  Frame theory is a powerful tool in the domain of signal processing and
communication. Among its numerous configurations, the ones which have drawn
much attention recently are Equiangular Tight Frame (ETF) and Grassmannian
Frame. These frames both have some kind of optimality in coherence, thus bring
robustness or optimal performance in applications such as digital fingerprint,
erasure channels, and Compressive Sensing. However, too strict constraint on
existence and construction of ETF and Grassmannian Frame became the main
obstacle for widespread use. In this paper, we propose a new configuration of
frame: Quasi-Equiangular Frame, as a compromise but more convenient and
flexible approximation of ETF and Grassmannian Frame. We will give formal
definition of Quasi-Equiangular Frame and analyze its relationship with ETF and
Grassmannian frame. Furthermore, for popularity of ETF and Grassmannian frame
in Compressive Sensing, we utilize the technique of random matrices to obtain
asymptotical concentration estimation of the Restricted Isometry Constant (RIC)
of Quasi-Equiangular Frame with respect to its key parameter.
