Large Scaled Multi-User MIMO System so called Massive MIMO Systems for Future Wireless Communication Networks Y.Mehmood; W.Afzal; F.Ahmad; U.Younas; I.Rashid; I.Mehmood Department of Electrical Engineering National University of Science & Technology Islamabad, Pakistan Emails: yasirhallian73@gmail.com; irashid@mcs.edu.pk Abstract—The massive or large scaled multiple input multiple output (MIMO) systems have gained huge consideration due to high achievable data rates and connection reliability for future wireless networks. Multiple signal paths due to multiple antennas positioned at transmitter or receiver are responsible for large throughput. The eventual objective of using array of small antennas is that each single antenna will have small power consumption. The rapid increase in the number of wireless applications has put some limitations on conventional MIMO systems on channel capacity, energy and spectral efficiency. One of the possible solutions to overcome these limitations is to use large antenna arrays at the base stations or to some extent on the user equipments (UEs). The essential factors that must be considered before the deployment of massive MIMO systems include the broadcast models, channel estimation, placement ways with applications, uplink & downlink benefits and precoding procedures, expected achievable energy & spectral efficiencies, etc. In this article a comparison of massive MIMO is made with conventional MIMO. The authors discussed the massive MIMO system deployment scenarios, the best possible downlink precoding scheme for maximum achievable throughput, energy and spectral efficiency. Keywords- Massive MIMO; broadcast models; channel estimation; precoding procedures. I. INTRODUCTION Comparing to various systems including single input single output (SISO), single input multiple outputs (SIMO) and multiple inputs single output (MISO), the multiple input multiple output (MIMO) uses multiple antennas at the transceiver to improve the system performance i.e. data rate and link reliability [1]. MIMO implementation has got its worth that is why; it is now identified as emerging and mature schemes in wireless communication to improve the data rates, system reliability, energy efficiency and by reducing the interference. It is the main reason of using MIMO in various standards like Universal Mobile Telecommunication System (UMTS) and Long Term Evolution (LTE) etc. [2]. For such systems we should have a keen knowledge about various demands for such large scaled multi user MIMO. Besides having the knowledge of the channel model for MIMO system, other requirements of knowledge includes placement ways with applications, uplink and downlink precoding ways and achievable energy and spectral efficiency of scalable MIMO systems over conventional MIMO systems. The deployment of base stations with enormous antenna i-e massive MIMO base stations uses spatial multiplexing in order to get capacity almost 10 times as more as conventional MIMO systems, also can increase 100 of times the energy efficiency [3]. The article contains systems model, the energy and spectral efficiency, deployment ways for massive MIMO systems and downlink precoding schemes. The concentrated antenna arrays design has transmitted signal energy beam width more directional than the distributed antenna arrays deployment. Authors after making comparison, proposed better deployment scheme for massive MIMO base stations. To achieve high system capacity, energy and spectral efficiency, user equipment (UE) should have communication over orthogonal channel. The interference cancellation can be achieved by using strong downlink precoding techniques. The next portion of the article will explain uplink and downlink benefits. The uplink benefits can be inspected through detection of UEs at the transmitter using Matched Filter (MF) and Minimum Mean Square Error detection algorithm (MMSE). The downlink benefits i.e. signal transmission in massive MIMO is analyzed and results are compared for Dirty Paper Coding (DPC), Block Diagonalization (BD) and Tomlinson-Harashima precoding (THP). We just explained DPC and Linear Precoding schemes including Zero Forcing (ZF) and Minimum Mean Square Error (MMSE). BD can be implemented using ZF or MMSE, but we implemented using ZF. BD and THP are not explained in this article but only considered for simulation. In this research paper, the purpose of focusing large antenna arrays for future wireless communication is to highlight the benefits of massive MIMO over the conventional MIMO [2]. The section II is related to channel model. Section III explains the spectral efficiency. Some deployment schemes are discussed in section IV. Efficient precoding schemes are presented in section V. We conclude our work in section VI. Proceedings of the 19 th International Conference on Automation & Computing, Brunel University, London, UK, 13-14 September 2013