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Comments on "A Square-Root-Free Matrix Decomposition Method for Energy-Efficient Least Square Computation on Embedded Systems"
A square-root-free matrix QR decomposition (QRD) scheme was rederived in [1]
based on [2] to simplify computations when solving least-squares (LS) problems
on embedded systems. The scheme of [1] aims at eliminating both the square-root
and division operations in the QRD normalization and backward substitution
steps in the LS computations. It is claimed in [1] that the LS solution only
requires finding the directions of the orthogonal basis of the matrix in
question, regardless of the normalization of their Euclidean norms. MIMO
detection problems have been named as potential applications that benefit from
this. While this is true for unconstrained LS problems, we conversely show here
that constrained LS problems such as MIMO detection still require computing the
norms of the orthogonal basis to produce the correct result