Fundamental Limits of Low-Density Spreading NOMA with Fading

Spectral efficiency of low-density spreading non-orthogonal multiple access channels in the presence of fading is derived for linear detection with independent decoding as well as optimum decoding. The large system limit, where both the number of users and number of signal dimensions grow with fixed ratio, called load, is considered. In the case of optimum decoding, it is found that low-density spreading underperforms dense spreading for all loads. Conversely, linear detection is characterized by different behaviors in the underloaded vs. overloaded regimes. In particular, it is shown that spectral efficiency changes smoothly as load increases. However, in the overloaded regime, the spectral efficiency of low- density spreading is higher than that of dense spreading

Energy Efficiency of Distributed Signal Processing in Wireless Networks: A Cross-Layer Analysis

In order to meet the growing mobile data demand, future wireless networks will be equipped with a mulitude of access points (APs). Besides the important implications for the energy consumption, the trend towards densification requires the development of decentralized and sustainable radio resource management techniques. It is critically important to understand how the distribution of signal processing operations affects the energy efficiency of wireless networks. In this paper, we provide a cross-layer framework to evaluate and compare the energy efficiency of wireless networks under different levels of distribution of the signal processing load: 1) hybrid, where the signal processing operations are shared between nodes and APs; 2) centralized, where signal processing is entirely implemented at the APs; and 3) fully distributed, where all operations are performed by the nodes. We find that in practical wireless networks, hybrid signal processing exhibits a significant energy efficiency gain over both centralized and fully distributed approaches

PV cell angle optimization for energy generation-consumption matching in a solar powered cellular network

An inherent problem of solar-energy-powered-smallcell base stations (SBSs) is that the energy generation of the photovoltaic (PV) cell does not match the energy consumption of the SBS in time. In this paper, we propose to optimize the PV cell orientation angle to achieve a good match between the energy generation and consumption profiles on a daily time scale. The optimization is formulated as an integer linear programming problem. We also derive an expression for the correlation between the energy generation and consumption profiles to evaluate their general interaction independent of the exact PV cell or SBS deployment setup. The numerical evaluation of the proposed angle optimization in a business area in London in summer/winter shows that the optimal PV cell orientation in summer contradicts the conventional assumption of south facing being optimal in the northern hemisphere. Instead, a southwest orientation should be chosen in summer due to its ability to shift the energy generation peak towards the energy consumption peak in the afternoon at a SBS in central London. This is in accordance with the prediction given by our derived correlation between the solar energy generation and consumption profiles

Coordinated Container Migration and Base Station Handover in Mobile Edge Computing

Offloading computationally intensive tasks from mobile users (MUs) to a virtualized environment such as containers on a nearby edge server, can significantly reduce processing time and hence end-to-end (E2E) delay. However, when users are mobile, such containers need to be migrated to other edge servers located closer to the MUs to keep the E2E delay low. Meanwhile, the mobility of MUs necessitates handover among base stations in order to keep the wireless connections between MUs and base stations uninterrupted. In this paper, we address the joint problem of container migration and base-station handover by proposing a coordinated migration-handover mechanism, with the objective of achieving low E2E delay and minimizing service interruption. The mechanism determines the optimal destinations and time for migration and handover in a coordinated manner, along with a delta checkpoint technique that we propose. We implement a testbed edge computing system with our proposed coordinated migration-handover mechanism, and evaluate the performance using real-world applications implemented with Docker container (an industry-standard). The results demonstrate that our mechanism achieves 30%-40% lower service downtime and 13%-22% lower E2E delay as compared to other mechanisms. Our work is instrumental in offering smooth user experience in mobile edge computing.Comment: 6 pages. Accepted for presentation at the IEEE Global Communications Conference (Globecom), Taipei, Taiwan, Dec. 202

Renewable energy sharing among base stations as a min-cost-max-flow optimization problem

Limited work has been done to optimize the power sharing among base stations (BSs) while considering the topology of the cellular network and the distance-dependent power loss (DDPL) in the transmission lines. In this paper, we propose two power sharing optimization algorithms for energy-harvesting BSs: the max-flow (MF) algorithm and the min-cost-max-flow (MCMF) algorithm. The two proposed algorithms minimize the power drawn from the main grid by letting BSs with power surpluses transmit harvested power to BSs with deficits. The MCMF algorithm has an additional DDPL cost associated with each transmission line. Hence, the MCMF algorithm shares the harvested power over shorter distances and loses less power during the transmission than the MF algorithm. Our numerical results show that for a fully connected cellular network, i.e., every pair of BSs can share power, with a moderate power loss coefficient per l(R⁺) meters of transmission line, the MCMF algorithm saves up to 10%, 22%, and 30% more main grid power than the MF algorithm for 5, 10, and 15 BSs uniformly distributed in a square area of l² square meters, respectively

Highly Conducting pi-Conjugated Molecular Junctions Covalently Bonded to Gold Electrodes

We measure electronic conductance through single conjugated molecules bonded to Au metal electrodes with direct Au-C covalent bonds using the scanning tunneling microscope based break-junction technique. We start with molecules terminated with trimethyltin end groups that cleave off in situ resulting in formation of a direct covalent sigma bond between the carbon backbone and the gold metal electrodes. The molecular carbon backbone used in this study consist of a conjugated pi-system that has one terminal methylene group on each end, which bonds to the electrodes, achieving large electronic coupling of the electrodes to the pi-system. The junctions formed with the prototypical example of 1,4-dimethylenebenzene show a conductance approaching one conductance quantum (G0 = 2e2/h). Junctions formed with methylene terminated oligophenyls with two to four phenyl units show a hundred-fold increase in conductance compared with junctions formed with amine-linked oligophenyls. The conduction mechanism for these longer oligophenyls is tunneling as they exhibit an exponential dependence of conductance with oligomer length. In addition, density functional theory based calculations for the Au-xylylene-Au junction show near-resonant transmission with a cross-over to tunneling for the longer oligomers.Comment: Accepted to the Journal of the American Chemical Society as a Communication

Analog IC test and product engineering curriculum for Malaysia microelectronics industry

Production test is a significant driver of semiconductor manufacturing cost. Parallel with the advances of semiconductor fabrication, the need for a pool of talented product and test engineers is significantly increasing. This paper describes the academia-industries collaboration effort in developing an analogue electronic test and product engineering to boost-up technical competencies of electronic engineering graduates particularly in microelectronic major. The program has been successfully conducted at Universiti Putra Malaysia with strong support from Texas Instruments and Teradyne

Comparing health workforce forecasting approaches for healthcare planning: The case for ophthalmologists

Health workforce planning is essential in the provision of quality healthcare. Several approaches to planning are customarily used and advocated, each with unique underlying assumptions. Thus, a thorough understanding of each assumption is required in order to make an informed decision on the choice of forecasting approach to be used. For illustration, we compare results for eye care requirements in Singapore using three established workforce forecasting approaches – workforce-to-population-ratio, needs based approach, utilization based approach – and a proposed robust integrated approach to discuss the appropriateness of each approach under various scenarios. Four simulation models using the systems modeling methodology of system dynamics were developed for use in each approach. These models were initialized and simulated using the example of eye care workforce planning in Singapore, to project the number of ophthalmologists required up to the year 2040 under the four different approaches. We found that each approach projects a different number of ophthalmologists required over time. The needs based approach tends to project the largest number of required ophthalmologists, followed by integrated, utilization based and workforce-to-population ratio approaches in descending order. The four different approaches vary widely in their forecasted workforce requirements and reinforce the need to be discerning of the fundamental differences of each approach in order to choose the most appropriate one. Further, health workforce planning should also be approached in a comprehensive and integrated manner that accounts for developments in demographic and healthcare systems