distortion computation peak noise that obtains.
Y-PSNR is a kind of objective measurement method based on mean square error (MSE) of video quality in this step, and video distortion is exactly the expression-form of MSE, so PSNR can be write as the function of transmission rate and error probability.Research in the past shows that also objective evaluation parameter and subjective assessment parameter have good contact, i.e. mapping from PSNR to MOS can be taked the mapping model of Linear Mapping model or hyperbolic tangent function formula.
Step 204: judge that according to the constraints of each user's who calculates MOS value and given MOS threshold value this user is whether in service range.
The setting of MOS threshold value can be according to user's sense organ needs in this step; And the qualification of service range is for fear of more users occupying system resources under the situation that obtains relatively poor video; Not only reduced the video transmission time; And improved resource utilization ratio, thereby help the minimizing of whole network energy consumption.
Step 205: make the utility function value reach minimum through the self adaptation of transmission rate and power is distributed.
The utility function expression formula of using in this step does
Wherein K representes total number of users, B
kIndicate to be transferred to each user's video resource size, R
k(w
k) transmission rate that obtains after the expression user scheduling result, P
kThe through-put power of representing user k can be expressed as the function of transmission rate and drop probabilities.
Step 206: based on the adaptive process of power and rate-allocation in the last step, we think to find the solution and are tending towards convergence during less than certain specific constant up to the changing value of utility function, and then self-optimizing iterative process finishes.
Step 207: the final result of self-optimizing is exported to wireless transmission unit.
Claims (5)
1. one kind based on the professional cross-layer optimizing method of the wireless video of user's perception, it is characterized in that may further comprise the steps:
Step 1: video sequence is stored in the digital server, and each user's in video sequence size, the broadcast multi-broadcasting transmission rate and power is carried out initialization, definition cross-layer optimizing (CLO) unit.
Step 2: calculate video source distortion and channel distortion.
Step 3: than (PSNR), and obtain each user's MOS value according to mapping model according to the distortion computation peak noise that obtains.
Step 4: judge that according to the constraints of each user's who calculates MOS value and given MOS threshold value this user is whether in service range.
Step 5: make the utility function value reach minimum through the self adaptation of transmission rate and power is distributed, promptly minimize the network energy consumption.
Step 6: based on the adaptive process of power and rate-allocation in the last step, we think to find the solution and are tending towards convergence during less than certain specific constant up to the changing value of utility function, and then self-optimizing iterative process finishes.
Step 7: self-optimizing final result-optimisation strategy is exported to wireless transmission unit.
2. according to claim 1 based on the professional cross-layer optimizing method of the wireless video of user's perception, it is characterized in that:
In the said step 1, the cross-layer optimizing unit can be realized at server side, and control Dynamic Resource Allocation for Multimedia module periodically is optimized the renewal of strategy.
3. according to claim 1 based on the professional cross-layer optimizing method of the wireless video of user's perception, it is characterized in that:
In the said step 2, taken into full account the thought of striding layer, Parameter Extraction is from application layer, physical layer and MAC layer.
4. according to claim 1 based on the professional cross-layer optimizing method of the wireless video of user's perception, it is characterized in that:
In the said step 4; The setting of MOS threshold value can be according to user's sense organ needs; And the qualification of service range is for fear of more users occupying system resources under the situation that obtains relatively poor video; Not only reduce the video transmission time, and improved resource utilization ratio, thereby helped the minimizing of whole network energy consumption.
5. according to claim 1 based on the professional cross-layer optimizing method of the wireless video of user's perception, it is characterized in that: in the said step 5, the utility function expression formula of use does
Wherein K representes total number of users, B
kIndicate to be transferred to each user's video resource size, R
k(w
k) transmission rate that obtains after the expression user scheduling result, P
kThe through-put power of representing user k can be expressed as the function of transmission rate and drop probabilities.The dynamic assignment of through-rate and power makes whole network energy consumption minimum.
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| CN104023402A (en) * | 2014-05-28 | 2014-09-03 | 北京邮电大学 | Cross-layer resource allocation method facing user experience in open wireless network |
| WO2015100560A1 (en) * | 2013-12-30 | 2015-07-09 | 华为技术有限公司 | Method for predicting quality of experience of mobile video service, and base station |
| CN107205274A (en) * | 2016-03-17 | 2017-09-26 | 北京邮电大学 | Resource allocation value calculating method and device |
| CN103987125B (en) * | 2014-05-21 | 2017-10-20 | 西安交通大学 | The multi-user's real-time video cross-layer scheduling method optimized in HSDPA based on utility function |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2015100560A1 (en) * | 2013-12-30 | 2015-07-09 | 华为技术有限公司 | Method for predicting quality of experience of mobile video service, and base station |
| CN105264907A (en) * | 2013-12-30 | 2016-01-20 | 华为技术有限公司 | Method for predicting quality of experience of mobile video service, and base station |
| CN105264907B (en) * | 2013-12-30 | 2018-08-21 | 华为技术有限公司 | The Quality of experience prediction technique of mobile video business and base station |
| CN103987125B (en) * | 2014-05-21 | 2017-10-20 | 西安交通大学 | The multi-user's real-time video cross-layer scheduling method optimized in HSDPA based on utility function |
| CN104023402A (en) * | 2014-05-28 | 2014-09-03 | 北京邮电大学 | Cross-layer resource allocation method facing user experience in open wireless network |
| CN107205274A (en) * | 2016-03-17 | 2017-09-26 | 北京邮电大学 | Resource allocation value calculating method and device |
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Application publication date: 20120815 |