Ultra-Reliable Cloud Mobile Computing with Service Composition and Superposition Coding

An emerging requirement for 5G systems is the ability to provide wireless ultra-reliable communication (URC) services with close-to-full availability for cloud-based applications. Among such applications, a prominent role is expected to be played by mobile cloud computing (MCC), that is, by the offloading of computationally intensive tasks from mobile devices to the cloud. MCC allows battery-limited devices to run sophisticated applications, such as for gaming or for the "tactile" internet. This paper proposes to apply the framework of reliable service composition to the problem of optimal task offloading in MCC over fading channels, with the aim of providing layered, or composable, services at differentiated reliability levels. Inter-layer optimization problems, encompassing offloading decisions and communication resources, are formulated and addressed by means of successive convex approximation methods. The numerical results demonstrate the energy savings that can be obtained by a joint allocation of computing and communication resources, as well as the advantages of layered coding at the physical layer and the impact of channel conditions on the offloading decisions.Comment: 8 pages, 5 figures, To be presented at CISS 201

Live Prefetching for Mobile Computation Offloading

The conventional designs of mobile computation offloading fetch user-specific data to the cloud prior to computing, called offline prefetching. However, this approach can potentially result in excessive fetching of large volumes of data and cause heavy loads on radio-access networks. To solve this problem, the novel technique of live prefetching is proposed in this paper that seamlessly integrates the task-level computation prediction and prefetching within the cloud-computing process of a large program with numerous tasks. The technique avoids excessive fetching but retains the feature of leveraging prediction to reduce the program runtime and mobile transmission energy. By modeling the tasks in an offloaded program as a stochastic sequence, stochastic optimization is applied to design fetching policies to minimize mobile energy consumption under a deadline constraint. The policies enable real-time control of the prefetched-data sizes of candidates for future tasks. For slow fading, the optimal policy is derived and shown to have a threshold-based structure, selecting candidate tasks for prefetching and controlling their prefetched data based on their likelihoods. The result is extended to design close-to-optimal prefetching policies to fast fading channels. Compared with fetching without prediction, live prefetching is shown theoretically to always achieve reduction on mobile energy consumption.Comment: To appear in IEEE Trans. on Wireless Communicatio

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Quantum Cryptography Beyond Quantum Key Distribution

Quantum cryptography is the art and science of exploiting quantum mechanical effects in order to perform cryptographic tasks. While the most well-known example of this discipline is quantum key distribution (QKD), there exist many other applications such as quantum money, randomness generation, secure two- and multi-party computation and delegated quantum computation. Quantum cryptography also studies the limitations and challenges resulting from quantum adversaries---including the impossibility of quantum bit commitment, the difficulty of quantum rewinding and the definition of quantum security models for classical primitives. In this review article, aimed primarily at cryptographers unfamiliar with the quantum world, we survey the area of theoretical quantum cryptography, with an emphasis on the constructions and limitations beyond the realm of QKD.Comment: 45 pages, over 245 reference

NOMA-based 802.11g/n: PHY analysis and MAC implementation

Industry 4.0 can be considered as the industrial revolution of the current century. Among others, one of its main objectives is the replacement of wired communications by wireless connectivity. The idea is to overcome the main drawbacks of the current wired ecosystem: the lack of mobility, the deployment costs, cable damage and the difficulties with scalability. However, for this purpose, the nature and requirements of the industrial applications must be taken into account, in particular, the proposed communications protocols must support very low loss rates and a strong robustness against failures. This is a very challenging condition due to the nature of the industrial environments (interference with other communication systems, reflections with metallic objects ...). In addition, another characteristic of the industrial applications is the strict requirement related to the latency. On the other hand, industrial applications are not only based on high challenging services, but also exist more flexible requirement applications, such as, web browser, email, video content or complementary information. Those services are considered Best Effort (BE) services. Eventually, in some wireless applications both critical and BE services have to be offered. For those cases, Non-Orthogonal Multiplexing Access (NOMA) technology together with the IEEE 802.11g/n standard is proposed in this document as the physical layer solution. The IEEE 802.11g/n standard has been modified in order to accommodate NOMA schemes, and then, comprehensive simulations are conducted to check and analyze the behavior of the proposed system. It has been determined that through NOMA technology it is possible to obtain better results in certain cases than those achieved in a transmission cases that implements the IEEE 802.11g/n standard in TDM/FDM basis

Reconfigurable Antenna Systems: Platform implementation and low-power matters

Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position