MIMO Architecture for Wireless Communication Intel

In this paper, we consider the use of multiple-input multiple-output (MIMO) architecture for wireless communication systems. We show how by employing MIMO architecture, architecture in which transmission and reception are carried out through multiple antennas, one can design a superior wireless communication system with respect to reliability, throughput, and power consumption. INTRODUCTION In recent years, wireless communication devices have become more and more popular. However, at the same time, the design of faster, more reliable, and powerefficient wireless communication systems has become evermore difficult. Wireless channels, as opposed to wireline channels, exhibit highly irregular amplitude behavior due to what is known as fading. The fading, essentially caused by the reception of multiple reflections of the transmitted signal (illustrated in Figure 1), is a key inherent problem of wireless channels, which, unfortunately, cannot be avoided. Fading causes the received signal power to change rapidly in time, making the task of information extraction from the received signal a fairly complicated endeavor. Furthermore, once the information is extracted, its reliability, manifested through error probability, is often poor. In this paper, we demonstrate how by exploiting the spatial diversity, namely, using multiple antennas, one can improve reliability, increase transmission throughput, and reduce transmission power. We also briefly discuss the benefits of using MIMO architecture along with orthogonal frequency division multiplexing (OFDM) modulation, and low-density parity check (LDPC) coding. First, we consider the reliability issue. We present a basic model for the wireless single-input single-output (SISO, single transmit antenna, single receive antenna) channel, and show how the corresponding error probability is critically damaged by fading. We then consider the singleinput multiple-output (SIMO, single transmit antenna, multiple receive antennas) channel and describe the concept of maximal ratio combining (MRC) as a way to exploit the receive diversity offered by this type of channel. We calculate the error probability achieved by the MRC, showing it to be much smaller than the one corresponding to the SISO channel, in which no spatial diversity exists. Next, we consider the multiple-input single-output (MISO, multiple transmit antennas, single receive antenna) channel, and we present some mechanisms that exploit the transmit diversity offered by this channel. Specifically, the beamforming technique and Alamouti’s [3] scheme are analyzed. Bringing together transmit and receive diversity, the MIMO channel is introduced. The beamforming technique and Alamoutibased scheme are shown to achieve full diversity, i.e., they take full advantage of both transmit and receive diversity provided by the MIMO channel. We discuss the performance of the aforementioned spatial diversity techniques, and we draw some conclusions as to when one should be preferred over the other. Figure 1: Wireless channel–fading problem due to multiple reflections Intel Technology Journal, Volume 10, Issue 2, 2006 MIMO Architecture for Wireless Communication 158 Improved reliability is not the only outcome of using multiple antennas. About ten years ago, a remarkable theoretical result regarding the capacity of MIMO channels [1] suggested that the transmission rate over wireless channels can be dramatically increased when using multiple antennas. It turns out that the ability to transmit and receive through multiple antennas does not only reject fading; better yet, it actually harnesses the fading itself in favor of increased throughput. We present the capacity of wireless MIMO channels, showing it to be greater than that of the wireline SISO channel. Moreover, the capacity formula is used to demonstrate how one can reduce transmission power by using multiple antenna systems. Finally, we briefly explain how, in principal, integration between MIMO architecture, OFDM modulation, and LDPC coding (essentially the basic building blocks for the most advanced wireless communication standards, e.g., 802.11n, 802.16), can give rise to a superior wireless communication system. The outline of the paper is as follows. We first present a basic model for the wireless SISO channel. We then consider the MRC technique, the beamforming technique, and Alamouti’s scheme. After that, we present the capacity of MIMO channels and then discuss the benefits of using MIMO architecture along with OFDM modulation and LDPC coding. We conclude with some remarks on the performance of MIMO architecture and how the Intel Centrino mobile technology benefits by embracing it. THE WIRELESS CHANNEL In this section, we present a basic model for the wireless channel and show its performance to be inferior to that of the wireline channel. The traditional wireline channel is modeled by the equation y x n = + (1.1) where x is the channel input. x is a complex number, referred to as symbol, representing two bits of information, i.e., it can take up to four different values according to the mapping (in general, x may be chosen to represent more than two bits of information): "00" "01" "10" "11" s s