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Dynamic spectrum sharing (DSS) has recently attracted keen interest from regulatory bodies around the world as a key strategy to overcome spectrum scarcity in beyond 5G networks. In the United States, the Federal Communications Commission has adopted a three-tier DSS model for the Citizens Broadband Radio Service (CBRS) band managed by a spectrum access system (SAS) to share incumbents' spectrum with commercial cellular broadband applications. In this article, we first present a survey of current DSS approaches and their limitations and then discuss the benefits of using in-band full-duplex (IBFD) techniques in DSS networks. To illustrate the improvement in the performance of priority access license (PAL) and general authorized access (GAA) users in an IBFD-assisted CBRS, we consider a CBRS mobile broadband network (MBN) architecture comprising an incumbent in the form of a MIMO radar system and an IBFD MIMO MBN, consisting of PAL and GAA users. In particular, we design joint beamformers at the MBN, with constraints on transmit power at the MBN and detection probability of the radar system, and beamformers at the radar system to mitigate the interference from the radar system toward the cellular system. It is shown that the IBFD CBRS network architecture not only leads to improved performance of PAL and GAA users, but does so while producing less interference toward the radar than state-of-the-art half-duplex solutions. Finally, we present some open research challenges to invigorate research on beyond 5G IBFD DSS networks. [ABSTRACT FROM AUTHOR]

Currently, there is no robust method that could calibrate the accelerometer output without explicitly deriving the error model of the device and estimate the nonlinear parameters of the model. This article presents a methodology to approximate the output of two-axis thermal accelerometers based on neural networks (NNs) for calibration and nonlinear correction. This method uses the output of the accelerometer and the Earth’s gravitational acceleration expected at a static position as data for training. The proposed method uses different optimization methods (adaptive moment estimation (ADAM), gradient descent, and gradient descent with momentum) to find the best solution using half mean squared error (HMSE) as the cost functions for evaluation. Experiments are conducted and presented to validate the NN-based calibration method using 2800 unseen data points. [ABSTRACT FROM AUTHOR]

Spectrum sharing has been recognized as a key component for 5G and beyond wireless networks. Recent trials have revealed the business value of spectrum sharing via the licensed shared access model, wherein both the incumbent and the licensee operators are protected from harmful interference by sharing the available spectrum using long-term spectrum access agreements. Further increase in capacity gains can be achieved by exploiting dynamic spectrum access, where access is granted in shorter time intervals, and the Spectrum Access System, which is a more flexible version of traditional LSA. This article first hints at LSA-type spectrum sharing in regulatory and standards bodies, then proposes a few relevant scenarios that would take advantage of LSA, and finally presents an LSA system architecture and some enabling technologies for LSA/DSA/SAS. These include novel sensing, dynamic and radioaware resource allocation, and advanced cooperative communication techniques. [ABSTRACT FROM AUTHOR]

In this paper, we classify digits written in mid-air using hand gestures. Impulse radio ultrawideband (IR-UWB) radar sensors are used for data acquisition, with three radar sensors placed in a triangular geometry. Conventional radar-based gesture recognition methods use whole raw data matrices or a group of features for gesture classification using convolutional neural networks (CNNs) or other machine learning algorithms. However, if the training and testing data differ in distance, orientation, hand shape, hand size, or even gesture speed or the radar setup environment, these methods become less accurate. To develop a more robust gesture recognition method, we propose not using raw data for the CNN classifier, but instead employing the hand’s mid-air trajectory for classification. The hand trajectory has a stereotypical shape for a given digit, regardless of the hand’s orientation or speed, making its classification easy and robust. Our proposed method consists of three stages: signal preprocessing, hand motion localization, and tracking and transforming the trajectory data into an image to classify it using a CNN. Our proposed method outperforms conventional approaches because it is robust to changes in orientation, distance, and hand shape and size. Moreover, this method does not require building a huge training database of digits drawn by different users in different orientations; rather, we can use training databases already available in the image processing field. Overall, the proposed mid-air handwritten digit recognition system provides a user-friendly and accurate mid-air handwriting modality that does not place restrictions on users. [ABSTRACT FROM AUTHOR]

Currently, there is no robust method that could calibrate the accelerometer output without explicitly deriving the error model of the device and estimate the nonlinear parameters of the model. This article presents a methodology to approximate the output of two-axis thermal accelerometers based on neural networks (NNs) for calibration and nonlinear correction. This method uses the output of the accelerometer and the Earth’s gravitational acceleration expected at a static position as data for training. The proposed method uses different optimization methods (adaptive moment estimation (ADAM), gradient descent, and gradient descent with momentum) to find the best solution using half mean squared error (HMSE) as the cost functions for evaluation. Experiments are conducted and presented to validate the NN-based calibration method using 2800 unseen data points. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a full duplex (FD) multi-user non-orthogonal multiple access (NoMA) communication system based on the optimization of received signal-to-interference-plus-noise ratio (SINR) per unit power. Since the communication system operates in the FD mode, co-channel interference (CCI) and self-interference (SI) dominate the system’s performance. Accordingly, to combat the CCI, we adopt a game-theoretic approach and propose users’ clustering algorithms and to suppress the SI, we formulate an optimization problem to maximize the power-normalized SINR (PN-SINR). While the user clustering optimization problem is constrained by: 1) the successive interference cancellation (SIC) constraint and 2) two binary constraints for the allocations of uplink (UL) and downlink (DL) users, the PN-SINR problem is constrained by: 1) total transmit power budget at the base station and UL users; 2) the fundamental condition for the implementation of successive interference cancellation in the NoMA; and 3) the minimum fairness condition for the UL users. The original PN-SINR problem is non-convex and hence is converted into an equivalent subtractive-form problem, after which we propose an iterative algorithm to find the optimal power allocation policy. Properties of all the proposed algorithms are thoroughly investigated and the numerical results are provided. Based on the channel conditions and suppression level of SI and CCI, the superiority of the proposed FD-NoMA system over half-duplex NoMA and FD orthogonal multiple access systems is verified. [ABSTRACT FROM AUTHOR]

With the massive increase in wireless data traffic in recent years, multi-tier wireless networks have been deployed to provide much higher capacities and coverage. However, heterogeneity of wireless networks bring new challenges for interference analysis and coordination due to spatial randomly distributed transmitters. In this paper, we present a distance-dependent interference alignment (IA) approach for a generic two-tier heterogeneous wireless network, where transmitters in the first and second tiers are distributed as poisson point process (PPP) and poisson cluster process, respectively. The feasibility condition of the IA approach is used to find upper bound of the number of interference streams that can be aligned. The proposed IA scheme maximizes the second-tier throughput by using the tradeoff between signal-to-interference ratio and multiplexing gain. It is shown that acquiring accurate knowledge of the distance between the receiver in the second-tier and the nearest cross-tier transmitter only brings insignificant throughput gain compared with statistical knowledge of distance. Furthermore, the remaining cross-tier and intercluster interferences are modeled and analyzed using stochastic geometry technique. Numerical results validate the derived expressions of success probabilities and throughput, and show that the distance-dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the performance of an uplink large-scale multiple-input-multiple-output system with a single base station (BS) serving spatially distributed multiantenna user devices (UDs) within a fixed coverage area. Stochastic geometry is used to characterize the spatially distributed users while large dimensional random matrix theory is used to achieve deterministic approximations of the sum rate of the system. In particular, the users in the vicinity of the BS are considered to follow a Poisson point process within the fixed coverage area. The sum rate of this system is analyzed with respect to different number of antennas at the BS as well as the intensity of the users within the coverage area of the cell. Closed-form approximations for the deterministic rate at low and high signal-to-noise ratio regimes are derived that have very low computational complexity. The deterministic rate for a general $k$th ordered user is also derived. It is shown that the deterministic approximations offer a reliable estimate of the ergodic sum rate obtained by Monte Carlo simulations. We also briefly touch on the growing issue of power consumption in wireless systems by analyzing the energy efficiency of the system using a power consumption model, taking into consideration the circuit power consumption, which is a function of the number of antennas of the BS and UDs. [ABSTRACT FROM PUBLISHER]

This paper investigates the performance of cooperative spectrum sensing in cognitive radio networks using the stochastic geometry tools. In order to cope with the diversity of received signal-to-noise ratios at secondary users, a practical and efficient cooperative spectrum sensing model is proposed and investigated based on the generalized likelihood ratio test detector. In order to investigate the cooperative spectrum sensing system, the theoretical expressions of the probabilities of false alarm and detection of the local decision are derived. The optimal number of cooperating secondary users is then investigated to achieve the minimum total error rate of the final decision by assuming that the secondary users follow a homogeneous Poisson point process. Moreover, the theoretical expressions for the achievable ergodic capacity and throughput of the secondary network are derived. Furthermore, the technique of determining an appropriate number of cooperating secondary users is proposed in order to maximize the achievable ergodic capacity and throughput of the secondary network based on a target total error rate requirement. The analytical and simulation results validate the chosen optimal number of collaborating secondary users in terms of spectrum sensing, achievable ergodic capacity, and throughput of the secondary network. [ABSTRACT FROM PUBLISHER]

The article focuses on cloud radio access network (C-RAN) systems. Topics include various end-to-end solutions offered by C-RAN for issues including design of power-effective signals and cost-effective hardware for remote radio heads (RRHs), conception of an elastic and flexible architecture, and distribution and design of data and control traffic for coordinated communications. It discusses the development and effectiveness of the load-controlled parasitic antenna array (LCPAA) for C-RANs.

In this paper, we analyze the performance of a cloud radio access network (CRAN), consisting of multiple randomly distributed remote radio heads (RRHs) and a macro base station (MBS), each equipped with multiple antennas. To model the spatial distribution of RRHs and analyze its performance, we use stochastic geometry tools. In contrast to previous works on CRAN that consider Poisson Point Process (PPP) model for the spatial distribution of RRHs, we consider a more realistic Matérn hard-core point process (MHCPP) model that imposes a certain minimal distance (referred to as hard-core distance) between the two RRHs so that the RRHs are not too close to each other. To compare system performance of CRAN when different transmission strategies are used, three RRH selection schemes are adopted including 1) the best RRH selection (BRS); 2) all RRHs participation (ARP); and 3) nearest RRH selection (NRS). Considering downlink transmission, the ergodic capacity, outage probability, and system throughput of CRAN are analytically characterized for different RRH selection schemes. The presented results demonstrate that compared to PPP model, the increase in hard-core distance will result in a higher outage probability and cause a negative impact on ergodic capacity. Furthermore, when the same total transmit power is consumed, BRS scheme provides the best outage performance while ARP scheme is the best RRH selection scheme when the same transmit SNR at each RRH is assumed. Moreover, it is shown that the hard-core distance has a more significant impact on systems with higher intensity of PPP distributed candidate points and in large hard-core distance regime increasing the intensity of candidate points can only provide a small improvement in outage performance. We extend our work to multiuser case with zero-forcing (ZF) precoding where it is proven that the results in multiuser case reduce to the derived results in this work by substituting K=1 for single-user. [ABSTRACT FROM PUBLISHER]

The presence of Corrosive sulphur in mineral transformer oil affects the performance of insulation system of transformers. In this paper results of experimental investigations carried out on voltage current characteristics and insulation resistance of paper oil insulation in presence of copper sulphide are presented and discussed. A model for copper sulphide migration is proposed to explain the increase in leakage current and reduction in insulation resistance. Existence of two regions in voltagecurrent characteristics, one dependent on the insulation properties of paper oil insulation and other due to semi-conducting copper sulphide is discussed and explained. [ABSTRACT FROM AUTHOR]

We consider linear precoding in the downlink of a multiuser multiple-input–single-output (MISO) overlay cognitive radio (CR) network, wherein a primary base station (PBS) and a cognitive base station (CBS) share the same frequency band to transmit to a number of primary users (PUs) and secondary users. Conventionally, linear precoding techniques in a CR network aim to limit or completely cancel interference to the PUs while achieving maximum downlink throughput of the CR system. In this paper, we investigate novel adaptive linear precoding techniques at the CBS to exploit the interference to the primary and secondary systems, instead of its cancellation, by exploring the potential of making use of interference energy when the interference between the two systems is mutually constructive on an instantaneous basis. By doing so, the received signal-to-noise ratio (SNR) is enhanced by the signal energy gleaned from the constructive interference. In this direction, constructive-interference-based adaptive linear precoding techniques are proposed for the CR network, assuming a simple zero-forcing precoder at the PBS and noncausal knowledge of the primary message at the CBS. The presented analysis and simulations show that the proposed precoding techniques outperform conventional techniques, as the CR transmission actively enhances the performance of the PUs through constructive interference while achieving significant throughput for its own transmission. [ABSTRACT FROM PUBLISHER]