An arbitrarily high sampling rate DLMS adaptive filter

The authors propose a new scheme for implementing gradient based transversal adaptive filters at speeds which are theoretically independent of both filter order and hardware speed. The design is based on an order recursive variant of the delayed least mean squares (DLMS) algorithm. The order recursive nature of this algorithm allows the use of pipelining techniques to design high speed adaptive filters whose sampling rates are independent of the filter order. It is shown that this algorithm can be vectorized so that an arbitrary number of outputs can be computed simultaneously using parallel hardware. The proposed system is shown to be capable of implementing transversal adaptive filters at sampling rates which are theoretically without bound. The performance of the proposed system is analyzed and simulation results are presented to verify the convergence properties of the algorithm