  We investigate a cognitive radio system where secondary user (SU) relays
primary user (PU) packets using two-phase relaying. SU transmits its own
packets with some access probability in relaying phase using time sharing. PU
and SU have queues of finite capacity which results in packet loss when the
queues are full. Utilizing knowledge of relay queue state, SU aims to maximize
its packet throughput while keeping packet loss probability of PU below a
threshold. By exploiting structure of the problem, we formulate it as a linear
program and find optimal access policy of SU. We also propose low complexity
sub-optimal access policies, namely constant probability transmission and step
transmission. Numerical results are presented to compare performance of
proposed methods and study effect of queue sizes on packet throughput.
