Fuzzy logic based cluster head election led energy efficiency in history assisted cognitive radio networks

The performance and the network lifetime of cooperative spectrum sensing (CSS) infrastructure-based cognitive radio (CR) networks are hugely affected by the energy consumption of the power-constrained CR nodes during spectrum sensing, followed by data transmission and reception. To overcome this issue and improve the network lifetime, clustering mechanisms with several nodes inside a single cluster can be employed. It is usually the cluster head (CH) in every cluster that is responsible for aggregating the data collected from individual CR nodes before it is being forwarded to the base station (BS). In this article, an energy-efficient fuzzy logic-based clustering (EEFC) algorithm is proposed, which uses a novel set of fuzzy input parameters to elect the most suitable node as CH. Unlike most of the other probabilistic as well as fuzzy logic-based clustering algorithms, EEFC increments the fuzzy input parameters from three to four to obtain improved solutions employing the Mamdani method for fuzzification and the Centroid method for defuzzification. It ensures that the best candidate is selected for the CH role by obtaining the crisp value from the fuzzy logic rule-based system. While compared to other well-known clustering algorithms such as low-energy adaptive clustering hierarchy (LEACH), CH election using fuzzy logic (CHEF), energy-aware unequal clustering using fuzzy logic (EAUCF), and fuzzy logic-based energy-efficient clustering hierarchy (FLECH), our proposed EEFC algorithm demonstrates significantly enhanced network lifetime where the time taken for first node dead (FND) in the network is improved. Moreover, EEFC is implemented in the existing history-assisted energy efficient infrastructure CR network to analyze and demonstrate the overall augmented energy efficiency of the system

Channels Reallocation In Cognitive Radio Networks Based On DNA Sequence Alignment

Nowadays, It has been shown that spectrum scarcity increased due to tremendous growth of new players in wireless base system by the evolution of the radio communication. Resent survey found that there are many areas of the radio spectrum that are occupied by authorized user/primary user (PU), which are not fully utilized. Cognitive radios (CR) prove to next generation wireless communication system that proposed as a way to reuse this under-utilised spectrum in an opportunistic and non-interfering basis. A CR is a self-directed entity in a wireless communications environment that senses its environment, tracks changes, and reacts upon its findings and frequently exchanges information with the networks for secondary user (SU). However, CR facing collision problem with tracks changes i.e. reallocating of other empty channels for SU while PU arrives. In this paper, channels reallocation technique based on DNA sequence alignment algorithm for CR networks has been proposed.Comment: 12 page

Cognitive radio networks : quality of service considerations and enhancements

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

Cognitive Radio and Dynamic Spectrum Access Using Fuzzy Logic

Cognitive Radio is artificially intelligent radio. This research paper work presents an application of Cognitive Radio and Dynamic Spectrum Access with the help of fuzzy logic considering the inputs: radio and satellite frequency and outputs: adjust power and modulation. This research paper shows the real approach of comparing the simulation and design algorithm result and its successful use

Spectrum Monitoring Using Fuzzy Logic for OFDM- Based Cognitive Radio Network

Spectrum sensing is a key function of cognitive radio network. This paper presents a spectrum monitoring algorithm according to fuzzy rules for Orthogonal Frequency Division Multiplexing (OFDM) based cognitive radios so that the primary user activity can be detected during the secondary user transmission. A Fuzzy based technique for primary user detection has also been proposed. In comparison with transmitter detection techniques Fuzzy based detection provides good results under low SNR values. This technique improve the jitter and throughput and also probability of false alarm and missed detection is improved

Cognitive Radio and Dynamic Spectrum Access Using Fuzzy Logic

Cognitive Radio is artificially intelligent radio and dynamic spectrum. This research paper presents an application of Cognitive Radio and Dynamic Spectrum Access with the help of fuzzy logic considering the inputs: radio and satellite frequency and outputs: adjust power and modulation. This research paper shows the real approach of comparing the simulation and design algorithm result and its successful use