scholarly journals Low-Complexity Failed Element Diagnosis for Radar-Communication mmWave Antenna Array with Low SNR

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 904
Author(s):  
Qingyu Li ◽  
Keren Dai ◽  
Xiaofeng Wang ◽  
Yu Zhang ◽  
He Zhang ◽  
...  
Keyword(s):  
Antenna Array ◽  
Large Scale ◽  
High Reliability ◽  
Doa Estimation ◽  
Low Complexity ◽  
Working Environment ◽  
Joint Decision ◽  
Communication Signals ◽  
Low Snr ◽  
Communication Signal

The millimeter-wave (mmWave) antenna array plays an important role in the excellent performance of wireless sensors networks (WSN) or unmanned aerial vehicle (UAV) clusters. However, the array elements are easily damaged in its harsh working environment but hard to be repaired or exchanged timely, resulting in a serious decline in the beamforming performance. Thus, accurate self-diagnosis of the failed elements is of great importance. In previous studies, there are still significant difficulties for large-scale arrays under extremely low SNR. In this paper, a diagnosis algorithm with low complexity and high reliability for the failed elements is proposed, which is based on a joint decision of communication signal and sensing echoes. Compared with the previous studies, the complexity of the algorithm is reduced by the construction of low-dimensional feature vectors for classification, the decoupling of the degree of arrival (DOA) estimation and the failed pattern diagnosis, with the help of the sub-array division. Simulation results show that, under an ultra-low SNR of −12.5 dB for communication signals and −16 dB for sensing echoes, an accurate self-diagnosis with a block error rate lower than 8% can be realized. The study in this paper will effectively promote the long-term and reliable operation of the mmWave antenna array in WSN, UAV clusters and other similar fields.

scholarly journals Trajectory Planning in UAV Emergency Networks with Potential Underlaying D2D Communication Based on K-means

2021 ◽  
Author(s):  
Shuo Zhang ◽  
Shuo Shi ◽  
Tianming Feng ◽  
Xuemai Gu
Keyword(s):  
Trajectory Planning ◽  
Communication Systems ◽  
High Speed ◽  
Large Scale ◽  
High Reliability ◽  
Base Station ◽  
Planning Problem ◽  
Communication Signal ◽  
User Coverage ◽  
Trajectory Length

Abstract Unmanned aerial vehicles (UAVs) have been widely used in communication systems due to excellent maneuverability and mobility. The ultra-high speed, ultra-low latency, and ultra-high reliability of 5th generation wireless systems (5G) have further promoted vigorous development of UAVs. Compared with traditional means of communication, UAV can provide services for ground terminal without time and space constraints, so it is often used as air base station (BS). Especially in emergency communications and rescue, it provides temporary communication signal coverage service for disaster areas. In the face of large-scale and scattered user coverage tasks, UAV's trajectory is an important factor affecting its energy consumption and communication performance. In this paper, we consider a UAV emergency communication network where UAV aims to achieve complete coverage of potential underlying D2D users (DUs). The trajectory planning problem is transformed into the deployment and connection problem of stop points (SPs). Aiming at trajectory length and sum throughput, two trajectory planning algorithms based on K-means are proposed. Due to the non-convexity of sum throughput optimization, we present a sub-optimal solution by using the successive convex approximation (SCA) method. In order to balance the relationship between trajectory length and sum throughput, we propose a joint evaluation index which is used as an objective function to further optimize trajectory. Simulation results show the validity of the proposed algorithms which have advantages over the well-known benchmark scheme in terms of trajectory length and sum throughput.

scholarly journals Constant Envelope MIMO-OFDM Precoding for Low Complexity Large-Scale Antenna Array Systems

2020 ◽  
Vol 19 (12) ◽  
pp. 7973-7985
Author(s):  
Stavros Domouchtsidis ◽  
Christos G. Tsinos ◽  
Symeon Chatzinotas ◽  
Bjorn Ottersten
Keyword(s):  
Antenna Array ◽  
Large Scale ◽  
Low Complexity ◽  
Constant Envelope ◽  
Mimo Ofdm

Symbol-Level Precoding for Low Complexity Transmitter Architectures in Large-Scale Antenna Array Systems

2019 ◽  
Vol 18 (2) ◽  
pp. 852-863 ◽  
Author(s):  
Stavros Domouchtsidis ◽  
Christos G. Tsinos ◽  
Symeon Chatzinotas ◽  
Bjorn Ottersten
Keyword(s):  
Antenna Array ◽  
Large Scale ◽  
Low Complexity

scholarly journals FRACTAL COMPLEXITY-BASED FEATURE EXTRACTION ALGORITHM OF COMMUNICATION SIGNALS

Fractals ◽  
2017 ◽  
Vol 25 (04) ◽  
pp. 1740008 ◽  
Author(s):  
HUI WANG ◽  
JINGCHAO LI ◽  
LILI GUO ◽  
ZHENG DOU ◽  
YUN LIN ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Radiation Source ◽  
Recognition Rate ◽  
Individual Characteristics ◽  
Accurate Identification ◽  
Communication Signals ◽  
Low Snr ◽  
Communication Signal ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of −10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

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