The next generation of Mission Critical Networks (MCNs) will likely be based on Long Term Evolution (LTE) technology. This is due to the many features LTE can offer such as reliable broadband communications and Proximity Services (ProSe). However, the environments where MCNs mostly work require irregular deployment of LTE. Such requirements can impose constraints on the Frequency Reuse (FR) algorithms and Medium Access Control (MAC) schedulers to be used. In this paper, we develop a high-level parameter selection framework to enable the testing of irregular deployments of LTE-based MCNs. The developed tool provides a Graphical User Interface (GUI) that can be easily used to change the system settings and the available resources in order to find the most suitable system parameters. The developed algorithm also considers minimizing the used spectrum and allows the end-user to select a Quality-of-Service (QoS) threshold to control the system performance. Results show that the proposed framework provides accurate recommendations on the needed resources, FR algorithms, and MAC schedulers to be used. Insights on the system performance and suggested deployment style are also provided.

A. Sabbah, A. Jarwan, L. Bonin, and M. Ibnkahla, “A High-Level Parameter Selection Framework for Irregular LTE-Based Mission Critical Networks,” in 2019 IEEE Wireless Communications and Networking Conference (WCNC), Apr. 2019, pp. 1–6. doi: 10.1109/WCNC.2019.8885413.

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Emerging technologies such as the Internet of Things (IoT) and their anticipated massive deployment stimulate the need for developing adaptive energy efficient modulation schemes to maximize network lifetime. IoT systems are typically comprised of limited energy heterogeneous devices in the sensing layer, imposing significant challenges in developing cross-layer schemes to solve the network lifetime problem. In this paper, we present a multi-objective adaptive modulation scheme for the physical layer of a heterogeneous IoT environment. We consider channel conditions to opportunistically maximize device prioritization, energy efficiency, and spectral efficiency. The problem is modeled as a Mixed Integer Linear Program (MILP) in GAMS and is solved by CPLEX under Rayleigh fading channel conditions. Performance evaluations show that considering device heterogeneity is crucial in order to exploit energy savings and spectral efficiency in IoT sensing nodes.

Y. Rafique, Z. Bouida, and M. Ibnkahla, “Optimized Channel-Aware Scheduling for Heterogeneous Internet of Things,” in 2019 IEEE Wireless Communications and Networking Conference (WCNC), Apr. 2019, pp. 1–6. doi: 10.1109/WCNC.2019.8885451.

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A. Jarwan, A. Sabbah, and M. Ibnkahla, “Data Transmission Reduction Schemes in WSNs for Efficient IoT Systems,” IEEE Journal on Selected Areas in Communications, vol. 37, no. 6, pp. 1307–1324, Jun. 2019, doi: 10.1109/JSAC.2019.2904357.

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The Internet of Things (IoT) has enabled unprecedented interactions with our physical world, with the aim to deliver a wide range of customizable services in many domains. With recent advancements in IoT technology, users are increasingly expecting these services to be intelligent and context aware. Nevertheless, there is still no framework capable of delivering personalized IoT services on a large scale. For such a framework to be conceived, it is likely that technologies from many domains have to be utilized. This paper examines the readiness of the leading state-of-the-art technologies in several key fields for realizing the goal of a truly scalable and personalized IoT experience. We discuss the important requirements and challenges for realizing this goal. Then, we identify the major approaches that can contribute to this goal and categorize them into: technologies for adaptive personalized sensing, scalable solutions for user-centric networking, and intelligence techniques that leverage context awareness and adaptability at the application and system levels. In the first category, our discussion centers around virtualization and reprogrammability at the sensing layer. In the second category, we investigate the readiness of Fog computing and information-centric networking to develop scalable personalized IoT infrastructures. These approaches were chosen for their combined ability to match dynamic user requirements with available system resources, while guaranteeing overall efficient utilization. Finally, in the third category, we examine context awareness, reasoning, and machine learning techniques as well as semantic technologies for realizing proactive and adaptive intelligent IoT systems and applications. This paper offers a focused discussion of the key topics that drive the research in the important and timely topic of scalable and personalized IoT networks.

A. El-Mougy, I. Al-Shiab, and M. Ibnkahla, “Scalable Personalized IoT Networks,” Proceedings of the IEEE, vol. 107, no. 4, pp. 695–710, Apr. 2019, doi: 10.1109/JPROC.2019.2894515.

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Public safety networks (PSNs) are very crucial for public protection and disaster relief (PPDR). Land mobile radio (LMR) technologies have been used extensively in the deployment of PSNs so far. LMR networks support sophisticated voice applications that can, to some extent, deal with the mission-critical nature of PPDR services. However, LMR networks lack technological advancements to support broadband (BB) applications. Due to this limitation, the attention is drawn to the long-term evolution (LTE) technology for public safety (PS) deployment as it has the potential to support various narrowband and BB applications and services. LTE-based PSNs should have strict requirements in terms of scalability, robustness, and resilience. In this survey, we will highlight the history of PSNs, including LMR and LTE-based PSNs, discuss the requirements that have to be inherited in PSNs, and examine the spectrum allocated for PS use. Moreover, we will study the architecture of LTE-based PSNs and provide deployment and migration solutions. Furthermore, voice delivery over LTE and LTE standardized solutions tailored to support PS services are discussed. Finally, rapid emergency deployment, spectrum management, priority management, and radio resource management schemes in LTE-based PSNs are discussed as well. At the end of the survey, we present PSNs simulation environment using network simulator and provide the results of multiple disaster scenarios.

A. Jarwan, A. Sabbah, M. Ibnkahla, and O. Issa, “LTE-Based Public Safety Networks: A Survey,” IEEE Communications Surveys Tutorials, vol. 21, no. 2, pp. 1165–1187, 2019, doi: 10.1109/COMST.2019.2895658.

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