TDMA for Low Sampling Rate IR-UWB Receivers

Abstract: In UWB communication sampling plays a key role in detection of the transmitted data. There are various methods of data transmission and detection at the receiver. Mostly, the detection methods are based on frequency domain methods. The popular method to lower the sampling rate is the sub-sampling technique, based on frequency of the transmitted signal. A special method like orthogonal frequency division multiplexing (OFDM) is needed to reduce inter symbol interference for a frequency based method. The power consumption associated with higher sampling rates is also a big challenge. Therefore some simple techniques are required to detect data on lower sampling rates without ISI in the multiple user environments and with lower power consumption. If selection of the sampling frequency would be flexible to detect data from multiple users then it could relax the UWB receiver design requirements. In this thesis we developed a transmission and reception methodology with reduced sampling frequency for data detection. In the proposed work, transmitted data is distributed using TDMA frames for all users within fixed time slots for each user. The TDMA technique is being used to achieve low sampling rates and to avoid multiple access interference (MAI). The sampling rate to detect the data of each user can be selected according to number of users and transmission bandwidth. For this purpose each data bit of a user is arranged once in a transmission frame. The data can be detected on frame repetition rate depends on the total number of users. The data of each user can be accessed directly by calculating the total time of each user place within each frame. Since each data bit of one user occurs once in a frame therefore it could be claimed that ISI within the same user has been avoided. The proposed scheme has been tested with 50 MHz, 100 MHz and 500 MHz sampling frequencies for 50 users, 25 users and 5 users respectively by using 2.5 GHz bandwidth. 8-bits of data was transmitted and detected for different users using Matlab and Simulink Models. The results were analyzed in perfect synchronization condition and compared between integrated window energy detector UWB receiver and an UWB receiver using a matched filter. The performances are evaluated on the basis of BER. To observe the impact of synchronization, both receivers were evaluated with some timing mismatch. It is concluded that the scheme works well for the lower sampling rate for both types of UWB receivers stated above. It can also be concluded by observing the results that the UWB receiver using matched filter has better performance in noisy environment compared to energy detector UWB receiver with integrated window. The performance of energy detector UWB receiver with integrated window and UWB receiver with matched filter were also evaluated with timing mismatch. It can be concluded that the UWB receiver with integrated window has better performance compared to UWB receiver using matched filter if the synchronization is not achieved properly. The UWB receiver with matched filter is more vulnerable against timing mismatch compared to UWB receiver with integrated window.