Spectrum sharing in energy harvesting cognitive radio networks: A cross-layer perspective

TL;DR

This paper investigates energy harvesting cognitive radio networks using a cross-layer approach, formulating a stochastic Stackelberg game to optimize delay and power allocation while ensuring primary user transmission.

Contribution

It introduces a novel cross-layer framework and distributed algorithms for energy harvesting CRNs, addressing the strategic interactions between primary and secondary users without information exchange.

Findings

Distributed algorithms achieve Nash equilibrium for secondary users

Stackelberg game effectively models primary-secondary user interactions

Proposed algorithms improve delay performance in simulations

Abstract

In the paper, we present a cross-layer perspective on data transmission in energy harvesting cognitive radio networks (CRNs). The delay optimal power allocation is studied while taking into account the randomness of harvested energy, data generation, channel state and the grid price. To guarantee primary user (PU)'s transmission, its Signal-Interference-Ratio (SIR) should be no less than a threshold. Each user, including PU as well as secondary user (SU), has energy harvesting devices, and the PU can also purchases the grid power. Each user is rational and selfish to minimize its own the buffer delay. We formulate a stochastic Stackelberg game in a bilevel manner. After decoupling via rewriting the objective and constraints, an equivalent tractable reconstruction is derived. First, we give a distributive algorithm to obtain the Nash equilibrium (NE) of the lower level SUs' noncooperative stochastic game. Thereafter, the stochastic Stackelberg game is discussed under the circumstances that there is no information exchange between PU and SU. Distributed iterative algorithms are designed. Furthermore, a distributive online algorithm is proposed. Finally, simulations are carried out to verify the correctness and demonstrate the effectiveness of proposed algorithms.