367 research outputs found

    An efficient MAC protocol with adaptive energy harvesting for machine-to-machine networks

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    In a machine-to-machine network, the throughput performance plays a very important role. Recently, an attractive energy harvesting technology has shown great potential to the improvement of the network throughput, as it can provide consistent energy for wireless devices to transmit data. Motivated by that, an efficient energy harvesting-based medium access control (MAC) protocol is designed in this paper. In this protocol, different devices first harvest energy adaptively and then contend the transmission opportunities with energy level related priorities. Then, a new model is proposed to obtain the optimal throughput of the network, together with the corresponding hybrid differential evolution algorithm, where the involved variables are energy-harvesting time, contending time, and contending probability. Analytical and simulation results show that the network based on the proposed MAC protocol has greater throughput than that of the traditional methods. In addition, as expected, our scheme has less transmission delay, further enhancing its superiority

    Protocol-Level Simulations of Massive Medium Access for Machine-Type Communications

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    In recent years, Machine-Type Communications (MTC) has become one of the most attractive technologies in the area of wireless networking. Different sources are predicting a large grow of smart grid machine-to-machine deployments in several decades, which also means that the total number of wireless devices will increase dramatically. In connection to this problem, the choice of the standard, which will satisfy all the MTC requirements without harming current wireless deployments has become very relevant. Because of these reasons, many companies are proposing to modify one (or several) of the current wireless standard in a way that it will be possible to use for MTC purposes. This will be perfect from point of view of interference problems, because they will be already included in a standard itself. Third Generation Partnership Project (3GPP) Long Term Evolution-Advanced (LTE- A) is one of the most rapidly developing wireless technologies, that seems to be an ideal candidate for future MTC implementation. However, while the capacity of typical LTE-A network should be enough to satisfy traffic demands of large number of MTC devices, the signaling is not ready to face new requirements. In this Thesis, we are considering and partly solving problems, that could occur in LTE-A signaling channels under MTC conditions. Particularly, these are data access mechanisms, which could be realized via Physical Uplink Control Channel (PUCCH) and Physical Random Access Channel (PRACH). Speaking about assessment methods, the research made in this work is based on 2 approaches: simulation and analysis. Both of them are also in details described in the pages of this Thesis. As a conclusion it could be said that PUCCH channel is not suitable for the MTC data access, while PRACH is having problems only in heavily loaded (overloaded) cases and should be slightly modified to face them

    Modern Random Access for Satellite Communications

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    The present PhD dissertation focuses on modern random access (RA) techniques. In the first part an slot- and frame-asynchronous RA scheme adopting replicas, successive interference cancellation and combining techniques is presented and its performance analysed. The comparison of both slot-synchronous and asynchronous RA at higher layer, follows. Next, the optimization procedure, for slot-synchronous RA with irregular repetitions, is extended to the Rayleigh block fading channel. Finally, random access with multiple receivers is considered.Comment: PhD Thesis, 196 page

    Channel Access Management for Massive Cellular IoT Applications

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    As part of the steps taken towards improving the quality of life, many of everyday life activities as well as technological advancements are relying more and more on smart devices. In the future, it is expected that every electric device will be a smart device that can be connected to the internet. This gives rise to the new network paradigm known as the massive cellular IoT, where a large number of simple battery powered heterogeneous devices are collectively working for the betterment of humanity in all aspects. However, different from the traditional cellular based communication networks, IoT applications produce uplink-heavy data traffic that is composed of a large number of small data packets with different quality of service (QoS) requirements. These unique characteristics pose as a challenge to the current cellular channel access process and, hence, new and revolutionary access mechanisms are much needed. These access mechanisms need to be cost-effective, enable the support of massive number of devices, scalable, practical, and energy and radio resource efficient. Furthermore, due to the low computational capabilities of the devices, they cannot handle heavy networking intelligence and, thus, the designed channel access should be simple and light. Accordingly, in this research, we evaluate the suitability of the current channel access mechanism for massive applications and propose an energy efficient and resource preserving clustering and data aggregation solution. The proposed solution is tailored to the needs of future IoT applications. First, we recognize that for many anticipated cellular IoT applications, providing energy efficient and delay-aware access is crucial. However, in cellular networks, before devices transmit their data, they use a contention-based association protocol, known as random access channel procedure (RACH), which introduces extensive access delays and energy wastage as the number of contending devices increases. Modeling the performance of the RACH protocol is a challenging task due to the complexity of uplink transmission that exhibits a wide range of interference components; nonetheless, it is an essential process that helps determine the applicability of cellular IoT communication paradigm and shed light on the main challenges. Consequently, we develop a novel mathematical framework based on stochastic geometry to evaluate the RACH protocol and identify its limitations in the context of cellular IoT applications with a massive number of devices. To do so, we study the traditional cellular association process and establish a mathematical model for its association success probability. The model accounts for device density, spatial characteristics of the network, power control employed, and mutual interference among the devices. Our analysis and results highlight the shortcomings of the RACH protocol and give insights into the potentials brought on by employing power control techniques. Second, based on the analysis of the RACH procedure, we determine that, as the number of devices increases, the contention over the limited network radio resources increases, leading to network congestion. Accordingly, to avoid network congestion while supporting a large number of devices, we propose to use node clustering and data aggregation. As the number of supported devices increases and their QoS requirements become vast, optimizing node clustering and data aggregation processes becomes critical to be able to handle the many trade-offs that arise among different network performance metrics. Furthermore, for cost effectiveness, we propose that the data aggregator nodes be cellular devices and thus it is desirable to keep the number of aggregators to minimum such that we avoid congesting the RACH channel, while maximizing the number of successfully supported devices. Consequently, to tackle these issues, we explore the possibility of combining data aggregation and non-orthogonal multiple access (NOMA) where we propose a novel two-hop NOMA-enabled network architecture. Concepts from queuing theory and stochastic geometry are jointly exploited to derive mathematical expressions for different network performance metrics such as coverage probability, two-hop access delay, and the number of served devices per transmission frame. The established models characterize relations among various network metrics, and hence facilitate the design of two-stage transmission architecture. Numerical results demonstrate that the proposed solution improves the overall access delay and energy efficiency as compared to traditional OMA-based clustered networks. Last, we recognize that under the proposed two-hop network architecture, devices are subject to access point association decisions, i.e., to which access point a device associates plays a major role in determining the overall network performance and the perceived service by the devices. Accordingly, in the third part of the work, we consider the optimization of the two-hop network from the point of view of user association such that the number of QoS satisfied devices is maximized while minimizing the overall device energy consumption. We formulate the problem as a joint access point association, resources utilization, and energy efficient communication optimization problem that takes into account various networking factors such as the number of devices, number of data aggregators, number of available resource units, interference, transmission power limitation of the devices, aggregator transmission performance, and channel conditions. The objective is to show the usefulness of data aggregation and shed light on the importance of network design when the number of devices is massive. We propose a coalition game theory based algorithm, PAUSE, to transform the optimization problem into a simpler form that can be successfully solved in polynomial time. Different network scenarios are simulated to showcase the effectiveness of PAUSE and to draw observations on cost effective data aggregation enabled two-hop network design

    Novel Network Paradigms: Microfluidic and M2M Communications

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    The present thesis focuses on two appealing paradigms that are expected to characterize the next generation of communication systems: microfluidic networking and Machine to Machine (M2M) Communications. Concerning the former topic, we show how it is possible to introduce switching and routing mechanism in microfluidic systems. We define some simple mathematical models that capture the macroscopic behavior of droplets in microfluidic networks. Then, we use them to implement a simulator that is able to reproduce the motion and predict the path of droplets in a generic microfluidic system. We validate the simulator and apply it to design a network with bus topology. Finally, we prove the feasibility of attaining molecular communication in this domain by describing a simple protocol that exploits droplets length/interdistance modulation to send information. The research activity on M2M, instead, is aimed at the investigation of two critical issues that are expected to affect Machine-Type Communication (MTC), i.e. energy efficiency and massive access. Regarding energy efficiency, we address the problem of delivering a fixed data payload over a Rayleigh fading wireless channel with the purpose of minimizing the average total energy cost, given by the sum of the transmit energy and an overhead circuit energy, to complete it. This scenario is well suited for uplink cellular MTC in future 5G Internet of Things (IoT) use cases, where the focus is more on device energy efficiency than on throughput. We describe the optimal transmission policies to be used under various coordinated access scenarios with different levels of channel state information and transmitter/receiver capabilities, and show the corresponding theoretical bounds. In the last part of the work, we study the asymptotic performance of uncoordinated access schemes with Multi Packet Reception (MPR) and Successive Interference Cancellation (SIC) techniques for contention resolution at the receiver. The corresponding results in terms of throughput in a massive access M2M scenario are finally evaluated and discussed

    Internet of Things and Sensors Networks in 5G Wireless Communications

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    The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

    Licensed Shared Access Evolution to Provide Exclusive and Dynamic Shared Spectrum Access for Novel 5G Use Cases

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    This chapter studies the Licensed Shared Access (LSA) concept, which was initially developed to enable the use of the vacant spectrum resources in 2.3–2.4 GHz band for mobile broadband (MBB) through long-term static licenses. The LSA system was developed to guarantee LSA licensees a predictable quality of service (QoS) and exclusive access to shared spectrum resources. This chapter describes the development and architecture of LSA for 2.3–2.4 GHz band and compares the LSA briefly to the Spectrum Access System (SAS) concept developed in the USA. 5G and its new use cases require a more dynamic approach to access shared spectrum resources than the LSA system developed for 2.3–2.4 GHz band can provide. Thus, a concept called LSA evolution is currently under development. The novel concepts introduced in LSA evolution include spectrum sensing, short-term license periods, possibility to allocate spectrum locally, and support for co-primary sharing, which can guarantee the quality of service (QoS) from spectrum perspective. The chapter also describes a demonstration of LSA evolution system with spectrum user prioritization, which was created for Programme Making and Special Events (PMSE) use case
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