  Integrating sensing into standardized communication systems can potentially
benefit many consumer applications that require both radio frequency functions.
However, without an effective sensing method, such integration may not achieve
the expected gains of cost and energy efficiency. Existing sensing methods,
which use communication payload signals, either have limited sensing
performance or suffer from high complexity. In this paper, we develop a novel
and flexible sensing framework which has a complexity only dominated by a
Fourier transform and also provides the flexibility in adapting for different
sensing needs. We propose to segment a whole block of echo signal evenly into
sub-blocks; adjacent ones are allowed to overlap. We design a virtual cyclic
prefix (VCP) for each sub-block that allows us to employ two common ways of
removing communication data symbols and generate two types of range-Doppler
maps (RDMs) for sensing. We perform a comprehensive analysis of the signal
components in the RDMs, proving that their interference-plus-noise (IN) terms
are approximately Gaussian distributed. The statistical properties of the
distributions are derived, which leads to the analytical comparisons between
the two RDMs as well as between the prior and our sensing methods. Moreover,
the impact of the lengths of sub-block, VCP and overlapping signal on sensing
performance is analyzed. Criteria for designing these lengths for better
sensing performance are also provided. Extensive simulations validate the
superiority of the proposed sensing framework over prior methods in terms of
signal-to-IN ratios in RDMs, detecting performance and flexibility.
