## 4 Problem Statement
### Sudden Decrease in CW  
Resetting the CW to its lowest value after a successful submission will destroy fairness. A node with successful transmission will have a better chance of channel access because of smaller CW as compared to a node that has had a collision. Concerning the analytical models of IEEE 802.11, most models assume a collision probability independent of the history of the node's transmission, which results in an inaccurate estimate of the possibility that a node transmits in a random period, thus resulting in an inaccurate analysis of throughput. This sudden increase and resetting of CW results in degraded performance [28]. In a dense scenario, resetting of CW to its minimum size can lead to high collisions probability resulting in poor network performance. Similarly, in the case of a small network, sudden increase in the size of CW can cause an unnecessary delay while accessing the channel. Moreover, doubling the CW size after every collision will take time and have to wait for a long time before counting down to zero, resulting in starvation. Furthermore, the Binary Exponential Backoff (BEB) algorithm always prefers the last node, which transmitted successfully. This can lead to an intensification of the fairness problem, resulting in the degradation of system performance. Frequent retransmissions also caused a lot of unnecessary energy waste.  
This problem can be explained with a simple scenario. Figure 2 shows a simple scenario where four nodes N1, N2, N3, and N4 are sensing the channel for data transmission using BEB.  
Figure 1: Variation in the size of CW due to collision and successful transmission.  
Both nodes N1 and N2, send data at the same time which causes collision. When the collision occurs, CW size is doubled which forces the collided nodes to wait for additional  
Figure 2: Four nodes competing for the channel using binary exponential backoff based distributed coordinated function.  
time before transmission attempt. N1 selects the value of the backoff counter (k) as 5, while N2 selects k = 12. N3 also senses the channel for data transmission and selects k = 10. N1 sends the data successfully and again decides k = 4 to send another packet of data. The backoff value chosen randomly by Node N1 in the second round is smaller than the remaining backoff counter of N2; therefore, N1 will again get the transmission opportunity. Moreover, as the remaining backoff of N3 is smaller than the remaining backoff of N2, N3 will get the opportunity of transmission. Now, N4 senses the channel for transmission and selects k = 2, which is smaller than the remaining backoff of N2 (i.e., k = 2), and N4 will get the transmission opportunity. The larger the size of the CW a node selects, the lower the opportunity to the channel it gets. This unfairness seriously compromises the performance of the network.  
To tackle the problems mentioned above, we have proposed an efficient method of setting the optimal value of CW using the principles of DRL. Using DRL techniques, individual devices and entire networks can be characterized from a high-level perspective that relies on the data extracted directly from the measurements. Our proposed scheme will provide better results regarding network performance.