Energy efficient cognitive radio networks: Green payment

Kablosuz ve Mobil teknolojilerin gelişmesi, kullanım rahatlığından dolayı artan kullanıcı istekleri, multimedya uygulamalarının yoğun kullanımı, frekans sahasının verimsiz kullanılması Bilişsel Radyo (BR) olarak isimlendirilen yeni bir iletişim teknolojisi kavramının ortaya çıkmasına neden olmuştur. BR’ler bütün telsiz iletişim sistemlerinde frekans sahasının daha etkin ve enerji kullanımının da daha verimli olmasını sağlayacaktır. Bu çalışmada BR kavramsal olarak açıklanmış, sisteme ilişkin donanım ve yazılım problemleri özetlenmiş, iletişim ağlarıyla ilgili artan enerji maliyetleri, gittikçe ağırlaştırılan çevrebilim sınırlamalarına bağlı olarak BR’nin enerji etkin çalışmalardaki rolü incelenmiştir. Bu çalışmalar kapsamında, BR’ler enerji etkinliği ve yeşil iletişim temaları altında benzerliklerine göre gruplandırılmış ve özellikle Yeşil iletişimdeki BR katkıları için “Yeşil Ödeme” isimli bir algoritma önerilmiştir. Önerilen Yeşil Ödeme algoritmasında frekans sahasının ikincil kullanıcıları haberleşme güç seviyelerine göre yüksek ve düşük güçlü kullanıcılar olarak ayrılmış, belli bir eşik değerin üstündeki yüksek güçlü kullanıcılara yaptırım olarak ek bir maliyet getirilerek kanal alımları zorlaştırılmıştır. Böylece toplam kullanılabilir kanal yüzdesi düşürülmüş ve harcanan güç miktarında azalma sağlanarak BR’lerin yeşil iletişime katkısı gösterilmiştir.Development of mobile and wireless technologies, increasing user demands due to the ease of use, intensive use of multimedia applications and the inefficient use of frequency spectrum enable the emergence of a new communication paradigm, namely Cognitive Radios (CR). The use of CRs will provide effective use of spectrum and efficient energy management in all wireless communication systems. In this study, we’ve explained the concept of CR, summarized hardware/software difficulties of the system and examined the role of CRs in energy efficient studies due to the continuous increase of energy costs and tightened ecological regulations in transmission networks. Within the scope of these studies, CRs have been categorized into groups of different similarities under the theme of green communication and energy efficiency and particularly proposed a “Green Payment” algorithm for the contributions in green communications. In the proposed “Green Payment” algorithm, secondary users of the frequency spectrum have been separated into high power and low power users according to the transmitting power levels. It has brought an additional cost for the high power users above a certain threshold value and made more difficult to purchase a free channel. This paper shows how our algorithm has achieved a considerable amount of power reduction while the total percentage of available channels falls down

Cooperative Spectrum Sensing in Cognitive Radio Networks Using Multidimensional Correlations

In this paper, a multidimensional-correlation-based sensing scheduling algorithm, (CORN)2, is developed for cognitive radio networks to minimize energy consumption. A sensing quality metric is defined as a measure of the correctness of spectral availability information based on the fact that spectrum sensing information at a given space and time can represent spectrum information at a different point in space and time. The scheduling algorithm is shown to achieve a cost of sensing (e.g., energy consumption, sensing duration) arbitrarily close to the possible minimum, while meeting the sensing quality requirements. To this end, (CORN)2 utilizes a novel sensing deficiency virtual queue concept and exploits the correlation between spectrum measurements of a particular secondary user and its collaborating neighbors. The proposed algorithm is proved to achieve a distributed and arbitrarily close to optimal solution under certain, easily satisfied assumptions. Furthermore, a distributed Selective-(CORN)2 (S-(CORN)2) is introduced by extending the distributed algorithm to allow secondary users to select collaboration neighbors in densely populated cognitive radio networks. In addition to the theoretically proved performance guarantees, the algorithms are evaluated through simulations

A secure and energy-aware approach for cognitive radio communications

The cognitive radio (CR) technique has revealed a novel way of utilizing the precious radiospectrum via allowing unlicensed users to opportunistically access unutilized licensed bands. Using sucha technique enables agile and flexible access to the radio spectrum and can resolve the spectrum-scarcityproblem and maximize spectrum efficiency. However, two major impediments have been limiting thewidespread adoption of cognitive radio technology. The software-defined radio technology, which is theenabling technology for the CR technique, is power-hungry and this raises a major concern for battery-constrained devices such as smart phones and laptops. Secondly, the opportunistic and open nature ofthe CR can lead to major security concerns about the data being sent and how safe it is. In this paper,we introduce an energy-and-security-aware CR-based communication approach that alleviates the powerconsumption of the CR technique and enhances its security measures according to the confidentialitylevel of the data being sent. Furthermore, the proposed approach takes into account user-related factors,such as the user’s battery level and user’s data type, and network-related factors, such as the number ofunutilized bands and vulnerability level and then models the research question as a constrained optimizationproblem. Considering the time complexity of the optimum solution, we also propose a heuristic solution.We examine the proposed solution against existing solutions, and our obtained results show that theproposed approach can save energy consumption up to 18%, increase user throughput up to 20%, andachieve better spectrum utilization, up to 98%. Our proposed admission approach has the potential toopen a new research direction towards safer and greener cognitive radio techniques

Energy and throughput efficient strategies for heterogeneous future communication networks

As a result of the proliferation of wireless-enabled user equipment and data-hungry applications, mobile data traffic has exponentially increased in recent years.This in-crease has not only forced mobile networks to compete on the scarce wireless spectrum but also to intensify their power consumption to serve an ever-increasing number of user devices. The Heterogeneous Network (HetNet) concept, where mixed types of low-power base stations coexist with large macro base stations, has emerged as a potential solution to address power consumption and spectrum scarcity challenges. However, as a consequence of their inflexible, constrained, and hardware-based configurations, HetNets have major limitations in adapting to fluctuating traffic patterns. Moreover, for large mobile networks, the number of low-power base stations (BSs) may increase dramatically leading to sever power consumption. This can easily overwhelm the benefits of the HetNet concept. This thesis exploits the adaptive nature of Software-defined Radio (SDR) technology to design novel and optimal communication strategies. These strategies have been designed to leverage the spectrum-based cell zooming technique, the long-term evolution licensed assisted access (LTE-LAA) concept, and green energy, in order to introduce a novel communication framework that endeavors to minimize overall network on-grid power consumption and to maximize aggregated throughput, which brings significant benefits for both network operators and their customers. The proposed strategies take into consideration user data demands, BS loads, BS power consumption, and available spectrum to model the research questions as optimization problems. In addition, this thesis leverages the opportunistic nature of the cognitive radio (CR) technique and the adaptive nature of the SDR to introduce a CR-based communication strategy. This proposed CR-based strategy alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the introduced strategy takes into account user-related factors, such as user battery levels and user data types, and network-related factors, such as the number of unutilized bands and vulnerability level, and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solutions for the above-mentioned strategies, heuristic solutions were proposed and examined against existing solutions. The obtained results show that the proposed strategies can save energy consumption up to 18%, increase user throughput up to 23%, and achieve better spectrum utilization. Therefore, the proposed strategies offer substantial benefits for both network operators and users