This work develops new achievable rate regions for the two way wiretap channel. In our setup, Alice and Bob wish to exchange messages securely in the presence of a passive eavesdropper Eve. In the full-duplex scenario, our achievability argument relies on allowing the two users to jointly optimize their channel prefixing distributions, such that the new channel conditions are favorable compared to that of Eve. Random binning and private key sharing over the channel are then used to exploit the secrecy advantage available in the equivalent cascade channel and to distribute the available secrecy

It is feasible and safe to use unmanned aerial vehicle (UAV) as the data collection platform of the Internet of things (IoT). In order to save the energy loss of the platform and make the UAV perform the collection work effectively, it is necessary to optimize the deployment of UAV. The objective problem is to minimize the sum of the lost energy of UAV and the loss of data transmission of Internet of things devices. The key to solving the problem is to calculate the location of the docking points and the number of docking points when the UAV is working to collect data. This paper proposes a

This paper introduces a heuristic solver based on neural networks and deep learning for the knapsack problem. The solver is inspired by mechanisms and strategies used by both algorithmic solvers and humans. The neural model of the solver is based on introducing several biases in the architecture. We introduce a stored memory of vectors that holds up items representations and their relationship to the capacity of the knapsack and a module that allows the solver to access all the previous outputs it generated. The solver is trained and tested on synthetic datasets that represent a variety of

This article proposes a new problem which is called the Stochastic Travelling Advisor Problem (STAP) in network optimization, and it is defined for an advisory group who wants to choose a subset of candidate workplaces comprising the most profitable route within the time limit of day working hours. A nonlinear binary mathematical model is formulated and a real application case study in the occupational health and safety field is presented. The problem has a stochastic nature in travelling and advising times since the deterministic models are not appropriate for such real-life problems. The

In this paper, we investigate the performance of an ALOHA random access wireless network consisting of nodes with and without RF energy harvesting capability. We develop and analyze a Markov model for the system when nodes with RF energy harvesting capability are infinitely backlogged. Our results indicate that the network throughput is improved when the conventional nodes are underloaded. On the contrary, when all types of nodes have finite backlogs, we numerically demonstrate that the network throughput and delay are improved when the overall system is overloaded. We show that there exists a

In this paper we study the problem of tag identification in multi-reader RFID systems. In particular, we propose a novel solution to the reader-to-reader collisions and tag collisions in multi-reader systems, using the concept of bit tracking [1]. Towards this objective, we propose the multi-reader RFID tag identification using bit tracking (MRTI-BT) algorithm which allows concurrent tag identification, by neighboring RFID readers, as opposed to time-consuming scheduling. First, MRTI-BT identifies tags exclusive to different RFIDs, concurrently. Second, the concept of bit tracking and the

This paper develops a novel framework for sharing secret keys using the Automatic Repeat reQuest (ARQ) protocol. We first characterize the underlying information theoretic limits, under different assumptions on the channel spatial and temporal correlation function. Our analysis reveals a novel role of dumb antennas in overcoming the negative impact of spatial correlation on the achievable secrecy rates. We further develop an adaptive rate allocation policy, which achieves higher secrecy rates in temporally correlated channels, and explicit constructions for ARQ secrecy coding that enjoy low

Cognitive radio technology would enable a set of secondary users (SU) to opportunistically use the spectrum licensed to a primary user (PU). On the appearance of this PU on a specific frequency band, any SU occupying this band should free it for PUs. Typically, SUs may collaborate to reduce the impact of cognitive users on the primary network and to improve the performance of the SUs. In this paper, we propose and analyze the performance of virtual reservation in collaborative cognitive networks. Virtual reservation is a novel link maintenance strategy that aims to maximize the throughput of

In this paper, we exploit tools from stochastic geometry to characterize the average probability of successful content delivery in a cache-enabled device-to-device (D2D) network under Nakagami- m fading. Specifically, we focus on the impact of temporal interference correlation due to erroneous packets retransmissions. The aggregate network interference is characterized under a slotted Aloha scheme in a homogeneous Poisson field of static interferers. In addition, the effect of different system parameters, such as the content popularity, intensity of devices, and D2D communication range, on the

Organic photovoltaic research is continuing in order to improve the efficiency and stability of the products. Organic devices have recently demonstrated excellent efficiency, bringing them closer to the market. Understanding the relationship between the microscopic parameters of the device and the conditions under which it is prepared and operated is essential for improving performance at the device level. This review paper emphasizes the importance of the parameter extraction stage for organic solar cell investigations by offering various device models and extraction methodologies. In order