Introduction
Long Term Evolution (LTE) products are quickly being seen on the market nowadays and much more products are expected in the future. With 5G proposed and expected to arrive around 2020, engineers must work and test these new products out quickly. However, the complexity of these devices does not make this task an easy one. There are many performance measures to consider such as SNR, SIR, capacity, and many more as well as different features that may be necessary to arrive at the desired results. For purposes of this project, I will evaluate a journal from Agilent Technologies that describes how to quickly determine if a MIMO channel is capable of supporting spatial multiplexing when given a particular signal-to-noise ratio (SNR). The term “condition number” will also be introduced when dealing with recovery of MIMO transmission.
Many wireless systems used today have improved data capacity using the multi-antenna system. However, not all MIMO wireless systems are suitable for spatial multiplexing. In order to accommodate this benefit, the wireless channel must have the appropriate antenna configuration and have the ability to accurately recover the channel coupling matrix coefficients. As mentioned before, engineers face many complexities when dealing with wireless channels. Among those complexities include channel correlation and interference/noise rates. That is where the condition number calculation comes in handy. The condition number is a deterministic calculation that evaluates the performance of a wireless channel while estimating for SNR demodulation for a LTE MIMO system. The aim would be to get a condition number as close as 0 dB as possible and try to avoid any values greater than 10 dB.
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...or medium correlation
>>H = evcdf(x,0.9,3) %cdf for high correlation
>>plot(x, L, x, M, x, H); %three plots
References
[1] Agilent Application Note, MIMO Channel Modeling and Emulation Test Challenges,
Literature Number 5989-8973N, October 2008.
[2] Agilent Technologies, MIMO Performance and Condition Number in LTE Test,
Literature Number 5990-4759EN, October 5, 2009.
[3] Advanced Engineering Mathematics, Erwin Kreyszig, 6th Edition, pg. 1025-26, 1988.
[4] LTE and the Evolution to 4G Wireless: Design and Measurement Challenges, Agilent
Technologies, 2nd Edition, chapter 6, April 1, 2013.
[5] Cumulative Distribution Plots, MathWorks, R2014a Documentation
[6] Condition Number of a Matrix, MathWorks, R2014a Documentation
[7] Rohde & Schwarz: “Assessing a MIMO Channel”, Application Note 1SP18, 2010
Research suggests that managers and employees in the wireless industry have faced tough challenges in their daily work. Managers have had the difficult job of crafting appropriate business strategies and human resource practices in the face of technological uncertainty, volatile demand, and heightened price competition in markets plagued by overcapacity (Batts, Colvin, Katz & Keefe (2005). This paper will examine the challenges facing the wireless industry the near future and recommend ways in which my new organization, Twenty1Wirless, can meet those challenges. First we will discuss the challenges we are facing as an organization. Next, we will explore the opportunities Twenty1 Wireless has to overcome these challenges. Finally, we will discuss
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Analysis of the Environment of the Mobile Network System Executive Summary 3 Glossary of Abbreviations 4 Introduction 5 Recent History
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Print. The. Gordon A. Gow, and Richard K. Smith. Mobile and wireless communications: an introduction, McGraw-Hill International, 2006. Print.
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