Combining Adaptive Coding and Modulation With Hierarchical Modulation in Satcom Systems

We investigate the design of a broadcast system in order to maximize throughput. This task is usually challenging due to channel variability. Forty years ago, Cover introduced and compared two schemes: time sharing and superposition coding. Even if the second scheme was proved to be optimal for some channels, modern satellite communications systems such as DVB-SH and DVB-S2 rely mainly on a time sharing strategy to optimize the throughput. They consider hierarchical modulation, a practical implementation of superposition coding, but only for unequal error protection or backward compatibility purposes. In this article, we propose to combine time sharing and hierarchical modulation together and show how this scheme can improve the performance in terms of available rate. We introduce a hierarchical 16-APSK to boost the performance of the DVB-S2 standard. We also evaluate various strategies to group the receivers in pairs when using hierarchical modulation. Finally, we show in a realistic case, based on DVB-S2, that the combined scheme can provide throughput gains greater than 10% compared to the best time sharing strategy

Quasi-optimal grouping for broadcast systems with hierarchical modulation

Recently, we proposed to combine time sharing with hierarchical modulation to increase the transmission rate of broadcast systems. Our proposal involves to group the receivers in pairs in order to transmit with hierarchical modulation. We introduced several grouping strategies but the optimal matching remained an open question. In this letter, we show that the optimal grouping is the solution of an assignment problem, for which efficient algorithms exist such as the Hungarian method. Based on this algorithm, we study the performance of the optimal grouping in terms of spectrum efficiency for a DVB-S2 system.Comment: Submitte

Performance Study of Layered Division Multiplexing Based on SDR Platform

[EN] Two of the main drawbacks of the current broadcasting services are, on the one hand, the lack of flexibility to adapt to the new generation systems requirements, and on the other hand, the incapability of taking a piece of the current mobile services market. In this paper, Layered Division Multiplexing (LDM), which grew out of the concept of Cloud Txn, is presented as a very promising technique for answering those challenges and enhancing the capacity of broadcasting systems. The major contribution of this work is to present the first comprehensive study of the LDM performance behavior. In particular, in this paper, the theoretical considerations of the LDM implementation are completed with the first computer based simulations and laboratory tests, covering a wide range of stationary channels and the mobile TU-6 channel. The results will support LDM as a strong candidate for multiplexing different services in the next generation broadcasting systems, increasing both flexibility and performance.This work has been financially supported in part by the University of the Basque Country UPV/EHU (UFI 11/30), by the Basque Government (IT-683-13 and SAIOTEK), by the Spanish Ministry of Science and Innovation under the project NG-RADIATE (TEC2009-14201), by the Spanish Ministry of Economy and Competitiveness under the project HEDYT-GBB (TEC2012-33302) and the European Regional Development Fund (ERDF)

64-APSK Constellation and Mapping Optimization for Satellite Broadcasting Using Genetic Algorithms

DVB-S2 and DVB-SH satellite broadcasting standards currently deploy 16- and 32-amplitude phase shift keying (APSK) modulation using the consultative committee for space data systems (CCSDS) mapping. Such standards also include hierarchical modulation as a mean to provide unequal error protection in highly variable channels over satellite. Foreseeing the increasing need for higher data rates, this paper tackles the optimization of 64-APSK constellations to minimize the mean square error between the original and received symbol. Optimization is performed according to the sensitivity of the data to the channel errors, by means of genetic algorithms, a well-known technique currently used in a variety of application domains, when close form solutions are impractical. Test results show that through non-uniform constellation and asymmetric symbol mapping, it is possible to significantly reduce the distortion while preserving bandwidth efficiency. Tests performed on real signals based on perceptual quality measurements allow validating the proposed scheme against conventional 64-APSK constellations and CCSDS mapping

Enable Reliable and Secure Data Transmission in Resource-Constrained Emerging Networks

The increasing deployment of wireless devices has connected humans and objects all around the world, benefiting our daily life and the entire society in many aspects. Achieving those connectivity motivates the emergence of different types of paradigms, such as cellular networks, large-scale Internet of Things (IoT), cognitive networks, etc. Among these networks, enabling reliable and secure data transmission requires various resources including spectrum, energy, and computational capability. However, these resources are usually limited in many scenarios, especially when the number of devices is considerably large, bringing catastrophic consequences to data transmission. For example, given the fact that most of IoT devices have limited computational abilities and inadequate security protocols, data transmission is vulnerable to various attacks such as eavesdropping and replay attacks, for which traditional security approaches are unable to address. On the other hand, in the cellular network, the ever-increasing data traffic has exacerbated the depletion of spectrum along with the energy consumption. As a result, mobile users experience significant congestion and delays when they request data from the cellular service provider, especially in many crowded areas. In this dissertation, we target on reliable and secure data transmission in resource-constrained emerging networks. The first two works investigate new security challenges in the current heterogeneous IoT environment, and then provide certain countermeasures for reliable data communication. To be specific, we identify a new physical-layer attack, the signal emulation attack, in the heterogeneous environment, such as smart home IoT. To defend against the attack, we propose two defense strategies with the help of a commonly found wireless device. In addition, to enable secure data transmission in large-scale IoT network, e.g., the industrial IoT, we apply the amply-and-forward cooperative communication to increase the secrecy capacity by incentivizing relay IoT devices. Besides security concerns in IoT network, we seek data traffic alleviation approaches to achieve reliable and energy-efficient data transmission for a group of users in the cellular network. The concept of mobile participation is introduced to assist data offloading from the base station to users in the group by leveraging the mobility of users and the social features among a group of users. Following with that, we deploy device-to-device data offloading within the group to achieve the energy efficiency at the user side while adapting to their increasing traffic demands. In the end, we consider a perpendicular topic - dynamic spectrum access (DSA) - to alleviate the spectrum scarcity issue in cognitive radio network, where the spectrum resource is limited to users. Specifically, we focus on the security concerns and further propose two physical-layer schemes to prevent spectrum misuse in DSA in both additive white Gaussian noise and fading environments