  Perceptive mobile network (PMN) is a recently proposed next-generation
network that integrates radar sensing into communication. One major challenge
for realizing sensing in PMNs is how to deal with spatially-separated
asynchronous transceivers. The asynchrony between sensing receiver and
transmitter will cause both timing offsets (TOs) and carrier frequency offsets
(CFOs) and lead to degraded sensing accuracy in both ranging and velocity
measurements. In this paper, we propose an uplink sensing scheme for PMNs with
asynchronous transceivers, targeting at resolving the sensing ambiguity and
improving the sensing accuracy. We first adopt a cross-antenna
cross-correlation (CACC) operation to remove the sensing ambiguity associated
with both TOs and CFOs. Without sensing ambiguity, both actual propagation
delay and actual Doppler frequency of multiple targets can be obtained using
CACC outputs. To exploit the redundancy of the CACC outputs and reduce the
complexity, we then propose a novel mirrored-MUSIC algorithm, which halves the
number of unknown parameters to be estimated, for obtaining actual values of
delays and Doppler frequencies. Finally, we propose a high-resolution
angles-of-arrival (AoAs) estimation algorithm, which jointly processes all
measurements from spatial, temporal, and frequency domains. The proposed AoAs
estimation algorithm can achieve significantly higher estimation accuracy than
that of using samples from the spatial domain only. We also derive the
theoretical mean-square-error of the proposed algorithms. Numerical results are
provided and validate the effectiveness of the proposed scheme.

Signal Processing