We propose cognitive spectrum sharing with generalized selection combining (GSC) at the secondary user (SU) in the presence of multiple primary transceivers with outdated channel information. Our main motivation is to determine the impact of GSC and outdated channel information on the outage probability of cognitive spectrum sharing subject to two practical power constraints: 1) maximum transmit power at…
Tags: OMNeT++ SDN
Energy Efficient COGnitive-MAC for Sensor Networks Under WLAN Co-existence
Energy efficiency has been the driving force behind the design of communication protocols for battery-constrained wireless sensor networks (WSNs). The energy efficiency and the performance of the proposed protocol stacks, however, degrade dramatically in case the low-powered WSNS are subject to interference from high-power wireless systems such as WLANs. In this paper we propose COG-MAC, a novel cognitive medium…
Bit error rate of underlay decode-and-forward cognitive networks with best relay selection
This paper provides an analytic performance evaluation of the bit error rate (BER) of underlay decode-and-forward cognitive networks with best relay selection over Rayleigh multipath fading channels. A generalized BER expression valid for arbitrary operational parameters is firstly presented in the form of a single integral, which is then employed for determining the diversity order and coding gain…
Engaging citizen communities in smart cities using IoT, serious gaming and fast markerless Augmented Reality
This paper describes a novel approach in engaging citizen communities based on serious gaming incorporating integration of the physical and digital worlds through aggregation of Internet of Things (IoT) service with Augmented Reality (AR) data visualization. The IoT service is provided by the ekoNET solution providing real-time monitoring of air quality and other atmospheric condition environmental data.…
Automatic modulation classification using S-transform based features
Automatic Modulation Classification plays a significant role in Cognitive Radio to identify the modulation format of the primary user. In this paper, we present the Stockwell transform (S-transform) based features extraction for classification of different digital modulation schemes using different classifiers such as Neural Network (NN), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), Naive Bayes (NB), k-Nearest Neighbor (k-NN).…
Energy Efficiency Maximization Framework in Cognitive Downlink Two-Tier Networks
To support the surge in wireless data traffic, the spectrum and energy efficiencies of cellular networksshould be largely increased. Heterogeneous two-tier architecture has been identified as one key solution. However, small-cell deployment raises questions about the resulting energy efficiency and interference mitigation. Therefore, we propose an energy-efficient and cognitive spectrum sharing scheme between primary macrocell and secondary small…
On the double threshold energy detection-based spectrum sensing over κ-μ fading channel
This paper presents the performance analysis of spectrum sensing systems based on double threshold energy detection over κ-μ fading channels, which represents the small-scale variations of the fading signal under both light-of-sight and multipath scenarios. Receiver Operation Characteristics (ROC) are obtained regarding the double threshold scheme and comparisons are performed against the traditional single threshold…
Unified approach for performance analysis of Cognitive Radio Spectrum Sensing over correlated multipath fading channels
In this work, we analyse the performance of Cognitive Radio Spectrum Sensing (CRSS) systems with multiple receiving antennas considering the effect of correlation among fading branches. Exact closed-form expressions for the average detection probabilities (P̅D) are derived employing Probability Density Functions (PDF) approach for n.i.i.d.-L number of diversity branches over Nakagami-m fading channels with Maximal Ratio Combining (MRC)…
Predictive Data Delivery to Mobile Users through Mobility Learning in Wireless Sensor Networks
We consider applications, such as indoor navigation, evacuation, or targeted advertising, where mobile users equipped with a smart-phone class device require access to sensor network data measured in their proximity. Specifically, we focus on efficient communication protocols between static sensors and users with changing location. Our main contribution is to predict a set of possible future paths…
Offshore low frequency AC transmission with back-to-back modular multilevel converter (MMC)
This paper evaluates the use of a back-to-back modular multilevel converter (B2B-MMC) in offshore low frequency (LF) AC transmission. The scheme is compared to two alternative transmission technologies: DC and 50Hz AC. The MMC topology is further compared to a cycloconverter. A high level design of a ±120kVdc, 250MW B2B-MMC system is described, with the…