On Secrecy Outage Probability for Downlink NOMA Systems With Relay-Antenna Selection

Secure transmission is essential for future non-orthogonal multiple access (NOMA) system. This paper investigates relay-antenna selection (RAS) to enhance physical-layer security (PLS) of cooperative NOMA system in the presence of an eavesdropper, where multiple antennas are deployed at the relays, the users, and the eavesdropper. In order to reduce expense on radio frequency (RF) chains, selection combining (SC) is employed at both the relays and the users, whilst the eavesdropper employs either maximal-ratio combining (MRC) or selection combining (SC) to process the received signals. Under the condition that the channel state information (CSI) of the eavesdropping channel is available or unavailable, two e↵ective relay-antenna selection schemes are proposed. Additionally, the closed-form expressions of secrecy outage probability (SOP) are derived for the proposed relay-antenna selection schemes. In order to gain more deep insights on the derived results, the asymptotic performance of the derived SOP is analyzed. In simulations, it is demonstrated that the theoretical results match well with the simulation results and the SOP of the proposed schemes is less than that of the conventional orthogonal multiple access (OMA) scheme obviously.

Multi-Label Feature Selection Combining Three Types of Conditional Relevance

With the rapid growth of the Internet, the curse of dimensionality caused by massive multi-label data has attracted extensive attention. Feature selection plays an indispensable role in dimensionality reduction processing. Many researchers have focused on this subject based on information theory. Here, to evaluate feature relevance, a novel feature relevance term (FR) that employs three incremental information terms to comprehensively consider three key aspects (candidate features, selected features, and label correlations) is designed. A thorough examination of the three key aspects of FR outlined above is more favorable to capturing the optimal features. Moreover, we employ label-related feature redundancy as the label-related feature redundancy term (LR) to reduce unnecessary redundancy. Therefore, a designed multi-label feature selection method that integrates FR with LR is proposed, namely, Feature Selection combining three types of Conditional Relevance (TCRFS). Numerous experiments indicate that TCRFS outperforms the other 6 state-of-the-art multi-label approaches on 13 multi-label benchmark data sets from 4 domains.

Beamforming Design and Covert Performance Analysis for Full-Duplex Multiantenna System

In this work, a wireless covert communication system with full-duplex (FD) multiantenna receiver is considered. In order to improve the convert performance of the wireless communication system in the FD mode, a scheme based on selection combining/zero forcing beamforming (SC/ZFB) is proposed. More specifically, a covert message receiver with a FD multiantenna uses the zero forcing beamforming method to transmit randomly varying noise power to the adversary while receiving covert information from the sender. Firstly, we derive the optimal detection threshold and the corresponding closed expression of the minimum detection error rate of the warden. Secondly, the transmission interruption probability is explored to measure the communication reliability between the sender and the receiver of the covert message. Finally, the throughput performance of the covert communication system is analyzed under random geometry. Our analysis shows that the proposed SC/ZFB scheme can achieve the positive effective convert rate while interfering with the detection of the warden as much as possible. It is worth noting that the increase of the number of antennas and the power of covert message transmission can improve the convert performance of the system.

Enchancement of GSC Using OFDM and QAM Over Reiyleign Fading Channel: A Review

As indispensable as communication has been to human endeavors, geographical and physical distance would have been a barrier to its effective deployment if not for the advent of wireless mobile communication. In the world today, most of the developments we see in all spheres of our modern life are influenced by communication technologies. However, the performance of each modulation scheme deployed in the communication system dictates the Quality of Service (QoS), effective cost management, efficient power, available bandwidth, Bit Error Rate (BER), and Signal to Noise Ratio (SNR). Extensive research has been done with different authors proffering wide ranging solutions for generalized selection combining (GSC) algorithms in the presence of noise and interfering signals. Some of the reported approaches include varying modulation schemes, changing the channel, and using different equalizing techniques. Many of these proposed solutions worked effectively in some areas while they understandably left other areas untouched, others show better performance by analyzing the channel using; Log-likelihood Ratio (LLR), integral expression, and multiple-mode transmission scheme which in turns proof to be of better performance with a good result. Despite all the efforts, overcoming the issue of noise interference in the communication channel has still been somewhat elusive. Conclusively, to reduce noise to the barest minimum in mobile/cellular communication, this review proposes modulation scheme synchronization with combined diversity technique over an improved channel that is less prone to noise.

Feature Selection Combining Filter and Wrapper Methods for Motor-Imagery Based Brain–Computer Interfaces

Motor imagery (MI) based brain–computer interfaces help patients with movement disorders to regain the ability to control external devices. Common spatial pattern (CSP) is a popular algorithm for feature extraction in decoding MI tasks. However, due to noise and nonstationarity in electroencephalography (EEG), it is not optimal to combine the corresponding features obtained from the traditional CSP algorithm. In this paper, we designed a novel CSP feature selection framework that combines the filter method and the wrapper method. We first evaluated the importance of every CSP feature by the infinite latent feature selection method. Meanwhile, we calculated Wasserstein distance between feature distributions of the same feature under different tasks. Then, we redefined the importance of every CSP feature based on two indicators mentioned above, which eliminates half of CSP features to create a new CSP feature subspace according to the new importance indicator. At last, we designed the improved binary gravitational search algorithm (IBGSA) by rebuilding its transfer function and applied IBGSA on the new CSP feature subspace to find the optimal feature set. To validate the proposed method, we conducted experiments on three public BCI datasets and performed a numerical analysis of the proposed algorithm for MI classification. The accuracies were comparable to those reported in related studies and the presented model outperformed other methods in literature on the same underlying data.

Eleven Namibian rains: A phenomenological analysis of experience in time

The Damara pastoralists ( ǂnūkhoen) in Namibia distinguish a diverse range of rains. Some rains kill livestock, others care for insects and still others wash away the footprints of the deceased, allowing the person to exist in the spirit realm. While anthropologists have documented cultural classifications like the Namibian rains for decades, we still lack a convincing theory to explain how they come to exist. To address this, I develop a phenomenological perspective and theorise how experience contributes to what rain becomes. I argue with Husserl that the present in which we experience the rain is not a discrete moment, but a unity across a succession of ‘nows’. In the process, perceptions, images, memories and expectations about past and future events blend. In other words, a web of meaningful relationships connects the rain we experience ‘now’ with multiple past and future entities, including people, plants, spirits and animals. I refer to this as network formation. Combining the analyses of the people's pastoral being-in-the-world and their historical–political context, including post-colonialism, allows an explanation as to why some of those combinations are singled out and become distinct ontological entities. I refer to this as node selection. Combining the two processes – network formation and node selection – allows for an explanation as to why precipitation becomes discernible and meaningful as eleven different Namibian rains.

Performance Analysis in DF Energy Harvesting Full-Duplex Relaying Network with MRC and SC at the Receiver under Impact of Eavesdropper

This paper investigates the decode-and-forward (DF) full-duplex (FD) relaying system under the presence of an eavesdropper. Moreover, the relay node is able to harvest energy from a transmitter, and then it uses the harvested energy for conveying information to the receiver. Besides, both two-hop and direct relaying links are taking into consideration. In the mathematical analysis, we derived the exact expressions for intercept probability and outage probability (OP) by applying maximal ratio combining (MRC) and selection combining (SC) techniques at the receiver. Next, the Monte Carlo simulation is performed to validate the mathematical analysis. The results show that the simulation curves match the mathematic expressions, which confirms the analysis section.