Buffer-aware power control for cognitive radio networks

In this paper we study the problem of buffer-aware power control in underlay cognitive radio networks. In particular, we investigate the role of buffer state information, manifested through the secondary users´ queue lengths, along with channel state information in the cognitive radio power control problem. Towards this objective, we formulate a constrained optimization problem to find the set of secondary user transmit powers that maximizes the sum of rates weighted by the respective buffer lengths subject to signal-to-interference-and-noise-ratio (SINR) and maximum power constraints. Motivated by the problem´s non-convexity, we cast the problem into a sequential Geometric Programming formulation which can be solved efficiently using known solvers. Our simulation results confirm the throughput-delay trade-off via comparing the performance of the buffer-aware scheme, measured in terms of throughput and queue length, to a baseline, buffer-independent scheme that simply maximizes the sum rate of the secondary users. The gathered numerical results reveal interesting insights about the problem. It demonstrates almost two-fold reduction in the average secondary transmitter queue length for the proposed scheme over the baseline. This is attained at the expense of slight degradation (e.g. 15% in our scenario) in the secondary sum rate (throughput). This, in turn, confirms the key role buffer state information plays in balancing the fundamental throughput-delay trade-off in cognitive radio networks and opens ample room for future research on multiple access and optimal resource allocation in delay-constrained cognitive radio networks.