1,721,138 research outputs found
Space Time Block Coded Multi-user CDMA Systems over Rayleigh Fading Channel
No full textThis paper investigates the performance and capacity of space time block coded (STBC) multi-user CDMA system over Rayleigh fading channel condition using multiple transmit antennas. Using simulation and analytical approach, we show that STBC CDMA system has increased performance in cellular networks. We also compare the performance of this system with the typical CDMA system and show that STBC and multiple transmit antennas for multi-user CDMA system provide performance gain without any need of extra processing or bandwidth
A Testbed for Spectrum Sensing in Cognitive Radio Networks
No full textDemand of wireless communication has been increasing rapidly in data transmission due to rising of the wireless services, devices and applications. Regarding such a context, the radio resource for supporting the demand is seriously lacked. In the coming decades, this problem will deteriorate due to an explosive growth of IoT (Internet of thing). Meanwhile, the spectrum allocation policy in which government agencies assign static spectrum to licensed users (or primary users (PUs)), leads to inefficient utilization of a large amount of licensed spectrum.
Due to under-utilization of radio spectrum resource, the concept of cognitive radio networks has been introduced by Mitola and considered as an alternative, that can be used to exploit the existence of unused licensed frequency bandwidth. In this concept the unlicensed users (or secondary user(SUs)) can sense the spectral environment to dynamically and opportunistically access the spectrum bands in absence of primary user at a particular time and specific geographic location.
In general, Pus’ have not been very receptive of the idea of opportunistic spectrum sharing. In particular, they are concerned that cognitive radio (CR) will harmfully interfere with their operation. There is considerable debate whether it is possible to build a CR that does not disturb PUs. However, this debate cannot be resolved on a theoretical basis. As it is impossible to test all possible cases, it is necessary to commonly agree on a set of “representative” test cases that a CR must pass to “prove” that the amount of interference is sufficiently low to justify allowing CR technology. There is a plethora of techniques such as cooperative sensing, Cyclostationary detectors, energy detection etc. that have been proposed to enhance detection. None of these techniques have been tested all in real world scenarios and their performance has yet to be characterized. Thus, there is a need for experimenting with different techniques in a real system, using a set of test cases and metrics to compare different CR implementations. In this research, we cover the details of such experiment testbed of spectrum sensing for CR based on energy detection algorithm and a software defined radio (SDR). This testbed has been built on GNU radio platform using the universal software radio peripheral (USRP) NI-2900 supported by National Instrument to evaluate the sensing performance of energy detection in a real environment. We also implement a cloud server-based spectrum sensing such that we can store, process, and share the sensing information more efficiently in the centralized way at the cloud server. Finally, we do implementation of a real LoRa network based on LoRaWAN protocol for Internet of thing (IoT), create a gateway and build an application, then process the data to the cloud server.Maste
Throughput and Energy Optimization for Future Wireless Networks, beyond 5G
No full textRecently, the next generation wireless networks (5G) is integrated by some novel paradigms such as cognitive radio, full-duplex, simultaneous wireless information and power transfer (SWIPT), multi-input multi-output (MIMO) and large-scale antenna arrays, etc. In cognitive radio networks, a secondary user opportunistically utilizes the licensed spectrum unused by a primary user in overlay mode or completely utilizes the licensed spectrum as long as the interference power caused by the secondary transmitter to each primary user is below a prescribed interference threshold in underlay mode. Moreover, with full-duplex technology, a transceiver is able to communicate in both directions over the same frequency channel. Simultaneous wireless information and power transfer (SWIPT), where transmitters can simultaneously provide both data and energy to receivers. In addition, multi-input multi-output systems can exploit spatial multiplexing or beamforming to focus the information or energy beam on wireless receivers. The high performance in large-scale MIMO systems is achieved when the transmitter are equipped with a very large number of antennas.
The throughput and energy have key roles in the operation of these novel paradigms. We need to investigate the answer to the fundamental questions: how to use minimum energy while ensuring the throughput, how to achieve the maximum throughput with a given maximum energy. The problems become complicated when there are combinations of some paradigms such as cognitive and SWIPT, cognitive and full-duplex, or SWIPT and MIMO. Therefore, it is very important to study the solutions for optimizing throughput and energy in the above novel paradigms.
First, we consider the throughput maximization
of a secondary user (SU) in a realistic cognitive radio (CR)
network where the battery suffers from constant energy leakage.
We investigate two different CR scenarios where the primary
user (PU) switches between idle and active states in a time-slotted
manner. In the first scenario, the SU knows the exact state
of the PU at the beginning of each time slot, whereas in the
second scenario, the SU attempts to detect state of the PU
by spectrum sensing. For both scenarios, we determine the
maximum throughput of the SU with consideration of battery
leakage of the SU and interference constraint of the PU. The
optimal solutions of transmitting power and sensing duration are
achieved by using golden section search method and a simplified
brute-force search method.
Second, we consider throughput maximisation for a secondary user (SU) in a full-duplex cognitive radio network (FD-CRN) when the SU has two separate antennas and a self-interference suppression capability. In the FD-CRN,
the SU can simultaneously sense the spectrum throughout the whole time slot and transmit data. They propose algorithms based on brute-force search and particle swarm optimisation methods to help the SU achieve optimal detection thresholds for spectrum sensing in two different FD-CRN scenarios. In the first scenario, the SU individually performs spectrum sensing, whereas in the second scenario the SU’s sensing results are improved by means of cooperative spectrum sensing. Theoretical and simulation results herein show that, for certain values of the system parameters in the above two scenarios, the system under consideration provides much higher throughput than previously proposed systems in conditions of high-transmission power or low signal-to-noise ratio of the primary signal
Next, we study a simultaneous wireless information and power transfer multi-input single-output cognitive radio network in which a multi-antenna secondary transmitter sends data streams to multiple single-antenna secondary receivers (SRs) equipped with a power-splitting (PS) structure for information decoding and energy harvesting in the presence of multiple single-antenna primary users (PUs). First, the max-min fair SRs' harvested energy problem is formulated and solved by combining the tight semidefinite relaxation (SDR)-based solution of the transmit power minimization problem with the bisection search method. Second, the balancing problem examines the tradeoff between the worst-user harvested energy at the SR and the interference power at the PU. The proposed solution for this challenging non-convex problem includes two steps. First, the problem with fixed PS ratios is solved using the SDR technique and
the tight solution is proved; then, the approximately optimal PS ratios are found using the particle swarm optimization method. Additionally, the closed-form solutions of transmit power minimization and harvested energy maximization problems are derived for the special case where only one SR and one PU are present.
Finally, the numerical results demonstrate the effectiveness of the proposed approaches in comparison with two baseline schemes.
Then, we study a simultaneous wireless information and power transfer (SWIPT) system in which the transmitter not only sends data
and energy to many types of wireless users, such as multiple information
decoding users, multiple hybrid power-splitting users (i.e., users with a
power-splitting structure to receive both information and energy), and multiple
energy harvesting users, but also prevents information from being intercepted
by a passive eavesdropper. The transmitter is equipped with multiple
antennas, whereas all users and the eavesdropper are assumed to be equipped
with a single antenna. Since the transmitter does not have any channel state
information (CSI) about the eavesdropper, artificial noise (AN) power is
maximized to mask information as well as to interfere with the eavesdropper
as much as possible. The non-convex optimization problem is formulated to
minimize the transmit power satisfying all signal-to-interference-plus-noise
(SINR) and harvested energy requirements for all users so that the remaining
power for generating AN is maximized. With perfect CSI, a semidefinite
relaxation (SDR) technique is applied, and the optimal solution is proven to
be tight. With imperfect CSI, SDR and a Gaussian randomization algorithm
are proposed to find the suboptimal solution. Finally, numerical performance
with respect to the maximum SINR at the eavesdropper is determined by
a Monte-Carlo simulation to compare the proposed AN scenario with a
no-AN scenario, as well as to compare perfect CSI with imperfect CSI.
After that, the combination of large-scale antenna arrays and simultaneous
wireless information and power transfer, which can provide
enormous increase of throughput and energy efficiency is a promising key
in next generation wireless system (5G). This paper investigates efficient
transceiver design to minimize transmit power, subject to users’ required
data rates and energy harvesting, in large-scale SWIPT system where the
base station utilizes a very large number of antennas for transmitting both
data and energy to multiple users equipped with time-switching (TS) or
power-splitting (PS) receive structures. We first propose the well-known
semidefinite relaxation (SDR) and Gaussian randomization techniques to
solve the minimum transmit power problems. However, for these large-scale
SWIPT problems, the proposed scheme, which is based on conventional
SDR method, is not suitable due to its excessive computation costs, and
a consensus alternating direction method of multipliers (ADMM) cannot
be directly applied to the case that TS or PS ratios are involved in the optimization problem. Therefore, in the second solution, our first step is to
optimize the variables of TS or PS ratios, and to achieve simplified problems.
After then, we propose fast algorithms for solving these problems, where
the outer loop of sequential parametric convex approximation (SPCA) is
combined with the inner loop of ADMM. Numerical simulations show the
fast convergence and superiority of the proposed solutions.
Finally, we consider the harvested-energy fairness
problem in cognitive multicast systems with simultaneous wireless information
and power transfer. In the cognitive multicast system, a
cognitive transmitter with multi-antenna sends the same information to
cognitive users in the presence of licensed users, and cognitive users can
decode information and harvest energy with a power-splitting structure. The
harvested-energy fairness problem is formulated and solved by using two
proposed algorithms, which are based on semidefinite relaxation (SDR) and
sequential parametric convex approximation (SPCA), respectively. At last,
the performances of the proposed solutions and baseline schemes are verified
by simulation results.Docto
Energy-efficient and Secure Cooperative Spectrum Sensing for Cognitive Radio Network
No full textIn recent times, the proliferation of wireless technology has spawned pervasive wireless services, devices and applications, thereby increasing demand for the radio spectrum by orders of magnitude. This trend is likely to grow at colossal rates in the coming decade as ever more wireless devices such as smart phones, tablets, personal digital assistants (PDAs), laptops, wearable and embedded wireless devices connect to the Internet. The radio spectrum scarcity problem is compounded as each device is generating huge amounts of data traffic owing to media rich applications and services such as YouTube, Facebook, Instagram, Twitter and similar social networking services. Moreover, emerging paradigms such as smart grid, Internet of Things (IoT), smart city, M2M and V2V communication, Bluetooth enabled services, UMTS and sensor networks are all based on wireless technology. The need for ubiquitous connectivity, which is driven by these ubiquitous services, has transpired into a problem of spectrum scarcity. Cognitive radio has been proposed as a solution to overcome the problems of spectrum scarcity and under-utilization.
The telecommunications data volume increases approximately by an order of 10 every 5 years, which results in an increase in the associated energy consumption by approximately 16−20 percent per annum [1]. By 2008, 3 percent of worldwide energy consumption was by the information and communication technology (ICT) infrastructure, which contributed about 2 percent to the worldwide CO2 emissions [2]. Half of this energy is consumed in wireless communication, thus making it liable for about 1% of global CO2 emissions. It is therefore imperative, to make wireless communication energy efficient, in order to reduce its carbon footprint and to prolong the lifetime of energy limited devices. The lifetime of energy constrained devices can be further enhanced by providing alternate sources of energy such as ambient energy harvesting besides efficiently using existing energy.
The first part of this dissertation proposes various approaches to efficiently utilize the limited energy of Secondary Users (SUs) while considering energy harvesting from Radio Frequency (RF) and non-RF sources. Energy efficiency is achieved, first, by proposing an energy efficient architecture and scheduling algorithm for the sensor network providing sensing service to the cognitive radio network. Secondly, an energy-efficient and quick spectrum handoff scheme is developed for the situations when the PU demands the SU to vacate the spectrum bands or when the current channels conditions are not suitable for transmission. Lastly, an energy efficient spectrum access strategy, using hybrid underlay-overlay scheme, is proposed for cognitive radios with energy harvesting capability.
In a cognitive radio network, the secondary users are opportunistically allowed to use the primary network without disrupting the quality of service of the primary users. The foremost requirement for the SUs is to guarantee protection of the primary user, which requires them to accurately and promptly detect the incumbent user before or while using the primary network. This makes spectrum sensing a critical function of the cognitive radios.
The sensing performance of a single SU deteriorates when channel destructive effects or the hidden terminal problem occur. Cooperation among multiple SUs, which exploit the spatial diversity of users to detect a weak primary signal, improves sensing performance of the network, but has some security vulnerabilities. Sensing performance of the secondary network can be degraded using different types of security attacks. For example, in spectrum sensing data falsification (SSDF) or Byzantine attack, the attacker or malicious user sends false sensing reports to the combining user or fusion center in order to malign the decision about the status of the primary user. Users with malicious behavior and unreliable sensing results need to be either isolated or suppressed in the decision combination process to avoid maligning the decision about the primary user.
The later part of the dissertation presents various methods such as similarity indices based on Smith-Waterman algorithm, non-uniform reliability, and CR users’ classification, to restrict malicious users and overcome security issues in cooperative spectrum sensing. Bioinformatics inspired quantized hard decision combination is also proposed as a decision combination to utilize the bandwidth efficiency of hard decision and sensing accuracy of soft combination.Docto
Spectrum-Aware Routing in Cognitive Ad Hoc Sensor Networks
No full textThe earth, a watery place because of a higher percentage of water than the land, has several communication technologies that help to improve our living standards. Observing our planet in this regard, there exist different living organisms on the land surface, the sea surface and in the ocean which communicate daily with their species using different spectrum. Along with these living things, there are several non-living things with some similar characteristics of living things on the earth e.g., vehicles that need to be fed with petrol, sensors that have ability to adapt according to the environment and need energy to continue existing, machines or robots that can move, and many more, which utilize the same spectrum for communications. Nowadays, we are more than 60\% dependent on these non-living things to make rapid advancements in inter-networking. Inter-networking is a connecting phenomenon that requires a routing protocol to transfer the data packets between different networks by using gateways. Routing is a process that helps sensor nodes to establish a stable link to forward a message to its destination. Hence, to improve communications among different kinds of communicating devices on the land, the sea surface, and in the ocean, three types of sensor networks: terrestrial, maritime, and underwater are designed to deal with various applications, respectively.
As we are exposed to a plethora of mobile applications over the past few years, our living standards are becoming increasingly the part of smart networking. Among various kinds of other systems that are essential to improve our living standards all over the world, the intelligent transportation system is the one that overcomes serious issues due to road accidents. Millions of deaths are caused by road accidents. Therefore, in this thesis, we consider vehicular ad hoc networks as the terrestrial networks. Vehicular ad hoc network is a promising mean for safe driving by enabling cooperation among vehicles. And when it comes to safe and stable communications at the sea surface, maritime ad hoc networks are the ones that play an essential role in providing a variety of safety to users aboard. Similarly, communications in the ocean have also been attracting significant interests to deal with various applications for underwater networks. Hence, in this thesis, we consider three different types of communications systems: vehicular ad hoc networks, maritime ad hoc networks, and underwater acoustic networks to deal with the developing requirements of their applications by ensuring safe and stable communications; and intend to overcome the existing issues in each of them. Both vehicular and maritime ad hoc networks use electromagnetic radio waves as a medium of communications, whereas underwater acoustic networks use acoustic waves.
Ubiquitous wireless communications is an essential goal for numerous applications ranging from traffic safety to entertainment-related information for various users either on the land, the sea surface or in the ocean. The dedicated licensed spectrum for each of these communications systems has been found insufficient to fulfill the increasing needs of vehicular, maritime, and underwater applications. To alleviate the spectrum scarcity in these networks, cognitive technology is a viable solution as it can utilize spectrum in an environment-friendly manner (i.e., avoiding harmful interference with licensed users). To this end, stable links are essential for communications with different users in order to meet the growing demands of vehicular, maritime, and underwater applications. A link is formed only when two communicating nodes have consensus about a common idle channel. Therefore, novel cognitive routing protocols are required for each of these networks to ensure cooperation among the respective users; thereby retaining stable links for vehicular, maritime, and underwater communications.
Various routing techniques have been proposed for vehicular, maritime, and underwater networks, but the number of routing protocols that consider cognitive capability with a routing technique is very limited for vehicular networks. Nevertheless, safe and stable communications issues for cognitive vehicular networks are still under investigation in order to reach a robust and distinguished solution. Similarly, for maritime and underwater networks, combining cognitive principles with routing schemes have not yet been considered. Therefore, in this thesis, we first propose cognitive routing protocols that ensure stable routes between sources and destinations in order to overcome the problems of spectrum scarcity and high latency in vehicular, maritime, and underwater networks, respectively. Our goal is to maintain network stability by considering spectrum sensing and routing simultaneously for vehicular, maritime, and underwater communications. We prove better network performance in each of these cognitive routing protocols in terms of end-to-end delay, delivery ratio, and routing overhead. From these results, we observe that the performance of these networks can be further improved by considering a logically centralized controller that has a global view of the network states and is responsible for selecting the stable paths. This is only possible with the physical separation of network control plane and the forwarding plane.
Therefore, we then apply a new concept of software-defined networking (SDN) in these cognitive vehicular, maritime, and underwater networks to further overcome the shortcomings with the existing architectures in these domains. We find that the SDN-based cognitive routing protocols for each of these vehicular, maritime, and underwater networks improve network performance in comparison with non-SDN-based cognitive routing protocols. All nodes in non-SDN based networks perform all functions (routing, forwarding, and network management) individually resulting in an inefficient utilization of resources, high latency, and large amounts of overhead. Due to SDN approach, these nodes do not further need to configure individually. Any change in the network can be now done centrally by the logically centralized controller. We further comprehend from these results that the improvement is only for networks with specific applications. In order to support multiple applications simultaneously under the same infrastructure and enable users to satisfy each application service with improved network flexibility, we finally introduce two integrated architectures. The first one supports different vehicular applications with the integration of software-defined networking, network function virtualization, and fog computing. However, the second one is an integrated coastal city that instate cognitive vehicular-to-ship communications in hybrid environments. Consequently, we end up this thesis opening a new door for routing in integrated cognitive vehicular and maritime networks in order to run multiple applications simultaneously under the same infrastructure.Docto
Sensing and Transmitting Schedule in Energy Harvesting Powered Cognitive Radio Network with Awareness of Secrecy Capacity
No full textThe proliferation of wireless communication technology has been raising the demand for more and more improvement in data transmission capacity under limited radio spectrum resource. Meantime, the static spectrum allocation policy of government agencies assigned to licensed users, or primary users (PUs), leads to inefficient utilization of a large amount of licensed spectrum. Therefore, the scarcity and under-utilization of radio spectrum resource have driven the concept of cognitive radio (CR). CR technology is a communication paradigm which allows non-licensed users, or cognitive users (CUs), to dynamically and opportunistically access spectrum holes (licensed spectrum bands are not being utilized at a particular time and a specific geographic location) that are temporally unoccupied by PUs. In addition, energy-harvesting powered CR networks (CRNs) have lately become attractive research issues in the literature. Although harvesting capacity has been limited and still need to be improved, energy-harvesting envisions to liberate the CUs in CRNs from energy constraints. Up to now, there have been more and more efforts in the literature to improve energy-harvesting capacity in the future. In the meantime, (i) limits in energy harvesting capacity should be considered as one of the most important criteria for the design of energy-harvesting powered-CRNs. In addition, similar to traditional wireless networks, (ii) CRNs have also some security vulnerabilities i.e. malicious attacking, eavesdropping which should be properly addressed in the design of these networks in future. Furthermore, the demand to improve the wireless communications rate under the scarcity of spectrum resources leads to (iii) the concept of full-duplex (FD) transmission protocol, which allows a radio device to simultaneously transmit and receive on the same frequency band. Recently, FD protocols represents as far as an attractive option for increasing the throughput of CR systems.
Generally, CRNs are not allowed to make any interference to PUs. Therefore, robust and reliable spectrum sensing (SS) schemes to detect PUs’ signal are utmost important for the operation of CRNs. To the best of our knowledge, SS schemes and transmitting power allocation algorithms for infinite-energy CRNs have been well-studied in literature up to now. However, sensing-transmitting schedule, transmission power allocation schedule, and transmission protocol switching schedule in energy-harvesting powered-CRNs with and without awareness of secrecy capacity are still under-investigated. Motivated from the foregoing survey, this dissertation will address these remaining challenges for energy-harvesting powered-CRNs as follows:
Firstly, considering channel switching delay and imperfect sensing, we proposed an optimal multi-slot multi-channel sensing order for the opportunistic access to a number of potential primary channels. In addition, the correlation of channel availability statistics across time slots and channels is also considered. The problem was formulated and solved based on the partially observable Markov decision process (POMDP) framework and the optimal stopping theorem. The goal of this work is finding an optimal sensing order of channels in order to maximize throughput of CU in CRNs.
Secondly, based on the theory of optimal stopping, we propose an algorithm to optimize the sequential cooperative SS and reporting process in which the fusion center (FC) sequentially asks each CU to report its sensing result until the stopping condition which provides maximum expected throughput for CRN is satisfied. Simulation shows that performance of the proposed scheme can be improved by further shortening the reporting overhead and reducing the probability of false alarm compared to other schemes in the literature.
Thirdly, considering energy-harvesting powered-CRNs utilizing multiple potential primary channels, we propose a scheme to find an optimal channel-sensing and transmitting schedule, consisting of finding (i) the optimal action (silent or active) and sensing order of channels and (ii) the optimal amount of transmission energy corresponding to the channels in the sensing order, for the operation of the CU in order to maximize the long-term expected throughput. The performance of the proposed scheme is evaluated in comparison to related schemes in the literature which only considered immediate throughput.
Next, we considered a practical scenario of energy-harvesting powered-CRNs under the presence of eavesdropper(s). A pair of CUs opportunistically accesses a potential licensed channel; meanwhile, they should ensure that their confidential communications are not leaked to the eavesdropper. Based on expected secrecy transmission rate calculated over subsequent time slots, we proposed a scheme to find an optimal spectrum sensing and transmitting schedule as well as the optimal amount of transmission energy in each processing time slot. In particular, the CUs decide either (i) to sense the channel and transmit its data if the channel is found vacant or (ii) to stay silent during the current time slot to save energy as well as to wait for more harvested energy for use in the next time slots. The proposed scheme aims to improve long-term secrecy transmission rate of CRNs.
Finally, we focuses on utilizing the full advantages of both half-duplex (HD) and FD transmission protocol for the operation of CU in energy-harvesting based-CRNs. Based on the available probability of potential primary channel, information about cognitive channel gain between cognitive base station (BS) and CU, and the amount of energy-harvesting rate, we propose a scheme to find an optimal switching schedule between HD and FD transmission protocol as well as the amount of transmission energy for the BS and CU corresponding to each transmission protocol for maximizing long-term expected transmission rate of the BS-CU transmission pair. Then, the problem is formulated and solved by adopting the POMDP-framework. Simulation shows that average throughput attained by the proposed scheme is greatly improved compared to that of the conventional scheme, and remarkably, when the energy-harvesting rate becomes low. We close our studies by raising another solution to this problem by adopting the Actor-Critic learning framework. Although the actor-critic learning process may converge to a locally optimal policy, this method generates the action directly from training policy; hence, it requires much less formulation and computation to select an action compared to POMDP framework.Docto
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Reliable Spectrum Sensing and Physical Layer Security for Cognitive Radio Networks
No full textThe need for spectrum is ever-growing as the use of data services is becoming pervasive. With the onset of new services like smart cities and internet of things (IoTs), and infotainment services in next generation of vehicles, the demand for data and thus for the limited spectrum is increasing. Wireless networks and services supported by wireless technology have been around for ages but because of the revolution in mobile computing brought by smart phones and other such devices the need and desire to stay connected 24/7 has put a unique demand on wireless networks. The services and the devices which need to be served are raising exponentially but the wireless spectrum is a physically limited spectrum. So, to meet all the demands the onus comes on managing the spectrum efficiently.
There is a focus for the last decade or so to come up with techniques which can exploit the loopholes in the present management of the spectrum and also in some ways to radically shift the ways in which the spectrum is accessed. One of such approaches is cognitive radio network (CRN) which aims to exploit the underutilization of the allocated spectrum to fixed and dedicated nodes and services. CRN is a secondary network which has an unlicensed access the spectrum under certain conditions. CRN is faced with architectural as well as management issues because it has to meet not only the constraints of the primary network and the primary user (PU) but also it has to meet the service demands of the CR users. This dissertation focuses on two of the architectural issues, reliable spectrum sensing and physical layer security. The CR user has to first ascertain that the PU is absent before it can access the channel. This process is known as spectrum sensing. There are myriad of issues in spectrum sensing including the reliability of the spectrum sensing data and learning the changing behavior of the PU. These are addressed in the first part of the dissertation. In the second part of the dissertation the need for secure communication among the CR users is considered. As the CR users are mobile devices so they have limited computing power. The channel codes and encryption techniques used in conventional wireless communications cannot be used in a CRN because of the ad-hoc nature of the CRN and also because of exhaustive demands for computing power of the encryption techniques. Physical layer security which employs digital signal processing techniques to ensure secrecy is suitable for CRN because rather than taking exhaustive computational power it uses the features of channels for providing information secrecy.
In the first part of the dissertation applying bioinformatics inspired techniques to be spectrum sensing is studied. String matching algorithms used in bioinformatics can be applied to scenarios in cognitive radios where reports of cooperative spectrum sensing nodes need to be compared with each other. Cooperative spectrum sensing is susceptible to security risks where malicious users who participate in the process falsify the spectrum sensing data, thus affecting cognitive radio network performance. In this work, an efficient spectrum sensing system is developed where each CR user senses the spectrum multiple times within an allocated sensing period. Each CR user quantizes its decision to predefined levels so as to achieve a trade-off between bandwidth utilization and decision reporting accuracy. The reports for all the CR users are compared at the fusion center using Smith-Waterman algorithm (SWA), an optimal algorithm for aligning biological sequences used in bioinformatics, and similarity indices are computed. Robust mean and robust deviation of the similarity indices are calculated and a threshold is determined by these values. The CR users who have similarity index below the given threshold are declared malicious and their reports are discarded. The local decisions of the remaining CR users are combined using the modified rules of decision combination to take a global decision. Simulation results show that our proposed scheme performs better than conventional schemes with and without malicious users.
The study is extended for investigating optimal quantization schemes for spectrum sensing next. Cooperative spectrum sensing can be made more reliable by excluding the reports of unreliable CR users from the final decision combination at the fusion center (FC). Hard decision combination provides bandwidth efficiency but the results produced are unreliable while on the other hand soft decision combination has better results but at the expense of much consumption of bandwidth. If instead of hard decision or soft decision combination, quantized information is sent by the CR users to the FC, an acceptable trade-off is achieved. In this paper an optimal quantization scheme is proposed in which the local sensing information is quantized in such a way which ensures that the maximum detection probability is met while the false alarm probability remains under a certain constraint. The proposed optimal scheme works on the basis of energy detection and the local quantization thresholds are found through iterative search. A method inspired from bioinformatics, Smith-Waterman algorithm (SWA) is used to compare the local sensing reports of the CR users and on the basis of comparison similarity indexes are found for the CR users. On the basis of robust mean and robust standard deviation a threshold is calculated for the cooperative spectrum sensing. The local sensing decisions of the CR users below the calculated threshold are rejected and are not included in the final decision combination at the FC. As quantized information is used so the conventionally used rules of decision combination are modified to work on the quantized information and the FC combines the local sensing decisions of rest of the CR users through the modified rules. For detailed analysis, SWA-based rules of decision combination with optimal quantization thresholds are compared with a scheme that employs SWA-based rules of decision combination with heuristically selected quantization thresholds and a conventional majority combination scheme based on heuristically selected quantization thresholds. Simulation results show that the proposed scheme performs better than the other two schemes.
After that a reliable spectrum sensing scheme is proposed, which uses K-nearest neighbor, a machine learning algorithm. In the training phase, each CR user produces a sensing report under varying conditions, and based on a global decision, either transmits or stays silent. In the training phase the local decisions of CR users are combined through a majority voting at the fusion center and a global decision is returned to each CR user. A CR user transmits or stays silent according to the global decision and at each CR user the global decision is compared to the actual primary user activity, which is ascertained through an acknowledgment signal. Based on this comparison, the sensing report is assigned to a sensing class. In the training phase enough information about the surrounding environment i.e. the activity of PU and the behavior of each CR to that activity is gathered. In the classification phase, each CR user compares its current sensing report to existing sensing classes, which are formed in the training phase, and distance vectors are calculated. Based on quantitative variables, the posterior probability of each sensing class is calculated and the sensing report is declared to represent either the absence or presence of a primary user at the CR user level. The quantitative variables used for calculating the posterior probability are calculated through K-nearest neighbor algorithm. These local decisions are then combined at the fusion center using a novel decision combination scheme, which takes into account the reliability of each CR user. The CR users then transmit or stay silent according to the global decision. Simulation results show that our proposed scheme outperforms conventional spectrum sensing schemes, both in fading and non-fading environments, where performance is evaluated using metrics such as the probability of detection, total probability of error and the ability to exploit data transmission opportunities.
The first part of the dissertation is concluded by investigating a joint spectrum sensing and transmission framework. Actor-Critic algorithm is employed to get the optimal policy and value function and the algorithm is trained through all possible actions and states. In transmission the CR user is constrained by the residual energy. So, energy harvesting is used to harvest energy and then to transmit with transmission energy which meets the long term requirement of the CR user. Given a state which is composed of the remaining energy, the belief and the local and global spectrum decisions an action is selected on the basis of optimal value function and optimal policy function after the training phase is done with. Simulation result show the occurrence of each action selected which points to the probability of the occurrence of the particular state and action combination. The average rate achieved is also shown and is compared with an exhaustive search scheme which acts as the upper bound for the scheme.
The second part of the dissertation deals with physical layer security. First, a physical layer-security scheme for an underlay relay-based CRN that uses OFDM as the medium access technique is proposed. Resource allocation in relay-aided CRNs becomes a hard problem especially if it is under security threat. Different from conventional relay-based OFDM schemes, in the paper we consider the relay network which has two dedicated relay nodes; One relay which is capable of subcarrier mapping forwards the received signal to the destination and the other sends a jamming signal to add noise to the signal received by the eavesdropper. Optimization is performed under a unified framework where power allocation at the source node, power allocation and subcarrier mapping in the relay network are optimized to maximize the secrecy rate of the CRN while satisfying the maximum transmission power constraints and the interference threshold of the PU. The power allocation problem at the forwarding relaying node is a non-convex optimization problem. Therefore, at first the optimization problem is simplified and a closed form solution is obtained which satisfies the maximum PU interference constraint. Afterwards, the optimization problem is solved for satisfying the maximum transmission power constraint. An algorithm is also proposed for subcarrier mapping at the forwarding relaying node. The proposed power allocation method and subcarrier mapping scheme have low complexity, compared to the baseline schemes. Finally, simulation results are provided for different parameters to show the performance improvement of the proposed scheme in terms of secrecy rate.
Physical layer security is furthered explored by proposing a physical layer security-based scheme for an underlay CRN that has energy-constrained relay nodes. In the scheme, the cooperative diversity of multiple relays is exploited to provide physical layer security against an eavesdropping attack. Different from conventional relay schemes, relay-based CRN faces other issues, such as the maximum interference–constraint with the PU, and takes into consideration leakage to eavesdroppers in case of an eavesdropping attack. For a CRN to be practical, the energy constraint should be taken into consideration because ad-hoc networks cannot have a fixed power supply all the time. If the nodes in a CRN are able to harvest energy and then spend less energy than the total energy available, we can ensure a perpetual lifetime for the network. In this paper, an energy-constrained CRN is considered where relay nodes are able to harvest energy. A cooperative, diversity-based relay and subchannel–selection algorithm is proposed, which selects a relay and a subchannel to achieve the maximum secrecy rate while keeping the energy consumed under a certain limit. A transmission power factor is also selected by the algorithm, which ensures long-term operation of the network. The power allocation problem at the selected relay and at the source also satisfies the maximum-interference constraint with the PU. The proposed scheme is compared with a variant of the proposed scheme where the relays are assumed to have an infinite battery capacity (so maximum transmission power is available in every time slot), and is compared with a scheme that uses jamming for physical layer security. The simulation results show that the proposed scheme closely follows the infinite battery capacity scheme, which works as the upper bound for the proposed scheme. The infinite battery–capacity scheme outperforms the jamming-based physical layer security scheme, thus validating that cooperative diversity–based schemes are suitable to use when channel conditions are better employed, instead of jamming for physical layer security.Docto
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
- …
