Modeling and Performance Analysis of Channel Assembling in Multi-channel Cognitive Radio Networks with Spectrum Adaptation

[EN] To accommodate spectrum access in multichannel cognitive radio networks (CRNs), the channel-assembling technique, which combines several channels together as one channel, has been proposed in many medium access control (MAC) protocols. However, analytical models for CRNs enabled with this technique have not been thoroughly investigated. In this paper, two representative channel-assembling strategies that consider spectrum adaptation and heterogeneous traffic are proposed, and the performance of these strategies is evaluated based on the proposed continuous-time Markov chain (CTMC) models. Moreover, approximations of these models in the quasistationary regime are analyzed, and closed-form capacity expressions are derived in different conditions. The performance of different strategies, including the strategy without assembling, is compared with one another based on the numerical results obtained from these models and validated by extensive simulations. Furthermore, simulation studies are also performed for other types of traffic distributions to evaluate the validity and the preciseness of the mathematical models. Through both analyses and simulations, we demonstrate that channel assembling represented by the investigated strategies can improve the system performance if a proper strategy is selected with appropriate system parameter configurations.This work was supported in part by the European Union Seventh Framework Programme Marie Curie Actions International Research Staff Exchange Scheme (EU FP7-PEOPLE-IRSES) through the Security, Services, Networking, and Performance of Next Generation IP-Based Multimedia Wireless Networks (S2EuNet) Project under Agreement 247083 and by the Spanish Government through Project TIN2010-21378-C02-02. The review of this paper was coordinated by Prof. Y. Ma.Jiao, L.; Li, FY.; Pla, V. (2012). Modeling and Performance Analysis of Channel Assembling in Multi-channel Cognitive Radio Networks with Spectrum Adaptation. IEEE Transactions on Vehicular Technology. 61:2686-2697. https://doi.org/10.1109/TVT.2012.2196300S268626976

Channel assembling and resource allocation in multichannel spectrum sharing wireless networks

Submitted in fulfilment of the academic requirements for the degree of Doctor of Philosophy (Ph.D.) in Engineering, in the School of Electrical and Information Engineering, Faculty of Engineering and the Built Environment, at the University of the Witwatersrand, Johannesburg, South Africa, 2017The continuous evolution of wireless communications technologies has increasingly imposed a burden on the use of radio spectrum. Due to the proliferation of new wireless networks applications and services, the radio spectrum is getting saturated and becoming a limited resource. To a large extent, spectrum scarcity may be a result of deficient spectrum allocation and management policies, rather than of the physical shortage of radio frequencies. The conventional static spectrum allocation has been found to be ineffective, leading to overcrowding and inefficient use. Cognitive radio (CR) has therefore emerged as an enabling technology that facilitates dynamic spectrum access (DSA), with a great potential to address the issue of spectrum scarcity and inefficient use. However, provisioning of reliable and robust communication with seamless operation in cognitive radio networks (CRNs) is a challenging task. The underlying challenges include development of non-intrusive dynamic resource allocation (DRA) and optimization techniques. The main focus of this thesis is development of adaptive channel assembling (ChA) and DRA schemes, with the aim to maximize performance of secondary user (SU) nodes in CRNs, without degrading performance of primary user (PU) nodes in a primary network (PN). The key objectives are therefore four-fold. Firstly, to optimize ChA and DRA schemes in overlay CRNs. Secondly, to develop analytical models for quantifying performance of ChA schemes over fading channels in overlay CRNs. Thirdly, to extend the overlay ChA schemes into hybrid overlay and underlay architectures, subject to power control and interference mitigation; and finally, to extend the adaptive ChA and DRA schemes for multiuser multichannel access CRNs. Performance analysis and evaluation of the developed ChA and DRA is presented, mainly through extensive simulations and analytical models. Further, the cross validation has been performed between simulations and analytical results to confirm the accuracy and preciseness of the novel analytical models developed in this thesis. In general, the presented results demonstrate improved performance of SU nodes in terms of capacity, collision probability, outage probability and forced termination probability when employing the adaptive ChA and DRA in CRNs.CK201

Dynamic Flow-Adaptive Spectrum Leasing with Channel Aggregation in Cognitive Radio Networks

Cognitive radio networks (CRNs), which allow secondary users (SUs) to dynamically access a network without affecting the primary users (PUs), have been widely regarded as an effective approach to mitigate the shortage of spectrum resources and the inefficiency of spectrum utilization. However, the SUs suffer from frequent spectrum handoffs and transmission limitations. In this paper, considering the quality of service (QoS) requirements of PUs and SUs, we propose a novel dynamic flow-adaptive spectrum leasing with channel aggregation. Specifically, we design an adaptive leasing algorithm, which adaptively adjusts the portion of leased channels based on the number of ongoing and buffered PU flows. Furthermore, in the leased spectrum band, the SU flows with access priority employ dynamic spectrum access of channel aggregation, which enables one flow to occupy multiple channels for transmission in a dynamically changing environment. For performance evaluation, the continuous time Markov chain (CTMC) is developed to model our proposed strategy and conduct theoretical analyses. Numerical results demonstrate that the proposed strategy effectively improves the spectrum utilization and network capacity, while significantly reducing the forced termination probability and blocking probability of SU flows.publishedVersio

Medium access in cognitive radio networks: From single hop to multiple hops

If channel assembling is enabled, this technique can be utilized for potential performance improvement in CRNs. Two use cases are envisaged for channel assembling. In the first use case, the system can accommodate parallel SU services in multiple channels, while in the second use case, the system allows only one SU service at a time. In the use case where parallel SU services are allowed, various channel assembling strategies are proposed and modeled in order to investigate their performance and to acquire better comprehension of the behavior of CRNs with channel assembling. Moreover, the capacity upper bound for CRNs with channel assembling in the quasistationary regime is derived. In the use case when there is only one SU service that can utilize the vacant channels at a time, we formulate channel access into two optimization problems on power allocation in multi-channel CRNs and propose various algorithms to solve these problems

Performance evaluation of channel aggregation strategies in cognitive radio networks with queues

With the growing usage of wireless communication devices, demand for the spectrum access is rapidly increasing. Therefore, an efficient spectrum management and spectrum access techniques are necessary and critical. However, studies on spectrum usage have revealed that most of the allotted spectrum is not used efficiently due to the static frequency allocation methods. With the evolution of cognitive radio, spectrum access techniques shift from static spectrum allocation to dynamic allocation with enhanced features such as spectrum sensing and spectrum adaptation. In the first part of this thesis, we study several spectrum access techniques in cognitive radio networks, which have been developed with spectrum adaptation. The performance of cognitive radio systems are evaluated in terms of capacity, blocking probability and forced termination probability of the secondary network. Due to the strict priority over primary users, the performance of the secondary network is restricted. One of the successful solutions to further improve the system performance by increasing the capacity and decreasing the blocking and forced termination probabilities is the integration of a queuing model. Most of already designed queuing models for cognitive radio systems have been designed with certain limitations of performance. Therefore in this thesis, a bunch of techniques of performance improvement have been taken into account when designing the queuing model. The features: channel aggregation, spectrum handover, channel sharing, priority based queuing and heterogeneous traffic are considered together in order to model the queuing system as much as more realistic way which can further enhance the overall system performance. In the second part of this thesis, we propose a queuing system referred to as Priority based Multiple Queue System (PMQS) which is designed with two queues separately for the real time and non-real time secondary user services. Channel access opportunities are distributed between two queues such a way that the real time services have the higher priority than elastic services. Two queuing approaches are introduced based on the queuing ability of the interrupted non-real time services. Continuous time Markov chain models are developed to evaluate the system performance in terms of capacity, blocking and forced termination probabilities of the secondary network. In addition, we explore the cost analysis of the proposed queuing model in terms of mean queuing delay. Other than that, spectrum utilization of the cognitive radio system is also evaluated. In order to minimize the associated queuing delay, a maximum value for the number of waiting lines inside a queue is set instead of an infinite queue size . Analytical results reveal that integration of the proposed queuing model could increase the capacity of the secondary network while decreasing the blocking probability. And also one of the proposed queuing methods can further decrease the forced termination rate of non-real time traffic. Associated queuing delay is controlled by proper selection of maximum queue sizes. For these reasons, it can be concluded that the proposed queuing model can be used to improve the system performance of multi-channel cognitive radio networks

Channel assembling policies for heterogeneous fifth generation (5G) cognitive radio networks.

Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2016.Abstract available in PDF file

Channel Access and Reliability Performance in Cognitive Radio Networks:Modeling and Performance Analysis

Doktorgradsavhandling ved Institutt for Informasjons- og kommunikasjonsteknologi, Universitetet i AgderAccording to the facts and figures published by the international telecommunication union (ITU) regarding information and communication technology (ICT) industry, it is estimated that over 3.2 billion people have access to the Internet in 2015 [1]. Since 2000, this number has been octupled. Meanwhile, by the end of 2015, there were more than 7 billion mobile cellular subscriptions in the world, corresponding to a penetration rate of 97%. As the most dynamic segment in ICT, mobile communication is providing Internet services and consequently the mobile broadband penetration rate has reached 47% globally. Accordingly, capacity, throughput, reliability, service quality and resource availability of wireless services become essential factors for future mobile and wireless communications. Essentially, all these wireless technologies, standards, services and allocation policies rely on one common natural resource, i.e., radio spectrum. Radio spectrum spans over the electromagnetic frequencies between 3 kHz and 300 GHz. Existing radio spectrum access techniques are based on the fixed allocation of radio resources. These methods with fixed assigned bandwidth for exclusive usage of licensed users are often not efficient since most of the spectrum bands are under-utilized, either/both in the space domain or/and in the time domain. In reality, it is observed that many spectrum bands are largely un-occupied in many places [2], [3]. For instance, the spectrum bands which are exclusively allocated for TV broadcasting services in USA remain un-occupied from midnight to early morning according to the real-life measurement performed in [4]. In addition to the wastage of radio resources, spectrum under-utilization constraints spectrum availability for other intended users. Furthermore, legacy fixed spectrum allocation techniques are not capable of adapting to the changes and interactions in the system, leading to degraded network performance. Unlike in the static spectrum allocation, a fraction of the radio spectrum is allocated for open access as license-free bands, e.g., the industrial, scientific and medical (ISM) bands (902-928, 2400-2483.5, 5725-5850 MHz). In 1985, the federal communications commission (FCC) permitted to use the ISM bands for private and unlicensed occupancy, however, under certain restrictions on transmission power [5]. Consequently, standards like IEEE 802.11 for wireless local area networks (WLANs) and IEEE 802.15 for wireless personal area networks (WPAN) have grown rapidly with open access spectrum policies in the 2.4 GHz and 5 GHz ISM bands. With the co-existence of both similar and dissimilar radio technologies, 802.11 networks face challenges for providing satisfactory quality of service (QoS). This and the above mentioned spectrum under-utilization issues motivate the spectrum regulatory bodies to rethink about more flexible spectrum access for licenseexempt users or more efficient radio spectrum management. Cognitive radio (CR) is probably the most promising technology for achieving efficient spectrum utilization in future wireless networks

Performance optimization of the mini-slotted spectrum allocation strategy with imperfect sensing

In this paper, in order to improve the normal throughput of secondary user packets and reduce the spectrum switching frequency in cognitive radio networks, a novel mini-slotted spectrum allocation strategy is proposed. Due to the mistake detection in practice, the secondary user packet and the primary user packet will occupy the spectrum simultaneously, i.e., a collision will occur on the spectrum. A heterogeneous discrete-time queueing model with possible collisions is established to model the system operation. Taking into account imperfect sensing results, the transition probability matrix is constructed. Applying the method of matrix geometric solution, performance measures in terms of the disruption rate of primary user packets, the normal throughput of secondary user packets, the spectrum switching rate and the average latency of secondary user packets are given. Numerical results are provided to verify the effectiveness of the proposed mini-slotted spectrum strategy. Finally, by trading off different system performance measures, a net benefit function is constructed, then the slot size is optimized

Convergent communication, sensing and localization in 6g systems: An overview of technologies, opportunities and challenges

Herein, we focus on convergent 6G communication, localization and sensing systems by identifying key technology enablers, discussing their underlying challenges, implementation issues, and recommending potential solutions. Moreover, we discuss exciting new opportunities for integrated localization and sensing applications, which will disrupt traditional design principles and revolutionize the way we live, interact with our environment, and do business. Regarding potential enabling technologies, 6G will continue to develop towards even higher frequency ranges, wider bandwidths, and massive antenna arrays. In turn, this will enable sensing solutions with very fine range, Doppler, and angular resolutions, as well as localization to cm-level degree of accuracy. Besides, new materials, device types, and reconfigurable surfaces will allow network operators to reshape and control the electromagnetic response of the environment. At the same time, machine learning and artificial intelligence will leverage the unprecedented availability of data and computing resources to tackle the biggest and hardest problems in wireless communication systems. As a result, 6G will be truly intelligent wireless systems that will provide not only ubiquitous communication but also empower high accuracy localization and high-resolution sensing services. They will become the catalyst for this revolution by bringing about a unique new set of features and service capabilities, where localization and sensing will coexist with communication, continuously sharing the available resources in time, frequency, and space. This work concludes by highlighting foundational research challenges, as well as implications and opportunities related to privacy, security, and trust