Title: Spectrum prediction and aggregation strategy in multi-user cooperative relay networks

Authors: Yifei Wei; Qiao Li; Xia Gong; Da Guo; Yong Zhang

Addresses: School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Rd., Haidian District, Beijing, 100876, China ' School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Rd., Haidian District, Beijing, 100876, China ' School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Rd., Haidian District, Beijing, 100876, China ' School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Rd., Haidian District, Beijing, 100876, China ' School of Electronic Engineering, Beijing University of Posts and Telecommunications, No. 10 Xitucheng Rd., Haidian District, Beijing, 100876, China

Abstract: In order to meet the constantly increasing demand by mobile terminals for higher data rate with limited wireless spectrum resources, cooperative relay and spectrum aggregation technologies have attracted much attention owing to their capacity in improving spectrum efficiency. Combining cooperative relay and spectrum aggregation technologies, in this paper, we propose a spectrum aggregation strategy based on the Markov prediction of the state of spectrum for the cooperatively relay networks on a multi-user and multi-relay scenario aiming at ensuring the user channel capacity and maximising the network throughput. The spectrum aggregation strategy is executed through two steps. First, predict the state of spectrum through Markov prediction. Based on the prediction results of state of spectrum, a spectrum aggregation strategy is proposed. Simulation results show that the spectrum prediction process can observably lower the outage rate, and the spectrum aggregation strategy can greatly improve the network throughput.

Keywords: Markov model; spectrum aggregation; multi-user; cooperative relay; outage probability; network throughput.

DOI: 10.1504/IJHPCN.2019.097500

International Journal of High Performance Computing and Networking, 2019 Vol.13 No.2, pp.241 - 250

Received: 17 Dec 2015
Accepted: 11 May 2016
Published online: 25 Jan 2019 *

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