Multiuser TDMA channel estimation
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[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Wireless communication systems require efficient utilization of the limited available spectrum. There are various methods in which division of spectrum between users have been done till date, including frequency division, time division, code division and hybrid combinations of these methods. Cellular architectures efficiently utilize the spectrum by reusing the same channel in spatially separated cells. However, frequency reuse introduces co-channel interference, which determines the data rate that can be supported by each channel. For increasing the capacity of the multiple access systems, over the past few years research has been done on the field of multiuser multiple access systems. For example, in the case of TDMA systems, more than one user is allowed to use the same slot, thereby increasing the capacity of the conventional TDMA system. Implementation of a multiuser system calls for using either of the two techniques for detecting the co-channel signals, interference cancellation or multiuser detection. Multiuser detection is jointly detecting all the co-channel signals, while in interference cancellation technique desired signal is detected and the other co-channel signals are considered as interference. Over the years, various methods have been proposed for detecting the signals at the receiver, however not much attention has been given to the area of channel estimation. Majority of the research done on the receiver side assumes perfect channel knowledge. In this thesis I have proposed a very computationally easy and efficient algorithm of joint channel estimation based on least squares. The channel for all the users is simultaneously estimated. For this pilot sequence of each user having appropriate auto and cross correlation properties are used. I have also implemented a multislot MMSE based channel estimation algorithm for Multiuser TDMA system, as a comparison basis for the proposed algorithm. The results for Mean Square Error show that the proposed algorithm gives acceptable results. Also a graph has been presented to compare between the two algorithms.
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