الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
The number of cellular devices has grown rapidly in recent years. Wireless networks serve and connect billions of wireless devices that require data rates greater and lower delay to assist video, IOT applications, smartphone apps and digital transformation. Furthermore, the energy dissipated by wireless systems will increase. As a result, fifth generation (5G) wireless networks must provide the highest data rates, utilize a greater number of consumers concurrently, and become more energy efficient. Massive Multiple Input Multiple Output (Massive MIMO), which has the potential to deliver paradigm-shifting gains in spectral efficiency (SE) and energy efficiency, is one of the effective applications that can fulfil the demands of the 5G network (EE). This technology’s fundamental idea is to outfit the base station utilizing multiple antennas to provide service to various of users concurrently.
Due to the scarcity and high cost of the wireless spectrum, spectral efficiency is the most crucial indicators of the effectiveness of cellular communication systems. Higher data rates, lower computational costs for the operator, coverage expansion, and improved service reliability are all benefits of better spectral efficiency. Large-scale MIMO (also known as massive MIMO) technology has lately emerged as one of the most significant methods for minimizing the consumed power for radiation and enhancing spectral efficiency to handle fifth-generation (5G) networks. As an alternative, spectral efficiency is directly enhanced by the use of millimeter wave technology, which allows for the use of unused spectrum.
On the other hand, energy efficiency (EE) has emerged as a critical design criterion because it ensures long-term evolution. A cellular network’s energy efficiency (EE) is the total number of bits which can be effectively transmitted per unit of energy. This definition is measured in bits per joule. It can be viewed as a profit -cost ratio in which the quality of service (throughput) is weighed against the correlated costs (power consumption). As a result, it measures the network’s bit-delivery effectiveness.
This dissertation presents a comprehensive discussion of techniques that enhance the EE gains offered by Massive MIMO. Also, a scheme to optimize EE in 5G using massive MIMO technology is proposed. The massive MIMO system is proposed to enhance the tradeoff between EE and throughput at the optimum number of antennas. Furthermore, linear precoding techniques such as Multiple-Minimum Mean Square Error (M_MMSE), Regularized Zero Forcing (RZF), Zero Forcing (ZF), and Maximum Ratio (MR) are utilized. The EE-SE tradeoff is optimized for up-linking and down-linking massive MIMO systems. Finally, the results prove that M_MMSE gives the optimum tradeoff between EE and throughput at the proven optimum ratio between the number of active antennas and the number of active user UEs.