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The fifth-generation (5G) wireless communication system requires massive connectivity with high data rates and low latency. One of the technologies to meet these requirements is mm Wave massive MIMO. This work, therefore, aspires to have an in-depth look at the channel estimation and beamforming techniques jointly with their respective architectures for mm Wave massive MIMO system. In particular; sparse, compressed sensing, machine learning and array signal processing based channel estimation are addressed from 5G channel estimation techniques. On the other hand, beamforming techniques like hybrid beamforming and the low-complexity hybrid block diagonalization schemes with their mathematical analysis are included. This work also discusses in detail the challenges, optimization methods and mitigation techniques of pilot contamination, signal detection, channel estimation and hybrid beamforming for mm Wave massive MIMO system. The result asserts that partially connected block-diagonal hybrid bema forming with array signal processing based channel estimation is more optimal than the others with respect to over all performance, complexity and energy consumption. Finally, open research directions and challenges are pointed out.
To address 5G design targets, massive MIMO and mmWave communication are enabling technologies. Luckily, in many respects these two technologies share a symbiotic integration. Accordingly, a logical step is to integrate mmWave communications and massive MIMO to form ”mmWave-massive MIMO” which substantially increases user throughput, improve spectral and energy efficiencies, increase the capacity of mobile networks and achieve high multiplexing gains. Thus, this work analyses the concepts, performances, comparison and discussion of these technologies called: massive MIMO, mmWave Communications and mmWave-massive MIMO systems jointly. Besides, outcomes of extensive researches, emerging trends together with their respective benefits, challenges, proposed solutions and their comparative analysis is addressed. The performance of hybrid beamforming architecture with a fully digital and analog beamforming techniques are also analyzed. Analytical and simulation results show that the low-complexity hybrid analog-digital precoding achieves all round comparable precoding gains for mmWave-Massive MIMO technology.
Massive MIMO is one of the 5G nominee technologies that provides high energy and bandwidth efficiencies. Precoding at the basestation is compulsory to ensure such efficiencies in the performance and design of massive MIMO. This work investigates the performance of all recent massive MIMO linear precoding techniques called: Zero Forcing, Maximum Ratio Transmission, Regularized Zero Forcing, Truncated Polynomial Expansion and Phased Zero Forcing. The performance metrics which are used for their performance assessment are: bit error rate, signal to noise ratio, spectral efficiency and energy efficiency for a single cell downlink massive MIMO network; where the base station has ideal channel state information. Analytical expressions are formulated to each performance metric for the evaluation of these linear precoding techniques. Besides, the relationship between the number of base station antennas, users and signal to noise ratio with the achievable rates are revealed. The simulation result shows that Zero Forcing is the optimum linear precoding scheme both in bandwidth and power efficiency. However, its computational complexity is very high relative to other linear precoders. As far as the overall performance is concerned, Phased Zero Forcing approaches to Zero Forcing with low computational complexity.
The main goals planned to achieve in fifth generation (5G) networks are to increase capacity, improve data rate, decrease latency, improve energy efficiency and provide a better quality of service. To achieve these goals, massive multiple input multiple output (MIMO) is considered as one of the competing technologies that provide high spectral efficiency (SE) and energy efficiency (EE). Hence, energy efficiency, spectral efficiency and transmission reliability are the main performance metrics for massive MIMO systems. Although these performance metrics are thoroughly studied independently, their joint effects are not considered and evaluated for massive MIMO systems. Hence, in this work, we investigate a mathematical model that jointly evaluates the spectral efficiency, energy efficiency and transmission reliability in downlink massive MIMO systems with linear precoding techniques. Closed-form analytical formulation is derived that jointly evaluates the impacts of spectral efficiency and transmission reliability on energy efficiency. Finally, numerical results are provided to validate the theoretical analysis.
A considerable amount of enabling technologies are being explored in the era of fifth generation (5G) mobile system. The dream is to build a wireless network that substantially improves the existing mobile networks in all performance metrics. To address this 5G design targets, massive MIMO (multiple input multiple output) and mmWave (millimeter wave) communication are also candidate technologies. Luckily, in many respects these two technologies share a symbiotic integration. Accordingly, a logical step is to integrate mmWave communications and massive MIMO to form mmWave-massive MIMO which substantially increases user throughput, improve spectral and energy efficiencies, increase the capacity of mobile networks and achieve high multiplexing gains. Thus, this work analyses the concepts, performances, comparison and discussion of these technologies called: massive MIMO, mmWave Communications and mmWave-massive MIMO systems jointly. Besides, outcomes of extensive researches, emerging trends together with their respective benefits, challenges, proposed solutions and their comparative analysis is addressed. The performance of hybrid analog-digital beamforming architecture with a fully digital and analog beamforming techniques are also analyzed. Analytical and simulation results show that the low-complexity hybrid analog-digital precoding achieves all round comparable precoding gains for mmWave-Massive MIMO technology.