Energy Efficiency Maximisation in Large-Scale MIMO Systems

Energy Efficiency Maximisation in Large-Scale MIMO SystemsAnalysis of Energy Efficiency Maximisation in Large-Scale MIMO Systems intro and Motivation1.1 BackgroundThe development of smart terminals and their application, the need for multimedia services rapidly increases lately 1. The capacity of radio the Quality of benefit necessities of mobile applications of wireless communication networks is increasing exponentially 1.Bandwidth Efficiency is typically one of the important c befuls to Systems 1, 1. Energy Efficiency commence a metric for assessing the performances of wireless communications systems with some BE restrictions 1 1.1.2 Research MotivationsAn accurate modelling of the fit power consumption is the primary of (BS) antennas and design of active (UEs) for LS-MIMO systems 15.1.3 Research admit and ObjectivesThe research objectives which are briefly explained and summarized as belowTo compare the performance of the proposed uplink and downlink of LS-MIMO systems f or ZF, MRT/MRC, and MMSE touch on schemes at BS.To implement a new delicate model of the total power consumption for LS-MIMO system.To derive closed-form EE-maximal values of number of (BS) antennas, number of active (UEs), and the transmit power using ZF impact in single-cell system and new refined model of the total power consumption when the other two are fixed.To evaluate analytic takingss for ZF processing scheme with perfect CSI.To measure numerical results for ZF, MRT/MRC, and MMSE processing schemes processing schemes with perfect CSI in a single-cell scenario.To measure numerical results for ZR processing schemes with rickety CSI, and in a multi-cell scenario.1.4 Main ContributionsThis thesis has contributions to knowledge in three research issues for LS-MIMO system, which are the new refined circuit power consumption model, efficacy efficiency maximisation with ZF processing scheme, and deployment of rickety CSI case and radial multi-cell scenario. Those main contr ibutions of this thesis are summarized and elaborated more detail as followsThe circuit power consumption is the sum of the power consumed by different line of latitude components and digital portend processing. The new refined model of the total power explicitly described how the total power consumption depends non-linearly on number of number of UEs, number of BS antennas, and transmit power.The closed-form EE expression under the assumption of ZF processing scheme is employed in the uplink and downlink for optimal number of UEs, number of BS antennas, and transmit power for a single-cell scenario with perfect CSI. This option is driven by analytic convenience and numerical results likewise which are close to optimal.Analysis of imperfect CSI case and symmetric multi-cell scenarios deployment are extended using the same method above. A New achievable rate derived for symmetric multi-cell scenarios with ZF processing.1.5 Research MethodologyIn the first stage of the research, lit erature review of past and current works on the area of MIMO, MU-MIMO, and LS-MIMO are extensively conducted to broaden the perspective on such(prenominal) areas of study. Furthermore, state of the art related to those addressed issues are deeply studied and intensively explored during this period.Following the literature review phase, implementation starts with formulating the EE maximisation problem. A new refined circuit power consumption model is proposed. All this then utilize to compute closed-form expression for the optimal number of UEs, number of BS antennas, and transmit power under the assumption of ZF processing scheme.The testing stage starts with simulation. All the simulations were performed using Monte Carlo Simulation techniques in Matlab. Monte Carlo simulation displace handle very complex and realistic. Monte Carlo Simulation were executed for all the investigated schemes with perfect CSI, for ZF with imperfect CSI, and in a multi-cell scenarioIn the validation stage, numerical results are used to authenticate the theoretical analysis and make comparison amongst different processing schemes.1.6 Thesis StructureThis thesis comprises of six chapters, where each chapter is inter- dependent.Chapter 1 cosmos Chapter 2 LS-MIMO-An overview This chapter presents an overview of the LS-MIMO concept.Chapter 3 Literature Review- Energy Efficiency Maximisation in LS-MIMOChapter 4 Techniques to Maximise Energy Efficiency The simulation procedures will be explained in this chapter.Chapter 5 Result and Analysis This chapter describes description and evaluation for this investigation of LS-MIMO .Chapter 6 Conclusion Further Work This chapter concludes the results of the implementations, and recommendation of developing revised model for LS-MIMO systems.LS-MIMO An Overview2.1 Introduction to LS-MIMOWireless communication is one of the most successful technologies is one of the most successful technologies in modern years, given that an exponential growt h rate in wireless traffic (known as Coopers law) 1. This trend will certainly drive by for example, augmented reality and internet-of-things 1.Figure 2-16 2.2 Antenna configurationsRadio-Frequency (RF) circuit is usually attached to its physical antennas through an RF cable in a passive AA. A Remote Radio Unit (RRU) in with a Baseband Unit (BBU) has become a preferred configuration recently 1.2.3 Channel MeasurementsRealistic pipeline measurements have been carried out in in an effort to identify the main characteristics of LS-MIMO convey 152.4 Channel toughieThree types of channel models have been used for evaluating the performance of wireless communications systems, namely the Correlation-Based Stochastic Model (CBSM), the Parametric Stochastic Model (PSM) and the Geometry- Based Stochastic Model (GBSM) in 1.2.5 Processing SchemesPrecoding LS-MIMO is based on linear processing at the BS. BS has observation of the multiple access conduct from the terminals 6. The BS applie s linear receive combining to discriminate the signal transmitted 6. The simplest choice is maximum ratio (MR) combining by adding the signal components coherently. In 6, this result signal amplification proportional to.Energy Efficiency Problem Literature Review3.1 System and Signal ModelThe uplink and downlink of a single-cell multiuser MIMO system operating is considered over a bandwidth of B Hz 15.3.2 Channel Model and Linear ProcessingThe M antennas at the BS are spaced apart such that the channel components between the BS antennas and the single-antenna UEs are uncorrelated 15. The channel describes propagation channel between antenna at the BS and the UE. We assume small scale fading distribution 15.3.3 UplinkIn 15, under the assumption of Gaussian, linear processing, and the perfect CSI, the achievable uplink rate of the th UE is (3.6)the pre-log factor accounts for pilot overhead and is thefraction of uplink transmission 15. In addition, (3.7)3.4 DownlinkA normalized pr ecoding vector and the downlink signal to the kth is assigned a transmit power of . In 15, assuming Gaussian codebooks and perfect CSI the achievable downlink rate of the kth UE with linear processing is (3.13)3.5 Problem StatementThe EE of a communication system is measured in bit/Joule and the average total power consumption (in tungsten = Joule/second) 15.The total EE of the uplink and downlink is (3.20)Energy Efficiency Maximisation-Techniques4.1 Realistic Circuit Power Consumption ModelThe sum of the power consumed by different components and signal processing is the circuit consumption is 15. A power consumption model is proposed (3.22)4.2 Energy Efficiency Maximisation with ZF ProcessingThe EE maximisation problem is stubborn under the assumption that ZF processing is employed. This solution is driven by analytic and the numerical results 15.For ZF processing, Problem 1 reduces to (3.30)4.3 Extension to Imperfect CSI and Multi-CellThe analysis is prolonged to single-cell scenarios with imperfect CSI. A new achievable rate is derived with ZF forcing processing. The achievable user rates in single-cell scenarios with imperfect CSI 15. (3.52)Simulation Setup and Numerical Results5.1 Simulation SetupSimulations used to validate the system design guidelines under ZF processing and to make comparison with other processing schemes 15. Numerical results provided under both perfect and imperfect CSI, and for single-cell and multi-cell scenarios 15. For affect ZF, and MRT analytic results were executed and MMSE, and Monte Carlo simulations were performed to maximise EE 15.5.2 Single-Cell ScenarioThe chosen deployment model validated.5.3 Multi-Cell ScenarioA lot of studies have been carried out.Conclusions and Future Research6.1 ConclusionsThis thesis focuses on the energy maximisation improvement of the LS-MIMO systems to cope with energy maximisation problem. The thesis has three main contributions all are elaborated in detail.6.2 Future Research some(pre nominal) recommendations, which may guide to the future research directions on LS-MIMO systems.Bibliography1 K. Zheng, L. Zhao, J. Mei, B. Shao, W. Xiang and L. Hanzo, Survey ofLarge- Scale MIMO Systems, in IEEE Communications Surveys Tutorials, vol.17, no. 3, pp. 1738-1760, third quarter 2015.2 D. Feng et al., A survey of energy-efficient wireless communications, IEEE Commun. Surveys Tuts., vol. 15, no. 1, pp. 167-168, 1st Quart. 2012.3 T. Kailath and A. J. 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