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This paper studies a generic model for cooperative cognitive radio networkswhere the secondary user is equipped with a finite relay queue as well as afinite battery queue. Our prime objective is to characterize the stablethroughput region. Nevertheless, the complete characterization of the stablethroughput region for such system is notoriously difficult, since thecomputation of the steady state distribution of the two-dimensional MarkovChain (MC) model for both finite queues is prohibitively complex. We firstpropose an algorithm to characterize the stable throughput region numerically,and show its sheer computational complexity for large queue lengths. To lendtractability and explore the nature of design parameters optimization at thecognitive node, we next focus on two simpler systems, namely, finite batteryqueue with infinite relay queue and finite relay queue with infinite batteryqueue (referred henceforth as dominant system $1$ and $2$, respectively). Foreach proposed dominant system, we investigate the maximum service rate of thecognitive node subject to stability conditions. Despite the complexity of theformulated optimization problems, due to their non-convexity, we exploit theproblems' structure to transform them into linear programs. Thus, we are ableto solve them efficiently using standard linear programming solvers. Ournumerical results demonstrate that, in practical systems, finite battery andrelay queues achieve the same level of benefits of a system with infinite queuesizes, when their sizes are sufficiently large. They also reveal that theachievable stable throughput region significantly expands when the arrival rateof the energy harvesting process increases.

Stable Throughput of Cooperative Cognitive Networks with Energy Harvesting: Finite Relay Buffer and Finite Battery Capacity