  Cognitive radio (CR) is a key enabler realizing future networks to achieve
higher spectral efficiency by allowing spectrum sharing between different
wireless networks. It is important to explore whether spectrum access
opportunities are available, but conventional CR based on transmitter (TX)
sensing cannot be used to this end because the paired receiver (RX) may
experience different levels of interference, according to the extent of their
separation, blockages, and beam directions. To address this problem, this paper
proposes a novel form of medium access control (MAC) termed sense-and-predict
(SaP), whereby each secondary TX predicts the interference level at the RX
based on the sensed interference at the TX; this can be quantified in terms of
a spatial interference correlation between the two locations. Using stochastic
geometry, the spatial interference correlation can be expressed in the form of
a conditional coverage probability, such that the signal-to-interference ratio
(SIR) at the RX is no less than a predetermined threshold given the sensed
interference at the TX, defined as an opportunistic probability (OP). The
secondary TX randomly accesses the spectrum depending on OP. We optimize the
SaP framework to maximize the area spectral efficiencies (ASEs) of secondary
networks while guaranteeing the service quality of the primary networks.
Testbed experiments using USRP and MATLAB simulations show that SaP affords
higher ASEs compared with CR without prediction.
