Real MIMO systems use multiple transmitter streams and multiple receivers. As shown in Figure 3, each transmitter sends independent data [Tx₁; Tx₂; … Tx_n] from different transmit antennas simultaneously and using the same radio channel. At the receiver end, each antenna receives the composite signal from all transmitters represented by [Rx₁; Rx₂; … Rx_m] where m and n represent the number of receivers and transmitters respectively. In a practical application, m and n are typically less than 4.

The different paths may be represented mathematically as:

(1)
Rx₁ = h₁₁Tx₁ +h₁₂Tx₂+…. h_1nTx_n
Rx₂ = h₂₁Tx₁ +h₂₂Tx₂+…. h_2nTx_n
:
:
Rx_m = h_m1Tx₁ +h_m2Tx₂+…. h_mnTx_n

or, in matrix form as

(2)
[Rx] = [H][Tx].

The [H] in equation (2) represents the transfer matrix of a MIMO channel.

In a traditional radio system, multipath signals decrease throughput as they cause co-channel interference. On the other hand, a MIMO system relies on this interference suppression to implement multidatastream detection and then separate the individual transmitted streams. By carefully designing a MIMO packet and by using advanced digital signal processing (DSP) techniques in the MIMO decoder, we can recover the variously independent transmitted datastreams.

To recover the transmitted datastream [Tx] at the [Rx], the MIMO system decoder must first estimate the individual channel transfer coefficient h_ij to determine the channel transfer matrix [H] during the MIMO preamble of the packet. Once the estimated [H] has been produced, the transmitted datastream [Tx] can be reconstructed by multiplying the vector [Rx] with the inverse of transfer matrix [H]^-1. This is represented by

(3)
[Tx] = [H]^-1[Rx].

The process, in principle, is equivalent to solving a set of N unknowns with N linear equations. To ensure that the channel matrix is invertible, MIMO systems require an environment rich in multipath.

It is important to note that unlike traditional methods of increasing throughput by increasing bandwidth, MIMO systems can increase throughput without increasing bandwidth. This is accomplished in a MIMO system by exploiting the spatial dimensions and increasing the number of signal paths between the transmitters and the receivers.

Because each independent datastream is transmitted in parallel from separate antennas, the data throughput increases linearly with every pair of antennas added to the MIMO system. This means that by using a MIMO system, wireless network operators can increase their broadband services within the currently allocated spectrum without having to expand to more spectrums.

MIMO-OFDM technology brings significant performance improvements to wireless systems. However, it also brings many challenges to product development and testing due to the OFDM modulation and additional complexity of multiple radio architectures involved.

For the benefit of lower cost and higher-efficiency digital modulation, a zero intermediate frequency (ZIF) radio architecture with in-phase and quadrature (I/Q) modulation is often used in a MIMO system. In this type of architecture, the baseband signal is split into I, the in-phase component of the waveform, and Q, the quadrature-phase component of the waveform. On the transmitter side, the baseband I and Q components directly convert into radio frequency and feed the power amplifier and antenna for transmission. On the receiver side, the RF signal goes through the I/Q demodulator and converts directly to baseband I and Q components. Imbalances (amplitude, phase and group delay) between I and Q signal paths will directly affect modulation accuracy. In addition other impairments such as carrier frequency accuracy, phase noise, local oscillator (LO) leakage, spurious interference, and amplifier compression can affect the performance of a MIMO system. These are the imbalances and impairments we are most concerned with uncovering.

A MIMO packet consists of a legacy 802.11 a/g preamble field and a MIMO preamble field followed by the payload data. For each composite data packet received, the MIMO decoder must be able to estimate the channel transfer matrix [H] during the MIMO preamble of the packet. We assume that within the length of each MIMO signal packet, the characteristics of the communication link between the MIMO transmitters and receivers remain constant. The channel transfer matrix [H] determines the link characteristic. The quality of the transmitted signal during the preamble has a significant impact on the accuracy of the channel transfer matrix [H] estimation, and thus the quality of the MIMO system.

For the transmitters, the traditional impairments like I/Q mismatch, group delay and group delay variation, compression and phase noise will affect the system performance. There are many impairments that can affect transmitter performance such as variations in the baseband and radio-frequency integrated circuits (RFICs), component tolerance, impedance mismatching in the transmission line, components along the signal path, differences in the parasitic capacitances and inductances along the printed circuit board (PCB) traces for the I and Q signal path variations, spurious interference, non-linear effects of the amplifier, etc.

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