WUB-IP : a high-precision UWB positioning scheme for indoor multi-user applications

High-precision positioning scheme, an important part of the indoor navigation system, can be implemented using an ultra-wide band (UWB) based ranging system. Recently, solutions for precise positioning in dense multi-path and non-line-of-sight (NLOS) conditions have attracted a lot of attention in literature. On the other hand, it is expected that Waveform Division Multiple Access (WDMA) technology for multi-user UWB positioning application will be indispensable in the near future. In this regard, a WDMA-UWB based positioning scheme is investigated in this paper, for enhancing the performance of positioning accuracy in multi-user applications. In accordance with practical requirements of indoor positioning, we propose a new indoor positioning scheme, termed as WUB-IP. This scheme adopts WDMA for multiple access, and utilizes an entropy-based approach for the Time of Arrival (TOA) estimation. Moreover, a transfer learning approach is used for ranging error mitigation in NLOS conditions, in order to improve the positioning accuracy in NLOS conditions. System-level simulations demonstrate that the proposed scheme enhances the performance of indoor positioning for multi-user applications

Coordinated direct and relay transmission with NOMA and network coding in Nakagami-m fading channel

Although the use of coordinated direct and relay transmission (CDRT) in non-orthogonal multiple access (NOMA) can extend the coverage, its duplicated transmission reduces the spectrum efficiency (SE) of NOMA. To improve the SE, we propose a spectrum-efficient scheme for NOMA-based CDRT over Nakagami-m fading channels. In this scheme, the base station (BS) connects with a cell-center user (CCU) directly while communicating with a cell-edge user (CEU) via a relay and the CCU. Then, the relay and the CCU use network coding to process and retransmit the signals sent by the BS first and the CEU later. Finally, the BS and the relay simultaneously broadcast downlink signals. We derive the closed-form expressions for the average SE, the user fairness index and the energy efficiency (EE) as well as the asymptotic average SE using both perfect and imperfect successive interference cancellation (SIC). Simulations verify the correctness of our theoretical analysis and the superiority of the proposed scheme in SE and EE

Resource allocation and trajectory optimization for UAV-enabled multi-user covert communications

In this correspondence, covert air-to-ground communication is investigated to hide the wireless transmission from unmanned aerial vehicle (UAV). The warden's total detection error probability with limited observations is first analyzed. Considering the location uncertainty of the warden, a robust resource allocation and UAV trajectory optimization problem with worst-case covertness constraint is then formulated to maximize the average covert rate. To solve this optimization problem, we propose a block coordinate descent method based iterative algorithm to optimize the time slot allocation, power allocation and trajectory alternately. Numerical results demonstrate the effectiveness of the proposed algorithm in covert communication for UAVs

Further results on detection and channel estimation for hardware impaired signals

Hardware impairment is inevitable in many wireless systems. It is particularly severe in low-cost applications due to the imperfect components used. In this paper, the channel estimation and non-coherent detection problems of hardware impaired signals are studied for a single-carrier, single-antenna and single-hop system. Specifically, three different cases are investigated: signals with additive distortion only, signals with in-phase and quadrature imbalance only, and signals with both impairments. The maximum likelihood and Gaussian approximation methods are used to derive the new non-coherent detectors for amplitude modulated signals, while the maximum likelihood and moment-based methods are employed to design the new channel estimators for all signals. Numerical results show that the new non-coherent detectors outperform the existing non-coherent detectors in the presence of hardware impairment. The performance gain can be as high as 8 dB. They also show that the new channel estimators have much higher accuracy than the existing estimator. In some conditions, the accuracy of the new estimator is about 100 times that of the existing estimator

Ieee access special section editorial: Cloud and big data-based next-generation cognitive radio networks

In cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to complicated data processing, non-real-Time information exchange and limited memory, SUs often suffer from imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the

Distributed few-shot learning for intelligent recognition of communication jamming

Effective recognition of communication jamming is of vital importance in improving wireless communication sys- tem’s anti-jamming capability. Motivated by the major challenges that the jamming data sets in wireless communication system are often small and the recognition performance may be poor, we introduce a novel jamming recognition method based on distributed few-shot learning in this paper. Our proposed method employs a distributed recognition architecture to achieve the global optimization of multiple sub-networks by federated learn- ing. It also introduces a dense block structure in the sub-network structure to improve network information flow by the feature multiplexing and configuration bypass to improve resistance to over-fitting. Our key idea is to first obtain the time-frequency diagram, fractional Fourier transform and constellation diagram of the communication jamming signal as the model-agnostic meta-learning network input, and then train the distributed network through federated learning for jamming recognition. Simulation results show that our proposed method leads to excellent recognition performance with a small data set

Location parameter estimation of moving aerial target in space-air-ground integrated networks-based IoV

Estimating the location parameters of moving target is an important part of intelligent surveillance for Internet of Vehicles (IoV). Satellite has the potential to play a key role in many applications of space-air-ground integrated networks (SAGIN). In this paper, a novel passive location parameter estimator using multiple satellites for moving aerial target is proposed. In this estimator, the direct wave signals in reference channels are first filtered by a band-pass filter, followed by a sequence cancellation algorithm to suppress the direct-path interference and multi-path interference. Then, the fourth-order cyclic cumulant cross ambiguity function (FOCCCAF) of the signals in the reference channels and the four-weighted fractional Fourier transform fourth-order cyclic cumulant cross-ambiguity function (FWFRFT-FOCCCAF) of signals in the surveillance channels are derived. Using them, the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) are estimated and the distance between the target and the receiver and the velocity of the moving aerial target are estimated by using multiple satellites. Finally, the Cramer-Rao Lower Bounds of the proposed location parameter estimators are derived to benchmark the estimator. Simulation results show that the proposed method can effectively and precisely estimate the location parameters of the moving aerial target

NMR Characterizations of the Ice Binding Surface of an Antifreeze Protein

Antifreeze protein (AFP) has a unique function of reducing solution freezing temperature to protect organisms from ice damage. However, its functional mechanism is not well understood. An intriguing question concerning AFP function is how the high selectivity for ice ligand is achieved in the presence of free water of much higher concentration which likely imposes a large kinetic barrier for protein-ice recognition. In this study, we explore this question by investigating the property of the ice binding surface of an antifreeze protein using NMR spectroscopy. An investigation of the temperature gradient of amide proton chemical shift and its correlation with chemical shift deviation from random coil was performed for CfAFP-501, a hyperactive insect AFP. A good correlation between the two parameters was observed for one of the two Thr rows on the ice binding surface. A significant temperature-dependent protein-solvent interaction is found to be the most probable origin for this correlation, which is consistent with a scenario of hydrophobic hydration on the ice binding surface. In accordance with this finding, rotational correlation time analyses combined with relaxation dispersion measurements reveals a weak dimer formation through ice binding surface at room temperature and a population shift of dimer to monomer at low temperature, suggesting hydrophobic effect involved in dimer formation and hence hydrophobic hydration on the ice binding surface of the protein. Our finding of hydrophobic hydration on the ice binding surface provides a test for existing simulation studies. The occurrence of hydrophobic hydration on the ice binding surface is likely unnecessary for enhancing protein-ice binding affinity which is achieved by a tight H-bonding network. Subsequently, we speculate that the hydrophobic hydration occurring on the ice binding surface plays a role in facilitating protein-ice recognition by lowering the kinetic barrier as suggested by some simulation studies

Cross-Mapping Events in miRNAs Reveal Potential miRNA-Mimics and Evolutionary Implications

MicroRNAs (miRNAs) have important roles in various biological processes. miRNA cross-mapping is a prevalent phenomenon where miRNA sequence originating from one genomic region is mapped to another location. To have a better understanding of this phenomenon in the human genome, we performed a detailed analysis in this paper using public miRNA high-throughput sequencing data and all known human miRNAs. We observed widespread cross-mapping events between miRNA precursors (pre-miRNAs), other non-coding RNAs (ncRNAs) and the opposite strands of pre-miRNAs by analyzing the high-throughput sequencing data. Computational analysis on all known human miRNAs also confirmed that many of them could be involved in cross-mapping events. The processing or decay of both ncRNAs and pre-miRNA opposite strand transcripts may contribute to miRNA enrichment, although some might be miRNA-mimics due to miRNA mis-annotation. Comparing to canonical miRNAs, miRNAs involved in cross-mapping events between pre-miRNAs and other ncRNAs normally had shorter lengths (17–19 nt), lower prediction scores and were classified as pseudo miRNA precursors. Notably, 4.9% of all human miRNAs could be accurately mapped to the opposite strands of pre-miRNAs, which showed that both strands of the same genomic region had the potential to produce mature miRNAs and simultaneously implied some potential miRNA precursors. We proposed that the cross-mapping events are more complex than we previously thought. Sequence similarity between other ncRNAs and pre-miRNAs and the specific stem-loop structures of pre-miRNAs may provide evolutionary implications