The wireless body sensor network (WBSN) technologies are one of the essential technologies of the Internet of things (IoT) growths of the healthcare paradigm, where every patient is monitored through a group of small-powered and lightweight sensor nodes. Thus, energy consumption is a major issue in WBSN. The major causes of energy wastage in WBSN are collisions and retransmission process. However, the major cause of the collision happened when two sensors are attempting to transmit data at exactly the same time and same frequency, and the major cause of the retransmission process happened when the collision takes place or data does not received properly due to channel fading. In this paper, we proposed a cognitive cooperative communication with two master nodes, namely, as two cognitive master nodes (TCMN), which can eliminate the collision and reduce the retransmission process. First, a complete study of a scheme is investigated in terms of network architecture. Second, a mathematical model of the link and outage probability of the proposed protocol are derived. Third, the end-to-end delay, throughput, and energy consumption are analyzed and investigated. The simulation and numerical results show that the TCMN can do system performance under general conditions with respect to direct transmission mode (DTM) and existing work.

In today’s healthcare environment, the Internet of Things technology provides suitability among physicians and patients, as it is valuable in numerous medicinal fields. Wireless body sensor network technologies are essential technologies in the growth of Internet of Things healthcare paradigm, where every patient is monitored utilising small-powered and lightweight sensor nodes. A dual-hop, inter–wireless body sensor network cooperation and an incremental inter–wireless body sensor network cooperation with energy harvesting in the Internet of Things health-based paradigm have been investigated and designed in this work. The three protocols have been named and abbreviated as follows: energy harvesting–based dual-hop cooperation, energy harvesting–based inter–wireless body sensor network cooperation and energy harvesting–based incremental inter–wireless body sensor network cooperation. Outage probabilities for the three designed protocols were investigated and inspected, and mathematical expressions of the outage probabilities were derived. The simulation and numerical results showed that the energy harvesting–based incremental inter–wireless body sensor network cooperation provided superior performance over the energy harvesting–based inter–wireless body sensor network cooperation and energy harvesting–based dual-hop cooperation by 1.38 times and 5.72 times, respectively; while energy harvesting–based inter–wireless body sensor network cooperation achieved better performance over energy harvesting–based dual-hop cooperation by 1.87 times.

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One of the most important stations in any communications system is the filtering station. Due to the noise power that effects on the signal, the system must include filtering process to eliminate this effect. In this paper, analog and digital filters are designed and implemented using Matlab tools to solve the problems occurred during receiving the signal that effects on the synchronization such as those for coherent receivers. The offsets of Phase and frequency are major problems in the identification of signals that results reduction in the performance; such as, whenever higher order modulations are used. Two systems are designed and simulated. The first one is analog system and the second one is digital system. 3rd order Butterworth filter is selected for system one and digital IIR filter is selected for system two. Filter order was selected according to diagnosis the level of noise power and the transmitted frequency to meet certain frequency domain design specifications. Obtained results showed excellent performance in the receiving and demodulating the received signal. Evaluation of the results is basically depend on comparison between the transmitted and received samples.