Session-Based Cooperation in Cognitive Radio Networks: A Network-Level Approach

TL;DR

This paper introduces a network-level session-based cooperative approach in cognitive radio networks, grouping secondary users to cooperate with primary sessions, thereby improving spectrum access and network throughput.

Contribution

It proposes a novel session-based cooperation scheme that addresses limitations of existing frame-based methods and develops an optimization algorithm for network resource management.

Findings

The NLC approach outperforms existing frame-based methods in simulations.

The augmented SIO-based algorithm effectively finds optimal scheduling solutions.

The proposed scheme enhances spectrum utilization and network throughput.

Abstract

In cognitive radio networks (CRNs), secondary users (SUs) can proactively obtain spectrum access opportunities by helping with primary users' (PUs') data transmissions. Currently, such kind of spectrum access is implemented via a cooperative communications based link-level frame-based cooperative (LLC) approach where individual SUs independently serve as relays for PUs in order to gain spectrum access opportunities. Unfortunately, this LLC approach cannot fully exploit spectrum access opportunities to enhance the throughput of CRNs and fails to motivate PUs to join the spectrum sharing processes. To address these challenges, we propose a network-level session-based cooperative (NLC) approach where SUs are grouped together to cooperate with PUs session by session, instead of frame by frame as what has been done in existing works, for spectrum access opportunities of the corresponding group. Thanks to our group-based session-by-session cooperating strategy, our NLC approach is able to address all those challenges in the LLC approach. To articulate our NLC approach, we further develop an NLC scheme under a cognitive capacity harvesting network (CCHN) architecture. We formulate the cooperative mechanism design as a cross-layer optimization problem with constraints on primary session selection, flow routing and link scheduling. To search for solutions to the optimization problem, we propose an augmented scheduling index ordering based (SIO-based) algorithm to identify maximal independent sets. Through extensive simulations, we demonstrate the effectiveness of the proposed NLC approach and the superiority of the augmented SIO-based algorithm over the traditional method.