Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

Enhanced Spectrum Sensing Techniques for Cognitive Radio Systems

Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources. Considering the limited radio spectrum, supporting the demand for higher capacity and higher data rates is a challenging task that requires innovative technologies capable of providing new ways of exploiting the available radio spectrum. Cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems, has received increasing attention and is considered a promising solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Spectrum sensing, which enables CRs to identify spectral holes, is a critical component in CR technology. Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends. In this thesis, we focus on enhanced spectrum sensing techniques that provide performance gains with reduced computational complexity for realistic waveforms considering radio frequency (RF) impairments, such as noise uncertainty and power amplifier (PA) non-linearities. The first area of study is efficient energy detection (ED) methods for spectrum sensing under non-flat spectral characteristics, which deals with relatively simple methods for improving the detection performance. In realistic communication scenarios, the spectrum of the primary user (PU) is non-flat due to non-ideal frequency responses of the devices and frequency selective channel conditions. Weighting process with fast Fourier transform (FFT) and analysis filter bank (AFB) based multi-band sensing techniques are proposed for overcoming the challenge of non-flat characteristics. Furthermore, a sliding window based spectrum sensing approach is addressed to detect a re-appearing PU that is absent in one time and present in other time. Finally, the area under the receiver operating characteristics curve (AUC) is considered as a single-parameter performance metric and is derived for all the considered scenarios. The second area of study is reduced complexity energy and eigenvalue based spectrum sensing techniques utilizing frequency selectivity. More specifically, novel spectrum sensing techniques, which have relatively low computational complexity and are capable of providing accurate and robust performance in low signal-to-noise ratio (SNR) with noise uncertainty, as well as in the presence of frequency selectivity, are proposed. Closed-form expressions are derived for the corresponding probability of false alarm and probability of detection under frequency selectivity due the primary signal spectrum and/or the transmission channel. The offered results indicate that the proposed methods provide quite significant saving in complexity, e.g., 78% reduction in the studied example case, whereas their detection performance is improved both in the low SNR and under noise uncertainty. Finally, a new combined spectrum sensing and resource allocation approach for multicarrier radio systems is proposed. The main contribution of this study is the evaluation of the CR performance when using wideband spectrum sensing methods in combination with water-filling and power interference (PI) based resource allocation algorithms in realistic CR scenarios. Different waveforms, such as cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM), enhanced orthogonal frequency division multiplexing (E-OFDM) and filter bank based multicarrier (FBMC), are considered with PA nonlinearity type RF impairments to see the effects of spectral leakage on the spectrum sensing and resource allocation performance. It is shown that AFB based spectrum sensing techniques and FBMC waveforms with excellent spectral containment properties have clearly better performance compared to the traditional FFT based spectrum sensing techniques with the CP-OFDM. Overall, the investigations in this thesis provide novel spectrum sensing techniques for overcoming the challenge of noise uncertainty with reduced computational complexity. The proposed methods are evaluated under realistic signal models

Advances and emerging challenges in cognitive internet-of-things

The evolution of IoT devices and their adoption in new generation intelligent systems has generated a huge demand for wireless bandwidth. This bandwidth problem is further exacerbated by another characteristics of IoT applications, i.e. IoT devices are usually deployed in massive number, thus leading to an awkward scenario that many bandwidth-hungry devices are chasing after the very limited wireless bandwidth within a small geographic area. As such, cognitive radio has received much attention of there search community as an important means for addressing the bandwidth needs of IoT applications. When enabling IoT devices with cognitive functionalities including spectrum sensing, dynamic spectrum accessing, circumstantial perceiving and self-learning, one will also need to fully study other critical issues such as standardization, privacy protection and heterogeneous coexistence. In this paper, we investigate the structural frameworks and potential applications of cognitive IoT. We further discuss the spectrum-based functionalities and heterogeneity for cognitive IoT. Security and privacy issues involved in cognitive IoT are also investigated. Finally, we present the key challenges and future direction of research on cognitiveradio-based IoT networks

Large-scale cognitive cellular systems: resource management overview

This paper presents recent advancements in resource management for large-scale DSA Systems. Although the problem of spectrum and power allocation is well addressed in the literature, the need for more efficient algorithms still persists due to the exponential growth of the number of wireless devices. Thus, developing efficient distributed approaches became an attractive solution that can follow the systems’ rapid growth. Despite the number of economic-driven methods that were presented such as game theoretic solutions, these methods still rely on excessive information exchange, which results in high delays. Inspired from the success of behavioral techniques, mainly learning and filtering approaches, applications of these techniques to spectrum management have attracted more interest due to their distributivity and minimal requirements of information exchange.This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE-Institute of Electrical and Electronics Engineers and can be found at: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=35 ©2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Transmitted Power Formulation for the Optimization of Spectrum Aggregation in LTE-A over 800 MHz and 2 GHz Frequency Bands

This work starts by proposing a formulation to calculate the transmitter power needed to cover cells of different sizes, whilst maintaining the average signal to interference-plus-noise ratio constant, and near the maximum, for two Long Term Evolution (LTE) systems operating over non-contiguous frequency bands, 800 MHz and 2 GHz, with an integrated common radio resource management (iCRRM) entity. In the context of spectrum aggregation (SA), iCRRM is able to switch users between the two LTE-Advanced scenarios to facilitate the best user allocation and maximize the total network throughput in these LTE systems. We address a formulation based on the computation of the average received power and average co-channel interference in cellular topologies with frequency reuse pattern K = 3, keeping the presence of coverage holes insignificant, whilst considering the COST-231 Hata path loss model. We have verified how the normalized power increases as the cell radius increases. The objective of applying this formulation in the dimensioning process is to save power for the shortest coverage distances. It has been found that without SA the maximum average cell throughput is observed in the presence of 80 simultaneous users within the cell (40 for each LTE system, operating in different frequency bands). We have considered traced-based video sessions with a (video) bit rate of 128 kbps. In this scenario, through extensive simulations cell average supported throughput of approximately 6,800, 8,500 and 9,500 kbps have been obtained for the cases without SA (considering the sum of the 800 MHz and 2 GHz systems capacities), with a simple CRRM and with iCRRM, respectively. It was also found that when the peak throughput is achieved with 80 users, the average cell packet loss ratio without SA, with CRRM and iCRRM present values of 22, 11 and 7 %. The average cell delay with both CRRM and iCRRM entities is 22 ms, whereas without SA is equal to 32 ms. Finally, the cost/revenue tradeoff is analysed from the operator/service provider’s point of view, whose main goal is obtain the maximum profit from his business. It was found that CRRM increases the total profit in percentage, compared to a simple allocation, without SA. Nevertheless, the profit growth with iCRRM is even larger, from 253 to 296 % for R = 1,000 m and a price of 0.010 €/MByte. Therefore, our proposal for SA is convenient not only in terms of technical features and QoS, as loss and delay have been obtained within a range of reasonable values, but also in terms of economic aspects.info:eu-repo/semantics/publishedVersio

A simplified optimization for resource management in cognitive radio network-based internet-of-things over 5G networks

With increasing evolution of applications and services in internet-of-things (IoT), there is an increasing concern of offering superior quality of service to its ever-increasing user base. This demand can be fulfilled by harnessing the potential of cognitive radio network (CRN) where better accessibility of services and resources can be achieved. However, existing review of literature shows that there are still open-end issues in this regard and hence, the proposed system offers a solution to address this problem. This paper presents a model which is capable of performing an optimization of resources when CRN is integrated in IoT using five generation (5G) network. The implementation uses analytical modeling to frame up the process of topology construction for IoT and optimizing the resources by introducing a simplified data transmission mechanism in IoT environment. The study outcome shows proposed system to excel better performance with respect to throughput and response time in comparison to existing schemes