The usage range of nowadays wireless communications become wide, all of the develop applications uses wireless communication which improve the mobility and improve the mobility of the network subscribers. As known that the antenna diversity scheme developed from “SISO” to “MIMO” that has a maximum capacity and ability to improve the communication quality with a good shields among the fading effects and other impairments. In this research work study and analysis to the antenna systems and antenna schemes was done taking into consideration the central antenna system and the distributed antenna system “CAS” and “DAS”. A Matlab simulation was developed to test antenna configuration system in term of effeteness of fading channel while using different modulation order.

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The channel could be evaluated by utilizing several estimation algorithms. The various patterns of pilot arrangements for the channel appreciation are a huge problem in channel appreciation techniques since all the processes depends on it; this paper discusses improvements in channel selection. The Least Square and Least Square Mean methods are common, simple ways to begin to estimate a channel; however, they are less efficient than more complex approaches. Due to the boost in demand with high data rates in communications, developers continue to invent new methods and mechanisms to adjust the capacity and the accuracy of the communication network. One of the primary troubles in wireless communication is the communication channel, which is affected by nonlinear and random noise sources, which decrease the quality of the service on the network; in this case, the channel must be equalized to increase performance with minimal error. In this paper, a Massive Multiple Input Multiple Output was designed and simulated in order to estimate the channel and the performance of the network through using Least Square and Least Square Mean.

In response to user demand for wearable devices, several WBAN deployments now call for effective communication processes for remote data monitoring in real time. Using sensor networks, intelligent wearable devices have exchanged data that has benefited in the evaluation of possible security hazards. If smart wearables in sensor networks use an excessive amount of power during data transmission, both network lifetime and data transmission performance may suffer. Despite the network's effective data transmission, smart wearable patches include data that has been combined from several sources utilizing common aggregators. Data analysis requires careful network lifespan control throughout the aggregation phase. By using the Nomadic People Optimizer-based Energy-Efficient Routing (NPO-EER) approach, which effectively allows smart wearable patches by minimizing data aggregation time and eliminating routing loops, the network lifetime has been preserved in this research. The obtained findings showed that the NPO method had a great solution. Estimated Aggregation time, Energy consumption, Delay, and throughput have all been shown to be accurate indicators of the system's performance.