THROUGHPUT OPTIMIZATION WITH MPR BY RANDOMIZING TRANSMISSION POWER LEVELS FOR WLAN
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Abstract
The IEEE 802.11 wireless standard for Wireless LAN (WLAN) is one of the promising technologies where achieving high throughput with limited channel capacity is very important. Many algorithms have been proposed for maximizing throughput but many of them are too complex to understand with many parameters. In this paper, a model has been proposed for maximizing throughput by randomizing transmission power levels with multiple packet reception (MPR) for WLAN. Kalman filter is used to reduce the noise effect with Received Signal Strength Indicator (RSSI) which can achieve a more accurate signal and good estimation of throughput. This technique shows that, randomized power level for multiple user can maximize the throughput of the system. Here an algorithm is proposed to determine the probability distribution of the various power level in the infrastructure mode where user can choose transmission power level randomly. Kalman-filter can reduce sampling quantity by 60(%) compared to other filter like mean filter. Simulation results are demonstrated that the system throughput is improved for MPR when the power is randomized compared with existing model. The system performance by improvement accuracy is evaluated via Mat-Lab.
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