Spectral and Energy Efficiency of Uplink D2D Underlaid Massive MIMO Cellular Networks

CCBY One of key 5G scenarios is that device-to-device (D2D) and massive multiple-input multiple-output (MIMO) will be co-existed. However, interference in the uplink D2D underlaid massive MIMO cellular networks needs to be coordinated, due to the vast cellular and D2D transmissions. To this end, this paper introduces a spatially dynamic power control solution for mitigating the cellular-to-D2D and D2D-to-cellular interference. In particular, the proposed D2D power control policy is rather flexible including the special cases of no D2D links or using maximum transmit power. Under the considered power control, an analytical approach is developed to evaluate the spectral efficiency (SE) and energy efficiency (EE) in such networks. Thus, the exact expressions of SE for a cellular user or D2D transmitter are derived, which quantify the impacts of key system parameters such as massive MIMO antennas and D2D density. Moreover, the D2D scale properties are obtained, which provide the sufficient conditions for achieving the anticipated SE. Numerical results corroborate our analysis and show that the proposed power control solution can efficiently mitigate interference between the cellular and D2D tier. The results demonstrate that there exists the optimal D2D density for maximizing the area SE of D2D tier. In addition, the achievable EE of a cellular user can be comparable to that of a D2D user

Questioning Classic Patient Classification Techniques in Gait Rehabilitation: Insights from Wearable Haptic Technology

Classifying stroke survivors based on their walking abilities is an important part of the gait rehabilitation process. It can act as powerful indicator of function and prognosis in both the early days after a stroke and long after a survivor receives rehabilitation. This classification often relies solely on walking speed; a quick and easy measure, with only a stopwatch needed. However, walking speed may not be the most accurate way of judging individual’s walking ability. Advances in technology mean we are now in a position where ubiquitous and wearable technologies can be used to elicit much richer measures to characterise gait. In this paper we present a case study from one of our studies, where within a homogenous group of stroke survivors (based on walking speed classification) important differences in individual results and the way they responded to rhythmic haptic cueing were identified during the piloting of a novel gait rehabilitation technique

An AUC-based Permutation Variable Importance Measure for Random Forests

The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html

Performance Optimization for Intelligent Reflecting Surface Assisted Multicast MIMO Networks

In this paper, the problem of maximizing the sum rate of all users in an intelligent reflecting surface (IRS)-assisted millimeter wave multicast multiple-input multiple-output communication system is studied. In the considered model, one IRS is deployed to assist the communication from a multi-antenna base station (BS) to the multi-antenna users that are clustered into several groups. Our goal is to maximize the sum rate of all users by jointly optimizing the transmit beamforming matrices of the BS, the receive beamforming matrices of the users, and the phase shifts of the IRS. To solve this non-convex problem, we first use a block diagonalization method to represent the beamforming matrices of the BS and the users by the phase shifts of the IRS. Then, substituting the expressions of the beamforming matrices of the BS and the users, the original sum-rate maximization problem can be transformed into a problem that only needs to optimize the phase shifts of the IRS. To solve the transformed problem, a manifold method is used. Simulation results show that the proposed scheme can achieve up to 13.3 % gain in terms of the sum rate of all users compared to the algorithm that optimizes the hybrid beamforming matrices of the BS and the users using our proposed scheme and randomly determines the phase shifts of the IRS

Beamforming Design for the Performance Optimization of Intelligent Reflecting Surface Assisted Multicast MIMO Networks

In this paper, the problem of maximizing the sum of data rates of all users in an intelligent reflecting surface (IRS)-assisted millimeter wave multicast multiple-input multiple-output communication system is studied. In the considered model, one IRS is deployed to assist the communication from a multi-antenna base station (BS) to the multi-antenna users that are clustered into several groups. Our goal is to maximize the sum rate of all users by jointly optimizing the transmit beamforming matrices of the BS, the receive beamforming matrices of the users, and the phase shifts of the IRS. To solve this non-convex problem, we first use a block diagonalization method to represent the beamforming matrices of the BS and the users by the phase shifts of the IRS. Then, substituting the expressions of the beamforming matrices of the BS and the users, the original sum-rate maximization problem can be transformed into a problem that only needs to optimize the phase shifts of the IRS. To solve the transformed problem, a manifold method is used. Simulation results show that the proposed scheme can achieve up to 28.6% gain in terms of the sum rate of all users compared to the algorithm that optimizes the hybrid beamforming matrices of the BS and the users using our proposed scheme and randomly determines the phase shifts of the IRS

Joint Deployment and Resource Management for VLC-enabled RISs-assisted UAV Networks

In this paper, the problem of the deployment and resource management for visible light communication (VLC)-enabled, reconfigurable intelligent surfaces (RISs)-assisted unmanned aerial vehicle (UAV) networks is investigated. In the considered model, UAVs provide terrestrial users with wireless services and illumination simultaneously. Moreover, RISs are utilized to further improve the channel quality between UAVs and users. This joint placement and resource management problem is constructed aiming at acquiring the optimal UAV deployment, RISs phase shift, user and RIS association that satisfies the users’ needs with minimum consumption of the UAVs’ energy. An iterative algorithm that alternately optimizes continuous and binary variables is proposed to solve this mixed-integer programming problem. Specifically, RISs phase shift optimization is solved by phases alignment method and semidefinite program algorithm. Next, the successive convex approximation algorithm is proposed to settle the UAV deployment problem. The user and RIS association variables are relaxed to the continuous ones before adopting the dual method to find the optimal solution. Moreover, a greedy algorithm is proposed as an alternative to RIS association optimization with low complexity. Simulation results show that the proposed two schemes harvest the superior performance of 34.85% and 32.11% energy consumption reduction over the case without RIS, respectively

Reconfigurable Intelligent Surface Assisted MEC Offloading in NOMA-Enabled IoT Networks

Integrating mobile edge computing (MEC) into the Internet of Things (IoT) enables resource-limited mobile terminals to offload part or all of the computation-intensive applications to nearby edge servers. On the other hand, by introducing reconfigurable intelligent surface (RIS), it can enhance the offloading capability of MEC, such that enabling low latency and high throughput. To enhance the task offloading, we investigate the MEC non-orthogonal multiple access (MEC-NOMA) network framework for mobile edge computation offloading with the assistance of a RIS. Different from conventional communication systems, we aim at allowing multiple IoT devices to share the same channel in tasks offloading process. Specifically, the joint consideration of channel assignments, beamwidth allocation, offloading rate and power control is formulated as a multi-objective optimization problem (MOP), which includes minimizing the offloading delay of computing-oriented IoT devices (CP-IDs) and maximizing the transmission rate of communication-oriented IoT devices (CM-IDs). Since the resulting problem is non-convex, we employ ϵ-constraint approach to transform the MOP into the single-objective optimization problems (SOP), and then the RIS-assisted channel assignment algorithm is developed to tackle the fractional objective function. Simulation results corroborate the benefits of our strategy, which can outperforms the other benchmark schemes

Effectiveness of additional follow-up telephone counseling in a smoking cessation clinic in Beijing and predictors of quitting among Chinese male smokers

published_or_final_versio

Low Resistance Polycrystalline Diamond Thin Films Deposited by Hot Filament Chemical Vapour Deposition

Polycrystalline diamond thin films with outgrowing diamond (OGD) grains were deposited onto silicon wafers using a hydrocarbon gas (CH4) highly diluted with H2 at low pressure in a hot filament chemical vapour deposition (HFCVD) reactor with a range of gas flow rates. X-ray diffraction (XRD) and SEM showed polycrystalline diamond structure with a random orientation. Polycrystalline diamond films with various textures were grown and (111) facets were dominant with sharp grain boundaries. Outgrowth was observed in flowerish character at high gas flow rates. Isolated single crystals with little openings appeared at various stages at low gas flow rates. Thus, changing gas flow rates had a beneficial influence on the grain size, growth rate and electrical resistivity. CVD diamond films gave an excellent performance for medium film thickness with relatively low electrical resistivity and making them potentially useful in many industrial applications

Factors Influencing Households’ Intention to Adopt Solar PV : A Systematic Review

Rising energy needs, concerns of energy security, mitigating greenhouse gas emissions, climate change phenomenon and a push to utilize indigenous sources for energy generation purposes has encouraged the use of solar photovoltaics (PV). The technological advancements of the recent past, improvement in technologies’ performance, reduction in the prices, policy and regulatory support, and its applicability at household level has made solar energy as a preferred form of energy generation. However, despite its rapid diffusion, it is widely believed that its current application is insignificant compared to its potential. This leads us to ask why solar PV has not been adopted to the level it should have. The existing literature has highlighted a number of factors affecting solar PV adoption. This paper systematically reviews the literature to identify the factors that have been instrumental to solar PV adoption. By exploring the Scopus database, this research identifies 39 articles matching the study objectives. Findings of this research will help academics, technology companies and policymakers in understanding the factors influencing the process and proposing solutions to address these.©2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Human Factors, Business Management and Leadership. AHFE 2020. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-50791-6_36fi=vertaisarvioitu|en=peerReviewed