CN105517184A - High-efficiency contention window adjusting mechanism in high-density radio random access network - Google Patents

Abstract

The invention belongs to the technical field of electronic information, and is an efficient contention window adjustment mechanism suitable for high-density wireless random access networks. The invention dynamically estimates the channel parameters by enabling the nodes in the network to monitor the channel state in real time, and selects a more reasonable competition window adjustment scheme according to the degree of deviation between the estimated value and the theoretical optimal value. The invention has the characteristics of the lowest complexity, easy implementation, high accuracy of channel access scheduling, and fast adjustment speed.

Description

An Efficient Contention Window Adjustment Mechanism in High Density Wireless Random Access Networks

technical field

The present invention relates to the field of electronic information technology, in particular to an efficient media intervention competition mechanism, and more specifically, designs an efficient competition window adjustment mechanism in a high-density wireless random access network.

Background technique

At present, distributed wireless random access networks have been widely used in military affairs, intelligent transportation, environmental monitoring, and health care. Thanks to the rapid development of micro-motor system, system-on-chip, wireless communication and low-power embedded technology, wireless random access network has gradually become an important part of cutting-edge communication technology fields such as Internet of Things communication, M2M communication and V2V communication. This will lead to a substantial increase in the number of wireless network nodes in a certain area. Therefore, we urgently need a more reasonable media access control (MAC) protocol, so that a large number of nodes in a high-density distributed wireless random access network can occupy limited channel resources more fairly and efficiently.

In wireless random access networks, the number of neighbors of a node increases exponentially with the increase of network density. Affected by the data generation rate of the application layer of each node, the number of competing nodes (nodes competing for channel resources at the same time) in the network will keep changing. Compared with the traditional wireless random access network, the high-density wireless random access network MAC protocol requires:

1. More precise scheduling. It enables the network to maintain a very high throughput rate when multiple nodes are connected at the same time.

2. Faster scheduling. This enables the network to effectively grasp changes in the number of competing nodes and make quick adjustments. Reduce the throughput loss caused by the rapid and large change in the number of competing nodes in the network.

In the existing research results, the technology capable of precise scheduling is often accompanied by the problem of slow adjustment speed, while the technology with fast scheduling ability is difficult to guarantee the accuracy of scheduling.

Contents of the invention

The purpose of the present invention is to overcome the deficiencies of the prior art, and propose an efficient contention window adjustment mechanism suitable for high-density wireless random access networks, by allowing nodes in the network to monitor the channel status in real time, dynamically estimate the channel parameters, and According to the degree of deviation between the estimated value and the theoretical optimal value, a more reasonable competition window adjustment scheme is selected. The invention has the characteristics of easy realization, high accuracy of channel access scheduling and fast adjustment speed.

In order to achieve the above object, an efficient contention window adjustment mechanism in a high-density wireless random access network proposed by the present invention has the following steps:

1. Each node monitors the status information of the channel in each time slot, including channel idle and busy.

2. When a node tries to access a channel, it first checks whether the amount of channel state information obtained by the node meets the requirements.

3. If the amount of channel state information obtained by the node is insufficient, the node generates a random backoff time according to the original contention window, and returns to step 1.

4. If the amount of channel state information obtained by the node meets the requirements, the node estimates the channel parameter X according to the information, and proceeds to step 5.

5. According to the network congestion analysis, the node uses a one-dimensional array with a length of 2M-1 to divide the possible values of the estimated value X_est of the channel parameter X into intervals.

6. According to the interval of X_est, the node dynamically selects different adjustment ranges to adjust the competition window, so that the channel competition state can return to the optimal state faster.

In the aforementioned efficient contention window adjustment mechanism in a high-density wireless random access network, in step 5, the division of X_est intervals by nodes under different channel contention conditions will be different. The node needs to repeatedly calculate the interval division of X_est during the running process. This will greatly increase the computational load of the node during operation.

In order to overcome this problem, the node can approximately map the divisions that may occur in different channel competition environments into one or several reference divisions. The node pre-stores the reference division, and directly uses the reference division to determine the interval to which X_est belongs during the running process.

In the process of approximately mapping the X_est interval division to the reference division that may occur in the aforementioned different channel competition environments, the node follows the following principle: the absolute error value during the mapping process is smaller than the maximum precision of X_est. Among them, the maximum accuracy of X_est is determined by the amount of channel state information used to estimate channel parameters.

In the aforementioned high-efficiency contention window adjustment mechanism in a high-density wireless random access network, in step 5, the number of elements in the space division array is determined by the amount of channel state information used to estimate channel parameters.

In the above-mentioned efficient contention window adjustment mechanism in a high-density wireless random access network, in step 5, the elements of the space division array are arranged in ascending order, and include M-1 elements smaller than X_opt, elements X_opt, and M- 1 element greater than X_opt.

In the aforementioned efficient contention window adjustment mechanism in a high-density wireless random access network, in step 6, X_est is located in a space larger than X_opt or smaller than X_opt, and different contention window adjustment strategies—expansion or reduction will be adopted.

In the aforementioned efficient contention window adjustment mechanism in a high-density wireless random access network, in step 6, the farther the space where X_est is located is from X_opt, the greater the adjustment range required for the contention window.

Description of drawings

Fig. 1 is a block diagram of the operation flow of the present invention

Fig. 2 is the flow chart of the adjustment of the contention window of the present invention

detailed description

An exemplary embodiment of the invention is described in detail below, a flow chart of which is shown in the drawing. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

Fig. 1 is a block diagram of the operation flow of the present invention. The invention provides an efficient contention window adjustment mechanism in a high-density wireless random access network. In the embodiment, the channel idle probability PI is selected as the channel parameter for evaluating the channel competition environment. Its specific operation includes the following steps:

1. Initialize channel monitoring parameters PA, PB, and contention window CW.

2. Generate a random number in the interval [0, CW-1] and assign it to the backoff counter BC, and use BS to record the initial value of the backoff counter.

3. The node detects the busy and idle state of the channel in units of time slots. If it is detected that the channel is busy, go to step 4. If the channel is detected to be idle, go to step 5.

4. Since the idle state of the channel is interrupted, the node returns to step 3 after performing the following operations.

a) Use the PA to accumulate the number of time slots in which the channel is continuously idle. The number of consecutive idle time slots of the channel can be obtained by calculating the difference between the initial value of the backoff counter and the current value of the backoff counter.

b) Use PB to record the number of times the idle channel is interrupted.

c) Use the BS to record the current backoff counter value.

5. Since the channel remains idle, the node first checks whether the backoff counter value is zero. If the value of the backoff counter is non-zero, the node decrements the value of the backoff counter by 1, and returns to step 3. If the value of the backoff counter is not greater than zero, the node goes to step 6.

6. The node accesses the channel successfully. And detect the number of interrupted idle channels, that is, PB+1. If the current idle channel is interrupted less than 5 times, the node keeps the contention window size unchanged and returns to step 2. If the current idle channel is interrupted more than 5 times, the node calculates the channel idle probability PI by using the currently obtained channel information, ie PA, PB. PI can be expressed as PA/(PA+PB). Using the calculated channel idle probability PI, the node adjusts the contention window CW, and finally returns to step 2.

After the node obtains the channel idle probability PI, it will adjust the contention window CW. The adjustment flow chart is shown in Figure 2, which specifically includes the following steps:

1. Parameter initialization. The initialization content is as follows:

a) PO is the channel idle probability when the channel competition remains in the optimal state. PO is about 0.7778 in this example.

b) BF is the basic backoff parameter. In this embodiment, the basic backoff parameter is set to 2, that is, the contention window is increased or decreased by a multiple of 2.

c) The PI value interval divides the array THR[2M-1]. The array consists of 2M-1 elements, the elements in the array are arranged in increments, and it contains M-1 elements smaller than PO, element PO, and M-1 elements larger than PO.

d) The value range of PI divides the array size M. The size of the PI value interval division array depends on the minimum idle channel interruption times required for contention window adjustment described in step 6 of the operation process. In this embodiment, the minimum number of idle channel interruptions is 5. At this time, in order to ensure that the elements in the interval division array can be effectively identified by the calculated PI, in this embodiment, the value of M is 5, that is, the PI value interval division array contains 9 elements. In this embodiment, THR[2M-1]={0.0274, 0.1655, 0.4068, 0.6378, 0.7778, 0.8937, 0.9453, 0.9722, 0.9861}.

e) Initialize the contention window adjustment index Index.

2. The node compares the size relationship between PI and the Mth element of THR, that is, PO, and performs the following corresponding operations:

a) If PI is equal to PO, the node keeps the competition window unchanged and ends the competition window adjustment.

b) If PI is greater than PO, the node performs the following operations:

i. Change the contention window to one-half of the existing value.

ii. Add 1 to the contention window adjustment index.

iii. Identify the current contention window adjustment index. If the index is greater than or equal to M, the node ends this competition window adjustment. If the index is less than M, go to step iv.

iv. Determine the relationship between PI and the M+Indexth element in the array THR. If PI is greater than this element, the node returns to step i. If PI is less than or equal to this element, the node ends this competition window adjustment.

c) If PI is smaller than PO, the node performs the following operations:

i. Double the contention window to the existing value.

ii. Add 1 to the contention window adjustment index.

iii. Identify the current contention window adjustment index. If the index is greater than or equal to M, the node ends this competition window adjustment. If the index is less than M, go to step iv.

iv. Determine the relationship between PI and the M-Indexth element in the array THR. If PI is greater than this element, the node returns to step i. If PI is less than or equal to this element, the node ends this competition window adjustment.

Claims (7)

1. the efficient competition window Regulation mechanism in a high-density wireless Network with Random Multiple Access System, it is characterized in that, by Real-Time Monitoring channel status, dynamically channel parameter X is estimated, and select more reasonably competition window Adjusted Option according to the departure degree of estimated value X_est and theoretially optimum value X_opt.Described method concrete steps are:

1.1 each node monitors channels, in the state information of each time slot, comprise channel idle, busy etc.

1.2 nodes are when attempting access channel, and whether the channel condition information quantity that first detection node obtains meets the demands.

If the channel condition information lazy weight that 1.3 nodes obtain, then node produces random-backoff time according to original competition window, and returns step 1.1.

If the channel condition information quantity that 1.4 nodes obtain meets the demands, then node is estimated channel parameter X according to those information, and continues step 1.5.

1.5 nodes are according to network congestion analysis, and the possible value of the estimated value X_est of channel parameter X is carried out interval division by the one-dimension array utilizing length to be 2M-1.

1.6 nodes are according between X_est location, and the amplitude of accommodation that Dynamic Selection is different adjusts competition window, thus make channel competition state return optimum faster.

2. the efficient competition window Regulation mechanism in a kind of high-density wireless Network with Random Multiple Access System according to claim 1, it is characterized in that, in described step 1.5, the dividing condition that may occur under different channels competitive environment is similar to mapping by node becomes one or several with reference to dividing.Node prestores with reference to dividing, and in running, directly utilizes and judges interval belonging to X_est with reference to dividing.

3. the efficient competition window Regulation mechanism in a kind of high-density wireless Network with Random Multiple Access System according to claim 2, it is characterized in that, the reference of X_est divides mapping and follows following principle: the maximal accuracy being less than X_est with reference to the absolute error value divided in mapping process.Wherein, X_est maximal accuracy by claim 1 step 1.2 for estimate channel parameter X channel condition information quantity determine.

4. the efficient competition window Regulation mechanism in a kind of high-density wireless Network with Random Multiple Access System according to claim 1, is characterized in that, in described step 1.5, the element number of spatial division array is determined by the channel condition information quantity in step 1.2.

5. the efficient competition window Regulation mechanism in a kind of high-density wireless Network with Random Multiple Access System according to claim 1, it is characterized in that, in described step 1.5, the element of spatial division array arranges according to ascending order, and wherein comprise the element that M-1 is less than X_opt, element X_opt, and the individual element being greater than X_opt of M-1.

6. the efficient competition window Regulation mechanism in a kind of high-density wireless Network with Random Multiple Access System according to claim 1, it is characterized in that, in described step 1.6, X_est is positioned at the space being greater than X_opt or the space being less than X_opt, will adopt different competition window adjustable strategies---and expand or reduce.

7. the efficient competition window Regulation mechanism in a kind of high-density wireless Network with Random Multiple Access System according to claim 1, is characterized in that, in described step 1.6, space length X_opt is far away at X_est place, and the amplitude of accommodation of carrying out needed for competition window is larger.