Due to its paramount relevance in transport planning and logistics, road traffic forecasting has been a subject of active research within the engineering community for more than 40 years. In the beginning most approaches relied on autoregressive models and other analysis methods suited for time series data. More recently, the development of new technology, platforms and techniques for massive data processing under the Big Data umbrella, the availability of data from multiple sources fostered by the Open Data philosophy and an ever-growing need of decision makers for accurate traffic predictions have shifted the spotlight to data-driven procedures. This paper aims to summarize the efforts made to date in previous related surveys towards extracting the main comparing criteria and challenges in this field. A review of the latest technical achievements in this field is also provided, along with an insightful update of the main technical challenges that remain unsolved. The ultimate goal of this work is to set an updated, thorough, rigorous compilation of prior literature around traffic prediction models so as to motivate and guide future research on this vibrant field.

This paper provides a review of the second generation of terrestrial digital video broadcasting standard (DVB-T2). DVB-T2 is the evolution of DVB-T and, together with DVB-S2 and DVB-C2, inaugurated a new transition from the first-generation digital broadcasting systems, similar to the transition from analog-to-digital systems. In this paper, the most relevant features of DVB-T2 are explained in detail, along with their benefits and trade-offs. This paper also presents a comprehensive review of the laboratory and field trial results available so far. Especial emphasis is placed in the results of the measurements carried out to test the mobile reception and the novel technologies as multiple input single output and time frequency slicing.

The increasing scarcity in the available spectrum for wireless communication is one of the current bottlenecks impairing further deployment of services and coverage. The proper exploitation of white spaces in the radio spectrum requires fast, robust, and accurate methods for their detection. This paper proposes a new strategy to detect adaptively white spaces in the radio spectrum. Such strategy works in cognitive radio (CR) networks whose nodes perform spectrum sensing based on energy detection in a cooperative way or not. The main novelty of the proposal is the use of a cost-function that depends upon a single parameter which, by itself, contains the aggregate information about the presence or absence of primary users. The detection of white spaces based on this parameter is able to improve significantly the deflection coefficient associated with the detector, as compared to other state-of-the-art algorithms. In fact, simulation results show that the proposed algorithm outperforms by far other competing algorithms. For example, our proposal can yield a probability of miss-detection 20 times smaller than that of an optimal soft-combiner solution in a cooperative setup with a predefined probability of false alarm of 0.1.

Cloud transmission (Cloud Txn) is a flexible multilayer system that uses spectrum overlay technology to simultaneously deliver multiple program streams with different characteristics and robustness for different services (mobile TV, HDTV, and UHDTV) in one radio frequency channel. Cloud Txn is a multilayer transmission system like layered-division multiplexing. The transmitted signal is formed by superimposing a number of independent signals at desired power levels to form a multilayered signal. The signals of different layers can have different coding, bit rate, and robustness. The upper layer system parameters are chosen to provide very robust transmission that can be used for high-speed mobile broadcasting. The bit rate is traded for powerful coding and robustness so that the signal-to-noise ratio (SNR) threshold at the receiver is in the range of ${-}{2}$ to ${-}{\rm 3}~{\rm dB}$ . The top layer is designed to withstand combined noise, co-channel interference and multipath distortion power levels higher than the desired signal power. The lower-layer signal can be a DVB-T2 signal or another new system to deliver HDTV/UHDTV to fixed receivers. The system concept is open to technological advances that might come in the future: BICM/non uniform-QAM, rotated constellations, time frequency slicing or MIMO techniques can be implemented in the Cloud Txn lower (high data rate) layer. The system can have backward compatible future extensions, adding more lower layers for additional services without impact legacy services. This paper describes the performance of Cloud Txn broadcasting system.