  In this paper we develop a novel needlet-based estimator to investigate the
cross-correlation between cosmic microwave background (CMB) lensing maps and
large-scale structure (LSS) data. We compare this estimator with its harmonic
counterpart and, in particular, we analyze the bias effects of different forms
of masking. In order to address this bias, we also implement a MASTER-like
technique in the needlet case. The resulting estimator turns out to have an
extremely good signal-to-noise performance. Our analysis aims at expanding and
optimizing the operating domains in CMB-LSS cross-correlation studies,
similarly to CMB needlet data analysis. It is motivated especially by next
generation experiments (such as Euclid) which will allow us to derive much
tighter constraints on cosmological and astrophysical parameters through
cross-correlation measurements between CMB and LSS.
