MMSE Indicator Error Rate Performance on MIMO When Increasing Modulation Order

MMSE Indicator Error Rate Performance on MIMO When Increasing Modulation Order

Evariste Some, Ibrahim Ayad, Bryan C. Boots
DOI: 10.4018/IJITN.2021070101
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Abstract

Research in estimation theory has given evidence that the rich scattering of wireless channels is capable of great theoretical capacity if the multipath is efficiently utilized. Spatial multiplexing using multiple-input multiple-output (MIMO) systems makes efficient use of a limited frequency spectrum and increases the transmission throughput in wireless communications systems. This paper reviews the performance of the minimum mean squared error estimator for MIMO. In this context, it shows that the minimum mean square error (MMSE) for MIMO receiver exhibits an intricate error behavior that depends on channel condition, the antenna configuration, and the degree of modulation order. To this purpose, an explicit step-by-step mathematical model is derived for the receiver estimator and the error covariance based on the MMSE MIMO. Analysis, simulation, and experiment based on open source and programmable hardware and software results show that the MMSE estimator receiver efficiency is also based on the modulation order.
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1. Introduction

Wireless communication technology has profoundly changed the way we communicate. It is one of the most vibrant areas in the communication field today due to the confluence of several factors. First, there is a rapid evolution of cellular networks which embody a sophisticated communication systems concept. Additionally, there has been an exponential increase in demand for wireless connectivity driven mainly by cellular communication systems, and by wireless data applications. Therefore, technology such as MIMO communication have introduced new perspective on how to effectively communicate over the wireless channels.

To keep up with an exponential growth rate while providing a ubiquitous connectivity, academic researchers and industrial constantly need to propose solutions to sustain the current communication technology growth (Björnson et al., 2017).

In wireless communication system, the propagation channel is characterized by multipath propagation due to scattering phenomenon on different obstacle. In a rich urban area, signals bounce off obstacles (buildings, trees, etc.) and pursuing their way in different directions to their destination or to the receiver. The use of Multiple-Input Multiple-Output is often described by Spatial multiplexing.

In spatial multiplexing technique using MIMO system, multiple parallel data stream carries different data between transmitter and receiver, and therefore increases the data rate. The theoretical peak data rate is proportional to the minimum of the number of transmit and receive antennas.

The principles of operation of spatial multiplexing in an LTE system can be illustrated from Figure 1. Symbols travel from transmitter to the receiver antennas. In Figure 1, two channel transmitters have created four separate paths to the two channel receivers. From the receiver perspective, the signals can be represented, in real number, as:

IJITN.2021070101.m01
(1)
IJITN.2021070101.m02
(2)

IJITN.2021070101.m03 and IJITN.2021070101.m04 are the signals sent from the two transmit antennas. IJITN.2021070101.m05 and IJITN.2021070101.m06 are the received signal from antenna 1 and 2. IJITN.2021070101.m07 and IJITN.2021070101.m08represent the received noise and all type of interferences. IJITN.2021070101.m09 illustrates the way in which the transmitted symbols get attenuated and phase shifted as they propagate to receive antenna IJITN.2021070101.m10from transmit antenna IJITN.2021070101.m11. Very often, all terms in the Equation (1) are complex. However, the use of complex number would make the example complicated and without adding too much extra information.

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