Baud-rate clock recovery (CR) is gradually gaining popularity in modern serial data transmission systems since these CR techniques do not require edge-samples for extracting timing information. However, previous baud-rate techniques for high-speed serial links either rely on specific 4-bit patterns or uncorrelated random data. This work describes the modeling and design of analog filter front-end aided baud-rate CR schemes. Unlike other baud-rate schemes, this technique is not constrained by the properties of the input random data. Firstly, the thesis develops a hardware-efficient baud-rate algorithm that requires only the slope information of the incoming random data. Called modified sign-sign minimum mean squared error (SSMMSE), this algorithm adjusts the clock sampling phase until the slope is zero through a bang-bang control loop. Secondly, the performance of a modified SSMMSE phase detector is investigated and compared with a conventional edge-sampled phase detector. It is shown that, at severe noise levels, the proposed modified SSMMSE method has better performance compared to the edge-sampled method for equal loop bandwidths.Thirdly, the thesis investigates different hardware-efficient slope detection techniques. Both passive and active filter based slope detection techniques are demonstrated in this work. In addition to slope generation, the active filter performs linear equalization as well. However, the passive filter generates the slope information at higher speeds than the active filter and also consumes less power. The two filters are used to recover a 2-GHz clock by using an external bang-bang loop. In short, the thesis demonstrates that area and power savings can be achieved by utilizing slope information from front-end filters without compromising the performance of the CR unit.

Baud-rate clock recovery (CR) is gradually gaining popularity in modern serial data transmission systems since these CR techniques do not require edge-samples for extracting timing information. However, previous baud-rate techniques for high-speed serial links either rely on specific 4-bit patterns or uncorrelated random data. This work describes the modeling and design of analog filter front-end aided baud-rate CR schemes. Unlike other baud-rate schemes, this technique is not constrained by the properties of the input random data. Firstly, the thesis develops a hardware-efficient baud-rate algorithm that requires only the slope information of the incoming random data. Called modified sign-sign minimum mean squared error (SSMMSE), this algorithm adjusts the clock sampling phase until the slope is zero through a bang-bang control loop. Secondly, the performance of a modified SSMMSE phase detector is investigated and compared with a conventional edge-sampled phase detector. It is shown that, at severe noise levels, the proposed modified SSMMSE method has better performance compared to the edge-sampled method for equal loop bandwidths.Thirdly, the thesis investigates different hardware-efficient slope detection techniques. Both passive and active filter based slope detection techniques are demonstrated in this work. In addition to slope generation, the active filter performs linear equalization as well. However, the passive filter generates the slope information at higher speeds than the active filter and also consumes less power. The two filters are used to recover a 2-GHz clock by using an external bang-bang loop. In short, the thesis demonstrates that area and power savings can be achieved by utilizing slope information from front-end filters without compromising the performance of the CR unit.

This thesis proposes a blind receiver for the Nyquist pulse shaped quadratureamplitude modulation (QAM) signals. The focus is on single carrier signals. The blind receiver includes the estimation of the symbol rate, the roll-off factor of the filter, the optimal sample phase, the frequency offset, the phase offset and as well as the correction of frequency and phase offsets. The blind receiver is proposed for the cognitive radio applications. Cognitive radios are intelligent devices which can adapt themselves according to its user and its environment, i.e. they are aware of the user and the environment. Another importance of cognitive radios is they can detect the incoming signal and demodulate it and also respond to the transmitting node with the same parameters. In order to demodulate the signal and to respond the transmitter node, there are some parameters which are needed to be known. The estimation starts with the bandwidth and carrier frequency, continued by the estimation of the symbol rate, which is a crucial factor. After the estimation and restrictions of these parameters, the roll-off factor of the filter is estimated for match filtering to remove the inter symbol interference (ISI) effect. Then the optimal sample phase is detected and the signal is downsampled. The following procedures include the modulation identification and estimation and correction of both frequency and phase offsets. The estimation algorithms performance is compared to the performances of the other algorithms available in the literature. These simulation results are presented and discussed in this thesis.

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