The Application of Power-Domain Non-Orthogonal Multiple Access in Satellite Communication Networks

in IEEE Access (2019), 7

Satellite communication networks are expected to be indispensable as part of an integrated complement for the upcoming 5G networks since they can provide the most comprehensive coverage and reliable ... [more ▼]

Satellite communication networks are expected to be indispensable as part of an integrated complement for the upcoming 5G networks since they can provide the most comprehensive coverage and reliable connection for areas where are economically unviable and/or difficult to deploy terrestrial infrastructures. Meanwhile, the power-domain non-orthogonal multiple access (NOMA), which can serve multiple users simultaneously within the same time/frequency block, has been viewed as another promising strategy used in the 5G network to provide high spectral efficiency and resource utilization. In this paper, we introduce a general overview of the application of the NOMA to various satellite architectures for the benefits of meeting the availability, coverage, and efficiency requirements targeted by the 5G. The fundamental and ubiquitous features of satellite link budget are first reviewed. Then, the advantage and benefit of introducing the NOMA scheme in various satellite architectures, such as conventional downlink/uplink satellite networks, cognitive satellite terrestrial networks, and cooperative satellite networks with satellite/terrestrial relays, are provided, along with the motivation and research methodology for each scenario. Finally, this paper reviews the potential directions for future research. [less ▲]

A Bayesian Poisson–Gaussian Process Model for Popularity Learning in Edge-Caching Networks

in IEEE Access (2019)

Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing

in IEEE Access (2019), 7

Wearable devices have become essential in our daily activities. Due to battery constrains the use of computing, communication, and storage resources is limited. Mobile Cloud Computing (MCC) and the ... [more ▼]

Wearable devices have become essential in our daily activities. Due to battery constrains the use of computing, communication, and storage resources is limited. Mobile Cloud Computing (MCC) and the recently emerged Fog Computing (FC) paradigms unleash unprecedented opportunities to augment capabilities of wearables devices. Partitioning mobile applications and offloading computationally heavy tasks for execution to the cloud or edge of the network is the key. Offloading prolongs lifetime of the batteries and allows wearable devices to gain access to the rich and powerful set of computing and storage resources of the cloud/edge. In this paper, we experimentally evaluate and discuss rationale of application partitioning for MCC and FC. To experiment, we develop an Android-based application and benchmark energy and execution time performance of multiple partitioning scenarios. The results unveil architectural trade-offs that exist between the paradigms and devise guidelines for proper power management of service-centric Internet of Things (IoT) applications. [less ▲]

An Uplink UE Group-Based Scheduling Technique for 5G mMTC Systems Over LEO Satellite

in IEEE Access (2019)

Narrowband Internet of Things (NB-IoT) is one of the most promising IoT technology to support the massive machine-type communication (mMTC) scenarios of the fifth generation mobile communication (5G ... [more ▼]

Narrowband Internet of Things (NB-IoT) is one of the most promising IoT technology to support the massive machine-type communication (mMTC) scenarios of the fifth generation mobile communication (5G). While the aim of this technology is to provide global coverage to the low-cost IoT devices distributed all over the globe, the vital role of satellites to complement and extend the terrestrial IoT network in remote or under-served areas has been recognized. In the context of having the global IoT networks, low earth (LEO) orbits would be beneficial due to their smaller propagation signal loss, which for the low complexity, low power, and cheap IoT devices is of utmost importance to close the link-budget. However, while this would lessen the problem of large delay and signal loss in the geostationary (GEO) orbit, it would come up with increased Doppler effects. In this paper, we propose an uplink scheduling technique for a LEO satellite-based mMTC NB-IoT system, able to mitigate the level of the differential Doppler down to a value tolerable by the IoT devices. The performance of the proposed strategy is validated through numerical simulations and the achievable data rates of the considered scenario are shown, in order to emphasize the limitations of such systems coming from the presence of a satellite channel. [less ▲]

SDR Implementation of a Testbed for Real-Time Interference Detection with Signal Cancellation

in IEEE Access (2018)

Interference greatly affects the quality of service of wireless and satellite communications, having also a financial impact for the telecommunication operators. Therefore, as the interfering events ... [more ▼]

Interference greatly affects the quality of service of wireless and satellite communications, having also a financial impact for the telecommunication operators. Therefore, as the interfering events increase due to the deployment of new services, there is an increasing demand for the detection and mitigation of interference. There are several interference detectors in the literature, evaluated by using extensive simulations. However, this paper goes one step further, designing, implementing and evaluating the performance of the developed interference detection algorithms experimentally using a software defined radio, and particularly the universal software radio peripheral platform. A realistic communication system is implemented, consisting of a transmitter, a channel emulator and a receiver. Based on this system, we implement all the appropriate communications features such as pulse shaping, synchronization and demodulation. The real-time system implementation is validated and evaluated through signal and interference detection. We observe that the interference detection threshold is critical to the functioning of the system. Several existing interference detection techniques fail in practice due to this fact. In this paper, we propose a robust and practically implementable method the selection of threshold. Finally, we present real-time experimental results for the probabilities of false alarm and detection in order to verify the accuracy of our study and reinforce our theoretical analysis. [less ▲]

End-to-End Network Slicing in Virtualized OFDMA-Based Cloud Radio Access Networks

in IEEE Access (2017), 5

We consider the resource allocation for the virtualized OFDMA uplink cloud radio access network (C-RAN), where multiple wireless operators (OPs) share the C-RAN infrastructure and resources owned by an ... [more ▼]

We consider the resource allocation for the virtualized OFDMA uplink cloud radio access network (C-RAN), where multiple wireless operators (OPs) share the C-RAN infrastructure and resources owned by an infrastructure provider (InP). The resource allocation is designed through studying tightly coupled problems at two different levels. The upper-level problem aims at slicing the fronthaul capacity and cloud computing resources for all OPs to maximize the weighted profits of OPs and InP considering practical constraints on the fronthaul capacity and cloud computation resources. Moreover, the lower-level problems maximize individual OPs' sum rates by optimizing users' transmission rates and quantization bit allocation for the compressed I/Q baseband signals. We develop a two-stage algorithmic framework to address this two-level resource allocation design. In the first stage, we transform both upper-level and lowerlevel problems into corresponding problems by relaxing underlying discrete variables to the continuous ones. We show that these relaxed problems are convex and we develop fast algorithms to attain their optimal solutions. In the second stage, we propose two methods to round the optimal solution of the relaxed problems and achieve a final feasible solution for the original problem. Numerical studies confirm that the proposed algorithms outperform two greedy resource allocation algorithms and their achieved sum rates are very close to sum rate upper-bound obtained by solving relaxed problems. Moreover, we study the impacts of different parameters on the system sum rate, performance tradeoffs, and illustrate insights on a potential system operating point and resource provisioning issues. [less ▲]

Live Data Analytics with Collaborative Edge and Cloud Processing in Wireless IoT Network

in IEEE Access (2017)

Recently, big data analytics has received important attention in a variety of application domains including business, finance, space science, healthcare, telecommunication and Internet of Things (IoT ... [more ▼]

Recently, big data analytics has received important attention in a variety of application domains including business, finance, space science, healthcare, telecommunication and Internet of Things (IoT). Among these areas, IoT is considered as an important platform in bringing people, processes, data and things/objects together in order to enhance the quality of our everyday lives. However, the key challenges are how to effectively extract useful features from the massive amount of heterogeneous data generated by resource-constrained IoT devices in order to provide real-time information and feedback to the endusers, and how to utilize this data-aware intelligence in enhancing the performance of wireless IoT networks. Although there are parallel advances in cloud computing and edge computing for addressing some issues in data analytics, they have their own benefits and limitations. The convergence of these two computing paradigms, i.e., massive virtually shared pool of computing and storage resources from the cloud and real-time data processing by edge computing, could effectively enable live data analytics in wireless IoT networks. In this regard, we propose a novel framework for coordinated processing between edge and cloud computing/processing by integrating advantages from both the platforms. The proposed framework can exploit the network-wide knowledge and historical information available at the cloud center to guide edge computing units towards satisfying various performance requirements of heterogeneous wireless IoT networks. Starting with the main features, key enablers and the challenges of big data analytics, we provide various synergies and distinctions between cloud and edge processing. More importantly, we identify and describe the potential key enablers for the proposed edge-cloud collaborative framework, the associated key challenges and some interesting future research directions. [less ▲]

CrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments

in IEEE Access (2017)

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the ... [more ▼]

Smart cities take advantage of recent ICT developments to provide added value to existing public services and improve quality of life for the citizens. The Internet of Things (IoT) paradigm makes the Internet more pervasive where objects equipped with computing, storage and sensing capabilities are interconnected with communication technologies. Because of the widespread diffusion of IoT devices, applying the IoT paradigm to smart cities is an excellent solution to build sustainable Information and Communication Technology (ICT) platforms. Having citizens involved in the process through mobile crowdsensing (MCS) techniques augments capabilities of these ICT platforms without additional costs. For proper operation, MCS systems require the contribution from a large number of participants. Simulations are therefore a candidate tool to assess the performance of MCS systems. In this paper, we illustrate the design of CrowdSenSim, a simulator for mobile crowdsensing. CrowdSenSim is designed specifically for realistic urban environments and smart cities services. We demonstrate the effectiveness of CrowdSenSim for the most popular MCS sensing paradigms (participatory and opportunistic) and we present its applicability using a smart public street lighting scenario. [less ▲]

Resource allocation optimization in multi-user multi-cell massive MIMO networks considering pilot contamination

in IEEE Access (2015), 3

In this paper, we study the joint pilot assignment and resource allocation for system energy efficiency (SEE) maximization in the multi-user and multi-cell massive multi-input multi-output network. We ... [more ▼]

In this paper, we study the joint pilot assignment and resource allocation for system energy efficiency (SEE) maximization in the multi-user and multi-cell massive multi-input multi-output network. We explicitly consider the pilot contamination effect during the channel estimation in the SEE maximization problem, which aims to optimize the power allocation, the number of activated antennas, and the pilot assignment. To tackle the SEE maximization problem, we transform it into a subtractive form, which can be solved more efficiently. In particular, we develop an iterative algorithm to solve the transformed problem where optimization of power allocation and number of antennas is performed, and then pilot assignment optimization is conducted sequentially in each iteration. To tackle the first sub-problem, we employ a successive convex approximation (SCA) technique to attain a solvable convex optimization problem. Moreover, we propose a novel iterative low-complexity algorithm based on the Hungarian method to solve the pilot assignment sub-problem. We also describe how the proposed solution approach can be useful to address the sum rate (SR) maximization problem. In addition to the algorithmic developments, we characterize the optimal structure of both SEE and SR maximization problems. The numerical studies are conducted to illustrate the convergence of the proposed algorithms, impacts of different parameters on the SR and SEE, and significant performance gains of the proposed solution compared the conventional design. [less ▲]