Abstract
The continuous growth of interconnected devices in the Internet of Things (IoT) presents a challenge in terms of network resources. Cognitive radio (CR) is a promising technology that can address the IoT spectral demands by enabling an opportunistic spectrum access (OSA) scheme. The application of full duplex (FD) radios in spectrum sensing enables secondary users (SUs) to perform sensing and transmission simultaneously, and improves the utilization of the spectrum. However, random and dense distributions of FD-enabled SU transmitters (FD-SU TXs) with sensing capabilities in small-cell CR-IoT environments poses new challenges, and creates heterogeneous environments with different spectral opportunities. In this paper, we propose a spatial and temporal spectral-hole sensing framework for FD-SU TXs deployed in CR-IoT spectrum-heterogeneous environment. Incorporating the proposed sensing model, we present the analytical formulation and an evaluation of a utilization of spectrum (UoS) scheme for FD-SU TXs present at different spatial positions. The numerical results are evaluated under different network and sensing parameters to examine the sensitivities of different parameters. It is demonstrated that self-interference, primary user activity level, and the sensing outcomes in spatial and temporal domains have a significant influence on the utilization performance of spectrum.
Highlights
Recent developments in wireless communication have presented a new networking paradigm, Internet of Things (IoT) [1]
utilization of spectrum (UoS) scheme is investigated in terms of average number of sensing slots used for the successful secondary communication in each time-slotted frame
Based on the proposed spatial–temporal spectral hole-sensing model in Section 3, we present an analytical formulation and evaluation of the UoS scheme for the full duplex (FD)-secondary users (SUs) TXs deployed at different spatial positions in Cognitive radio (CR)-IoT spectrum-heterogeneous environment
Summary
Recent developments in wireless communication have presented a new networking paradigm, Internet of Things (IoT) [1]. Maintaining continuous connectivity and the enormous number of IoT devices present challenges to a radio network. Traditional wireless spectrum standards rely on the static spectrum allocation policies where specific frequency bands are assigned to a specific licensed service and its users. Unlicensed users are not authorized to access the licensed bands, resulting in the underutilized bands. Such policies cause unbalanced utilization of spectrum and degrade the spectral efficiency. Static spectrum allocation policies are insufficient to address the high demands of spectrum resources required for the wireless access of large number of IoT sensor devices [4]. Sensors 2019, 19, 1441 technologies such as long term evolution (LTE) wireless local area networks (WLAN) aggregation (LWA), non-orthogonal multiple access (NOMA), operations in millimeter-wave band, LTE over unlicensed band (LTE-U), ultra-dense 5G small cells, and software-defined cognitive radio network (SD-CRN) [5]
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