Spatial correlation based analysis of soft combination and user selection algorithm for cooperative spectrum sensing

Hybrid cooperative spectrum sensing scheme based on spatial–temporal correlation in cognitive radio enabled VANET

“…Theorem 1: The covariance matrix Ψ Ψ in (16) can be calculated by taking full consideration of the joint spatial-temporal correlation as (see (17)…”

“…In [16], the performance of CSS in spatially correlated environments has been investigated, and the majority rule is shown to outperform other combining rules for hard decision. Besides, an analytical method has been provided in [17] to evaluate the impact of spatial correlation on CSS when soft combining is used at the FC. Although the conventional user selection schemes show effectiveness in diminishing the influence of spatial correlation, it seems that they could hardly be applied to CR-VANET directly since they are all designed for static scenarios.…”

Efficient error detection in soft data fusion for cooperative spectrum sensing

“…, where s(t) is the PU signal energy transmitted during the sensing interval t. Hence we can write it as [30],…”

“…The energy detection does not require any priori knowledge of primary signals and most importantly it has much lower complexity than the others. Therefore, it is widely applied in cognitive radio networks [17].…”

Performance improvement for machine learning‐based cooperative spectrum sensing by feature vector selection

“…In soft fusion, SUs can transmit the complete local test statistics for soft decision. Soft fusion can achieve better detection performance at the cost of control channel overhead while the hard fusion requires much less control channel bandwidth with possibly degraded performance due to the loss of information [8–10].…”