Simulative Investigation on Different Multi Input Multi Output Signal Detection Technique

Abstract

The number of users of wireless communication is increasing day by day, but as the radio spectrum is limited hence the only solution is to increase the data rates to accommodate more users. These data rates can be achieved only by designing more efficient signaling techniques. Multiple Input Multiple Output (MIMO) technology is one of the most promising wireless technologies that can efficiently boost the data transmission rate, improve system coverage, and enhance link reliability. By employing multiple antennas at transmitter and receiver sides, MIMO techniques enable a new dimension called the spatial dimension that can be utilized in different ways to combat the impairments of wireless channels, but Inter Symbol Interference (ISI) is the main problem. To reduce ISI there are different detection techniques used. Detection is a well known technique for combating intersymbol interference. This paper will focus different types of detectors like Minimum Mean Square Error (MMSE), Maximum likelihood (ML), Minimum Mean Square Error Successive Interference Cancellation (MMSE-SIC), Zero Forcing Successive Interference Cancellation (ZF-SIC),Zero Forcing (ZF), Expected Propagation (EP-10), Gaussian Tree Approximation (GTA) and Gaussian Tree Approximation Successive Interference Cancellation (GTA-SIC) detector. These detectors are compared and analyzed for different Signal Error Rate (SER) v/s Signal to Noise Ratio (SNR) in spatial multiplexing domain. A simulation results shows that ZF, MMSE and MMSE-SIC detectors have better performance in terms of SER and SNR and have less computing time as over other detectors.