On the Parallel Processing for Wireless Sensors Converged Network

This paper studies the capability of multi-parallel processing to be accommodated in machine-to-machine communications. A testbed convergence between the wireless sensor network and the wireless mobile network is performed. It deals with enhancing wireless mobile network performance. This testbed is divided into three stages; combating the peak-to-average power ratio problem, observing a real data making use of an actual wireless sensors, and proposing a multi-parallel processing communications. The mentioned testbed above is done in a realistic academic environment, where selected signals from those sensors are evaluated. Thus, a design improvement is detailed in terms of the peak-to-average power ratio and the efficient use of the limited resources. In particular, the scope focuses on the mitigation of the nonlinear distortion and its effect on bit error rate. The validation process is attained based on performing an extensive simulation. It is observing some certain performance parameters such as the sensor life time, and the consumed energy. From the testbed simulation results, the proposed work shows promising results comparing to the conventional wireless sensor network. The delay reduction reaches around 85%, while the peak to average power ratio values has improved by 42.3%.