In this paper, the performance of non-orthogonal multiple access (NOMA) is characterized in a downlink visible light communication (VLC) system for two separate scenarios. For the case of guaranteed quality of service (QoS) provisioning, we derive analytical expressions of the system coverage probability and show the existence of optimal power allocation coefficients on two-user paired NOMA. For the case of opportunistic besteffort service provisioning, we formulate a closed-form expression of the ergodic sum rate, which is applicable for arbitrary power allocation strategies. The probability that NOMA achieves higher individual rates than orthogonal multiple access (OMA) is derived. Also, we give an upper bound of the sum rate gain of NOMA over OMA in high signal-to-noise ratio (SNR) regimes. Both simulation and analytical results prove that the performance gain of NOMA over OMA can be further enlarged by pairing users with distinctive channel conditions. We also find out that the choice of light emitting diodes (LEDs) has a significant impact on the system performance. For the case of guaranteed QoS provisioning, LEDs with larger semi-angles have better performance; while for the case of opportunistic besteffort service provisioning, LEDs with 35 • semi-angle give nearly optimal performance.Index Terms-Non-orthogonal multiple access (NOMA), visible light communication (VLC), coverage probability, ergodic sum rate, order statistics.
African swine fever (ASF) entered China in August 2018 and rapidly spread across the entire country, severely threatening the Chinese domestic pig population, which accounts for more than 50% of the pig population worldwide. In this study, an ASFV isolate, Pig/Heilongjiang/2018 (Pig/HLJ/18), was isolated in primary porcine alveolar macrophages (PAMs) from a pig sample from an ASF outbreak farm. The isolate was characterized by using the haemadsorption (HAD) test, Western blotting and immunofluorescence, and electronic microscopy. Phylogenetic analysis of the viral p72 gene revealed that Pig/HLJ/18 belongs to Genotype II. Infectious titres of virus propagated in primary PAMs and pig marrow macrophages were as high as 10
7.2
HAD
50
/ml. Specific-pathogen-free pigs intramuscularly inoculated with different virus dosages at 10
3.5
–10
6.5
HAD
50
showed acute disease with fever and haemorrhagic signs. The incubation periods were 3–5 days for virus-inoculated pigs and 9 days for contact pigs. All virus-inoculated pigs died between 6–9 days post-inoculation (p.i.), and the contact pigs died between 13–14 days post-contact (p.c.). Viremia started on day 2 p.i. in inoculated pigs and on day 9 p.c. in contact pigs. Viral genomic DNA started to be detected from oral and rectal swab samples on 2–5 days p.i. in virus-inoculated pigs, and 6–10 days p.c. in contact pigs. These results indicate that Pig/HLJ/18 is highly virulent and transmissible in domestic pigs. Our study demonstrates the threat of ASFV and emphasizes the need to control and eradicate ASF in China.
We consider the problem of distributed scheduling in wireless networks subject to simple collision constraints. We define the efficiency of a distributed scheduling algorithm to be the largest number (fraction) such that the throughput under the distributed scheduling policy is at least equal to the efficiency multiplied by the maximum throughput achievable under a centralized policy. For a general interference model, we prove a lower bound on the efficiency of a distributed scheduling algorithm by first assuming that all of the traffic only uses one hop of the network. We also prove that the lower bound is tight in the sense that, for any fraction larger than the lower bound, we can find a topology and an arrival rate vector within the fraction of the capacity region such that the network is unstable under a greedy scheduling policy. We then extend our results to a more general multihop traffic scenario and show that similar scheduling efficiency results can be established by introducing prioritization or regulators to the basic greedy scheduling algorithm.
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