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

Outage Probability of Dual-Hop Selective AF With Randomly Distributed and Fixed Interferers

The outage probability performance of a dual-hop amplify-and-forward selective relaying system with global relay selection is analyzed for Nakagami-$m$ fading channels in the presence of multiple interferers at both the relays and the destination. Two different cases are considered. In the first case, the interferers are assumed to have random number and locations. Outage probability using the generalized Gamma approximation (GGA) in the form of one-dimensional integral is derived. In the second case, the interferers are assumed to have fixed number and locations. Exact outage probability in the form of one-dimensional integral is derived. For both cases, closed-form expressions of lower bounds and asymptotic expressions for high signal-to-interference-plus-noise ratio are also provided. Simplified closed-form expressions of outage probability for special cases (e.g., dominant interferences, i.i.d. interferers, Rayleigh distributed signals) are studied. Numerical results are presented to show the accuracy of our analysis by examining the effects of the number and locations of interferers on the outage performances of both AF systems with random and fixed interferers.Comment: 35 pages, 11 figures, accepted with minor revisions for publication as a regular paper in the IEEE Transactions on Vehicular Technology on 21/09/201

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