This paper highlights the development of a human voice command system that is able to activate the electrical appliances at home in wireless environment. The idea is to establish a wireless connection between a client computer and a server in a real application. It is developed especially to assist disabled person to do their house chores. Via the wireless communication system, this system utilizes the remote voice recognition system server to translate the voice input received from a serviced client computer into a symbolic data file to be processed by the client's computer. The wireless technology implemented in this project is the Wi-Fi network and the computer server utilizes the GUI manager for implementing the speech recognition system. The GUI system is developed using the Microsoft Visual Basic.net software and the speech recognition software used is the Microsoft Speech (SAPI). In conclusion, from the result analyses, the performance of the system depends on the wireless coverage and distance, voice input type and the environment condition.
Abstract-Energy Efficiency (EE) is becoming increasingly important for wireless communications and has caught more attention due to steadily rising energy costs and environmental concerns. Recently, a new network architecture known as Massive Multiple-Input Multiple-Output (MIMO) has been proposed with the remarkable potential to achieve huge gains in EE with simple linear processing. In this paper, a power allocation algorithm is proposed for EE to achieve the optimal EE in Massive MIMO. Based on the simplified expression, we develop a new algorithm to compute the optimal power allocation algorithm and it has been compared with the existing scheme from the previous literature. An improved water filling algorithm is proposed and embedded in the power allocation algorithm to maximize EE and Spectral Efficiency (SE). The numerical analysis of the simulation results indicates an improvement of 40% in EE and 50% in SE at the downlink transmission, compared to the other existing schemes. Furthermore, the results revealed that SE does not influence the EE enhancement after using the proposed algorithm as the number of Massive MIMO antenna at the Base Station (BS) increases.
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