الفهرس 
Survey on Multiple-Input Multiple-Output systemsOnly 14 pages are availabe for public view
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Abstract
Multiple-Input Multiple-Output, or MIMO, refers to the use of multiple antennas at both the transmitter and receiver sides to improve communication performance. MIMO systems offer significant increases in data throughput and link range without additional bandwidth or transmit power. Because of these properties, MIMO is a current field of international wireless research. There are numerous MIMO signal detection techniques that have been studied in the previous decades such as Maximum Likelihood (ML), Sphere Decoding(SD), Zero Forcing (ZF), and Minimum Mean Square Error (MMSE) detectors.It is well known that the additive and multiplicative noise in the information signal can significantly degrade the performance of MIMO detectors. During the last few years, the noise problem has been the focus of several research, and its solution could lead to profound improvements in symbol error rate performance of the MIMO detectors. In this thesis, ML, ZF, MMSE, and SD based wavelet de-noising detectors are proposed. In these techniques, the noise contaminated signals from each receiving antenna element are de-noised individually in parallel to boost the SNR of each branch. The de-noised signals are applied directly to the desired signal detector. The simulation results revealed that the proposed detectors based on de-noising basis achieve better symbol error rate(SER) performance than that of the traditional systems currently in use. The ML based wavelet de-noising detector achieves better symbol error rate (SER)performance than the other proposed techniques.