Introduction
Through this series of blogs we would be covering the different and prominent equalization techniques inherited in order the increase the reliability and widen the coverage of data transmitted using MIMO technique.
What is MIMO ?
Multiple Input- Multiple Output is a technique for wireless communication. Here, as the name suggests, multiple antennas are used at each end (Tx and Rx) for signal transmission. The use of multiple antennas at each end minimizes the possibility of error, optimizes data speed and capacity of the signal to be transmitted at the same time using multiple paths. The transmission of the signal over different paths also reduces fading signal, increases the SNR (signal to noise ratio) and opens a way to recover a lost signal.
MIMO system uses a radio- wave phenomena known as multi- path, where the signal bounces off the surface or object and reach the receiving antenna multiple times at different angles.
Though MIMO system enhances the spatial diversity of signal for communication, it is vulnerable to distortions due to the inter- symbol interference or ISI.
Inter symbol interference refers to the phenomena where a symbol in a signal interferes with subsequent symbols having similar effect as noise. It is responsible for causing bit error at the receiver end. It is considered as a major drawback in the high speed data transmission over wireless networks.
This creates a need for introduction of a process to suppress the effect of noise in the transmitted signal. Equalization technique can be used to combat this corruption of data and enhance reliability.
What is Equalization?
Equalization in communication is the reversal of the deformation occurred in a transmitted signal. The deformations may occur due to multi path fading, inter- symbol interference, additive noise, etc. This is usually applied at the baseband or the intermediate frequency in the receiver.
Through this series of blogs we would review a few methods of equalization , namely:
> Minimum Mean Square Error Equalization
> Zero Forcing Equalization
>Maximum Likelihood Equalization
> Maximal Ratio Combining
Reference
[1] Chaves, Fabiano & Romano, João & Turki, Mohamed & Abou-Kandil, Hisham. (2011). A convex combination of H2 and H∞ filters for space-time adaptive equalization. 717–720. 10.1109/SSP.2011.5967803.
