Opportunistic Spectrum Utilization by Cognitive Radio Networks: Challenges and Solutions

Cognitive Radio Network (CRN) is an emerging paradigm that makes use of Dynamic Spectrum Access (DSA) to communicate opportunistically, in the un-licensed Industrial, Scientific and Medical bands or frequency bands otherwise licensed to incumbent users such as TV broadcast. Interest in the development of CRNs is because of severe under-utilization of spectrum bands by the incumbent Primary Users (PUs) that have the license to use them coupled with an ever-increasing demand for unlicensed spectrum for a variety of new mobile and wireless applications. The essence of Cognitive Radio (CR) operation is the cooperative and opportunistic utilization of licensed spectrum bands by the Secondary Users (SUs) that collectively form the CRN without causing any interference to PUs\u27 communications. CRN operation is characterized by factors such as network-wide quiet periods for cooperative spectrum sensing, opportunistic/dynamic spectrum access and non-deterministic operation of PUs. These factors can have a devastating impact on the overall throughput and can significantly increase the control overheads. Therefore, to support the same level of QoS as traditional wireless access technologies, very closer interaction is required between layers of the protocol stack. Opportunistic spectrum utilization without causing interference to the PUs is only possible if the SUs periodically sense the spectrum for the presence of PUs\u27 signal. To minimize the effects of hardware capabilities, terrain features and PUs\u27 transmission ranges, DSA is undertaken in a collaborative manner where SUs periodically carry out spectrum sensing in their respective geographical locations. Collaborative spectrum sensing has numerous security loopholes and can be favorable to malicious nodes in the network that may exploit vulnerabilities associated with DSA such as launching a spectrum sensing data falsification (SSDF) attack. Some CRN standards such as the IEEE 802.22 wireless regional area network employ a two-stage quiet period mechanism based on a mandatory Fast Sensing and an optional Fine Sensing stage for DSA. This arrangement is meant to strike a balance between the conflicting goals of proper protection of incumbent PUs\u27 signals and optimum QoS for SUs so that only as much time is spent for spectrum sensing as needed. Malicious nodes in the CRN however, can take advantage of the two-stage spectrum sensing mechanism to launch smart denial of service (DoS) jamming attacks on CRNs during the fast sensing stage. Coexistence protocols enable collocated CRNs to contend for and share the available spectrum. However, most coexistence protocols do not take into consideration the fact that channels of the available spectrum can be heterogeneous in the sense that they can vary in their characteristics and quality such as SNR or bandwidth. Without any mechanism to enforce fairness in accessing varying quality channels, ensuring coexistence with minimal contention and efficient spectrum utilization for CRNs is likely to become a very difficult task. The cooperative and opportunistic nature of communication has many challenges associated with CRNs\u27 operation. In view of the challenges described above, this dissertation presents solutions including cross-layer approaches, reputation system, optimization and game theoretic approaches to handle (1) degradation in TCP\u27s throughput resulting from packet losses and disruptions in spectrum availability due non-deterministic use of spectrum by the PUs (2) presence of malicious SUs in the CRN that may launch various attacks on CRNs\u27 including SSDF and jamming and (3) sharing of heterogeneous spectrum resources among collocated CRNs without a centralized mechanism to enforce cooperation among otherwise non-cooperative CRN

A Review and Evaluation of Queue Based Control Power Efficient Spectrum Allocation Method for LTE Networks

The cognitive radio based wireless regional area networks (WRAN) is nothing but IEEE-802.22 standard. IEEE 802.22 standard enables opportunistic access to in-use or free 900 MHz TV sub bands by secondary networks. There are many other standards presented; however there is no efficient methods for cognitive networks like LTE for channel access and bandwidth utilization. The existing methods for spectrum access in LTE networks, however most of methods are not flexible, power consuming. Also in literature, we studied that existing methods of spectrum allocation in LTE networks does not efficiently achieve the tradeoff between network QoS (Quality of Service) and power efficiency. The goal of this paper is to present the review on such different spectrum efficiency techniques for LTE networks and then evaluate the recent Queue Based Control (QBC) for power efficient spectrum allocation with its limitations and benefits. QBC approach helps in solving the research problem related to the energy efficiency as well as QoS efficiency to some extent. There are two variants of QBC method such as QBC1 and QBC2 with different objectives and configurations. We are evaluating both this approach on LTE network which is composed of Spectrum Manager (SM), evolved Nodes B (eNBs) and number of user’s. The experimental work is conducted using network simulator (NS2) for delay and energy consumption parameters

Novel Approaches for the Performance Enhancement of Cognitive Radio Networks

This research is dedicated to the study of the challenges faced by Cognitive Radio (CR) networks, which include self-coexistence of the networks in the spectral environment, security and performance threats from malicious entities, and fairness in spectrum contention and utilization. We propose novel channel acquisition schemes that allow decentralized CR networks to have multiple channel access with minimal spectrum contentions. The multiple channel acquisition schemes facilitate fast spectrum access especially in cases where networks cannot communicate with each other. These schemes enable CR networks to self-organize and adapt to the dynamically changing spectral environment. We also present a self-coexistence mechanism that allows CR networks to coexist via the implementation of a risk-motivated channel selection based deference structure (DS). By forming DS coalitions, CR networks are able to have better access to preferred channels and can defer transmission to one another, thereby mitigating spectrum conflicts. CR networks are also known to be susceptible to Sybil threats from smart malicious radios with either monopolistic or disruptive intentions. We formulate novel threat and defense mechanisms to combat Sybil threats and minimize their impact on the performance of CR networks. A dynamic reputation system is proposed that considerably minimizes the effectiveness of intelligent Sybil attacks and improves the accuracy of spectrum-based decision-making processes. Finally, we present a distributed and cheat-proof spectrum contention protocol as an enhancement of the adaptive On-Demand Spectrum Contention (ODSC) protocol. The Modified On-Demand Spectrum Contention (MODSC) protocol enhances fairness and efficiency of spectrum access. We also show that there is substantial improvement in spectrum utilization with the incorporation of channel reuse into the MODSC protocol

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

Spectrum Trading: An Abstracted Bibliography

This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{[email protected]})

The Spectrum Shortage Problem: Channel Assignment and Cognitive Networks

Recent studies have shown that the proliferation of wireless applications and services, experienced in the last decade, is leading to the challenging spectrum shortage problem. We provide a general overview regarding the spectrum shortage problem from the point of view of different technologies. First, we propose solutions based on multi-radio multi-channel wireless mesh networks in order to improve the usage of unlicensed wireless resources. Then, we move our focus on cognitive networks in order to analyze issues and solutions to opportunistically use licensed wireless resources. In wireless mesh networks, the spectrum shortage problem is addressed equipping each device with multiple radios which are turned on different orthogonal channels. We propose G-PaMeLA, which splits in local sub-problems the joint channel assignment and routing problem in multi-radio multi-channel wireless mesh networks. Results demonstrate that G-PaMeLA significantly improves network performance, in terms of packet loss and throughput fairness compared to algorithms in the literature. Unfortunately, even if orthogonal channels are used, wireless mesh networks result in what is called spectrum overcrowding. In order to address the spectrum overcrowding problem, careful analysis on spectrum frequencies has been conducted. These studies identified the possibility of transmitting on licensed channels, which are surprisingly underutilized. With the aim of addressing the resources problem using licensed channels, cognitive access and mesh networks have been developed. In cognitive access networks, we identify as the major problem the self-coexistence, which is the ability to access channels on a non-interfering basis with respect to licensed and unlicensed wireless devices. We propose two game theoretic frameworks which differentiate in having non-cooperative (NoRa) and cooperative (HeCtor) cognitive devices, respectively. Results show that HeCtor achieves higher throughput than NoRa but at the cost of higher computational complexity, which leads to a smaller throughput in cases where rapid changes occur in channels' occupancy. In contrast, NoRa attains the same throughput independent of the variability in channels' occupancy, hence cognitive devices adapt faster to such changes. In cognitive mesh networks, we analyze the coordination problem among cognitive devices because it is the major concern in implementing mesh networks in environments which change in time and space. We propose Connor, a clustering algorithm to address the coordination problem, which establishes common local control channels. Connor, in contrast with existing algorithms in the literature, does not require synchronization among cognitive mesh devices and allows a fast re-clustering when changes occur in channel's occupancy by licensed users. Results show that Connor performs better than existing algorithms in term of number of channels used for control purposes and time to reach and stay on stable configurations

Energy-aware Resource Allocating Mechanism Based on MAC/PHY for Wireless Network

针对无线网络服务能耗较高的问题,提出了一种基于机会主义的能量感知调度方案(OEARS)。首先,该方法将资源分配过程中的能耗和其他自然因素同时考虑; ,采用一种称为MAC/PHY机会主义方法对系统吞吐量进行优化;然后,利用唤醒-休眠模式和信道条件进行实现能耗最小化,并利用物理层信息提高系统容量; ,最大化能量效率。仿真实验结果表明,在保持接近的系统性能的前提下,OEARS的能耗低于现有的其他调度方案。Aimed at the problem of high energy consumption of wireless network; service, an energy-aware resource scheduling scheme-OEARS based on the; opportunism is proposed. Firstly, this method considers the energy; consumption and other natural factors in the process of resource; allocation. An opportunistic approach called MAC/PHY is used to optimize; the system throughput. Then, the energy consumption is minimized by; using the wake-sleep mode and the channel condition, and the physical; layer information is used to improve the system capacity and maximize; the energy efficiency. The simulation results show that the energy; consumption of OEARS is lower than that of other existing scheduling; schemes on the premise of keeping the close system performance.国家自然科学基金面上项目; 广东省教育部科技部中国科学院产学研结合项

Using hypergraph theory to model coexistence management and coordinated spectrum allocation for heterogeneous wireless networks operating in shared spectrum

Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity.Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity