PROJECT TITLE :
An Approach to Sensor Network Throughput Enhancement by PHY-Aided MAC
Low power sensor networks with communication enabled by WiFi are expected to be widely deployed. A serious challenge is collecting event-driven uplink information from a large range of low-power sensors with low latency. In WiFi, the access point (AP) typically polls nodes individually to schedule uplink transmission times, ensuing during a massive latency. In this paper, we tend to gift a physical (PHY) layer-aided medium access management (MAC) framework to enhance the uplink throughput of sensor information traffic. In the approach, the acknowledgements from the sensor nodes to the poll message are parallelized. By detecting the parallel acknowledgement, the AP knows which nodes have knowledge to send and allocates channel resources by sending a pull message. This approach is called the probe and pull MAC (PPMAC) mechanism. Our theme relies on maximizing the achievable throughput of PPMAC by optimizing the PHY layer parts. Additional exactly, we tend to investigate the parallel acknowledgement detector style downside and develop a non-convex optimization framework that maximizes the PPMAC throughput by optimizing the parallel acknowledgement detection statistics. Numerical examples illustrate that PPMAC outperforms the purpose coordination function (PCF) and distributed coordination perform (DCF) mechanisms, standardized in IEEE 802.eleven, in terms of the achievable throughput and the overhead.
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