MIMO wireless is a technological breakthrough that will allow Gb/s speeds in NLOS wireless networks. These systems exploit the space dimension to improve wireless systems capacity, range and reliability. Specifically, these systems explore multi-path propagation using different transmission paths between transmitter and receiver. Here a message signal is transmitted using multiple antennas via different independent paths. These different paths have different fading characteristics affecting the same signal in different ways. These multiple versions of the same signal are received and combined at the receiver. Combining is the process to extract the main transmitted signal with minimum channel effects. This process is based on digital signal processing techniques. Properly combining the multiple signals will greatly reduce the effect of fading and improve reliability of transmission. This is due to the fact that deep fades can not occur simultaneously during the same time intervals on two or more paths. All the received signals are uncorrelated, the strongest signal is picked, further equalized and demodulated to receive with minimum bit error rate. This scheme is called as diversity. The general basic model of diversity is illustrated in Figure 3. The signal s(t) travels through different independent fading paths having different channel impulse response $h_1(t), h_2(t) , ….. h_n(t)$ and signal gets distorted due to addition of interfering signal $I_1, I_2,…., I_n$ and white Gaussian noise. Finally the multiple signals $y_1(t), y_2(t),….y_n(t)$ are received and used for combining and equalization.

Based on the type of fading, diversity techniques can be divided in to two categories, Microscopic diversity and Macroscopic diversity.

i) Microscopic Diversity techniques: These techniques are used in small scale fading environment. As the user moves over distances of just a few wavelengths, deep and rapid amplitude fluctuations occur due to multiple reflections from the surrounding objects. The rapidly changing signal is exploited to avoid deep fades by separating antennas by fraction of a meter, one antenna may receive null while other may receive a strong signal. By selecting the best or strong signal at all times, the receiver can mitigate small scale fading effects. Figure 4 illustrates the microscopic diversity.

ii) Macroscopic Diversity techniques: These techniques are used in large scale fading environments, where shadowing is present due to variations in terrain profile and surrounding. It occurs at large distances from the base station and that base station is selected which is not shadowed in comparison to others. Figure 5 illustrates the macroscopic diversity.

The concept of diversity encouraged the development of many forms of MIMO systems such as Single Input Multiple Output (SIMO) systems, Multiple Input Single Output (MISO) system and Multiple Input Multiple Output (MIMO) systems as illustrated in Figure 5.

With reference to Figure 6, various systems can be defined as follows,

SISO: Traditionally systems with one transmit and one receive antenna are denoted as single input single output (SISO) systems. This system is very simple and deals with communication between a transmitter and a receiver. In this system, diversity feature is absent so probability of error is very high and capacity is limited by fading.

SIMO: Systems with one transmit and multiple receive antennas are denoted as single input multiple output (SIMO) systems. These systems receive multiple versions of one signal through multiple antennas, therefore exhibit receive diversity. If M antennas are used at the receiver end and the average amplitude of signal received on all antennas is same, they can be added coherently to produce $M^2$ times increase in the signal power, hence increase in SNR ($\gamma$) for SIMO system can be represented as $\gamma \ \text{SIMO} = M^{2} \times \text{Signal Power} / M \times \text{Noise power} = M. \gamma$ So, the channel capacity becomes, $C_{SIMO}= B log_2 (1+ M.\gamma)$.

MISO: Systems with multiple transmit and one receive antenna are called multiple input single output (MISO) systems. In such systems, a signal is transmitted via multiple antennas at the same time and received by a single antenna, exhibit transmit diversity. If N antennas are used at the transmitter, the total transmitted power is divided in to N branches and noise power is same as SISO, then SNR ($\gamma$) for MISO system can be represented as $\gamma \ \text{MISO} = (N^{2} \times \text{Signal Power} / N)/ \text{Noise power} = N. \gamma$ and the channel capacity in this case becomes, $C_{MISO}=B log_2 (1+ N.\gamma)$.

MIMO: Systems with multiple input antennas and multiple output antennas are referred as MIMO system. In fact it can be viewed as a combination of MISO and SIMO. Therefore it exhibits transmit receive diversity and it is possible to get MN fold increase in the SNR providing a channel capacity approximately equal to $C_{MIMO}= B log_2 (1+ M N.\gamma)$.

By analyzing the above equations, it can be concluded that the channel capacity for the MIMO system is higher. Usually, multiple antennas or antenna arrays are present at the base station, as there is enough space and since it is cheaper to install multiple antennas at base stations than to install them in every mobile station.