A test of the power law relationship between gamma-ray burst pulse width ratio and energy expected in fireballs or uniform jets

Recently, under the assumption that the Doppler effect of the relativistically expanding fireball surface is important, Qin et al. showed that in most cases the power law relationship between the pulse width and energy of gamma-ray bursts (GRBs)would exist in a certain energy range. We check this prediction with two GRB samples which contain well identified pulses. A power law anti-correlation between the full pulse width and energy and a power law correlation between the pulse width ratio and energy are seen in the light curves of the majority (around 65%) of bursts of the two samples within the energy range of BATSE, suggesting that these bursts are likely to arise from the emission associated with the shocks occurred on a relativistically expanding fireball surface. For the rest of the bursts, the relationships between these quantities were not predicted previously. We propose to consider other spectral evolutionary patterns or other radiation mechanisms such as a varying synchrotron or Comptonized spectrum to check if the observed relationships for these rest bursts can also be accounted for by the Doppler model. In addition, we find that the upper limits of the width ratio for the two samples do not exceed 0.9, in agrement with what predicted previously by the Doppler model. The plateau/power law/plateau and the peaked features predicted and detected previously by Qin et al. are generally observed, with the exceptions being noticed only in a few cases. According to the distinct values of two power law indices of FWHM and ratio and energy, we divide the bursts into three subsets which are located in different areas of the two indices plane. We suspect that different locations of the two indices might correspond to different mechanisms.Comment: 16 pages, 7 figures, MNRAS accepte

Energy Efficient Uplink Transmissions in LoRa Networks

LoRa has been recognized as one of the most promising low-power wide-area (LPWA) techniques. Since LoRa devices are usually powered by batteries, energy efficiency (EE) is an essential consideration. In this paper, we investigate the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. Specifically, our objective is to maximize the corresponding EE by jointly exploiting user scheduling, spreading factor (SF) assignment, and transmit power allocations. To solve them efficiently, we first propose a suboptimal algorithm, including the low-complexity user scheduling scheme based on matching theory and the heuristic SF assignment approach for LoRa users scheduled on the same channel. Then, to deal with the power allocation, an optimal algorithm is proposed to maximize the SEE. To maximize the MEE of LoRa users assigned to the same channel, an iterative power allocation algorithm based on the generalized fractional programming and sequential convex programming is proposed. Numerical results show that the proposed user scheduling algorithm achieves near-optimal EE performance, and the proposed power allocation algorithms outperform the benchmarks. © 2020 IEEE

Deep Learning Enabled Semantic Communication Systems

Recently, deep learned enabled end-to-end (E2E) communication systems have been developed to merge all physical layer blocks in the traditional communication systems, which make joint transceiver optimization possible. Powered by deep learning, natural language processing (NLP) has achieved great success in analyzing and understanding large amounts of language texts. Inspired by research results in both areas, we aim to providing a new view on communication systems from the semantic level. Particularly, we propose a deep learning based semantic communication system, named DeepSC, for text transmission. Based on the Transformer, the DeepSC aims at maximizing the system capacity and minimizing the semantic errors by recovering the meaning of sentences, rather than bit- or symbol-errors in traditional communications. Moreover, transfer learning is used to ensure the DeepSC applicable to different communication environments and to accelerate the model training process. To justify the performance of semantic communications accurately, we also initialize a new metric, named sentence similarity. Compared with the traditional communication system without considering semantic information exchange, the proposed DeepSC is more robust to channel variation and is able to achieve better performance, especially in the low signal-to-noise (SNR) regime, as demonstrated by the extensive simulation results.Comment: 13 pages, Journal, accepted by IEEE TS

Spike Effects on Drag Reduction for Hypersonic Lifting Body

A high lift-to-drag ratio is considered crucial for high-altitude and long-endurance hypersonic vehicles. One of the simplest and most useful methods is to install an aerospike in front of the vehicle’s nose. In this paper, the flight aerodynamic characteristics are investigated by simulating and comparing the lifting body with or without the aerospikes at Ma=8. The flowfields around aerospikes using different spike lengths and a hemispherical disk along with the lifting body are analyzed. The results of aerodynamic characteristics indicate that L/D=2 is the best ratio of the spike length to the nose diameter. By comparing with the baseline model, the maximum drag reduction of the nose’s part is 49.3% at α=8  deg using a hemispherical disk. In addition, three shapes of aerospike disks are compared to search for the best disk for hypersonic drag reduction. The best drag reduction is found for the double flat-faced disk aerospike, which gives a pressure drag reduction of 60.5% of the nose’s part at α=8  deg. Furthermore, when the flight angle of attack increases, the drag increases significantly. Employing a certain installation angle is shown to effectively improve the drag reduction around the angle of attack and results in improving the lift-to-drag ratio. At the end, the lift-to-drag ratio of the final optimized design is 9.1% better than that of the baseline model. The pressure center is moved forward by 1.6%, barely influencing the vertical static stability of the vehicle