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Interference management and power transfer can provide a significant improvement over the 5th generation mobile networks (5G) dense Internet of Things (IoT) heterogeneous networks (HetNets). In this paper, we present a novel approach to simultaneously manage inferences at the downlink (DL) and uplink (UL), and to identify opportunities for power transfer and additional UL transmissions integrated with existing protocols and infrastructures for enhanced inter-cell interference coordination (eICIC) protocol in dense IoT HetNets, while considering practical non-linear energy harvesting (EH) model. The design is formulated as the joint optimization of interference aware UL/DL decoupling, airtime resource allocation and energy transfer. The key insight of our algorithm is to translate the original, intractable joint-optimization problem into a problem space where a good approximate solution can be quickly found. We evaluate our scheme through theoretical analysis and simulation. The evaluation shows that our approach improves the system utility by over 20% compared to start-of-the-art in dense IoT HetNets. Compared to alternative schemes, our approach maintains the best user fairness and rate experience and can solve the problem in a fast and scalable way. [ABSTRACT FROM AUTHOR]

As a powerful visualization tomography technique, electrical capacitance tomography (ECT) method, which reconstructs the permittivity distribution in a sensing domain according to the measured capacitance data, has been widely used in different industry scenarios. However, the image reconstruction in ECT is an ill-posed problem, and its application is plagued by low-quality reconstructions, and seeking for a robust algorithm to reduce reconstruction errors and artifacts is crucial. To increase the reconstruction quality, a novel cost function is built for imaging, in which the $L_{1-2}$ norm is designed as a regularizer for encoding the sparsity prior of imaging objects. The ant lion optimizer (ALO) algorithm and the alternating direction method of multipliers (ADMMs) with the Douglas–Rachford splitting (DRS) method and the soft thresholding algorithm as powerful optimizers for minimizing the subproblems are combined into a novel solver for solving the built cost function more effectively. Simulation and experimental results indicate that the proposed imaging technique can improve the quality of reconstructed images. [ABSTRACT FROM AUTHOR]

In a real wind farm, complex airflow conditions result in complexities of wind speed and direction, with possibly significant intermittency and fluctuations. This problem can be alleviated if the wind speed distribution over a wind farm is known in advance. In this article, a new method is proposed for real-time wind field reconstruction for large areas, based on the idea of a “virtual time”, i.e., a time span needed for an object to travel across a certain distance. The distribution of wind speed and direction can be acquired prior to its occurrence in the wind farm with refined spatial resolutions. A procedure is also developed to stabilize the solution process, and this stabilization leads to an optimal allocation of the wind speed sensors; this allocation is necessary for the efficient use of a limited number of sensors. The reconstruction algorithm has been substantially studied, and a mathematical quantity was correlated to the reconstruction error. This correlation enables us to obtain good reconstruction results by using the greedy algorithm we proposed in this study. Simulation and experimental results demonstrated the strong feasibility of successful reconstructions by our proposed algorithm. Moreover, the sensor optimization scheme not only reduces the error significantly but also improves the efficiency of sensor applications; this improvement should apply to a wide range of conditions. [ABSTRACT FROM AUTHOR]

Tag anticollision is critical to the performance of many radio frequency identification systems in industrial applications. Tree-based schemes are popular arbitration algorithms for tag collision, as they are scalable and easy to implement. In these schemes, collided tags are recursively divided into two groups until each group contains only one tag. However, we have determined that previous pure tree-based schemes do not fully utilize the information that can be collected; they allow only the responding tags to be involved in the splitting process. In this paper, we propose a novel pure tree-based method that we named parallel splitting with retrieve (PSR), which allows both the nonresponding and unidentified tags to also be involved in the splitting process. PSR consists of two mechanisms: parallel splitting (PS) and retrieve. The PS mechanism can reduce the total number of tag collisions and the retrieve mechanism can reduce the extra idle slots caused by PS. In comparison with conventional pure tree-based schemes, the proposed PSR algorithm achieves higher efficiency without the need to estimate the number of tags; simulation results indicate an efficiency level of 0.41. The PSR algorithm also has similar performance to state-of-the-art algorithms that do not need to estimate the number of tags, but it is simpler to implement and is thus preferred for resource constrained systems. [ABSTRACT FROM PUBLISHER]

In radio frequency identifications (RFIDs), an idle slot can be interrupted by the reader and takes less time than the other slots. In this case, the widely used binary splitting (BS) protocol is not optimal. M-ary splitting (M>2) with a carefully selected M outperforms BS, because it can take into account smaller duration of the idle slots. In this paper, we provide optimal value of M (Mopt) for varying slot sizes that yields minimum identification time. The proposed scheme is called optimal splitting (OS). We also revise OS to deal with mobile tags and propose the optimal splitting with arrival tags blocking (OS-ATB) protocol. Extensive simulations show that OS and OS-ATB consistently yield better performance than the other splitting and tree-based schemes. [ABSTRACT FROM PUBLISHER]

This work studies a cognitive radio (CR) communication system in which multiple antennas assist the secondary user to achieve transmission diversity, while the constraint of zero interference to the primary user is satisfied. We show that due to the zero interference constraint, the secondary link may occasionally suffer from low signal levels, as if it is in deep fading. Employing space time coding for diversity does not help this situation. We show that a beamformer that is mutually orthogonal in time domain across the antennas is effective in mitigating the low signal effects. Further, N antennas provide an equivalent (N-1) x 1 Rayleigh channel due to the function of this beamformer. The effect of a non-orthogonal beamformer is also analyzed and shown by simulations. [ABSTRACT FROM PUBLISHER]