Multiple-input, multiple- output (MIMO) spatial-diversity antenna configurations are specified for emerging 3GPP Long- Term Evolution (LTE) mobile communications systems. In reality, LTE systems specify three types of antenna techniques: MIMO, beamforming, and diversity approaches. The three techniques are considered essential for improving signal robustness and achieving LTE system capacity. Understanding how the different antenna techniques work can also aid in testing systems using these approaches.

Figure 1 depicts simple versions of various antenna techniques. The name given to each technique indicates how the radio channel is accessed by the system’s transmitters and receivers. The single-input, single-output (SISO) approach is the most basic radio-channel access mode with one transmitter and one receiver.

The multiple-input, single-output (MISO) mode is slightly more complex, using two or more transmit antennas and a single receive antenna. In a MISO system, which is commonly referred to as a transmit diversity system, the same data is sent on both of the transmitting antennas but is coded in such a way that the receiver can identify each transmitter. Transmit diversity makes the signal more resistant to fading and can improve performance under low signalto- noise-ratio (SNR) conditions. This technique does not directly increase data rates but rather supports current data rates with less power. Transmit diversity can be enhanced with closed-loop feedback from the receiver to indicate the balance of phase and power used for each antenna.

The single-input, multiple-output (SIMO) approach, often referred to as a receive diversity technique, employs one transmit antenna and two or more receive antennas. As with the transmit diversity method, it is well suited for low-SNR conditions, making a theoretical gain of 3 dB possible when two receivers are used. There is no change in the data rate since only one data stream is transmitted.

The MIMO approach requires two or more transmit antennas and two or more receive antennas. This mode is not just a superposition of MISO and SIMO, because multiple data streams are transmitted simultaneously in the same frequency and time, taking full advantage of the different paths in the radio channel. A MIMO system must have at least as many receivers as data streams transmitted. The number of these transmit streams should not be confused with the number of transmit antennas. Consider the transmit diversity (MISO) case with two transmit antennas but only one transmit stream.

Adding receive diversity (SIMO) to MISO does not create a MIMO system, even though there are now two transmit and two receive antennas involved. It is always possible to have more transmitters than data streams but not the other way around. If a number, N, of data streams is transmitted from fewer than N transmit antennas, the data cannot be fully descrambled no matter how many receivers are present. Overlapping data streams without the addition of spatial diversity simply creates interference. However, if the N streams are spatially separated across at least N antennas, N receivers will be able to fully reconstruct the original data streams, provided that crosstalk and noise in the radio channel are sufficiently low not to cause lost data.

For MIMO operation, the transmissions from each antenna must be uniquely identifiable so that each receiver can determine what combination of transmissions it has received. This identification is usually accomplished with pilot signals, which use orthogonal patterns for each antenna. Spatial diversity of the radio channel in this case gives MIMO the potential to increase the data rate.

A basic form of MIMO assigns one data stream to each antenna (Fig. 2). The channel then mixes up the two transmissions such that at the receivers each antenna sees a combination of each stream. Decoding the received signals is a clever process in which the receivers analyze patterns that identify each transmitter to determine what combination is present. Applying an inverse filter and summing received streams recreates the original data.

A more advanced form of MIMO includes special precoding to match the transmissions to the Eigen modes of the channel. This optimization results in each stream being spread across more than one transmit antenna. For this technique to work effectively the transmitter must have knowledge of the channel conditions and, in some instances, these conditions must be provided in real time by feedback from the user equipment (UE). Such optimization complicates the system but can boost performance.

The theoretical gains from MIMO are a function of the number of transmit and receive antennas, the radio propagation conditions, the ability of the transmitter to adapt to the changing conditions, and the SNR. The ideal case is one in which the paths in the radio channel are uncorrelated, almost as if there were separate, physically cabled connections with no crosstalk between the transmitters and receivers. Because such conditions are almost impossible to achieve in free space, it is neither helpful nor possible to quote MIMO gains without stating the conditions. The upper limit of MIMO gain in ideal conditions is more easily defined, and for a 2 x 2 system with two simultaneous data streams a doubling of capacity and data rate is possible.

MIMO techniques work best in conditions of high SNR with minimal line of sight. Line of sight equates to channel crosstalk and diminishes the potential for gain improvement. As a result, MIMO is particularly suited to indoor environments, which often exhibit a high degree of multipath and limited line-of-sight conditions.

Although the simple depictions of Fig. 1 do not clarify whether multiple transmitters and receivers are used in a MIMO system, details on a few example cases shown in Fig. 3 may help to explain different MIMO setups. The first case is a singleuser MIMO (SU-MIMO) system, which is the most common form of MIMO and can be applied in the uplink or downlink of a wireless system. The primary purpose of SU-MIMO is to increase the data rate to one user. There is also a corresponding increase in the capacity of the cell. Figure 3 shows the downlink form of a 2 x 2 SU-MIMO system in which two data streams are allocated to one UE. The data streams in the example are coded red and blue, and in this case, are further precoded in such a way that each stream is represented at a different power and phase on each antenna. The colors of the data streams change at the transmit antennas, which is meant to signify the mixing of the data streams. The transmitted signals are further mixed by the channel. The purpose of the precoding is to optimize the transmissions to the characteristics of the radio channel so that when the signals are received, they can be more easily separated back into the original data streams.

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