An adaptive LTE listen-before-talk scheme towards a fair coexistence with Wi-Fi in unlicensed spectrum

The technological growth combined with the exponential increase of wireless traffic are pushing the wireless community to investigate solutions to maximally exploit the available spectrum. Among the proposed solutions, the operation of Long Term Evolution (LTE) in the unlicensed spectrum (LTE-U) has attracted significant attention. Recently, the 3rd Generation Partnership Project announced specifications that allow LTE to transmit in the unlicensed spectrum using a Listen Before Talk (LBT) procedure, respecting this way the regulator requirements worldwide. However, the proposed standards may cause coexistence issues between LTE and legacy Wi-Fi networks. In this article, it is discussed that a fair coexistence mechanism is needed to guarantee equal channel access opportunities for the co-located networks in a technology-agnostic way, taking into account potential traffic requirements. In order to enable harmonious coexistence and fair spectrum sharing among LTE-U and Wi-Fi, an adaptive LTE-U LBT scheme is presented. This scheme uses a variable LTE transmission opportunity (TXOP) followed by a variable muting period. This way, co-located Wi-Fi networks can exploit the muting period to gain access to the wireless medium. The scheme is studied and evaluated in different compelling scenarios using a simulation platform. The results show that by configuring the LTE-U with the appropriate TXOP and muting period values, the proposed scheme can significantly improve the coexistence among LTE-U and Wi-Fi in a fair manner. Finally, a preliminary algorithm is proposed on how the optimal configuration parameters can be selected towards harmonious and fair coexistence

Cooperation techniques between LTE in unlicensed spectrum and Wi-Fi towards fair spectral efficiency

On the road towards 5G, a proliferation of Heterogeneous Networks (HetNets) is expected. Sensor networks are of great importance in this new wireless era, as they allow interaction with the environment. Additionally, the establishment of the Internet of Things (IoT) has incredibly increased the number of interconnected devices and consequently the already massive wirelessly transmitted traffic. The exponential growth of wireless traffic is pushing the wireless community to investigate solutions that maximally exploit the available spectrum. Recently, 3rd Generation Partnership Project (3GPP) announced standards that permit the operation of Long Term Evolution (LTE) in the unlicensed spectrum in addition to the exclusive use of the licensed spectrum owned by a mobile operator. Alternatively, leading wireless technology developers examine standalone LTE operation in the unlicensed spectrum without any involvement of a mobile operator. In this article, we present a classification of different techniques that can be applied on co-located LTE and Wi-Fi networks. Up to today, Wi-Fi is the most widely-used wireless technology in the unlicensed spectrum. A review of the current state of the art further reveals the lack of cooperation schemes among co-located networks that can lead to more optimal usage of the available spectrum. This article fills this gap in the literature by conceptually describing different classes of cooperation between LTE and Wi-Fi. For each class, we provide a detailed presentation of possible cooperation techniques that can provide spectral efficiency in a fair manner

Without magic bullets: the biological basis for public health interventions against protein folding disorders

Protein folding disorders of aging like Alzheimer's and Parkinson's diseases currently present intractable medical challenges. 'Small molecule' interventions - drug treatments - often have, at best, palliative impact, failing to alter disease course. The design of individual or population level interventions will likely require a deeper understanding of protein folding and its regulation than currently provided by contemporary 'physics' or culture-bound medical magic bullet models. Here, a topological rate distortion analysis is applied to the problem of protein folding and regulation that is similar in spirit to Tlusty's (2010a) elegant exploration of the genetic code. The formalism produces large-scale, quasi-equilibrium 'resilience' states representing normal and pathological protein folding regulation under a cellular-level cognitive paradigm similar to that proposed by Atlan and Cohen (1998) for the immune system. Generalization to long times produces diffusion models of protein folding disorders in which epigenetic or life history factors determine the rate of onset of regulatory failure, in essence, a premature aging driven by familiar synergisms between disjunctions of resource allocation and need in the context of socially or physiologically toxic exposures and chronic powerlessness at individual and group scales. Application of an HPA axis model is made to recent observed differences in Alzheimer's onset rates in White and African American subpopulations as a function of an index of distress-proneness

A Q-learning scheme for fair coexistence between LTE and Wi-Fi in unlicensed spectrum

During the last years, the growth of wireless traffic pushed the wireless community to search for solutions that can assist in a more efficient management of the spectrum. Toward this direction, the operation of long term evolution (LTE) in unlicensed spectrum (LTE-U) has been proposed. Targeting a global solution that respects the regional regulations worldwide, 3GPP has published the LTE licensed assisted access (LAA) standard. According to LTE LAA, a listen before talk (LBT) procedure must precede any LTE transmission burst in the unlicensed spectrum. However, the proposed standard may cause coexistence issues between LTE and Wi-Fi, especially in the case that the latter does not use frame aggregation. Toward the provision of a balanced channel access, we have proposed mLTE-U that is an adaptive LTE LBT scheme. According to mLTE-U, LTE uses a variable transmission opportunity (TXOP), followed by a variable muting period. This muting period can be exploited by co-located Wi-Fi networks to gain access to the medium. In this paper, the system model of the mLTE-U scheme in coexistence with Wi-Fi is studied. In addition, mLTE-U is enhanced with a Q-learning technique that is used for autonomous selection of the appropriate combinations of TXOP and muting period that can provide fair coexistence between co-located mLTE-U and Wi-Fi networks. Simulation results showcase the performance of the proposed model and reveal the benefit of using Q-learning for self-adaptation of mLTE-U to the changes of the dynamic wireless environment, toward fair coexistence with Wi-Fi. Finally, the Q-learning mechanism is compared with conventional selection schemes showing the superior performance of the proposed model over less complex mechanisms

Fault-Tolerant Secure Data Aggregation Schemes in Smart Grids: Techniques, Design Challenges, and Future Trends

Secure data aggregation is an important process that enables a smart meter to perform efficiently and accurately. However, the fault tolerance and privacy of the user data are the most serious concerns in this process. While the security issues of Smart Grids are extensively studied, these two issues have been ignored so far. Therefore, in this paper, we present a comprehensive survey of fault-tolerant and differential privacy schemes for the Smart Gird. We selected papers from 2010 to 2021 and studied the schemes that are specifically related to fault tolerance and differential privacy. We divided all existing schemes based on the security properties, performance evaluation, and security attacks. We provide a comparative analysis for each scheme based on the cryptographic approach used. One of the drawbacks of existing surveys on the Smart Grid is that they have not discussed fault tolerance and differential privacy as a major area and consider them only as a part of privacy preservation schemes. On the basis of our work, we identified further research areas that can be explored

Planning & Acting: Optimal Markov Decision Scheduling of Aggregated Data in WSNs by Genetic Algorithm

Data aggregation techniques have emerged as promising solutions for extending Wireless Sensor Networks (WSNs) lifetime. However, this approach suffers from a design issue in delivering the strict requirements needed by some monitoring applications. Carefully balancing Energy, Delay and Accuracy is essential for achieving these requirements. In this work, we focus on distributed data aggregation, where a sensor estimates the network information by the exchange of readings with different priority levels. We then propose an optimal decision policy for scheduling the transmission of the aggregated data at the node level. To model the investigated problem, we first adopt Markov Decision Process (MDP) whereby we define the reward function. Then, we apply a Genetic Algorithm (GA) to find a set of optimal decisions that ensures the best trade-off between energy saving, delay and accuracy of the received data based on their priority level. The simulation results yield excellent performance and our optimization shows a significant enhancement up to 20% compared to the other policies

Analysis of Qos Aware Cloud Based Routing for Improved Security

The recent advances and the convergence of micro electro-mechanical systems technology, integrated circuit technologies, microprocessor hardware and Nano-technology, wireless communications, Ad-hoc networking routing protocols, distributed signal processing, and embedded systems have made the concept of Wireless Sensor Networks (WSNs). Sensor network nodes are limited with respect to energy supply, restricted computational capacity and communication bandwidth. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. To prolong the lifetime of the sensor nodes, designing efficient routing protocols is critical. Even though sensor networks are primarily designed for monitoring and reporting events, since they are application dependent, a single routing protocol cannot be efficient for sensor networks across all applications. In this paper, we analyze the design issues of sensor networks and present a classification and comparison of routing protocols. This comparison reveals the important features that need to be taken into consideration while designing and evaluating new routing protocols for sensor networks. A reliable transmission of packet data information, with low latency and high energy-efficiency, is truly essential for wireless sensor networks, employed in delay sensitive industrial control applications. The proper selection of the routing protocol to achieve maximum efficiency is a challenging task, since latency, reliability and energy consumption are inter-related with each other. It is observed that, Quality of Service (QoS) of the network can improve by minimizing delay in packet delivery, and life time of the network, can be extend by using suitable energy efficient routing protocol