  We present a novel iterative algorithm for approximating the linear least
squares solution with low complexity. After a motivation of the algorithm we
discuss the algorithm's properties including its complexity, and we present
theoretical results as well as simulation based performance results. We
describe the analysis of its convergence behavior and show that in the noise
free case the algorithm converges to the least squares solution.
