The paper presents a novel digital timing recovery mechanism for communication systems. The proposed approach jitters the ADC clock based on phase information obtained directly or indirectly from the received signal. The paper studies the effect of jitter resolution and its distribution on the timing SNR. It is demonstrated through simulations that the best SNR is achieved when the jitters are equally spaced. The proposed timing recovery scheme can be implemented by means of a numerically controlled oscillator (NCO), a tapped delay line, or a combination of the two. Practical aspects of all these schemes are presented. The resulting mechanism is able to achieve voltage controlled crystal oscillator (VCXO)-like performance at a much lower implementation cost. Although the proposed methodology can be applied to most communication systems, we focus on its application to asymmetric digital subscriber line (ADSL) modems.

This paper proposes a practical evaluation methodology for timing recovery mechanisms in ADSL systems. The proposed methodology decouples the generation of timing imperfections to transform a closed-loop problem into a more tractable open-loop system. This results in a simpler and less computational intensive evaluation methodology as compared to detailed time domain simulations. We demonstrate the versatility of the proposed methodology by evaluating three timing recovery mechanisms, one based on a voltage controlled crystal oscillator (VCXO) and two jitter-based mechanisms. The first jitter-based approach applies all the jitters in the same instant while the second distributes the jitters over time. We also study the effect of non-ideal system behavior, like clock jitter, using the same framework.

Much of the work on turbo decoding assumes that the decoder has access to infinitely soft (unquantized) channel data. In practice, however, a quantizer is used at the receiver and the turbo decoder must operate on finite precision, quantized data. Hence, the maximum a posteriori (MAP) component decoder which was designed assuming infinitely soft data is not necessarily optimum when operating on quantized data. We modify the well-known normalized MAP algorithm taking into account the presence of the quantizer. This algorithm is optimum given any quantizer and is no more complex than quantized implementations of the MAP algorithm derived based on unquantized data. Simulation results on an additive white Gaussian noise channel show that, even with four bits of quantization, the new algorithm based on quantized data achieves a performance practically equal to the MAP algorithm operating on infinite precision data.