  Cooperative spectrum sensing is a robust strategy that enhances the detection
probability of primary licensed users. However, a large number of detectors
reporting to a fusion center for a final decision causes significant delay and
also presumes the availability of unreasonable communication resources at the
disposal of a network searching for spectral opportunities. In this work, we
employ the idea of sequential detection to obtain a quick, yet reliable,
decision regarding primary activity. Local detectors take measurements, and
only a few of them transmit the log likelihood ratios (LLR) to a fusion center
in descending order of LLR magnitude. The fusion center runs a sequential test
with a maximum imposed on the number of sensors that can report their LLR
measurements. We calculate the detection thresholds using two methods. The
first achieves the same probability of error as the optimal block detector. In
the second, an objective function is constructed and decision thresholds are
obtained via backward induction to optimize this function. The objective
function is related directly to the primary and secondary throughputs with
inbuilt privilege for primary operation. Simulation results demonstrate the
enhanced performance of the approaches proposed in this paper. We also
investigate the case of fading channels between the local sensors and the
fusion center, and the situation in which the sensing cost is negligible.
