Improved energy detector for random signals in Gaussian noise

New and improved energy detector for random signals in Gaussian noise is proposed by replacing the squaring operation of the signal amplitude in the conventional energy detector with an arbitrary positive power operation. Numerical results show that the best power operation depends on the probability of false alarm, the probability of detection, the average signal-to-noise ratio or the sample size. By choosing the optimum power operation according to different system settings, new energy detectors with better detection performances can be derived. These results give useful guidance on how to improve the performances of current wireless systems using the energy detector. It also confirms that the conventional energy detector based on the generalized likelihood ratio test using the generalized likelihood function is not optimum in terms of the detection performance

Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks

The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter

Counterions and water molecules in charged silicon nanochannels: the influence of surface charge discreteness

In order to detect the effect of the surface charge discreteness on the properties at the solid-liquid interface, molecular dynamics simulation model taking consideration of the vibration of wall atoms was used to investigate the ion and water performance under different charge distributions. Through the comparison between simulation results and the theoretical prediction, it was found that, with the degree of discreteness increasing, much more counterions were attracted to the surface. These ions formed a denser accumulating layer which located much nearer to the surface and caused charge inversion. The ions in this layer were non-hydrated or partially hydrated. When a voltage was applied across the nanochannel, this dense accumulating layer did not move unlike the ions near uniformly charged surface. From the water density profiles obtained in nanochannels with different surface charge distributions, the influence of the surface charge discreteness on the water distributions could be neglected

Hard-input-hard-output capacity analysis of UWB BPSK systems with timing errors

The hard-input-hard-output capacity of a binary phase-shift keying (BPSK) ultrawideband system is analyzed for both additive white Gaussian noise and multipath fading channels with timing errors. Unlike previous works that calculate the capacity with perfect synchronization and/or multiple-access interference only, our analysis considers timing errors with different distributions, as well as the interpath (IPI), interchip (ICI), and intersymbol (ISI) interferences, as in practical systems. The sensitivity of the channel capacity to the timing error is examined. The effects of pulse shape, the multiple-access technique, the number of users, and the number of chips are studied. It is found that time hopping is less sensitive to the pulse shape and that the timing error has higher capacity than direct sequence due to its low duty of cycle. Using these results, one can choose appropriate system parameters for different applications

Accelerating federated learning via momentum gradient descent

Federated learning (FL) provides a communication-efficient approach to solve machine learning problems concerning distributed data, without sending raw data to a central server. However, existing works on FL only utilize first-order gradient descent (GD) and do not consider the preceding iterations to gradient update which can potentially accelerate convergence. In this article, we consider momentum term which relates to the last iteration. The proposed momentum federated learning (MFL) uses momentum gradient descent (MGD) in the local update step of FL system. We establish global convergence properties of MFL and derive an upper bound on MFL convergence rate. Comparing the upper bounds on MFL and FL convergence rates, we provide conditions in which MFL accelerates the convergence. For different machine learning models, the convergence performance of MFL is evaluated based on experiments with MNIST and CIFAR-10 datasets. Simulation results confirm that MFL is globally convergent and further reveal significant convergence improvement over FL

Analysis of Spectrum Occupancy Using Machine Learning Algorithms

In this paper, we analyze the spectrum occupancy using different machine learning techniques. Both supervised techniques (naive Bayesian classifier (NBC), decision trees (DT), support vector machine (SVM), linear regression (LR)) and unsupervised algorithm (hidden markov model (HMM)) are studied to find the best technique with the highest classification accuracy (CA). A detailed comparison of the supervised and unsupervised algorithms in terms of the computational time and classification accuracy is performed. The classified occupancy status is further utilized to evaluate the probability of secondary user outage for the future time slots, which can be used by system designers to define spectrum allocation and spectrum sharing policies. Numerical results show that SVM is the best algorithm among all the supervised and unsupervised classifiers. Based on this, we proposed a new SVM algorithm by combining it with fire fly algorithm (FFA), which is shown to outperform all other algorithms.Comment: 21 pages, 6 figure

Maximum likelihood receivers for space-time coded MIMO systems with gaussian estimation errors

Maximum likelihood (ML) receivers for space-time coded multiple-input multiple-output (MIMO) systems with Gaussian channel estimation errors are proposed. Two different cases are considered. In the first case, the conditional probability density function (PDF) of the channel estimate is assumed Gaussian and known. In the second case, the joint PDF of the channel estimate and the true channel gain is assumed Gaussian and known. In addition to ML signal detection for space-time coded MIMO with ML and minimum mean-squared-error channel estimation, ML signal detection without channel estimation is also studied. Two suboptimal structures are derived. The Alamouti space-time codes are used to examine the performances of the new receivers. Simulation results show that the new receivers can reduce the gap between the conventional receiver with channel estimation errors and the receiver with perfect channel knowledge at least by half in some cases

Energy harvesting AF relaying in the presence of interference and Nakagami-m fading

Energy-harvesting relaying is a promising solution to the extra energy requirement at the relay. It can transfer energy from the source to the relay. This will encourage more idle nodes to be involved in relaying. In this paper, the outage probability and the throughput of an amplify-and-forward relaying system using energy harvesting are analyzed. Both time switching and power-splitting harvesting schemes are considered. The analysis takes into account both the Nakagami-$m$ fading caused by signal propagation and the interference caused by other transmitters. Numerical results show that time switching is more sensitive to system parameters than power splitting. Also, the system performance is more sensitive to the transmission rate requirement, the signal-to-interference-plus-noise ratio in the first hop and the relaying method

Optimization of the front end of CDTE solar cells

The front end of CdTe solar cells consists of two layers: a transparent conducting oxide (TCO) layer and a window layer. New wider band gap materials, ZnMgO are being used to replace CdS as the window layer for the purpose of removing blue loss. For ZnMgO, three important parameters, including the atomic Mg content (x), thickness (t), and doping concentration (n) can play important roles on the performance of CdTe solar cells. In this dissertation, systematic simulation, by solar cell capacitance simulator (SCAPS), and experiments are used to investigate the influences of these parameters on the performance of CdTe solar cells. The optimized parameters of the window layer are found as follows: 10% atomic Mg content to adjust the value of conduction band offset at 0.3 eV. 40 nm thickness with 1018 cm-3 doping concentration to form an n+-p junction structure with the p-type CdTe absorber. Besides, the optimized thickness of different types of TCO is also theoretical calculated. Some novel ideas have been proposed and discussed, but may not be able to enhance the performance of CdTe solar cells

Identification and characterization of a chicken major histocompatibility complex class II[beta] gene promoter

The major histocompatibility complex (MHC) contains a variety of genes. Among them, the class II genes encode proteins involved in antigen presentation to helper T cells, a key step in initiating immune responses. The regulation of class II gene expression has been extensively studied in mammals. Such studies have been lacking in the avian species, despite the well-established association of the avian MHC with disease resistance and production traits. The objective of this study was to functionally analyze a putative chicken MHC class II gene promoter;Using the chloramphenicol acetyltransferase (CAT) reporter system, a functional chicken MHC class II[beta] gene promoter has been identified. A 0.7 kb DNA fragment from the 5[superscript]\u27 flanking region of a class II gene was cloned into the vectors upstream of the CAT structural gene, and transfected into the MQ-NCSU chicken macrophage cell line that expresses MHC class II antigens. Three transfection methods were evaluated to establish a system for DNA transfection into the cell line. The calcium phosphate method had the highest transfection efficiency. The CAT results indicated that the 0.7 kb chicken DNA fragment contains a functional promoter. Promoter activity was relatively weak, which may be explained by the low level of MHC class II expression in this cell line, or by a requirement for additional enhancer sequences. Deletion analysis of this 0.7 kb DNA revealed a short fragment in the 3[superscript]\u27 end that was crucial for the promoter function, and identified negative regulatory elements further upstream. Deletion of the conserved MHC class II X and Y boxes did not have a significant influence on promoter activity. Sequence analysis of the 0.7 kb class II gene upstream region suggested possible involvement of interferon, ETS-related proteins, and other factors in regulating this promoter. An interferon-rich chicken T cell line culture supernatant increased surface expression of MHC class II antigens and class II[beta] promoter activity in this macrophage cell line. This induction effect was inhibited by glucocorticoids. This first functional characterization of a chicken MHC class II gene promoter will aid in understanding the regulatory mechanisms that control the expression of these immune function-related genes