2 research outputs found

    Channel coding adoption versus increasing sensing time in secondary service to manage the effect of imperfect spectrum sensing in cognitive radio networks

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    In this paper we consider an overlay cognitive network in which to guarantee a Quality of Service (QoS) for the primary users, a maximum probability of collision is enforced to secondary service. When collision, caused by imperfect spectrum sensing, happens, it results in increasing error rate in both primary and secondary systems. While such degradation in primary service conforms with QoS requirements of that service, this may not be acceptable from secondary user perspective. Such degradation can be dealt with in secondary service either by employing channel coding techniques at the expense of effective rate reduction or increasing the sensing time to reduce the collision probability. This results in the reduction of the data transmission time which also results in the reduction of effective data rate for secondary users. In this paper, we compare these two cases and show that using rate-compatible Low-Density Parity-Check codes, the effective data rate for the coded case can be significantly more than that of the case without channel coding while exhibiting a considerably better performance

    Cognitive radio networks : quality of service considerations and enhancements

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    The explosive growth of wireless and mobile networks, such as the Internet of Things and 5G, has led to a massive number of devices that primarily use wireless channels within a limited range of the radio frequency spectrum (RFS). The use of RFS is heavily regulated, both nationally and internationally, and is divided into licensed and unlicensed bands. While many of the licensed wireless bands are underutilised, useable unlicensed bands are usually overcrowded, making the efficient use of RFS one of the critical challenges faced by future wireless communication technologies. The cognitive radio (CR) concept is proposed as a promising solution for the underutilisation of useful RFS bands. Fundamentally, CR technology is based on determining the unoccupied licensed RFS bands, called spectrum white spaces or holes, and accessing them to achieve better RFS utilisation and transmission propagation. The holes are the frequencies unused by the licensed user, or primary user (PU). Based on spectrum sensing, a CR node, or secondary user (SU), senses the surrounding spectrum periodically to detect any potential PU transmission in the current channel and to identify the available spectrum holes. Under current RFS regulations, SUs may use spectrum holes as long as their transmissions do not interfere with those of the PU. However, effective spectrum sensing can introduce overheads to a CR node operation. Such overheads affect the quality of service (QoS) of the running applications. Reducing the sensing impact on the QoS is one of the key challenges to adopting CR technology, and more studies of QoS issues related to implementing CR features are needed. This thesis aims to address these QoS issues in CR while considered the enhancement of RFS utilisation. This study concentrates on the spectrum sensing function, among other CR functions, because of its major impact on QoS and spectrum utilisation. Several spectrum sensing methods are reviewed to identify potential research gaps in analysing and addressing related QoS implications. It has been found that none of the well-known sensing techniques is suitable for all the diverse QoS requirements and RFS conditions: in fact, higher accuracy sensing methods cause a significant QoS degradation, as illustrated by several simulations in this work. For instance, QoS degradation caused by high-accuracy sensing has not yet been addressed in the IEEE 802.11e QoS mechanism used in the proposed CR standard, IEEE 802.11af (or White-Fi). This study finds that most of the strategies proposed to conduct sensing are based on a fixed sensing method that is not adaptable to the changeable nature of QoS requirements. In contrast, this work confirms the necessity of using various sensing techniques and parameters during a CR node operation for better performance
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