Rachad Atat

Enabling cyber-physical communication in 5G cellular networks: challenges, spatial spectrum sensing, and cyber-security

Cyber-physical systems (CPS) help create new services and applications by revolutionising our world in different fields through their tight interactions and automated decisions. This is especially true with the ongoing increase in the number of physical things (sensors, actuators, smartphones, tablets, and so on) along with the explosive increase in the usage of online networking services and applications. Future fifth generation (5G) cellular networks will facilitate the enabling of CPS communications over current network infrastructure through different technologies such as device-to-device (D2D) communications. In this study, the authors discuss about the main challenges that cellular providers will face as the massive number of CPS devices attempt to access the cellular spectrum. A case study is presented on how to ease the spectrum access of these devices through D2D spatial spectrum sensing. Furthermore, the authors discuss about protecting these D2D links from eavesdropping, since security is becoming a critical aspect in the cyber-physical space, especially with the large amount of traffic that is constantly flowing through the network.

Energy Harvesting-Based D2D-Assisted Machine-Type Communications

Supporting massive numbers of machine-type communication (MTC) devices poses several challenges for future 5G networks, including network control, scheduling, and powering these devices. A potential solution is to offload MTC traffic onto device-to-device (D2D) communication links to better manage radio resources and reduce MTC devices’ energy consumption. However, this approach requires D2D users to use their own limited energy to relay MTC traffic, which may be undesirable. This motivates us to exploit recent advancements in RF energy harvesting for powering D2D relay transmissions. In this paper, we consider a D2D communication as an underlay to the cellular network, where D2D users access a fraction of the spectrum occupied by cellular users. This underlay model presents a fundamental trade-off: to protect cellular users, the spectrum available to D2D users needs to be reduced, which limits the number of D2D transmissions, but increases the amount of time that D2D users can spend harvesting energy to support MTC traffic. We study this trade-off by characterizing the spectral efficiency of MTC, D2D, and cellular users using stochastic geometry. The optimal spectrum partition factor is characterized to achieve fairness and balance in the network, while increasing the average MTC spectral efficiency.

Full length article: Mobile relays for enhanced broadband connectivity in high speed train systems

With the introduction of wireless modems and smart phones, the passenger transport industry is witnessing a high demand to ensure not only the safety of the trains, but also to provide users with Internet access all the time inside the train. When the Mobile Terminal (MT) communicates directly with the Base Station (BS), it will experience a severe degradation in the Quality of Service due to the path loss and shadowing effects as the wireless signal is traveling through the train. In this paper, we study the performance in the case of relays placed on top of each train car. In the proposed approach, these relays communicate with the cellular BS on one hand, and with the MTs inside the train cars on the other hand, using the Long Term Evolution (LTE) cellular technology. A low complexity heuristic LTE radio resource management approach is proposed and compared to the Hungarian algorithm, both in the presence and absence of the relays. The presence of the relays is shown to lead to significant enhancements in the effective data rates of the MTs. In addition, the proposed resource management approach is shown to reach a performance close to the optimal Hungarian algorithm.

Enabling Sustainable Cyber Physical Security Systems through Neuromorphic Computing

As the novel paradigm in the field of machine learning, reservoir computing possesses exceptional performance, e.g., energy efficiency, in tasks in which the traditional von Neumann computing systems cannot incorporate. This makes reservoir computing an ideal candidate to enable the sustainable development of cyber-physical systems (CPS). In the realm of CPS, the tight interaction among physical objects places security threats under the spotlight of attention. For such systems, especially the power grid network, false data injection could potentially lead to catastrophic consequences such as blackouts in large geographical areas. In this paper, we will introduce a reservoir computing architecture, the delayed feedback system, and apply the reservoir computing architecture for anomaly detection. To be specific, detailed design of the three imperative components in the delayed feedback system will be discussed and the corresponding energy efficiency performance will be analyzed. The application of the reservoir computing architecture to anomaly detection in a smart grid network will be introduced.

A Physical Layer Security Scheme for Mobile Health Cyber-Physical Systems

Mobile health (m-Health) is one potential application of cyber-physical systems, where biomedical sensors and mobile devices interact tightly together to transmit medical data to an m-Health server. In this paper, we consider a three-tier hierarchical m-Health system: 1) the sensor network tier capturing vital signals; 2) the mobile computing network tier processing and routing the sensed data to a fixed remote location; and 3) the back-end network tier processing and analyzing the sensed medical data along with patient’s medical history. Based on this architecture, a physical layer security scheme for the second tier is developed and network performance of the introduced scheme is analyzed under different metrics using stochastic geometry. To be specific, secure transmission range and average end-to-end delay are analyzed for two different strategies: the mobile device transmits: 1) to the nearest neighbor and 2) to the furthest neighbor. Furthermore, we consider the cases of full knowledge on eavesdroppers’ locations and when such information is unavailable. Results show that transmitting to the nearest neighbor achieves the highest secure transmission distance with the lowest mean delay when full information on eavesdroppers is available.

Performance Analysis on Nano-Networks: A Stochastic Geometry Approach

Pulse based communication scheme, e.g., On-OFF Keying modulation Spread in Time (TS-OOK), is currently the only solution for nano-networks. In this paper, we present an initial analysis on the performance of pulse based communication scheme in nano-networks using stochastic geometry. To be specific, by modeling the transmission of pulse as random events, we theoretically characterize the cumulative distribution function of signal-to-interference-plus-noise ratio and link throughput in nano-networks. Furthermore, both simulation and numerical results are presented to verify our analysis. Our results show that low-weight codes for TS-OOK can significantly increase the average throughput in dense nano-networks where the interference cannot be neglected.