RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations

The increasing demand for spectral and energy efficient communication networks has spurred a great interest in energy harvesting (EH) cognitive radio networks (CRNs). Such a revolutionary technology represents a paradigm shift in the development of wireless networks, as it can simultaneously enable the efficient use of the available spectrum and the exploitation of radio frequency (RF) energy in order to reduce the reliance on traditional energy sources. This is mainly triggered by the recent advancements in microelectronics that puts forward RF energy harvesting as a plausible technique in the near future. On the other hand, it is suggested that the operation of a network relying on harvested energy needs to be redesigned to allow the network to reliably function in the long term. To this end, the aim of this survey paper is to provide a comprehensive overview of the recent development and the challenges regarding the operation of CRNs powered by RF energy. In addition, the potential open issues that might be considered for the future research are also discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin

Using remote sensing, occupancy estimation, and fine-scale habitat characterization to evaluate fall chum salmon (Oncorhynchus keta) spawning habitat usage in Arctic Alaska

Thesis (M.S.) University of Alaska Fairbanks, 2017Groundwater upwellings provide stable temperatures for overwinter salmon embryo development and this process may be particularly important in cold, braided, gravel-bed Arctic rivers where rivers may freeze solid in the absence of upwellings. Aerial counts and remote sensing were used during 2013-2015 to estimate fall chum salmon (Oncorhynchus keta) spawner abundance states (e.g., low or high), classify river segments by geomorphic channel type (primary, flood, and spring), and map thermal variability along a 25.4 km stretch of the Chandalar River in interior Alaska. Additionally, I used on-the-ground examination of fine scale variation in physical habitat characteristics at 11 representative sites to characterize habitat variability, placed temperature loggers to assess overwinter thermal conditions in redds, and used a developmental model to predict hatching and emergence timing given known spawning dates and incubation temperatures. I delineated 330 unique river segments (mean length = 536 m) and used a multi-season multistate occupancy model to estimate detectability, occupancy, and local colonization and extinction rates. Triplicate surveys performed in 2014 allowed me to estimate detectability and the influence of observer bias. I found that detectability did not vary by observer, channel type, or segment length, but was better for high abundance (0.717 ± 0.06 SE) relative to low abundance (0.367 ± 0.07 SE) aggregations. After correcting for imperfect detection, the proportion of segments occupied by spawning fall chum salmon was highest in 2014 (0.41 ± 0.04 SE), relative to 2013 (0.23 ± 0.04) and 2015 (0.23 ± 0.04). Transition probabilities indicated unoccupied segments were likely to remain so from year to year (2013→2014 = 0.67; 2014→2015 = 0.90), but low abundance spawning segments were dynamic and rarely remained in that state. One-third of high abundance sites remained so, indicating the presence of high quality spawning habitat. Mean segment temperatures ranged from -0.5 to 4.4°C, and occupancy varied positively with temperature. I predicted a 50% probability of occupancy in segments with temperatures of 3°C. With my on-the-ground work, I found that habitat characteristics varied among the three channel types, with most significant differences between main channel and off-channel habitats. Dissolved oxygen and pH decreased with increasing temperature, and conductivity increased with temperature. Predicted hatching and emergence timing ranged from 78 and 176 days (December 11th and March 18th) to 288 and 317 days (July 8th and August 6th), respectively, post-spawning, and were highly variable within sites and among channel types owing to high habitat thermal heterogeneity. Because the Chandalar River supports 30% of the fall chum salmon run in the Yukon River Basin, information such as provided by this study will be critical to allow resource managers to better understand the effects of future climate and anthropogenic change in the region.General introduction -- Chapter 1: A remote sensing and occupancy estimation approach to quantify spawning habitat use by fall chum salmon (Oncorhynchus keta) along the Chandalar River, Alaska -- Chapter 2: Spawning habitat characteristics and phenology of fall chum salmon (Oncorhynchus keta) on the Chandalar River, Alaska -- General conclusions

Contributions to Resource Allocation in Cognitive Radio Networks

The continuous increase in the number of wireless devices and the huge demand for higher data rates have promoted the development of new wireless communications technologies with improved spectrum sharing features. Recently, the concept of cognitive radio (CR) has gained increased popularity for the efficient utilization of radio frequency (RF) spectrum. A CR is characterized as a communication system which is capable to learn the spectrum environment through sensing, and to adapt its signaling schemes for a better utilization of the radio frequency resources. Resource allocation, which involves scheduling of spectrum and power resources, represents a crucial problem for the performance of CR networks in terms of system throughput and bandwidth utilization. In this dissertation, we investigate resource allocation problems in a CR network by exploring a variety of optimization techniques. Specifically, in the first part of the dissertation, our goal is to maximize the total throughput of secondary users (SUs) in an orthogonal frequency division multiple access (OFDMA) CR network. In addition, the power of SUs is controlled to keep the interference introduced to primary users (PUs) under certain limits, which gives rise to a non-convex mixed integer non-linear programming (MINLP) optimization problem. It is illustrated that the original non-convex MINLP formulation admits a special structure and the optimal solution can be achieved efficiently using any standard convex optimization method under a general and practical assumption. In the second part of the dissertation, considering the imperfect sensing information, we study the joint spectrum sensing and resource allocation problem in a multi-channel-multi-user CR network. The average total throughput of SUs is maximized by jointly optimizing the sensing threshold and power allocation strategies. The problem is also formulated as a non-convex MINLP problem. By utilizing the continuous relaxation and convex optimization tools, the dimension of the non-convex MINLP problem is significantly reduced, which helps to reformulate the optimization problem without resorting to integer variables. A newly-developed optimization technique, referred to as the monotonic optimization, is then employed to obtain an optimal solution. Furthermore, a practical low-complexity spectrum sensing and resource allocation algorithm is proposed to reduce the computational cost

Cooperative Spectrum Sensing based on 1-bit Quantization in Cognitive Radio Networks

The wireless frequency spectrum is a very valuable resource in the field of communications. Over the years, different bands of the spectrum were licensed to various communications systems and standards. As a result, most of the easily accessible parts of it ended up being theoretically occupied. This made it somewhat difficult to accommodate new wireless technologies, especially with the rise of communications concepts such as the Machine to Machine (M2M) communications and the Internet of Things (IoT). It was necessary to find ways to make better use of wireless spectrum. Cognitive Radio is one concept that came into the light to tackle the problem of spectrum utilization. Various technical reports stated that the spectrum is in fact under-utilized. Many frequency bands are not heavily used over time, and some bands have low activity. Cognitive Radio (CR) Networks aim to exploit and opportunistically share the already licensed spectrum. The objective is to enable various kinds of communications while preserving the licensed parties' right to access the spectrum without interference. Cognitive radio networks have more than one approach to spectrum sharing. In interweave spectrum sharing scheme, cognitive radio devices look for opportunities in the spectrum, in frequency and over time. Therefore, and to find these opportunities, they employ what is known as spectrum sensing. In a spectrum sensing phase, the CR device scans certain parts of the spectrum to find the voids or white spaces in it. After that it exploits these voids to perform its data transmission, thus avoiding any interference with the licensed users. Spectrum sensing has various classifications and approaches. In this thesis, we will present a general review of the main spectrum sensing categories. Furthermore, we will discuss some of the techniques employed in each category including their respective advantages and disadvantages, in addition to some of the research work associated with them. Our focus will be on cooperative spectrum sensing, which is a popular research topic. In cooperative spectrum sensing, multiple CR devices collaborate in the spectrum sensing operation to enhance the performance in terms of detection accuracy. We will investigate the soft-information decision fusion approach in cooperative sensing. In this approach, the CR devices forward their spectrum sensing data to a central node, commonly known as a Fusion Center. At the fusion center, this data is combined to achieve a higher level of accuracy in determining the occupied parts and the empty parts of the spectrum while considering Rayleigh fading channels. Furthermore, we will address the issue of high power consumption due to the sampling process of a wide-band of frequencies at the Nyquist rate. We will apply the 1-bit Quantization technique in our work to tackle this issue. The simulation results show that the detection accuracy of a 1-bit quantized system is equivalent to a non-quantized system with only 2 dB less in Signal-to-Noise Ratio (SNR). Finally, we will shed some light on multiple antenna spectrum sensing, and compare its performance to the cooperative sensing

New Approaches in Cognitive Radios using Evolutionary Algorithms

Cognitive radio has claimed a promising technology to exploit the spectrum in an ad hoc network. Due many techniques have become a topic of discussion on cognitive radios, the aim of this paper was developed a contemporary survey of evolutionary algorithms in Cognitive Radio. According to the art state, this work had been collected the essential contributions of cognitive radios with the particularity of base they research in evolutionary algorithms. The main idea was classified the evolutionary algorithms and showed their fundamental approaches. Moreover, this research will be exposed some of the current issues in cognitive radios and how the evolutionary algorithms will have been contributed. Therefore, current technologies have matters presented in optimization, learning, and classification over cognitive radios where evolutionary algorithms can be presented big approaches. With a more comprehensive and systematic understanding of evolutionary algorithms in cognitive radios, more research in this direction may be motivated and refined

DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version