Multi-Cell, Multi-Channel Scheduling with Probabilistic Per-Packet Real-Time Guarantee

For mission-critical sensing and control applications such as those to be enabled by 5G Ultra-Reliable, Low-Latency Communications (URLLC), it is critical to ensure the communication quality of individual packets. Prior studies have considered Probabilistic Per-packet Real-time Communications (PPRC) guarantees for single-cell, single-channel networks with implicit deadline constraints, but they have not considered real-world complexities such as inter-cell interference and multiple communication channels. Towards ensuring PPRC in multi-cell, multi-channel wireless networks, we propose a real-time scheduling algorithm based on \emph{local-deadline-partition (LDP)}. The LDP algorithm is suitable for distributed implementation, and it ensures probabilistic per-packet real-time guarantee for multi-cell, multi-channel networks with general deadline constraints. We also address the associated challenge of the schedulability test of PPRC traffic. In particular, we propose the concept of \emph{feasible set} and identify a closed-form sufficient condition for the schedulability of PPRC traffic. We propose a distributed algorithm for the schedulability test, and the algorithm includes a procedure for finding the minimum sum work density of feasible sets which is of interest by itself. We also identify a necessary condition for the schedulability of PPRC traffic, and use numerical studies to understand a lower bound on the approximation ratio of the LDP algorithm. We experimentally study the properties of the LDP algorithm and observe that the PPRC traffic supportable by the LDP algorithm is significantly higher than that of a state-of-the-art algorithm

Performance Optimization in Wireless Local Area Networks

Wireless Local Area Networks (WLAN) are becoming more and more important for providing wireless broadband access. Applications and networking scenarios evolve continuously and in an unpredictable way, attracting the attention of academic institutions, research centers and industry. For designing an e cient WLAN is necessary to carefully plan coverage and to optimize the network design parameters, such as AP locations, channel assignment, power allocation, MAC protocol, routing algorithm, etc... In this thesis we approach performance optimization in WLAN at di erent layer of the OSI model. Our rst approach is at Network layer. Starting from a Hybrid System modeling the ow of tra c in the network, we propose a Hybrid Linear Varying Parameter algorithm for identifying the link quality that could be used as metric in routing algorithms. Go down to Data Link, it is well known that CSMA (Carrier Sense Multiple Access) protocols exhibit very poor performance in case of multi-hop transmissions, because of inter-link interference due to imperfect carrier sensing. We propose two novel algorithms, that are combining Time Division Multiple Access for grouping contending nodes in non-interfering sets with Carrier Sense Multiple Access for managing the channel access behind a set. In the rst solution, a game theoretical study of intra slot contention is introduced, in the second solution we apply an optimization algorithm to nd the optimal degree between contention and scheduling. Both the presented solutions improve the network performance with respect to CSMA and TDMA algorithms. Finally we analyze the network performance at Physical Layer. In case of WLAN, we can only use three orthogonal channels in an unlicensed spectrum, so the frequency assignments should be subject to frequent adjustments, according to the time-varying amount of interference which is not under the control of the provider. This problem make necessary the introduction of an automatic network planning solution, since a network administrator cannot continuously monitor and correct the interference conditions su ered in the network. We propose a novel protocol based on a distributed machine learning mechanism in which the nodes choose, automatically and autonomously in each time slot, the optimal channel for transmitting through a weighted combination of protocols

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

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

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors