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

This paper studies a generic model for cooperative cognitive radio networks where the secondary user is equipped with a finite length relaying queue as well as a finite length battery queue. Our prime objective is to characterize the stable throughput region. Nevertheless, the complete characterization of stable throughput region is notoriously difficult, since the computation of the steady state distribution of the two-dimensional Markov Chain (MC) model for both finite queues is prohibitively complex. We first propose an algorithm to characterize the stable throughput region numerically, and show its sheer computational complexity for large queue lengths. Hence, we next focus on two simpler systems, namely, finite battery queue with infinite relay queue and finite relay queue with infinite battery queue. The motivation behind the relaxation of having two finite queues at the same time is to lend tractability, explore the nature of design parameters optimization at the cognitive node and provide efficient lower computational complexity algorithms for stable throughput region characterization. For each proposed system, we investigate the maximum service rate of the cognitive node subject to stability conditions. Despite the complexity of the formulated optimization problems due to their non-convexity, we exploit the problems’ structure to transform them into linear programs. Thus, we are able to solve them efficiently using standard linear programming solvers. Our numerical results demonstrate that, in practical systems, finite battery and relaying queues achieve the same level of benefits of a system with infinite queue sizes when their sizes are sufficiently large. They also reveal that the achievable stable throughput region significantly expands when the arrival rate of the energy harvesting process increases.