Cognitive MAC protocols for mobile Ad-Hoc networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The term of Cognitive Radio (CR) used to indicate that spectrum radio could be accessed dynamically and opportunistically by unlicensed users. In CR Networks, Interference between nodes, hidden terminal problem, and spectrum sensing errors are big issues to be widely discussed in the research field nowadays. To improve the performance of such kind of networks, this thesis proposes Cognitive Medium Access Control (MAC) protocols for Mobile Ad-Hoc Networks (MANETs). From the concept of CR, this thesis has been able to develop a cognitive MAC framework in which a cognitive process consisting of cognitive elements is considered, which can make efficient decisions to optimise the CR network. In this context, three different scenarios to maximize the secondary user's throughput have been proposed. We found that the throughput improvement depends on the transition probabilities. However, considering the past information state of the spectrum can dramatically increases the secondary user's throughput by up to 40%. Moreover, by increasing the number of channels, the throughput of the network can be improved about 25%. Furthermore, to study the impact of Physical (PHY) Layer errors on cognitive MAC layer in MANETs, in this thesis, a Sensing Error-Aware MAC protocols for MANETs has been proposed. The developed model has been able to improve the MAC layer performance under the challenge of sensing errors. In this context, the proposed model examined two sensing error probabilities: the false alarm probability and the missed detection probability. The simulation results have shown that both probabilities could be adapted to maintain the false alarm probability at certain values to achieve good results. Finally, in this thesis, a cooperative sensing scheme with interference mitigation for Cognitive Wireless Mesh Networks (CogMesh) has been proposed. Moreover, a prioritybased traffic scenario to analyze the problem of packet delay and a novel technique for dynamic channel allocation in CogMesh is presented. Considering each channel in the system as a sub-server, the average delay of the users' packets is reduced and the cooperative sensing scenario dramatically increases the network throughput 50% more as the number of arrival rate is increased

20 Years of Evolution from Cognitive to Intelligent Communications

It has been 20 years since the concept of cognitive radio (CR) was proposed, which is an efficient approach to provide more access opportunities to connect massive wireless devices. To improve the spectrum efficiency, CR enables unlicensed usage of licensed spectrum resources. It has been regarded as the key enabler for intelligent communications. In this article, we will provide an overview on the intelligent communication in the past two decades to illustrate the revolution of its capability from cognition to artificial intelligence (AI). Particularly, this article starts from a comprehensive review of typical spectrum sensing and sharing, followed by the recent achievements on the AI-enabled intelligent radio. Moreover, research challenges in the future intelligent communications will be discussed to show a path to the real deployment of intelligent radio. After witnessing the glorious developments of CR in the past 20 years, we try to provide readers a clear picture on how intelligent radio could be further developed to smartly utilize the limited spectrum resources as well as to optimally configure wireless devices in the future communication systems.Comment: The paper has been accepted by IEEE Transactions on Cognitive Communications and Networkin

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe

Spectrum sharing systems for improving spectral efficiency in cognitive cellular network

Since spectrum is the invisible infrastructure that powers the wireless communication, the demand has been exceptionally increasing in recent years after the implementation of 4G and immense data requirements of 5G due to the applications, such as Internet-of-Things (IoT). Therefore, the effective optimization of the use of spectrum is immediately needed than ever before. The spectrum sensing is the prerequisite for optimal resource allocation in cognitive radio networks (CRN). Therefore, the spectrum sensing in wireless system with lower latency requirements is proposed first. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. The proposed method in this Thesis is a multi-channel cooperative spectrum sensing technique, in which an independent network of sensors, namely, spectrum monitoring network, detects the spectrum availability. The locally aggregated decision in each zone associated with the zone aggregator (ZA) location is then passed to a decision fusion centre (DFC). The secondary base station (SBS) accordingly allocates the available channels to secondary users to maximize the spectral efficiency. The function of the DFC is formulated as an optimization problem with the objective of maximizing the spectral efficiency. The optimal detection threshold is obtained for different cases with various spatial densities of ZAs and SBSs. It is further shown that the proposed method reduces the spectrum sensing latency and results in a higher spectrum efficiency. Furthermore, a novel power allocation scheme for multicell CRN is proposed where the subchannel power allocation is performed by incorporating network-wide primary system communication activity. A collaborative subchannel monitoring scheme is proposed to evaluate the aggregated subchannel activity index (ASAI) to indicate the activity levels of primary users. Two utility functions are then defined to characterize the spectral efficiency (SE) and energy efficiency (EE) as a function of ASAI to formulate a utility maximization problem. The optimal transmit power allocation is then obtained with the objective of maximizing the total utility at the SBS, subject to maximum SBS transmit power and collision probability constraint at the primary receivers. Since optimal EE and SE are two contradicting objectives to obtain the transmit power allocation, the design approach to handle both EE and SE as a function of common network parameter, i.e., ASAI, is provided which ultimately proves the quantitative insights on efficient system design. Extensive simulation results confirm the analytical results and indicate a significant improvement in sensing latency and accuracy and a significant gain against the benchmark models on the rate performance, despite the proposed methods perform with lower signalling overhead

Spectrum sharing systems for improving spectral efficiency in cognitive cellular network

Since spectrum is the invisible infrastructure that powers the wireless communication, the demand has been exceptionally increasing in recent years after the implementation of 4G and immense data requirements of 5G due to the applications, such as Internet-of-Things (IoT). Therefore, the effective optimization of the use of spectrum is immediately needed than ever before. The spectrum sensing is the prerequisite for optimal resource allocation in cognitive radio networks (CRN). Therefore, the spectrum sensing in wireless system with lower latency requirements is proposed first. In such systems with high spatial density of the base stations and users/objects, spectrum sharing enables spectrum reuse across very small regions. The proposed method in this Thesis is a multi-channel cooperative spectrum sensing technique, in which an independent network of sensors, namely, spectrum monitoring network, detects the spectrum availability. The locally aggregated decision in each zone associated with the zone aggregator (ZA) location is then passed to a decision fusion centre (DFC). The secondary base station (SBS) accordingly allocates the available channels to secondary users to maximize the spectral efficiency. The function of the DFC is formulated as an optimization problem with the objective of maximizing the spectral efficiency. The optimal detection threshold is obtained for different cases with various spatial densities of ZAs and SBSs. It is further shown that the proposed method reduces the spectrum sensing latency and results in a higher spectrum efficiency. Furthermore, a novel power allocation scheme for multicell CRN is proposed where the subchannel power allocation is performed by incorporating network-wide primary system communication activity. A collaborative subchannel monitoring scheme is proposed to evaluate the aggregated subchannel activity index (ASAI) to indicate the activity levels of primary users. Two utility functions are then defined to characterize the spectral efficiency (SE) and energy efficiency (EE) as a function of ASAI to formulate a utility maximization problem. The optimal transmit power allocation is then obtained with the objective of maximizing the total utility at the SBS, subject to maximum SBS transmit power and collision probability constraint at the primary receivers. Since optimal EE and SE are two contradicting objectives to obtain the transmit power allocation, the design approach to handle both EE and SE as a function of common network parameter, i.e., ASAI, is provided which ultimately proves the quantitative insights on efficient system design. Extensive simulation results confirm the analytical results and indicate a significant improvement in sensing latency and accuracy and a significant gain against the benchmark models on the rate performance, despite the proposed methods perform with lower signalling overhead

Comprehensive survey on quality of service provisioning approaches in cognitive radio networks : part one

Much interest in Cognitive Radio Networks (CRNs) has been raised recently by enabling unlicensed (secondary) users to utilize the unused portions of the licensed spectrum. CRN utilization of residual spectrum bands of Primary (licensed) Networks (PNs) must avoid harmful interference to the users of PNs and other overlapping CRNs. The coexisting of CRNs depends on four components: Spectrum Sensing, Spectrum Decision, Spectrum Sharing, and Spectrum Mobility. Various approaches have been proposed to improve Quality of Service (QoS) provisioning in CRNs within fluctuating spectrum availability. However, CRN implementation poses many technical challenges due to a sporadic usage of licensed spectrum bands, which will be increased after deploying CRNs. Unlike traditional surveys of CRNs, this paper addresses QoS provisioning approaches of CRN components and provides an up-to-date comprehensive survey of the recent improvement in these approaches. Major features of the open research challenges of each approach are investigated. Due to the extensive nature of the topic, this paper is the first part of the survey which investigates QoS approaches on spectrum sensing and decision components respectively. The remaining approaches of spectrum sharing and mobility components will be investigated in the next part