Abstract-In a wireless local area network (LAN), packets can be lost due to a multitude of reasons. It is possible to reduce the probability of occurrence of some of these loss mechanisms by reducing packet length at the medium access control (MAC) layer. However, there is an inherent tradeoff in that shorter packets decrease efficiency with respect to overhead. In current packet length adaptation literature, simplified or incomplete packet loss models are used, neglecting channel fading or collisions due to hidden nodes. In this paper, we apply a more complete packet loss model and propose a local packet length adaptation algorithm whereby each node dynamically adjusts its packet length based on estimates of the probabilities of each significant type of packet loss. In our technique, the access point periodically broadcasts channel occupancy information which each node uses in conjunction with its own local observations in order to estimate current network conditions. These are used to estimate the derivative of throughput with respect to packet length at each node under the current network conditions and to adapt the packet lengths accordingly. We demonstrate throughput gains of up to 20% via NS-2 simulations.
Abstract-As a Carrier Sense Multiple Access (CSMA) network, the performance of IEEE 802.11 networks highly depends on the accuracy of the carrier sensing procedure. However, conventional carrier sensing approaches suffer from the well known hidden and exposed node problems, adversely affecting aggregate throughput of the IEEE 802.11 networks. In this paper, we propose a novel scheme through which each station can adaptively select its Carrier Sense Threshold (CST) in order to mitigate the hidden/exposed node problems. The basic idea behind our approach is for the Access Point (AP) to periodically transmit a Busy/Idle (BI) signal to all the stations. Individual stations then use the BI signal from the AP together with their own local BI signal in order to adjust their CST. We use NS-2 simulations to show that our approach can enhance the aggregate throughput by as much as 50%.
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