Hybrid annihilation transformation (HAT) for pipelining QRD-based least-square adaptive filters

A novel transformation, referred to as hybrid annihilation transformation ( HAT), for pipelining the QR decomposition (QRD) based least square adaptive filters has been developed. HAT provides a unified framework for the deriv ation of high-throughput/low-power VLSI architectures of three kinds of QRD adaptive filters, namely, QRD recursive least-square (LS) adaptive filters , QRD LS lattice adaptive filters, and QRD multichannel LS lattice adaptive filters. In this paper, HAT is presented as a solution to break the bottle neck of a high-throughput implementation introduced by the inherent recursi ve computation in the QRD based adaptive filters. The most important featur e of the proposed solution is that it does not introduce; any approximation in the entire filtering process. Therefore, it causes no performance degra dation no matter how deep the filter is pipelined. It allows a linear speed up in the throughput rate by a linear increase in hardware complexity. The sampling rate can be tradedoff for power reduction with lower supply voltag e for applications where high-speed is not required. The proposed transform ation is addressed both analytically, with mathematical proofs, and experim entally, with computer simulation results on its applications in wireless c ode division multiple access (CDMA) communications, conventional digital co mmunications and multichannel linear predictions.