Scalable Learning-Based Heterogeneous Multi-Band Multi-User Cooperative Spectrum Sensing for Distributed IoT Systems

Anastassia Gharib,Mohamed Ibnkahla,Waleed Ejaz

doi:10.1109/ojcoms.2020.3012906

Abstract

The emerge of Internet of Things (IoT) brings up revolutionary changes to wireless communications. Cognitive radio (CR) can be seen as one of the prominent solutions to spectrum scarcity in IoT, where multi-band cooperative spectrum sensing (CSS) is the key. However, lack of centralized control and increase in number of devices place a room for many challenges. One of the main challenges is secondary users' (SUs') scheduling to sense a subset of channels in heterogeneous distributed CR networks (CRNs). To overcome the aforementioned challenge, in this paper, we propose a novel heterogeneous multi-band multi-user CSS (HM2CSS) scheme. The proposed scheme allows heterogeneous SUs to sense multiple channels and consists of two stages. We formulate a mathematical model to optimize leader-selection for each channel in the first stage. We then formulate another optimization problem to determine corresponding cooperative SUs to sense these channels in the second stage. After that, diffusion learning is used to decide on the availability of channels. Simulations illustrate that the proposed scheme improves detection performance and CRN throughput, is scalable in terms of detection performance, and provides fair energy consumption for CSS on all channels compared to existing multi-band CSS schemes.

Highlights

I NTERNET of Things (IoT) has brought a rapid increase in the usage of wireless spectrum [1]
We assume that 100 secondary users (SUs) and 50 primary users (PUs) are randomly distributed in a 1000×1000m2 area
The IEEE 802.22 standard is used as a benchmark for simulation results, according to which the total detection probability should be greater than 90%, while the false alarm probability should be less than 10% [38]

Summary

Introduction

I NTERNET of Things (IoT) has brought a rapid increase in the usage of wireless spectrum [1]. SUs can acquire the knowledge of whether the spectrum is occupied by PUs or not, and utilize the spectrum when it is not used by PUs. Generally, wide-band spectrum owned by PUs is divided into non-overlapping sub-bands, called channels. Wide-band spectrum owned by PUs is divided into non-overlapping sub-bands, called channels This causes a multi-band structure of the spectrum. Due to hardware limitations and energy constraints of IoT devices, instead of sensing all channels, each SU can sense multiple channels and exchange the sensed information with other SUs to determine spectrum availability [4]. This process is called multi-band cooperative spectrum sensing (CSS)

Objectives

Results

Conclusion