【資料名稱】：MIMO Performance and Con

【資料作者】：安捷倫

【資料日期】：2009

【資料語(yǔ)言】：中文

【資料格式】：DOC

【資料目錄和簡(jiǎn)介】：

As companies rush to get Long Term Evolution (LTE)
products to market, engineers face tough challenges in
testing these often complex devices. The mandate to
include Multiple-Input Multiple-Output (MIMO) means
many engineers are working to optimize their multi-antenna
architectures. To achieve time-to-market goals, the MIMO
solutions under development need to work correctly in
real-world situations. Defining situations when MIMO
transmissions will improve system performance can
be complicated, but it is a critical aspect of successful
implementation.
Of particular interest is how to quickly determine whether a
MIMO channel is capable of supporting spatial multiplexing
under a given signal-to-noise ratio (SNR). Fortunately
with the proper test equipment, a figure of merit called
“condition number” can provide a short-term indication of
the SNR required to properly recover a MIMO transmission
over the selected wireless channel.
This application note will review the basic concepts of
MIMO with specific application to spatial multiplexing
in 3rd Generation Partnership Project (3GPP) LTE. It will
show measurements of channel coefficients and associated
condition numbers as they relate to the SNR at the LTE
receiver. How antenna and channel correlation affects
system performance will also be discussed, along with
recommendations for the best measurement tools to use
when developing LTE products and systems.
Multi-antenna wireless systems have been shown to
improve data capacity through spatial multiplexing and
improve system reliability through antenna diversity and
spatial coding such as Space-Time Block Coding (STBC)
and Space-Frequency Block Coding (SFBC). The suitability
of a MIMO wireless system for spatial multiplexing is
largely dependent on the characteristics of the wireless
channel, the antenna configuration and the ability of the
receiver to accurately recover the channel coupling matrix
coefficients. The complexity of the wireless channel
including channel correlation, interference and noise rate
may create difficulties when measuring the operation
and troubleshooting a MIMO system. Fortunately, the
operation of a LTE MIMO system with application to spatial
multiplexing can be quickly verified with a calculation of the
channel matrix “condition number” using a vector signal
analyzer (VSA) such as the Agilent 89601A. The condition
number is a deterministic calculation for evaluating the
performance of the wireless channel and estimating the
associated increase in SNR required for successful signal
demodulation in the LTE MIMO system. For example, a
condition number close to the ideal value of 0 dB would
imply perfect channel conditions for the application of
spatial multiplexing, while values greater than 10 dB would
point to the need for a dB per dB improvement in the
relative SNR in order to properly demodulate the MIMO
transmission. It can also be shown using the Agilent
89601A VSA that the channel matrix and associated
condition number is a function of subcarrier frequency and
time which may be a useful tool when studying the effects
of banding subcarriers at the evolved Node B (eNB) for the
highest performance.