Modeling and Predictability Analysis on Channel Spectrum Status Over Heavy Wireless LAN Traffic Environment

Using the real wireless spectrum occupancy status in 2.4 and 5 GHz bands collected at a railway station as representative of a heavy wireless LAN (WLAN) traffic environment, this paper studies the modeling of durations of busy/idle (B/I) status and its predictability based on predictability theory. We first measure and model the channel status in the heavy traffic environment over almost all of the WLAN channels at 2.4 GHz and 5 GHz bands in a busy (rush hour) period and non-busy period. Then, using two selected channels at 2.4 GHz and 5 GHz bands, we analyze the upper bound (UB) and lower bound (LB) of predictability of the busy/idle durations based on predictability theory. The analysis shows that the LB predictability of durations can be easily increased by changing their probability distribution. Based on this property, we introduce the data categorization (DC) method. By categorizing the busy/idle durations into different streams, the proposed data categorization can improve the prediction performance of some streams with large LB predictability, even if it employs a simple low-complexity auto-regressive (AR) predictor

Performance analysis of energy detection algorithm in cognitive radio

Rapid growth of wireless applications and services has made it essential to address spectrum scarcity problem. if we were scan a portion of radio spectrum including revenue-rich urban areas, we find that some frequency bands in the spectrum are largely unoccupied most of the time, some other frequency bands are partially occupied and the remaining frequency bands are heavily used. This leads to a underutilization of radio spectrum, Cognitive radio (CR) technology attempts alleviate this problem through improved utilization of radio spectrum. Cognitive radio is a form of wireless communication in which a transceiver can intelligently detect which RF communication channels are in use and which are not, and instantly move into vacant channels while avoiding occupied ones. This optimizes the use of available radio-frequency (RF) spectrum while minimizing interference to other users. There two types of cognitive radio, full cognitive radio and spectrum-sensing cognitive radio. Full cognitive radio takes into account all parameters that a wireless node or network can be aware of. Spectrum-sensing cognitive radio is used to detect channels in the radio frequency spectrum. Spectrum sensing is a fundamental requirement in cognitive radio network. Many signal detection techniques can be used in spectrum sensing so as to enhance the detection probability. In this thesis we analyze the performance of energy detector spectrum sensing algorithm in cognitive radio. By increasing the some parameters, the performance of algorithm can be improved as shown in the simulation results. In cognitive radio systems, secondary users should determine correctly whether the primary user is absent or not in a certain spectrum within a short detection period. Spectrum detection schemes based on fixed threshold are sensitive to noise uncertainty, the energy detection based on dynamic threshold can improve the antagonism of noise uncertainty; get a good performance of detection while without increasing the computer complexity uncertainty and improves detection performance for schemes are sensitive to noise uncertainty in lower signal-to-noise and large noise uncertainty environments

A Holistic Investigation on Terahertz Propagation and Channel Modeling Toward Vertical Heterogeneous Networks

User-centric and low latency communications can be enabled not only by small cells but also through ubiquitous connectivity. Recently, the vertical heterogeneous network (V-HetNet) architecture is proposed to backhaul/fronthaul a large number of small cells. Like an orchestra, the V-HetNet is a polyphony of different communication ensembles, including geostationary orbit (GEO), and low-earth orbit (LEO) satellites (e.g., CubeSats), and networked flying platforms (NFPs) along with terrestrial communication links. In this study, we propose the Terahertz (THz) communications to enable the elements of V-HetNets to function in harmony. As THz links offer a large bandwidth, leading to ultra-high data rates, it is suitable for backhauling and fronthauling small cells. Furthermore, THz communications can support numerous applications from inter-satellite links to in-vivo nanonetworks. However, to savor this harmony, we need accurate channel models. In this paper, the insights obtained through our measurement campaigns are highlighted, to reveal the true potential of THz communications in V-HetNets.Comment: It has been accepted for the publication in IEEE Communications Magazin

A survey of measurement-based spectrum occupancy modeling for cognitive radios

Spectrum occupancy models are very useful in cognitive radio designs. They can be used to increase spectrum sensing accuracy for more reliable operation, to remove spectrum sensing for higher resource usage efficiency, or to select channels for better opportunistic access, among other applications. In this survey, various spectrum occupancy models from measurement campaigns taken around the world are investigated. These models extract different statistical properties of the spectrum occupancy from the measured data. In addition to these models, spectrum occupancy prediction is also discussed, where autoregressive and/or moving-average models are used to predict the channel status at future time instants. After comparing these different methods and models, several challenges are also summarized based on this survey