Optimizing Access Mechanisms for QoS Provisioning in Hardware Constrained Dynamic Spectrum Access

TL;DR

This paper introduces efficient algorithms for optimizing sensing and transmission policies in hardware-constrained DSA systems to ensure QoS by minimizing queuing delays, using Large Deviations asymptotics for approximation.

Contribution

It presents novel algorithms that derive policies minimizing delay probabilities in DSA, surpassing previous mean data rate maximization approaches, with proven properties and efficiency.

Findings

Algorithms effectively minimize queuing delay probabilities.

Proposed methods outperform exhaustive search in efficiency.

Theoretical analysis confirms properties of optimal policies.

Abstract

One of the major challenges in Dynamic Spectrum Access (DSA) systems is to guarantee a required level of Quality of Service (QoS) to secondary users of the spectrum. In this paper, we propose efficient algorithms for deriving optimal policies for the sensing / transmitting trade-off in hardware-constrained DSA systems. Unlike previous approaches which seek to maximize mean data rate for the secondary users, the proposed algorithms derive policies which minimize the probability of excessive queuing delays. Large Deviations (LD) asymptotics are used to approximate the probability of interest and policies maximizing the associated LD exponent are proposed. Although dynamic programming is not able to identify the optimal policy in this case, much more efficient algorithms than exhaustive search are proposed. These algorithms are based on specific properties of the optimal policy which are described and proven in this paper.