Optimal Spectrum Access for Cognitive Radios

TL;DR

This paper introduces optimized spectrum access schemes for cognitive radios that improve secondary throughput while maintaining primary user stability, using adaptive sensing durations and feedback-based estimations.

Contribution

It proposes novel spectrum access mechanisms with optimized probabilities and sensing durations, enhancing cognitive radio performance over traditional methods.

Findings

Performance gains over conventional sensing schemes

Optimized access probabilities based on misdetection and false alarm rates

Effective primary feedback-based estimation methods

Abstract

In this paper, we investigate a time-slotted cognitive setting with buffered primary and secondary users. In order to alleviate the negative effects of misdetection and false alarm probabilities, a novel design of spectrum access mechanism is proposed. We propose two schemes. First, the SU senses primary channel to exploit the periods of silence, if the PU is declared to be idle, the SU randomly accesses the channel with some access probability $a_s$. Second, in addition to accessing the channel if the PU is idle, the SU possibly accesses the channel if it is declared to be busy with some access probability $b_s$. The access probabilities as function of the misdetection, false alarm and average primary arrival rate are obtained via solving an optimization problem designed to maximize the secondary service rate given a constraint on primary queue stability. In addition, we propose a variable sensing duration schemes where the SU optimizes over the optimal sensing time to achieve the maximum stable throughput of the network. The results reveal the performance gains of the proposed schemes over the conventional sensing scheme. We propose a method to estimate the mean arrival rate and the outage probability of the PU based on the primary feedback channel, i.e., acknowledgments (ACKs) and negative-acknowledgments (NACKs) messages.