CN101345756A - A real-time video transmission method in wireless Ad Hoc network based on bandwidth prediction - Google Patents

Abstract

The present invention discloses a wireless Ad Hoc network real-time video transmission method based on band-width forecast, including the following steps: the sender node obtaining intensity of wireless signals and the stand-by time of routing switch through a cross-layer mechanism, acquiring packet loss amount and network jitter value by a receiver node feedback method, and inputting these parameter values into a Bayesian network prediction model, to obtain the Ad Hoc network bandwidth prediction value of the next period of time; the sender node regulating the coding code rate according to the predicted value, and outputting the video stream data with the corresponding code rate and performing sub-stream transmission; the receiver node receiving the data packets, decoding and then outputting in real time, and simultaneously transmitting the information feedback to the sender node. The present inventive method can grasp the Ad Hoc network bandwidth change rhythm in real-time, makes full use of network bandwidth, and reduces packet loss amount of real-time video transmission; and can reduce the occurrence of network congestion, reduce network delay and improve the quality of real-time video transmission.

Description

A real-time video transmission method in wireless Ad Hoc network based on bandwidth prediction

technical field

The invention relates to a network real-time video transmission technology, in particular to a bandwidth prediction-based wireless Ad Hoc network real-time video transmission method.

Background technique

With the development of wireless Ad Hoc network technology and the increasing popularity of multimedia applications, the transmission of real-time video services in Ad Hoc networks has become an important application direction. Ad Hoc network is an emerging wireless self-organizing mobile network, and its characteristics are: no base station, equal status of communication terminals in the network, any communication node is both a host and a router; communication nodes can move freely, and data transmission between any two nodes needs to pass The changed intermediate route is multi-hop completed.

Since the spatial position of nodes in the Ad Hoc network changes at any time, the network topology changes frequently. Ad Hoc networks usually use IEEE 802.11x as a transmission standard. This series of standards uses frequency bands above 2.4GHz for transmission, and wireless transmission in high frequency bands is easily interfered and blocked, resulting in network delays, bandwidth changes, and data loss. question.

The measurement standard for real-time multimedia video services is whether the data can be decoded and restored to high-quality video images in real time at the receiving node after the data is sent and transmitted. Real-time multimedia video services have relatively high requirements for real-time transmission of video streams and data integrity. Therefore, how to guarantee the real-time video transmission image quality under the wireless Ad Hoc network is a technical issue that engineers in this field are very concerned about.

As shown in Figure 1, an existing wireless Ad Hoc network real-time video transmission module structure includes a sender node and a receiver node. The sender node is composed of a video data processing module and a sender network processing module, and the receiver node is composed of a receiver node. It consists of a square network processing module, a video decoding module and a display output module. The video processing module of the sender node collects video source data, encodes them, and sends the encoded video stream data to the sender’s network processing module for packaging and sending; the receiver’s network processing module receives the video stream data and sends it to the video decoding module for decoding , the decoded data is displayed in real time by the display output module.

Frequent changes in the Ad Hoc network topology will cause bandwidth changes, and bandwidth changes usually cause video stream data to be lost during transmission. In order to prevent video stream data from being lost during transmission, the existing transmission mechanism usually performs flow control based on the network status information fed back by the receiving node. That is, the receiver node receives the real-time video data packet, extracts the sequence label from the data packet header, determines whether the network packet is lost through the continuity of the sequence label, and then feeds back the packet loss statistics information to the sender node; the sender node according to the packet loss By adjusting the video transmission bit rate to control the video data transmission flow, reduce the packet loss rate as much as possible.

Although the existing transmission mechanism solves the problem of video stream data loss during transmission to a certain extent, this mechanism has the following two limitations: on the one hand, the flow is only controlled when the data packet is lost, and the flow The degree of control is determined by the amount of data packet loss, which still causes unnecessary loss of real-time video data; on the other hand, the condition for the end of flow control is that the network no longer loses packets. With the improvement of network conditions, the sender node strategy It will not immediately increase the amount of packets sent, but lags behind the network packet loss statistics, and slowly increases the number of video data packets sent, which leads to unnecessary loss of network bandwidth.

The quality of wireless Ad Hoc network video data transmission is degraded. In the final analysis, it is caused by the change of network bandwidth. If you can grasp the law of bandwidth change and change the data transmission rate according to the change rhythm, you can maximize the use of network bandwidth and obtain the best possible results. Real-time video transmission effect.

Contents of the invention

The invention provides a wireless Ad Hoc network real-time video transmission method based on bandwidth prediction with low packet loss rate and high video image quality.

A wireless Ad Hoc network real-time video transmission method based on bandwidth prediction, comprising the following steps:

(1) The sender node performs real-time video collection, and stores the collected video source data into the cache;

(2) The sender node obtains the wireless signal strength (D) and the waiting time (T _w ) of routing switching through the cross-layer mechanism, and obtains the packet loss (N _loss ) and network jitter value (J) through the feedback method of the receiver node ;

The way to obtain the wireless signal strength and the waiting time of routing switching through the cross-layer mechanism is as follows:

a. By modifying the Ad Hoc network protocol stack, the link loss message and the link establishment message of the network layer are directly obtained at the application layer, and the waiting time for routing switching is calculated;

b. Obtain the wireless signal strength of the physical layer directly at the application layer by modifying the Ad Hoc network protocol stack.

The Ad Hoc network protocol stack can be varied, preferably the AODV protocol stack.

(3) The sender node inputs the wireless signal strength, the waiting time of routing switching, the amount of packet loss and the network jitter value into the Bayesian network prediction model, and obtains the Ad Hoc network bandwidth prediction value in the next period to maximize the use of network bandwidth;

In the Bayesian network prediction model, the logical relationship between the wireless signal strength, the waiting time for routing switching, the amount of packet loss, the network jitter value and the predicted value of the Ad Hoc network bandwidth in the next period is as follows:

The amount of packet loss is the waiting time for routing switching, the wireless signal strength and the child node of the network jitter value; the network jitter value is the child node of the wireless signal strength; the Ad Hoc network bandwidth prediction value for the next period is the wireless signal strength, network jitter value And the child nodes of packet loss.

The previous time period and the next time period represent two adjacent time periods, and the length of the time period can be set by yourself.

(4) The sender node reads the video source data from the cache, adjusts the encoding bit rate according to the Ad Hoc network bandwidth prediction value of the next period, encodes the video source data, and outputs the video stream data of the corresponding bit rate;

(5) The sender node sends each video frame in the video stream data into packets;

(6) The receiver node receives the data packet, decodes it and outputs it in real time, and at the same time counts the amount of packet loss and calculates the network jitter value and feeds it back to the sender node.

The calculation method of the above network jitter value is:

The receiver node uses the network time protocol to keep time synchronization with the sender node at all times, and calculates the network jitter value by extracting the header time stamp in each data packet and comparing it with the absolute time difference.

The wireless Ad Hoc network real-time video transmission method based on bandwidth prediction provided by the present invention adopts a Bayesian network prediction model to predict the Ad Hoc network bandwidth in real time, adjusts the video transmission code rate according to the predicted bandwidth value, and controls the video data transmission flow. This method can grasp the change rhythm of the Ad Hoc network bandwidth in real time, use the network bandwidth as much as possible, and reduce the packet loss of real-time video transmission; it can also reduce the occurrence of network congestion, reduce network delay, and improve the quality of real-time video transmission.

Description of drawings

Fig. 1 is the schematic flow chart of existing wireless Ad Hoc network real-time video transmission method;

Fig. 2 is the schematic flow chart of wireless Ad Hoc network real-time video transmission method of the present invention;

Fig. 3 is a frame diagram of the real-time video transmission system of the present invention;

Fig. 4 is a schematic diagram of adjusting the code rate of the video encoding of the sender node in the present invention;

Fig. 5 is a structural schematic diagram of a Bayesian network prediction model of a sender node in the present invention;

Fig. 6 is wireless Ad Hoc network topological diagram of the present invention;

Fig. 7 is a comparative schematic diagram of the amount of packet loss between the method of the present invention and the conventional method;

Fig. 8 is a schematic diagram showing the comparison of video image PSNR between the method of the present invention and the conventional method.

Detailed ways

The experimental environment parameters of this embodiment are configured as follows: 802.11b wireless transmission is used, the Ad Hoc routing protocol uses AODV (Ad hoc On-demand Distance Vector), the data transmission rate of the wireless link is 1 Mbps, and the moving speed of the receiving node is 2 meters/ seconds, the video stream parameters are: H.263, CIF (353×288), 25fps, 768Kbps. Figure 6 shows the network topology structure of this embodiment. The receiving node moves from the initial position to the target position along the trajectory shown in the figure at a speed of 2 meters per second, passing through the transmission range of each intermediate route sequentially on the way, and the number of hops changes accordingly. During the whole process, there will be Ad Hoc network topology changes, bandwidth changes, and route loss and recovery between the sender node and the receiver node.

As shown in Figure 2, the above-mentioned Ad Hoc network real-time video data transmission method is as follows:

(1) The sender node performs real-time video collection, and stores the collected video source data into the cache;

(2) The sender node obtains the wireless signal strength and the waiting time of routing switching through the cross-layer mechanism, and obtains the packet loss and network jitter value through the feedback method of the receiver node;

The way to obtain the wireless signal strength and the waiting time of routing switching through the cross-layer mechanism is as follows:

a. By modifying the Ad Hoc network protocol stack, the link loss message and the link establishment message of the network layer are directly obtained at the application layer, and the waiting time for routing switching is calculated;

b. Obtain the wireless signal strength of the physical layer directly at the application layer by modifying the Ad Hoc network protocol stack.

The Ad Hoc network protocol stack can be varied, preferably the AODV protocol stack.

(3) The sender node inputs the wireless signal strength, the waiting time for routing switching, the amount of packet loss, and the network jitter value into the Bayesian network prediction model to obtain the Ad Hoc network bandwidth prediction value for the next period;

In the Bayesian network prediction model, the logical relationship between the wireless signal strength, the waiting time for routing switching, the amount of packet loss, the network jitter value and the predicted value of the Ad Hoc network bandwidth in the next period is as follows:

As shown in Figure 4, the amount of packet loss is the waiting time for routing switching, the wireless signal strength and the sub-node of the network jitter value; the sub-node of the network jitter value is the wireless signal strength; the predicted value of the AdHoc network bandwidth in the next period is the wireless signal Subnodes for strength, network jitter value, and packet loss.

(4) The sender node reads the video source data from the cache, adjusts the encoding bit rate according to the Ad Hoc network bandwidth prediction value in the next period, encodes the video source data, and outputs the video stream data of the corresponding bit rate to maximize utilization network bandwidth;

As shown in Figure 5, the quantization parameter (Quantization Parameter, QP) reflects the compression of spatial details. When QP is small, most of the image details are preserved, and the bit rate is high; when QP increases, some details will be lost, and image distortion will be enhanced. And the quality is degraded, and the code rate is reduced. That is to say, there is an inverse relationship between QP and bit rate, and as the complexity of video source data increases, this inverse relationship becomes more obvious. Input the corresponding target bit rate value according to the predicted Ad Hoc network bandwidth, and then convert it into the corresponding QP value and input it into the encoder through the bit rate controller module to obtain the encoded video data of the corresponding bit rate.

The higher the bit rate, the higher the quality of the video image, the larger the amount of data transmitted, and the smaller the amount of packet loss, the larger the required network bandwidth. In order to maximize the use of network bandwidth and minimize the amount of packet loss, it can only be achieved by adjusting the bit rate, and the adjustment of the bit rate needs to be based on the predicted value of the Ad Hoc network bandwidth in the next period. The larger the predicted network bandwidth is , the higher the code rate, and vice versa, the lower the code rate.

(5) The sender node sends each video frame in the video stream data into packets. After the video frame is packetized, multiple data packets will be formed. The size of each data packet is limited to the maximum transmission unit (MTU). Prevent the network layer from fragmenting again to reduce transmission performance.

(6) The receiver node receives the data packet, decodes it and outputs it in real time, and at the same time counts the amount of packet loss and calculates the network jitter value and feeds it back to the sender node.

The receiving node extracts the sequence label from the header of the data packet, and judges whether the network loses packets through the continuity of the sequence label, and then counts the amount of packet loss.

The calculation method of the above network jitter value is:

The receiver node uses the network time protocol to keep time synchronization with the sender node at all times, and calculates the network jitter value by extracting the header time stamp in each data packet and comparing it with the absolute time difference.

Fig. 7, Fig. 8 are the comparison of embodiment adopting the wireless Ad Hoc network real-time video transmission method based on bandwidth prediction of the present invention and conventional real-time video transmission method for the average peak signal-to-noise ratio (APSNR) of packet loss and image respectively. The abscissa in Figure 7 takes time as the axis, corresponding to the topology conditions in Figure 6, it can be seen that the number of hops increases with time. According to statistics, at the second hop, the packet loss rate of the bandwidth-based prediction method of the present invention is 5.3% higher than that of the conventional method, and this advantage becomes more obvious as the number of hops increases. FIG. 8 shows that the bandwidth-based prediction method of the present invention also has obvious advantages in APSNR compared with conventional methods.

Claims (5)

1, a kind of wireless Ad Hoc network real-time video transmission method based on bandwidth prediction may further comprise the steps:

(1) the transmit leg node carries out real time video collection, deposits the video source data that collects in buffer memory;

(2) the transmit leg node obtains packet loss amount and network jitter value by the stand-by period of cross-layer mechanism acquisition wireless signal strength and route switching by the method for recipient's node feedback;

(3) the transmit leg node obtains the Ad Hoc network bandwidth predicted value of next period with stand-by period, packet loss amount and the network jitter value input Bayesian network forecast model of wireless signal strength, route switching;

(4) the transmit leg node reads video source data from buffer memory, adjusts encoder bit rate according to the Ad Hoc network bandwidth predicted value of next period, and video source data is encoded, and the video stream data of output phase code rate is at utmost to utilize the network bandwidth;

(5) the transmit leg node carries out the subpackage transmission with each frame of video in the video stream data;

(6) recipient's node receives packet, and packet loss amount and computing network jitter value are added up in the output in real time of decoding back simultaneously, feed back to the transmit leg node.

2, wireless Ad Hoc network real-time video transmission method as claimed in claim 1 is characterized in that, the described stand-by period implementation of switching by cross-layer mechanism acquisition wireless signal strength and route is:

A. by revising Ad Hoc network protocol stack, directly obtain loss of link message, the link establishment message of network layer, calculate the stand-by period that route is switched in application layer;

B. by revising Ad Hoc network protocol stack, directly obtain the wireless signal strength of physical layer in application layer.

3, wireless Ad Hoc network real-time video transmission method as claimed in claim 2 is characterized in that: described Ad Hoc network protocol stack is the AODV protocol stack.

4, wireless Ad Hoc network real-time video transmission method as claimed in claim 1, it is characterized in that: the computational methods of the network jitter value in the described step (6) are:

Recipient's node uses NTP (Network Time Protocol) and transmit leg node time to keep synchronously, by extracting the head time tag in each packet, compares with the absolute time difference, obtains the network jitter value.

5, wireless Ad Hoc network real-time video transmission method as claimed in claim 1, it is characterized in that, in the Bayesian network forecast model, the logical relation of the Ad Hoc network bandwidth predicted value of stand-by period, packet loss amount, network jitter value and next period that wireless signal strength, route are switched is as follows:

The packet loss amount is the child node of stand-by period, wireless signal strength and the network jitter value of route switching; The network jitter value is the child node of wireless signal strength; The Ad Hoc network bandwidth predicted value of next period is the child node of wireless signal strength, network jitter value and packet loss amount.

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